Conditions: Psoriatic Arthritis
Keywords: Psoriatic Arthritis PsA Bimekizumab
Allocation: RANDOMIZED | Intervention model: PARALLEL
Enrollment: 400
Healthy volunteers: no

Brief summary:
This is a study to demonstrate the clinical efficacy, safety and tolerability of bimekizumab administered subcutaneously (sc) compared with placebo in the treatment of tumor necrosis factor alpha-inadequate responders (TNFα-IR) subjects with active Psoriatic Arthritis (PsA).

Detailed description:

Arms:
arm 1: Subjects randomized to this arm will receive assigned bimekizumab dosage regimen. arm 2: Subjects randomized to this arm will receive placebo.

Interventions: intervention 1: Bimekizumab intervention 2: Placebo
Intervention descriptions: intervention 1: Subjects will receive bimekizumab at pre-specified time-points. intervention 2: Subjects will receive placebo at pre-specified time-points.

Protocol document:
Prot_000.pdf: 
UCB 
 
01 Apr 2021 
Clinical Study Protocol 
Bimekizumab 
PA0011 
 
 
 
Confidential 
Page 1 of 142 
PROTOCOL PA0011 AMENDMENT 2 
A MULTICENTER, PHASE 3, RANDOMIZED, DOUBLE-BLIND, 
PLACEBO-CONTROLLED STUDY EVALUATING THE 
EFFICACY AND SAFETY OF BIMEKIZUMAB IN THE 
TREATMENT OF SUBJECTS WITH ACTIVE PSORIATIC 
ARTHRITIS 
PHASE 3 
EudraCT Number: 2017-002804-29 
IND Number: 128708 
Sponsor: 
UCB Biopharma SRL 
Allée de la Recherche 60 
1070 Brussels 
BELGIUM 
 
 
Protocol/Amendment number 
Date 
Type of amendment 
Final Protocol 
29 Nov 2018 
Not applicable 
Protocol Amendment 1 
14 May 2020 
Substantial 
Protocol Amendment 2 
01 Apr 2021 
Substantial 
Confidential Material 
Confidential 
This document is the property of UCB and may not – in full or in part – be passed on, 
reproduced, published, or otherwise used without the express permission of UCB. 
 
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01 Apr 2021 
Clinical Study Protocol 
Bimekizumab 
PA0011 
 
 
 
Confidential 
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STUDY CONTACT INFORMATION 
Sponsor 
UCB Biopharma SRL 
Allée de la Recherche 60  
1070 Brussels  
BELGIUM 
Sponsor Study Physician 
Name: 
 
Address: 
UCB Celltech Ltd 
208 Bath Road 
Slough SL1 3WE 
UNITED KINGDOM 
Phone: 
 
Clinical Project Manager 
Name: 
 
Address: 
UCB Biopharma SRL 
Chemin du Foriest 
Brain-l'Alleud B-1420 
Belgium 
Phone: 
 
Clinical Trial Biostatistician 
Name: 
 
Address: 
UCB BIOSCIENCES Inc.  
4000 Paramount Pkwy, 
 
Morrisville, NC 27560 
UNITED STATES 
Phone: 
 
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01 Apr 2021 
Clinical Study Protocol 
Bimekizumab 
PA0011 
 
 
 
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Clinical Monitoring Contract Research Organization 
Name: 
PAREXEL International (IRL) Limited-Ireland 
Address: 
Ireland Limited at 70 Sir John Rogerson’s Quay, Dublin 2, Ireland 
Phone: 
+353-(1)-477-3171 
Fax: 
+353-(1)-477-3308 
 
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01 Apr 2021 
Clinical Study Protocol 
Bimekizumab 
PA0011 
 
 
 
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SERIOUS ADVERSE EVENT REPORTING 
Serious adverse event reporting (24h) 
All serious adverse events will be reported and transmitted to Patient Safety through the 
eCRF system. The numbers below are to be used to send ancillary documentation only 
(discharge summaries, death certificates, etc) or in the event that the electronic reporting 
(eCRF) is not available. 
Fax 
Europe and Rest of the World: +32-2-386-24-21 
USA and Canada: +1-800-880-6949 or +1-866-890-3175 
Email 
Global: DS_ICT@ucb.com  
 
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01 Apr 2021 
Clinical Study Protocol 
Bimekizumab 
PA0011 
 
 
 
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TABLE OF CONTENTS 
LIST OF ABBREVIATIONS .................................................................................................. 11 
1 
SUMMARY ..................................................................................................................... 16 
2 
INTRODUCTION ........................................................................................................... 17 
2.1 
Psoriatic arthritis .......................................................................................................... 17 
2.1.1 
Psoriatic arthritis epidemiology ........................................................................... 17 
2.1.2 
Current treatments for psoriatic arthritis .............................................................. 17 
2.2 
Bimekizumab ............................................................................................................... 18 
2.2.1 
Nonclinical ........................................................................................................... 18 
2.2.2 
Clinical ................................................................................................................. 19 
2.2.2.1 
Completed studies ..................................................................................... 19 
2.2.2.2 
Ongoing studies ......................................................................................... 22 
3 
STUDY OBJECTIVES .................................................................................................... 23 
3.1 
Primary objective ......................................................................................................... 23 
3.2 
Secondary objectives ................................................................................................... 23 
3.3 
Other objectives ........................................................................................................... 23 
4 
STUDY VARIABLES ..................................................................................................... 24 
4.1 
Efficacy variables......................................................................................................... 24 
4.1.1 
Primary efficacy variable ..................................................................................... 24 
4.2 
Secondary variables ..................................................................................................... 24 
4.2.1 
Secondary efficacy variables ............................................................................... 24 
4.2.2 
Secondary safety variables .................................................................................. 24 
4.3 
Other variables ............................................................................................................. 24 
4.3.1 
Other efficacy variables ....................................................................................... 24 
4.3.2 
Other safety variables .......................................................................................... 26 
4.3.3 
Pharmacokinetic variable ..................................................................................... 27 
4.3.4 
Pharmacogenomic variables ................................................................................ 27 
4.3.5 
Immunological variables ..................................................................................... 27 
5 
STUDY DESIGN ............................................................................................................. 27 
5.1 
Study description ......................................................................................................... 27 
5.2 
Screening Period/Baseline ........................................................................................... 28 
5.2.1 
Within-study rescreening/retesting requirements ................................................ 28 
5.3 
Treatment Period .......................................................................................................... 28 
5.3.1 
Double-Blind Treatment Period .......................................................................... 28 
5.4 
Safety Follow-Up Visit ................................................................................................ 29 
5.5 
Study duration per subject ........................................................................................... 29 
5.6 
Planned number of subjects and sites .......................................................................... 29 
5.7 
Anticipated regions and countries ................................................................................ 29 
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5.8 
Schedule of study assessments..................................................................................... 29 
5.9 
Schematic diagram ....................................................................................................... 35 
5.10 
Rationale for study design and selection of dose ......................................................... 35 
6 
SELECTION AND WITHDRAWAL OF SUBJECTS ................................................... 36 
6.1 
Inclusion criteria .......................................................................................................... 36 
6.2 
Exclusion criteria ......................................................................................................... 37 
6.3 
Withdrawal criteria ...................................................................................................... 40 
6.3.1 
Potential drug-induced liver injury IMP discontinuation criteria ........................ 43 
7 
STUDY TREATMENTS ................................................................................................. 43 
7.1 
Description of investigational medicinal products ...................................................... 43 
7.2 
Treatments to be administered ..................................................................................... 44 
7.3 
Packaging ..................................................................................................................... 44 
7.4 
Labeling ....................................................................................................................... 44 
7.5 
Handling and storage requirements ............................................................................. 44 
7.6 
Drug accountability ...................................................................................................... 45 
7.7 
Procedures for monitoring subject compliance ............................................................ 45 
7.8 
Concomitant medications/treatments ........................................................................... 45 
7.8.1 
Permitted concomitant treatments (medications and therapies) .......................... 46 
7.8.1.1 
Psoriasis treatments ................................................................................... 46 
7.8.2 
Prohibited concomitant treatments (medications and therapies) ......................... 46 
7.8.3 
Vaccines ............................................................................................................... 48 
7.9 
Blinding........................................................................................................................ 48 
7.9.1 
Procedures for maintaining and breaking the treatment blind ............................. 48 
7.9.1.1 
Maintenance of study treatment blind ....................................................... 48 
7.9.1.2 
Breaking the treatment blind in an emergency situation ........................... 48 
7.10 
Randomization and numbering of subjects .................................................................. 49 
8 
STUDY PROCEDURES BY VISIT ............................................................................... 49 
8.1 
Screening Period/Baseline ........................................................................................... 49 
8.1.1 
Screening ............................................................................................................. 49 
8.1.2 
Baseline (Day 1) .................................................................................................. 51 
8.2 
Double-Blind Treatment Period ................................................................................... 52 
8.2.1 
Week 4 ................................................................................................................. 52 
8.2.2 
Week 8 ................................................................................................................. 53 
8.2.3 
Week 12 ............................................................................................................... 54 
8.2.4 
Week 16 ............................................................................................................... 55 
8.3 
Early Termination Visit ............................................................................................... 57 
8.4 
Safety Follow-Up Visit (20 weeks [-3 days/+7 days] after the final dose) ................. 58 
8.5 
Unscheduled Visits ...................................................................................................... 59 
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9 
ASSESSMENT OF EFFICACY ...................................................................................... 60 
9.1 
Joint assessments ......................................................................................................... 60 
9.1.1 
68/66 joint evaluation for ACR response and verification of Inclusion 
Criterion 5 ............................................................................................................ 60 
9.1.2 
28 joint evaluation for determination of DAS28(CRP) ....................................... 61 
9.2 
ACR20, ACR50, and ACR70 response ....................................................................... 61 
9.3 
Patient’s Global Assessments ...................................................................................... 61 
9.3.1 
Patient’s Global Assessment of Psoriatic Arthritis (PGA-PsA) .......................... 61 
9.3.2 
Patient’s Global Assessment of Arthritis (PGA-arthritis) ................................... 62 
9.4 
Physician’s Global Assessments .................................................................................. 62 
9.4.1 
Physician’s Global Assessment of Psoriatic Arthritis (PhGA-PsA) .................... 62 
9.4.2 
Physician’s Global Assessment of Arthritis (PhGA-Arthritis) ............................ 62 
9.5 
Patient’s Assessment of Arthritis Pain (PtAAP) .......................................................... 62 
9.6 
Health Assessment Questionnaire-Disability Index score (HAQ-DI) ......................... 63 
9.7 
High sensitivity C-reactive protein levels (hs-CRP) .................................................... 63 
9.8 
Evaluation of psoriasis ................................................................................................. 63 
9.8.1 
Body surface area psoriasis (BSA-PSO) ............................................................. 63 
9.8.2 
Psoriasis Area and Severity Index (PASI) ........................................................... 63 
9.8.3 
Investigator’s Global Assessment (IGA) ............................................................. 64 
9.8.4 
Modified Nail Psoriasis Severity Index (mNAPSI) ............................................. 65 
9.9 
Minimal Disease Activity (MDA) and Very Low Disease Activity (VLDA) ............. 65 
9.10 
Disease Activity Index for Psoriatic Arthritis (DAPSA) ............................................. 65 
9.11 
Disease Activity Score-28 based on C-reactive protein (DAS28[CRP]) ..................... 66 
9.12 
Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) ............................... 66 
9.13 
Leeds Enthesitis Index (LEI) ....................................................................................... 66 
9.14 
Spondyloarthritis Research Consortium of Canada (SPARCC) .................................. 66 
9.15 
Leeds Dactylitis Index (LDI) ....................................................................................... 66 
9.16 
Psoriatic Arthritis Quality of Life (PsAQoL) .............................................................. 67 
9.17 
Psoriatic Arthritis Impact of Disease-12 (PsAID-12) .................................................. 67 
9.18 
Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue subscale ......... 67 
9.19 
Short-Form 36-item Health Survey (SF-36) ................................................................ 67 
9.20 
Euro Quality of life 5-Dimensions-3 Level (EQ-5D-3L) ............................................ 68 
9.21 
Work Productivity and Activity Impairment Questionnaire – Specific Health Problem 
(WPAI-SHP) ................................................................................................................ 68 
9.22 
Psoriatic Arthritis Response Criteria (PsARC) ............................................................ 68 
9.23 
Psoriatic Arthritis Disease Activity Score (PASDAS) ................................................ 68 
10 ASSESSMENT OF PHARMACOKINETIC AND PHARMACOGENOMIC 
VARIABLES ................................................................................................................... 69 
10.1 
Pharmacokinetic variable ............................................................................................. 69 
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10.2 
Pharmacogenomic variables ........................................................................................ 69 
11 ASSESSMENT OF IMMUNOLOGICAL VARIABLES ............................................... 70 
12 ASSESSMENT OF SAFETY .......................................................................................... 70 
12.1 
Adverse events ............................................................................................................. 70 
12.1.1 
Definitions ........................................................................................................... 70 
12.1.1.1 
Adverse event ............................................................................................ 70 
12.1.1.2 
Serious adverse event ................................................................................ 71 
12.1.1.3 
Adverse events of special interest ............................................................. 72 
12.1.1.4 
Other safety topics of interest .................................................................... 73 
12.1.2 
Procedures for reporting and recording adverse events ....................................... 73 
12.1.2.1 
Description of adverse events .................................................................... 73 
12.1.2.2 
Rule for repetition of an adverse event...................................................... 73 
12.1.2.3 
Additional procedures for reporting serious adverse events ..................... 74 
12.1.3 
Follow up of adverse events ................................................................................ 74 
12.1.4 
Pregnancy ............................................................................................................ 75 
12.1.5 
Suspected transmission of an infectious agent via a medicinal product .............. 76 
12.1.6 
Overdose of investigational medicinal product ................................................... 76 
12.1.7 
Safety signal detection ......................................................................................... 76 
12.2 
Laboratory measurements ............................................................................................ 76 
12.2.1 
Evaluation of potential drug-induced liver injury................................................ 78 
12.2.1.1 
Consultation with Medical Monitor and local hepatologist ...................... 83 
12.2.1.2 
Immediate action: determination of IMP discontinuation ......................... 83 
12.2.1.3 
Testing: identification/exclusion of alternative etiology ........................... 84 
12.2.1.4 
Follow-up evaluation ................................................................................. 86 
12.3 
Other safety measurements .......................................................................................... 86 
12.3.1 
Vital signs ............................................................................................................ 86 
12.3.2 
Body weight and height ....................................................................................... 87 
12.3.3 
Physical examination ........................................................................................... 87 
12.3.4 
12-lead electrocardiogram ................................................................................... 87 
12.3.5 
Patient Health Questionnaire-9 (PHQ-9) ............................................................. 87 
12.3.6 
Assessment and management of TB and TB risk factors .................................... 87 
12.3.6.1 
Tuberculosis assessment by IGRA ............................................................ 91 
12.3.6.2 
Chest x-ray for tuberculosis ...................................................................... 91 
12.3.6.3 
Tuberculosis questionnaire ........................................................................ 91 
12.3.6.4 
Tuberculosis management ......................................................................... 91 
12.3.7 
Pregnancy testing ................................................................................................. 92 
12.3.8 
Assessment of suicidal ideation and behavior ..................................................... 92 
13 STUDY MANAGEMENT AND ADMINISTRATION ................................................. 93 
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13.1 
Adherence to protocol .................................................................................................. 93 
13.2 
Monitoring ................................................................................................................... 93 
13.2.1 
Definition of source data ..................................................................................... 93 
13.2.2 
Source data verification ....................................................................................... 94 
13.3 
Data handling ............................................................................................................... 94 
13.3.1 
Case Report form completion .............................................................................. 94 
13.3.2 
Database entry and reconciliation ........................................................................ 94 
13.3.3 
Subject Screening and Enrollment log/Subject Identification Code list.............. 95 
13.4 
Termination of the study .............................................................................................. 95 
13.5 
Archiving and data retention ........................................................................................ 95 
13.6 
Audit and inspection .................................................................................................... 96 
13.7 
Good Clinical Practice ................................................................................................. 96 
14 STATISTICS ................................................................................................................... 96 
14.1 
Definition of analysis sets ............................................................................................ 96 
14.2 
General statistical considerations ................................................................................. 97 
14.3 
Planned efficacy analyses ............................................................................................ 97 
14.3.1 
Analysis of the primary and secondary efficacy variables .................................. 97 
14.3.1.1 
Analysis of the primary efficacy variable ................................................. 98 
14.3.1.2 
Analyses of the secondary efficacy variables .......................................... 100 
14.3.2 
Analyses of the other efficacy variables ............................................................ 101 
14.3.3 
Subgroup analyses ............................................................................................. 102 
14.4 
Planned safety analyses.............................................................................................. 103 
14.4.1 
Safety analyses ................................................................................................... 103 
14.5 
Other planned analyses .............................................................................................. 103 
14.5.1 
Pharmacokinetics analyses ................................................................................ 103 
14.5.2 
Immunological analyses .................................................................................... 103 
14.6 
Handling of protocol deviations................................................................................. 103 
14.7 
Handling of dropouts or missing data ........................................................................ 104 
14.8 
Planned interim analysis and data monitoring ........................................................... 105 
14.8.1 
Data monitoring ................................................................................................. 105 
14.8.2 
Interim analysis .................................................................................................. 105 
14.9 
Determination of sample size ..................................................................................... 105 
14.9.1 
Power calculation for primary endpoint ............................................................ 106 
14.9.2 
Power calculations for secondary endpoints ...................................................... 106 
15 ETHICS AND REGULATORY REQUIREMENTS .................................................... 107 
15.1 
Informed consent ....................................................................................................... 107 
15.2 
Subject identification cards ........................................................................................ 108 
15.3 
Institutional Review Boards and Independent Ethics Committees ............................ 108 
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Bimekizumab 
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15.4 
Subject privacy........................................................................................................... 109 
15.5 
Protocol amendments ................................................................................................. 109 
16 FINANCE, INSURANCE, AND PUBLICATION ....................................................... 109 
17 REFERENCES .............................................................................................................. 109 
18 APPENDICES ............................................................................................................... 114 
18.1 
Classification Criteria for Psoriatic Arthritis ............................................................. 114 
18.2 
Protocol Amendment 1 .............................................................................................. 115 
18.3 
Protocol Amendment 2 .............................................................................................. 129 
19 DECLARATION AND SIGNATURE OF INVESTIGATOR ..................................... 141 
20 SPONSOR DECLARATION ........................................................................................ 142 
 
LIST OF TABLES 
Table 5-1: 
Schedule of study assessments......................................................................... 30 
Table 7‒1: 
Prohibited or restricted medications and required wash-out periods ............... 46 
Table 7-2: 
Additional prohibited psoriasis treatments ...................................................... 48 
Table 9-1: 
Swelling and tenderness grading ..................................................................... 61 
Table 9-2: 
Body areas for calculation of percent BSA for PASI ...................................... 64 
Table 9-3: 
Five-point IGA ................................................................................................. 64 
Table 12-1: 
Anticipated SAEs for the population of subjects with PsA ............................. 72 
Table 12-2: 
Laboratory measurements ................................................................................ 78 
Table 12‒3: 
Required investigations and follow-up for PDILI ........................................... 80 
Table 12-4: 
PDILI laboratory measurements ...................................................................... 85 
Table 12-5: 
PDILI information to be collected ................................................................... 86 
Table 18-1: 
CASPAR Criteria ........................................................................................... 114 
 
LIST OF FIGURES 
Figure 5-1: 
Study schematic diagram ................................................................................. 35 
Figure 12-1: 
Schematic diagram of TB test results and study eligibility ............................. 89 
Figure 12‒2: Schematic diagram of TB test results during the study ................................... 90 
Figure 14-1: 
Sequential testing procedure of primary/secondary efficacy endpoints 
(fixed sequence testing procedure) .................................................................. 98 
 
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Bimekizumab 
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LIST OF ABBREVIATIONS 
ACR 
American College of Rheumatology 
AE 
adverse event 
ALP 
alkaline phosphatase 
ALT 
alanine aminotransferase 
ANCOVA 
analysis of covariance 
AS 
ankylosing spondylitis 
AST 
aspartate aminotransferase 
BA 
bioanalytics 
BASDAI 
Bath Ankylosing Spondylitis Disease Activity Index 
bDMARD 
biologic disease modifying antirheumatic drug 
BP 
blood pressure 
BSA 
body surface area 
CASPAR 
Classification Criteria for Psoriatic Arthritis 
CCP 
cyclic citrullinated peptide 
CDMS 
clinical data management system 
CI 
confidence interval 
cDMARD 
conventional disease-modifying antirheumatic drugs 
COVID-19 
coronavirus disease 2019 
COX-2 
cyclooxygenase-2 
CPM 
Clinical Project Manager 
CRO 
contract research organization 
CRP 
C-reactive protein 
CSR 
Clinical Study Report 
CZP 
certolizumab pegol 
DAPSA 
Disease Activity Index for Psoriatic Arthritis 
DAS28(CRP) 
Disease Activity Score-28 based on C-reactive protein 
DIP 
distal interphalangeal  
DMARD 
disease-modifying antirheumatic drug 
DMC 
Data Monitoring Committee 
DNA 
deoxyribonucleic acid 
ECG 
electrocardiogram 
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eCRF 
electronic Case Report Form 
eC-SSRS 
electronic Columbia-Suicide Severity Rating Scale 
EDC 
electronic data capture 
ePRO 
electronic Patient-Reported Outcome 
EQ-5D-3L 
EuroQol-5 Dimensions-3 Level 
ET 
Early Termination 
EudraCT 
European Union Drug Regulating Authorities Clinical Trials 
FACIT 
Functional Assessment of Chronic Illness Therapy 
FAS 
Full Analysis Set 
GCP 
Good Clinical Practice 
GI  
gastrointestinal  
GMP 
Good Manufacturing Practice 
HAQ-DI 
Health Assessment Questionnaire – Disability Index 
HCQ 
hydroxychloroquine 
HCV 
hepatitis C virus 
HDL 
high density lipoprotein 
HIV 
human immunodeficiency virus 
HLA-B27 
human leukocyte antigen B27 
HRQoL 
Health-Related Quality of Life 
HS 
hidradenitis suppurativa 
hs-CRP 
high sensitivity C-reactive protein 
IB 
Investigator’s Brochure 
IBD 
inflammatory bowel disease 
ICF 
Informed Consent form 
ICH 
International Council for Harmonisation 
IEC 
Independent Ethics Committee 
IGA 
Investigator’s Global Assessment 
IGRA 
interferon gamma release assay 
IL 
interleukin 
IMP 
investigational medicinal product 
IRB 
Institutional Review Board 
iv 
intravenous 
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IXRS 
interactive voice or web response system  
LDI 
Leeds Dactylitis Index 
LDL 
low density lipoprotein 
LEF 
leflunomide 
LEI 
Leeds Enthesitis Index 
LN 
natural logarithm 
LTB 
latent tuberculosis 
LTBI 
latent tuberculosis infection 
MAR 
missing at random 
MCMC 
Markov-Chain Monte Carlo 
MCS 
Mental Component Summary 
MDA 
Minimal Disease Activity 
MI 
multiple imputation 
mNAPSI 
modified Nail Psoriasis Severity Index 
mRNA 
messenger ribonucleic acid 
MTX 
methotrexate 
NRI 
Nonresponder Imputation 
NSAID 
nonsteroidal anti-inflammatory drug 
NTMB 
nontuberculous mycobacteria 
OC 
observed case 
OLE 
open-label extension  
PASDAS 
Psoriatic Arthritis Disease Activity Score 
PASI 
Psoriasis Area and Severity Index 
PCS 
Physical Component Summary 
PD 
pharmacodynamics 
PDILI 
potential drug-induced liver injury 
PFS 
prefilled syringe 
PGADA 
Patient’s Global Assessment of Disease Activity 
PGA-Arthritis 
Patient’s Global Assessment of Arthritis 
PGA-PsA 
Patient’s Global Assessment of Psoriatic Arthritis 
PhGADA 
Physician’s Global Assessment of Disease Activity 
PhGA-arthritis 
Physician’s Global Assessment of Arthritis 
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PhGA-PsA 
Physician’s Global Assessment of Psoriatic Arthritis 
PHQ-9 
Patient Health Questionnaire-9 
PK 
pharmacokinetic 
PK-PPS 
Pharmacokinetics Per-Protocol Set 
PPS 
Per-Protocol Set 
PS 
Patient Safety 
PsA 
psoriatic arthritis 
PsAID-12 
Psoriatic Arthritis Impact of Disease-12 
PsAQoL 
Psoriatic Arthritis Quality of Life 
PsARC 
Psoriatic Arthritis Response Criteria  
PSO 
psoriasis 
PtAAP 
Patient’s Assessment of Arthritis Pain 
Q4W 
every 4 weeks 
RA 
rheumatoid arthritis 
RNA 
ribonucleic acid 
RS 
Randomized Set 
SAE 
serious adverse event 
SAP 
Statistical Analysis Plan 
sc 
subcutaneous(ly) 
SD 
standard deviation 
SF-36 
Short-Form 36-item Health Survey 
SFU 
Safety Follow-Up 
SJC 
swollen joint count 
SOP 
Standard Operating Procedure 
SPARCC 
Spondyloarthritis Research Consortium of Canada 
SS 
Safety Set 
SSZ 
sulfasalazine 
TB 
tuberculosis 
TEAE 
treatment-emergent adverse event 
TJC 
tender joint count 
TNF 
tumor necrosis factor 
TNFα 
tumor necrosis factor alpha 
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TNFα-IR 
TNFα-inadequate responders 
UC 
ulcerative colitis 
ULN 
upper limit of normal 
VAS 
visual analog scale 
VLDA 
Very Low Disease Activity 
WPAI-SHP 
Work Productivity and Activity Impairment Questionnaire – Specific 
Health Problem 
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1 
SUMMARY 
This is a Phase 3, multicenter, randomized, double-blind, placebo-controlled study to evaluate 
the efficacy and safety of bimekizumab in subjects with active psoriatic arthritis (PsA). To be 
eligible to participate in this study, subjects must be adults with a diagnosis of active PsA based 
on the Classification Criteria for Psoriatic Arthritis (CASPAR), and have disease with tender 
joint count (TJC) ≥3 and swollen joint count (SJC) ≥3, as well as an inadequate response (lack of 
efficacy after at least 3 months of therapy at an approved dose) or intolerance to treatment with 
1 or 2 tumor necrosis factor alpha (TNFα) inhibitors for either PsA or psoriasis (PSO). 
The primary objective is to demonstrate the efficacy of bimekizumab administered 
subcutaneously (sc) every 4 weeks (Q4W) for 16 weeks compared with placebo in the treatment 
of prior TNFα-inadequate responder (TNFα-IR) (inadequate or intolerance to prior 
TNFα inhibitors) subjects with active PsA, as assessed by the American College of 
Rheumatology (ACR) 50% response. The secondary efficacy and safety objectives of the study 
are listed in Section 3.2, and other objectives are listed in Section 3.3. 
The primary efficacy variable for this study is the ACR50 at Week 16. The secondary and other 
efficacy variables are listed in Section 4.2.1 and Section 4.3.1, respectively. 
Safety variables are listed in Section 4.2.2 (secondary) and Section 4.3.2 (other). The 
pharmacokinetic (PK), and pharmacogenomic variables are listed in Section 4.3.3, and 
Section 4.3.4, respectively. The immunological variable is listed in Section 4.3.5.  
PA0011 will evaluate the efficacy and safety of bimekizumab 160mg sc Q4W in adult subjects 
with active PsA. The dose regimen was selected based on available efficacy data, safety data, 
and PK/pharmacodynamics (PD) modeling.  
The overall study design consists of a Screening Period (≥14 days to ≤35 days), a 16-week 
placebo-controlled Double-Blind Treatment Period, and a Safety Follow-Up 
(SFU) Visit, 20 weeks after the final dose of investigational medicinal product (IMP) (for 
subjects not entering the open-label extension [OLE] study or who discontinue early, including 
those withdrawn from IMP). The maximum study duration per subject will be up to 37 weeks.  
Subjects completing Week 16 are eligible for enrollment in an OLE study to continue to receive 
bimekizumab. 
Approximately 390 subjects will be randomly assigned in a 2:1 ratio to the following treatment 
groups: bimekizumab 160mg sc Q4W (260 subjects), and placebo (130 subjects). The planned 
number of study sites is approximately 89.  
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2 
INTRODUCTION 
2.1 
Psoriatic arthritis 
Psoriatic arthritis is a chronic inflammatory musculoskeletal disorder, which occurs in 
approximately 6% to 41% of people affected by PSO (Ogdie and Weiss, 2015). A substantial 
proportion of subjects have polyarthritis (McHugh et al, 2003). These disorders are distinct from 
rheumatoid arthritis (RA), the prototypical inflammatory arthritis, and generally have an earlier 
onset, distal interphalangeal (DIP) joint involvement, asymmetric distribution, dactylitis 
(inflammation of the whole digit), enthesitis (inflammation at the site of tendon insertion into 
bone), spinal involvement, and an association with the human leukocyte antigen (HLA)-B27 
allele.  
Previous work has implicated various isoforms of the interleukin (IL)-17 cytokine family in the 
pathophysiology of PSO and of PsA (Raychaudhuri et al, 2012; Fujishima et al, 2010; 
Watanabe et al, 2009; Harper et al, 2009; Johansen et al, 2009). Numbers of IL-17A-positive 
cells are increased and localized in psoriatic skin lesions (Fujishima et al, 2010; 
Watanabe et al, 2009; Harper et al, 2009; Johansen et al, 2009), and IL-17A and IL-17F are 
overexpressed in the serum and skin lesions of subjects with PSO (Johansen et al, 2009), while 
IL-17F in particular is a key inflammatory cytokine contributing to PSO pathology 
(Fujishima et al, 2010; Watanabe et al, 2009). Cluster of differentiation (CD) 4 + T helper 17 
(Th17) cells, IL-17A, and IL-17 receptor A (IL-17-RA) have recently been shown to play a role 
in PsA (Raychaudhuri et al, 2012). Anti-IL-17 antibodies have been shown to be effective 
treatments for PSO (Papp et al, 2012; Leonardi et al, 2012; Hueber et al, 2010) and have also 
shown activity in subjects with RA, PsA, and ankylosing spondylitis (AS) (McInnes et al, 2014; 
Mease et al, 2015; Hueber et al, 2010; Genovese et al, 2010). Taken together, these data suggest 
that inhibition of both IL-17A and IL-17F could be therapeutically effective in subjects with 
PSO, PsA, and axial spondyloarthritis. 
2.1.1 
Psoriatic arthritis epidemiology 
Psoriatic arthritis is usually diagnosed years after PSO appears. A substantial proportion of 
subjects have polyarthritis (Gladman, 2015; McHugh et al, 2003). More than 50% of patients 
with PsA experience progressive, erosive arthritis that is often accompanied by pain, fatigue, and 
functional impairment. The combination of joint and skin manifestations of PsA can have a 
profound impact on patient function, well-being, and Health-Related Quality of Life (HRQoL). 
The functional impairments are also associated with significant direct health care costs and 
substantial work-related disability, including a lower rate of employment (Lee et al, 2010, 
Salaffi et al, 2009). 
2.1.2 
Current treatments for psoriatic arthritis 
Disease-modifying anti-rheumatic drugs (DMARDs) and biological agents targeting tumor 
necrosis factor alpha (TNFα), IL-17, and IL-12/23 are effective for the treatment of PsA 
(Kavanaugh et al, 2012; Kavanaugh et al, 2009; Gottlieb et al, 2009; Gladman et al, 2007; 
Genovese et al, 2007; Kavanaugh et al, 2006; Antoni et al, 2005a; Antoni et al, 2005b; 
Mease et al, 2005; Mease et al, 2004; McInnes et al, 2015; Mease et al, 2015). Current treatments 
include DMARDs (hydroxychloroquine, azathioprine, cyclosporine, cyclophosphamide, 
mycophenolic acid, mycophenolate mofetil, sulfasalazine [SSZ], tofacitinib, apremilast, 
methotrexate [MTX], and leflunomide [LEF]), IL-17A inhibitor (secukinumab), and 
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TNFα inhibitors (infliximab, adalimumab, etanercept, golimumab, and certolizumab pegol 
[CZP]). However, some subjects are not responsive to these treatments (defined as achieving 
ACR20 response criteria), do not maintain a clinical response, or have contraindications or 
intolerance to these agents. The long-term goals of therapy include improvement in symptoms of 
the disease, psoriatic plaque clearance, inhibition of disease progression, and prevention of bone 
destruction. 
2.2 
Bimekizumab 
Bimekizumab (UCB4940) is an engineered, humanized full-length monoclonal antibody of the 
immunoglobulin G1 (IgG1) subclass of approximately 150,000 Dalton, which is expressed in a 
genetically engineered Chinese Hamster Ovarian (CHO) cell line. Bimekizumab has high affinity 
for human IL-17A and human IL-17F, and selectively and potently inhibits the activity of both 
isoforms in vitro. Interleukin-17A and IL-17F are key proinflammatory cytokines believed to 
play important roles in autoimmune and inflammatory diseases. Interleukin-17A has been shown 
to have a role in pathogenesis of several autoimmune disorders and IL-17F has been increasingly 
recognized to contribute to the pathogenesis of a number of inflammatory diseases, including 
PSO, ulcerative colitis, asthma, AS, PsA, and RA (Raychaudhuri et al, 2012; 
Fujishima et al, 2010; Watanabe et al, 2009).  
While anti-IL-17A antibodies have demonstrated efficacy in subjects with PSO, PsA, and AS, 
there is currently no therapeutic approach available that fully inhibits the activity of IL-17F. 
Bimekizumab selectively and potently inhibits the activity of both IL-17A and IL-17F isoforms 
in vitro. Therefore, it permits an evaluation of the potential for additional efficacy, which may be 
conferred by dual inhibition of both cytokines in patients with diseases in which both cytokines 
are active. Furthermore, a proof-of-concept study (PA0007) with bimekizumab in subjects with 
moderate to severe PsA demonstrated a strong efficacy signal that warrants further exploration of 
bimekizumab in this indication. A Phase 2b, dose-ranging study (PA0008) was designed to 
investigate the efficacy and safety of various bimekizumab dose regimens in subjects with active 
PsA. The current Phase 3, randomized, double-blind, placebo-controlled confirmatory study 
(PA0011) is designed to investigate the efficacy and safety of bimekizumab in subjects with 
active PsA. 
2.2.1 
Nonclinical 
There is increasing evidence of the role of IL-17F in various inflammatory diseases. 
Simultaneous inhibition of IL-17A and IL-17F has been shown to be more efficacious than 
inhibition of IL-17A alone in in vitro models. Intravenously or sc administered bimekizumab 
was well tolerated in repeat-dose toxicology studies in Cynomolgus monkeys with dosing up to 
200mg/kg/week for up to 26 weeks. The findings of note varied from study to study but were all 
compatible with decreased muco-epidermal immunity induced by the inhibition of IL-17A and F 
signaling. They consisted of diarrhea-related to infectious enteritis, asymptomatic proliferation of 
a protozoan commonly found in the Cynomolgus monkey, Balantidium coli, superficial 
dermatitis associated with increased bacterial load on the skin (mainly gram-positive cocci, 
including Staphylococcus aureus), and abscesses.  
Infection-related safety findings in a nonhuman primate can be highly variable from study to 
study and have limited ability to accurately predict the incidence and type of infection that can be 
expected in humans, especially because nonhuman primates bear different commensal flora and 
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show different sensitivity to different pathogens. Immunomodulators can increase the 
susceptibility of monkeys to potential pathogens that are endemic in nonhuman primate 
populations and usually remain clinically undetectable or are mild and self-limiting in 
immunocompetent animals. Moreover, infections associated with the gastrointestinal (GI) tract 
that result in chronic enterocolitis are a persistent and widespread colony problem in nonhuman 
primates, often multifactorial in origin.  
The nonclinical studies have highlighted the already known risk of infection linked to decreased 
muco-epidermal immunity that needs to be carefully monitored in the clinic but are unlikely to 
predict the risk of infection in humans based on dose and exposure for the aforementioned 
reasons. To date, similar findings have not been seen in studies in humans. 
Results from the embryofetal and postnatal study conducted in the Cynomolgus monkey indicate 
no effects of bimekizumab on the gestation, gestation duration, or the parturition of pregnant 
females. No bimekizumab-related effects were noted in infants at birth, during postnatal 
development, or on infant survival rate. Toxicokinetic data confirmed dose-related exposure of 
maternal animals during the pregnancy and the lactation phase, and of infants at birth and during 
the postnatal phase. 
Additional information on the nonclinical data for bimekizumab is available in the current 
version of the Investigator’s Brochure (IB). 
2.2.2 
Clinical 
2.2.2.1 
Completed studies 
In the overall bimekizumab development program, the following clinical studies in healthy 
volunteers and subjects with PSO, RA, PsA, AS, ulcerative colitis (UC), and hidradenitis 
suppurativa (HS) have been completed: 
• UP0008 was a Phase 1, first-in-human study in subjects with mild to moderate PSO.  
• RA0124 and UP0031 were 2 Phase 1, bioavailability studies in healthy subjects. 
• UP0033 was a Phase 1, open-label, multicenter, randomized, parallel-group, 3-arm, single-
dose bioequivalence study of bimekizumab injected sc either by a prefilled syringe (PFS) or 
by an auto-injector in adult healthy subjects. 
• UP0034 is a Phase 1, open-label, randomized, parallel-group, single-dose study to evaluate 
the antibody response of influenza vaccination following concomitant exposure to 
bimekizumab in adult healthy subjects. 
• UP0074 was a Phase 1, open-label, randomized, parallel-group, single-dose study to evaluate 
the PK, safety, and tolerability of bimekizumab given as 2x1mL or 1x2mL sc administration 
in healthy subjects. 
• PA0007 was a Phase 1b study in subjects with moderate to severe PsA. 
• UP0042 was a Phase 1, PK study in healthy Japanese and Caucasian subjects. 
• RA0123 was a Phase 2a study evaluating safety, PK, PD, and efficacy in subjects with 
moderate to severe RA who received bimekizumab as an add-on therapy to CZP. 
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• UC0011 was a Phase 2a, multinational, multicenter, subject- and Investigator-blind, 
randomized, placebo-controlled study to evaluate the efficacy, safety, tolerability, and PK of 
bimekizumab in adult subjects with moderate to severe active UC (discontinued study). 
• PS0016 was a Phase 2a study evaluating the time course of Psoriasis Area and Severity Index 
(PASI) response, safety, and PK in subjects with moderate to severe chronic plaque PSO. 
PS0018 was the corresponding Phase 2 extension study. 
• PS0018 was a Phase 2 OLE study evaluating the long-term safety, tolerability, and efficacy 
of bimekizumab in subjects who completed PS0016. 
• PS0010 was a Phase 2b, placebo-controlled, dose-ranging study evaluating safety, efficacy, 
PK, and PD in subjects with moderate to severe PSO. 
• PS0011 was a Phase 2b, multicenter, 48-week, double-blind, parallel-group, extension study 
to assess the long-term safety, tolerability, and efficacy of bimekizumab in adult subjects 
with moderate to severe chronic plaque PSO who completed PS0010. 
• PS0008 is a Phase 3, multicenter, randomized, double-blind, parallel-group, active-
comparator-controlled study to evaluate the efficacy and safety of bimekizumab in adult 
subjects with moderate to severe chronic plaque PSO. 
• PS0009 is a Phase 3 randomized, double-blind, placebo- and active comparator-controlled 
study to evaluate the efficacy and safety of bimekizumab administered sc to adult subjects 
with moderate to severe plaque PSO. 
• PS0013 is a Phase 3, multicenter, randomized withdrawal, double-blind, placebo-controlled 
study to evaluate the efficacy and safety of bimekizumab in adult subjects with moderate to 
severe chronic plaque PSO. 
• PA0008 was a Phase 2b study evaluating the efficacy and safety in subjects with active PsA. 
• AS0008 was a Phase 2b, placebo-controlled study evaluating the efficacy and safety of 
bimekizumab in subjects with active AS. 
• HS0001 was a Phase 2 study to evaluate the safety, efficacy, and PK of bimekizumab in 
subjects with moderate to severe HS. 
To evaluate treatment in subjects with PsA, bimekizumab has also been investigated in a 
Phase 1b, proof of concept, randomized, placebo-controlled, multiple dose study (PA0007). The 
primary objective of PA0007 was to assess the safety and PK of multiple dose administration of 
iv bimekizumab in subjects with PsA. Four active doses and a placebo were tested. Drug was 
administered as a loading dose at Week 1, and 2 additional doses were administered at Week 4 
and Week 7. In each treatment group, subjects received a total of 3 doses of bimekizumab, 
administered every 3 weeks as shown below: 
• 80mg loading dose followed by 40mg at Weeks 4 and 7 
• 160mg loading dose followed by 80mg at Weeks 4 and 7 
• 240mg loading dose followed by 160mg at Weeks 4 and 7 
• 560mg loading dose followed by 320mg at Weeks 4 and 7 
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The results of this study demonstrated that all doses of bimekizumab were well tolerated and 
there were no unexpected clinically relevant safety findings. 
Infections (mostly nasopharyngitis) were the most commonly reported events in both the active 
treatment and the placebo group. None of the infections were considered serious or required 
treatment with antibiotics. Two subjects in the active treatment group experienced 1 local 
candida infection each (oropharyngitis and vulvovaginitis, respectively) that were nonserious and 
resolved with topical therapy. There was a potential reduction in mean neutrophil count in the 
active treatment group, although this drop was not clinically relevant and a clear relationship 
with dose or time was not evident. Some increases in liver function tests were reported, but none 
had a clear relationship to exposure to IMP. The exploratory analysis showed clinically relevant 
improvement in activity of PsA and in skin involvement in those subjects with concomitant 
active psoriatic lesions. 
PA0008 was a Phase 2b, placebo-controlled study to evaluate the efficacy, safety, tolerability, 
PK, PD, and immunogenicity of bimekizumab in subjects with active PsA. The primary 
objective of PA0008 was to assess the dose response based on the efficacy of bimekizumab 
administered sc Q4W (monthly) for 12 weeks in the treatment of subjects with active PsA. 
During the 12-week Double-Blind Period, subjects were randomized 1:1:1:1:1 (stratified by 
region and prior tumor necrosis factor [TNF] inhibitor exposure) to receive the following blinded 
IMP regimens. The enrollment of TNF inhibitor-experienced subjects was planned to be limited 
to approximately 30% of the total study population (actual enrollment was 18.9% of all subjects). 
• Placebo 
• Bimekizumab 16mg administered sc Q4W 
• Bimekizumab 160mg administered sc Q4W 
• Bimekizumab 320mg administered sc Q4W 
• Bimekizumab 320mg loading dose followed by 160mg administered sc starting at Week 4 
and Q4W thereafter  
After the 12-week Double-Blind Period, subjects entered the 36-week Dose-Blind Period. At the 
Week 12 Visit, subjects were allocated to bimekizumab treatment regimens: 160mg Q4W or 
320mg Q4W. 
The results of this study demonstrated a statistically significant dose response in the primary 
efficacy variable (ACR50 response at Week 12), and the dose response was linear for 
bimekizumab doses up to 160mg. The results of all secondary efficacy endpoints (ACR20, 
ACR70, PASI75, and PASI90 response at Week 12) were consistent with and supported the 
findings of the primary endpoint. All bimekizumab doses were associated with a greater response 
compared with placebo. 
In PA0008, all doses of bimekizumab were well tolerated, and there were no unexpected 
clinically relevant safety findings. During the overall study, the most commonly reported adverse 
events (AEs) in subjects treated with bimekizumab were nasopharyngitis (12.3%), upper 
respiratory tract infection (10.3%), respiratory tract infection (5.9%), and pharyngitis (5.4%); all 
other AEs were reported by <5.0% of subjects. There was no apparent relationship to 
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bimekizumab dose with regard to the incidence of treatment-emergent adverse events (TEAEs). 
Eight subjects (3.9%) had serious adverse events (SAEs) in bimekizumab arms, and no SAE (by 
preferred term) was reported by more than 1 subject. Eight subjects (3.9%) discontinued due to a 
TEAE. 
Additional information on the clinical data for bimekizumab is available in the current version of 
the IB. 
2.2.2.2 
Ongoing studies 
The following studies of bimekizumab are ongoing:  
• PS0014 is a Phase 3, long-term extension study for eligible subjects from the Phase 3 PSO 
feeder studies to assess the safety, tolerability, and efficacy of bimekizumab. 
− DV0002 and DV0006 are multicenter, randomized, open-label studies to evaluate the 
safe and effective use of the prefilled safety syringe or the auto-injector for the sc 
self-injection of bimekizumab solution by subjects with moderate to severe PSO. 
DV0002 and DV0006 are substudies of PS0014; DV0002 is being conducted in North 
America, and DV0006 is being conducted in the EU and Japan. 
• PS0015 is a Phase 3b, randomized, double-blind, secukinumab-controlled, parallel-group 
study to evaluate the efficacy and safety of bimekizumab administered sc to subjects with 
moderate to severe chronic plaque PSO. 
• PA0009 is a Phase 2b, long-term extension study for eligible subjects from PA0008 to assess 
the safety, tolerability, and efficacy of bimekizumab. 
• PA0010 is a Phase 3, multicenter, randomized, double-blind, placebo-controlled study 
evaluating the efficacy and safety of bimekizumab in the treatment of subjects with active 
PsA. 
• PA0012 is a Phase 3, multicenter, OLE study to assess the long-term safety, tolerability, and 
efficacy of bimekizumab in the treatment of subjects with active PsA who complete PA0010 
or PA0011. 
− DV0004 is a multicenter, randomized, open-label study to evaluate the safe and effective 
use of the prefilled safety syringe or auto-injector for the sc self-injection of 
bimekizumab solution by subjects with active PsA. DV0004 is a substudy of PA0012. 
• AS0009 is a Phase 2b, long-term extension study for eligible subjects from AS0008 to assess 
the safety, tolerability, and efficacy of bimekizumab.  
• AS0010 is a Phase 3, multicenter, randomized, double-blind, placebo-controlled study 
evaluating the efficacy and safety of bimekizumab in subjects with active nonradiographic 
axial spondyloarthritis. 
• AS0011 is a Phase 3, multicenter, randomized, double-blind, placebo-controlled study 
evaluating the efficacy and safety of bimekizumab in subjects with active AS. 
• AS0014 is a Phase 3, multicenter, OLE study to assess the long-term safety, tolerability, and 
efficacy of bimekizumab in the treatment of subjects who complete AS0010 or AS0011. 
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• AS0013 is a Phase 2a, active-controlled study evaluating the efficacy and safety of 
bimekizumab compared with CZP in subjects with active AS. 
• HS0003 and HS0004 are Phase 3, multicenter, randomized, double-blind, placebo-controlled 
studies evaluating the efficacy and safety of bimekizumab in subjects with moderate to 
severe HS. 
• HS0005 is a Phase 3, multicenter, OLE study to assess the long-term safety, tolerability, and 
efficacy of bimekizumab in the treatment of subjects who complete HS0003 or HS0004. 
Additional information on the clinical data for bimekizumab is available in the current version of 
the IB. 
3 
STUDY OBJECTIVES 
3.1 
Primary objective 
The primary objective is to demonstrate the clinical efficacy of bimekizumab administered sc 
Q4W for 16 weeks compared with placebo in the treatment of TNFα-IR subjects with active 
PsA, as assessed by the ACR50 response. 
3.2 
Secondary objectives 
The secondary objectives of the study are as follows: 
• To assess the efficacy of bimekizumab compared with placebo  
• To assess the safety and tolerability of bimekizumab 
• To assess the impact of bimekizumab on patient-reported quality of life 
• To assess the impact of bimekizumab on skin PSO in the subgroup of affected subjects at 
Baseline 
• To assess the impact of bimekizumab on functional improvement  
3.3 
Other objectives 
Other objectives are as follows: 
• To assess the immunogenicity of bimekizumab 
• To assess the impact of bimekizumab on extra-articular disease manifestations (dactylitis, 
enthesitis) 
• To assess nail PSO in the subgroup of affected subjects at Baseline 
• To explore the exposure-response relationship of bimekizumab 
• To assess the impact of bimekizumab treatment on axial disease 
• To assess the effect of bimekizumab on gene and protein expression, and explore the 
relationship between genomic, genetic, and proteomic biomarkers and disease biology, drug 
treatment and inflammatory and immune responses (from consenting subjects who agree to 
participate in the biomarkers substudy) 
• To assess the impact of bimekizumab on social life and work productivity 
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4 
STUDY VARIABLES 
4.1 
Efficacy variables 
4.1.1 
Primary efficacy variable 
The primary efficacy variable for this study is the ACR50 response at Week 16. 
4.2 
Secondary variables 
4.2.1 
Secondary efficacy variables 
The secondary efficacy variables for this study are as follows: 
• Change from Baseline in Health Assessment Questionnaire—Disability Index (HAQ-DI) at 
Week 16 
• PASI90 response at Week 4 and Week 16 in the subgroup of subjects with PSO involving at 
least 3% BSA at Baseline 
• Change from Baseline in the Short-Form 36-item Health Survey (SF-36) Physical 
Component Summary (PCS) score at Week 16 
• Minimal Disease Activity (MDA) response at Week 16 
• ACR20 response at Week 16 
• ACR70 response at Week 16 
• Proportion of subjects with an Investigator Global Assessment (IGA) score of 0 (clear) or 
1 (almost clear) AND at least a 2-grade reduction from Baseline at Week 4 and Week 16 in 
the subset of subjects with psoriatic skin lesions at Baseline  
• Change from Baseline in the Patient’s Assessment of Arthritis Pain (PtAAP) at Week 16 
• Change from Baseline in Psoriatic Arthritis Impact of Disease-12 (PsAID-12) total score at 
Week 16  
4.2.2 
Secondary safety variables 
Secondary safety variables to be assessed are as follows: 
• Incidence of TEAEs 
• Incidence of treatment-emergent SAEs 
• Treatment-emergent adverse events leading to withdrawal from IMP  
4.3 
Other variables 
4.3.1 
Other efficacy variables 
Other efficacy variables will be assessed as specified in Table 5-1 (all time points not specified 
in Section 4.1.1 or Section 4.2.1 are exploratory):  
• Time to ACR20, ACR50, and ACR70 response from Baseline (Day 1)  
• ACR20, ACR50, and ACR70 response  
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• PASI75, PASI90 and PASI100 response in the subgroup of subjects with PSO involving at 
least 3% BSA at Baseline 
• Composite endpoint composed of ACR50 and PASI90 response in subjects with PSO 
involving at least 3% BSA at Baseline 
• Composite endpoint composed of ACR50 and PASI100 response in subjects with PSO 
involving at least 3% BSA at Baseline 
• Proportion of Psoriatic Arthritis Response Criteria (PsARC) responders 
• Psoriatic Arthritis Disease Activity Score (PASDAS) categories 
• Change from Baseline in the PASDAS  
• MDA response 
• Very Low Disease Activity (VLDA) response 
• Proportion of subjects with an IGA score of 0 (clear) or 1 (almost clear) AND at least a 
2-grade reduction from Baseline in the subset of subjects with psoriatic skin lesions at 
Baseline 
• Disease Activity Index for Psoriatic Arthritis (DAPSA) score categories 
• Change from Baseline in DAPSA score 
• Change from Baseline in the Disease Activity Score-28 based on C-reactive protein 
(DAS28[CRP]) 
• Change from Baseline in all individual ACR core components: 
− SJC 
− TJC 
− HAQ-DI  
− PtAAP  
− Physician’s Global Assessment of Psoriatic Arthritis (PhGA-PsA)  
− Patient’s Global Assessment of Psoriatic Arthritis (PGA-PsA) 
− High sensitivity C-reactive protein (hs-CRP) 
• Enthesitis-free state based on the Leeds Enthesitis Index (LEI) in the subgroup of subjects 
with enthesitis at Baseline 
• Change from Baseline in the LEI in the subgroup of subjects with enthesitis at Baseline 
• Enthesitis-free state based on the Spondyloarthritis Research Consortium of Canada 
(SPARCC) index in the subgroup of subjects with enthesitis at Baseline 
• Change from Baseline in SPARCC index in the subgroup of subjects with enthesitis at 
Baseline 
• Dactylitis-free state based on the Leeds Dactylitis Index (LDI) in the subgroup of subjects 
with dactylitis at Baseline 
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• Change from Baseline in the LDI in the subgroup of subjects with dactylitis at Baseline 
• Proportion of subjects with a decrease of HAQ-DI from Baseline of at least 0.35 in those 
subjects with HAQ-DI>0.35 at Baseline 
• Change from Baseline in the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) 
in the subgroup of subjects with axial involvement defined by a score of ≥4 at Baseline 
• Change from Baseline in the modified Nail Psoriasis Severity Index (mNAPSI) score in the 
subgroup of subjects with psoriatic nail disease at Baseline 
• Change from Baseline in PsAID-12 total score 
• Change from Baseline in the individual domain scores of PsAID-12 
• Proportion of subjects achieving PsAID-12 total score ≤4 
• Proportion of PsAID-12 responders (decrease from Baseline in PsAID-12 total score ≥3) in 
subjects with PsAID-12 total score >3 at Baseline 
• Change from Baseline in the Psoriatic Arthritis Quality of Life (PsAQoL) total score 
• Change from Baseline in the SF-36 PCS and SF-36 Mental Component Summary (MCS) 
scores, as well as the 8 domain scores (Physical Functioning, Role Physical, Bodily Pain, 
General Health, Vitality, Social Functioning, Role Emotional, and Mental Health) 
• Change from Baseline in Functional Assessment of Chronic Illness Therapy (FACIT)-
Fatigue subscale score 
• Proportion of FACIT-Fatigue subscale responders (subjects with a minimum clinically-
important difference for FACIT-Fatigue subscale score, defined as an increase of ≥4) in 
subjects with FACIT-Fatigue subscale score ≤48 at Baseline 
• Change from Baseline in Work Productivity and Activity Impairment Questionnaire–Specific 
Health Problem (WPAI-SHP) v2.0 adapted to PsA scores 
• Responses to the EuroQol-5D-3-Level (EQ-5D-3L) dimensions 
• Change from Baseline in EQ-5D-3L Visual Analog Scale (VAS) scores 
• Change from Baseline in Physician's Global Assessment of Arthritis (PhGA-Arthritis) 
• Change from Baseline in Patient's Global Assessment of Arthritis (PGA-Arthritis) 
4.3.2 
Other safety variables 
Other safety variables to be assessed are: 
• Change from Baseline in vital signs (blood pressure [BP], temperature, and pulse rate) 
• Standard 12-lead electrocardiogram (ECG) results 
• Change from Baseline in clinical laboratory values (hematology, biochemistry and 
urinalysis) 
• Change from Baseline in Patient Health Questionnaire-9 (PHQ-9) 
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Physical examination findings considered clinically significant changes since the physical 
examination at the Screening Visit will be recorded as AEs. 
4.3.3 
Pharmacokinetic variable 
The PK variable is the plasma concentration of bimekizumab. 
4.3.4 
Pharmacogenomic variables 
Additional blood samples will be collected from subjects who consent to participate in the 
substudy at specific time points and stored at -80°C for up to 20 years. 
Genomic, genetic, epigenetic, proteins, and metabolite biomarkers may be measured to evaluate 
the relationship with response to treatment with bimekizumab, psoriatic arthritis disease biology, 
and inflammatory and immune response processes. The nature and format of these tentative 
substudy analyses will be determined when the results of the main study are made available. 
The candidate exploratory variables are the blood or blood derivative (eg, serum) concentrations 
of cytokines and chemokines of relevance to IL-17A/F signaling pathway and psoriatic arthritis 
biology. Additional variables may include but will not be limited to serum complement 
concentrations. 
4.3.5 
Immunological variables 
The immunological variables are the anti-bimekizumab antibody status and the 
treatment-emergent antibody positivity derived from anti-drug antibody assays. 
5 
STUDY DESIGN 
5.1 
Study description 
This is a Phase 3, multicenter, randomized, double-blind, placebo-controlled study to evaluate 
the efficacy and safety of bimekizumab in subjects with active PsA. To be eligible to participate 
in this study, subjects must be adults with a diagnosis of active PsA based on the CASPAR 
criteria, and have disease with TJC ≥3 and SJC ≥3, as well as an inadequate response (lack of 
efficacy after at least 3 months of therapy at an approved dose) or intolerance to treatment with 
1 or 2 TNFα inhibitors for either PsA or PSO. Detailed inclusion and exclusion criteria are 
presented in Section 6.1 and Section 6.2, respectively. 
The study will include 3 periods: a Screening Period (≥14 days to ≤35 days), a Double-Blind 
Treatment Period (16 weeks), and a Safety Follow-Up Period (20 weeks after the final dose of 
IMP). The maximum study duration per subject will be up to 37 weeks. 
Eligible subjects will be randomized 2:1 to receive 1 of 2 blinded treatments (bimekizumab 
160mg sc Q4W or placebo) and will remain on their allowable background medication. Details 
of the Treatment Period are provided in Section 5.3. 
Subjects completing Week 16 and meeting eligibility criteria are eligible for enrollment in an 
OLE study to continue to receive bimekizumab.  
A final analysis of all available data will be undertaken after all randomized subjects have 
completed 16 weeks of treatment or have been withdrawn from the study. The purpose of this 
analysis is to compare the efficacy and safety of the 2 treatment arms. For subjects who are 
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ineligible for the OLE study at Week 16, a follow up analysis will be undertaken after the 
SFU Visit.  
Additional details for data monitoring in this study are provided in Section 14.8.1. A detailed 
schedule of study assessments is presented in Table 5-1 and a study schematic diagram is 
presented in Figure 5-1.  
5.2 
Screening Period/Baseline 
The Screening Period will last for a minimum duration of 14 days and a maximum duration of 
35 days and will involve obtaining laboratory data and verifying that the doses of nonsteroidal 
anti-inflammatory drugs (NSAIDs) or permitted DMARDs, if used to treat PsA, are stable. The 
Screening Period will also enable washout of any medications not permitted for use during the 
study.  
5.2.1 
Within-study rescreening/retesting requirements 
Rules for rescreening or repetition of screening tests within the study are listed below: 
• Subjects who fail to meet the eligibility criteria for PHQ-9, electronic Columbia-Suicide 
Severity Rating Scale (eC-SSRS), or the tuberculosis (TB) questionnaire are not allowed to 
be rescreened. 
The Medical Monitor must be contacted for confirmation of rescreening/retesting in all other 
cases. 
• Subjects who initially fail to meet selected eligibility criteria (eg, documented completion of 
latent tuberculosis infection [LTBI] prophylactic therapy) may be rescreened. 
• Subjects for whom eligibility assessments could not be completed as planned (eg, for 
technical reasons) within the defined Screening Period of 35 days may be rescreened.  
• Subjects with individual laboratory screening tests for which the results are exclusionary, can 
be retested.  
Of note, repetition of laboratory screening tests within the Screening Period is permitted for 
technical reasons (eg, frozen sample, expired laboratory kit) without contacting the Medical 
Monitor. 
5.3 
Treatment Period 
5.3.1 
Double-Blind Treatment Period 
During the Double-Blind Treatment Period, subjects will be randomized 2:1 (stratified by region 
and prior TNFα inhibitor exposure [inadequate response to 1 or 2 prior TNFα inhibitors, or 
intolerance to TNFα inhibitors]) to receive 1 of 2 blinded treatment regimens. 
Investigational medicinal product treatment details are provided in Section 7.2. 
Visit windows of ±3 days are allowed from the first dose at all visits through Week 16. The visit 
window is relative to the Day 1 (Baseline) Visit.  
Bimekizumab and placebo will be administered sc by unblinded study personnel at the clinical 
site. 
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The time between IMP doses should be ≥21 days and ≤35 days during the Double-Blind 
Treatment Period. The Double-Blind Treatment Period is 16 weeks in duration. 
Subjects discontinuing IMP during the Double-Blind Treatment Period will return for all 
scheduled visits through Week 16 and the SFU Visit (20 weeks after the final dose of IMP) as 
applicable (Section 8.4). Subjects withdrawing from the study will have an Early 
Termination (ET) Visit and a SFU Visit 20 weeks after the final dose of IMP, as applicable.  
5.4 
Safety Follow-Up Visit 
All subjects who complete the study and do not enter the extension study will undergo the 
SFU Visit 20 weeks after their final dose of IMP (see Section 8.4). 
Subjects withdrawing from the IMP during the study, will return for all scheduled visits through 
Week 16 and the SFU Visit. 
Subjects withdrawing from IMP who are not continuing for all scheduled visits, will undergo the 
ET Visit and the SFU Visit 20 weeks after their final dose of IMP. 
5.5 
Study duration per subject 
For each subject, the study will last up to 37 weeks, as follows: 
• ≥14 days to ≤35 days in the Screening Period  
• 16 weeks in the placebo-controlled, Double-Blind Treatment Period 
• An SFU Visit 20 weeks after the final dose of IMP (for subjects not entering the OLE study 
or who discontinue early, including those withdrawn from IMP) 
The end of the study is defined as the date of the last visit of the last subject in the study. 
Subjects completing Week 16 are eligible for enrollment in an OLE study to continue to receive 
bimekizumab. 
5.6 
Planned number of subjects and sites 
Approximately 390 subjects will be randomly assigned in a 2:1 ratio to the following treatment 
groups: bimekizumab 160mg sc Q4W (260 subjects) and placebo (130 subjects). The planned 
number of study sites is approximately 120.  
5.7 
Anticipated regions and countries 
This will be a multicenter, international study. Enrollment will be competitive among study sites 
and may be capped at sites.  
5.8 
Schedule of study assessments 
The schedule of study assessments is presented in Table 5-1. 
 
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Table 5-1: 
Schedule of study assessments 
                                                                     Visita/ 
                                                                     Week 
Protocol activity 
Screening 
(V1) 
Baseline 
(Day 1) (first 
dose) (V2 
Double-Blind Treatment Period 
(weeks after first dose) 
ET 
SFU b 
3/ 
(4) 
4/ 
(8) 
5/ 
(12) 
6/ 
(16) 
Written Informed consent 
X 
 
 
 
 
 
 
 
Inclusion/exclusion 
X 
X 
 
 
 
 
 
 
Demographic data c 
X 
 
 
 
 
 
 
 
Psoriatic arthritis history 
X 
 
 
 
 
 
 
 
Significant past medical history and concomitant 
diseases 
X 
X d 
 
 
 
 
 
 
Prior medication 
X 
 
 
 
 
 
 
 
Concomitant medication 
X 
X 
X 
X 
X 
X 
X 
X 
PHQ-9 
X 
X 
X 
X 
X 
X 
X 
X 
eC-SSRS 
X 
X 
X 
X 
X 
X 
X 
X 
Height e 
 
X 
 
 
 
 
 
 
Weight e 
 
X 
 
 
 
X 
X 
X 
Vital signs f 
X 
X  
X 
X 
X 
X 
X 
X 
ECG by central reader 
X 
 
 
 
 
X 
X 
X 
Hematology/biochemistry g 
X 
X 
X 
X 
X 
X 
X 
X 
hs-CRP h 
X 
X 
X 
X 
X 
X 
X 
X 
Urinalysis 
X 
X 
X 
X 
X 
X 
X 
X 
Pregnancy testing i 
X 
X 
X 
X 
X 
X 
X 
X 
Urine drug screen 
X 
 
 
 
 
 
 
 
Hepatitis B and C testing 
X 
 
 
 
 
 
 
 
HIV testing 
X 
 
 
 
 
 
 
 
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Table 5-1: 
Schedule of study assessments 
                                                                     Visita/ 
                                                                     Week 
Protocol activity 
Screening 
(V1) 
Baseline 
(Day 1) (first 
dose) (V2 
Double-Blind Treatment Period 
(weeks after first dose) 
ET 
SFU b 
3/ 
(4) 
4/ 
(8) 
5/ 
(12) 
6/ 
(16) 
HLA-B27 
 
X 
 
 
 
 
 
 
RF and anti-CCP antibodies 
X 
 
 
 
 
 
 
 
Blood sample for bimekizumab plasma concentrations j 
 
X 
X 
X 
X 
X 
X 
X 
Anti-bimekizumab antibody detection j 
 
X 
X 
X 
X 
X 
X 
X 
Serum and plasma blood samples for exploratory 
biomarkersj 
 
X 
 
 
 
X 
 
 
RNA blood samples for exploratory biomarkers j 
 
X 
 
 
 
X 
 
 
Blood samples for genetic/epigenetic analysis j 
 
X 
 
 
 
X 
 
 
IGRA tuberculosis test 
X 
 
 
 
X 
 
 
 
Tuberculosis questionnaire 
X 
X 
 
 
X 
X 
X 
X 
Physical examination k 
X 
X 
 
 
 
X 
X 
X 
BSA affected by PSO l 
X 
X 
X 
X 
X 
X 
X 
X 
PASI m 
X 
X 
X 
X 
X 
X 
X 
X 
IGAm 
X 
X 
X 
X 
X 
X 
X 
X 
TJC and SJC 
X 
X 
X 
X 
X 
X 
X 
X 
HAQ-DI 
 
X 
X 
X 
X 
X 
X 
X 
PtAAP 
 
X 
X 
X 
X 
X 
X 
X 
PhGA-PsA 
 
X 
X 
X 
X 
X 
X 
X 
PhGA-Arthritis 
 
X 
X 
X 
X 
X 
X 
X 
PGA-PsA 
 
X 
X 
X 
X 
X 
X 
X 
PGA-Arthritis 
 
X 
X 
X 
X 
X 
X 
X 
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Table 5-1: 
Schedule of study assessments 
                                                                     Visita/ 
                                                                     Week 
Protocol activity 
Screening 
(V1) 
Baseline 
(Day 1) (first 
dose) (V2 
Double-Blind Treatment Period 
(weeks after first dose) 
ET 
SFU b 
3/ 
(4) 
4/ 
(8) 
5/ 
(12) 
6/ 
(16) 
BASDAI 
 
X 
X 
X 
X 
X 
X 
X 
mNAPSIn 
 
X 
X 
X 
X 
X 
X 
 
LEI 
 
X 
X 
X 
X 
X 
X 
X 
SPARCC 
 
X 
X 
X 
X 
X 
X 
X 
LDI o 
 
X 
X 
X 
X 
X 
X 
X 
PsAQoL 
 
X 
X 
 
X 
X 
X 
X 
PsAID-12 
 
X 
X 
 
X 
X 
X 
 
FACIT-Fatigue subscale 
 
X 
X 
 
X 
X 
X 
 
SF-36 
 
X 
X 
 
X 
X 
X 
X 
EQ-5D-3L 
 
X 
X 
 
X 
X 
X 
 
WPAI-SHP 
 
X 
 
 
X 
X 
X 
 
Chest x-ray p 
X 
 
 
 
 
 
 
 
X-ray of hands and feet q 
X 
 
 
 
 
 
 
 
Adverse events r 
X 
X 
X 
X 
X 
X 
X 
X 
IXRS s 
X 
X 
X 
X 
X 
X 
X 
X 
IMP administrationt 
 
X 
X 
X 
X 
 
 
 
BASDAI=Bath Ankylosing Spondylitis Disease Index; BP=blood pressure; BSA=body surface area; CASPAR=Classification Criteria for Psoriatic 
Arthritis; CCP=cyclic citrullinated peptide; ECG=electrocardiogram; eC-SSRS=electronic Columbia-Suicide Severity Rating Scale; 
EQ-5D-3L=EuroQol-5-Dimensions-3L; ET=Early Termination; FACIT=Functional Assessment of Chronic Illness Therapy; HAQ-DI=Health 
Assessment Questionnaire—Disability Index; HDL=high density lipoprotein; HIV=human immunodeficiency virus; HLA-B27=human leukocyte 
antigen B27; hs-CRP=C-reactive protein; IGA=Investigator’s Global Assessment; IGRA=interferon gamma release assay; IMP=investigational 
medicinal product; IXRS=interactive voice or web response system; LDI=Leeds Dactylitis Index; LDL=low density lipoprotein; LEI=Leeds Enthesitis 
Index; OLE=open-label extension; mNAPSI=modified Nail Psoriasis Severity Index; PASI=Psoriasis Area and Severity Index; PGA-arthritis=Patient’s 
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Table 5-1: 
Schedule of study assessments 
                                                                     Visita/ 
                                                                     Week 
Protocol activity 
Screening 
(V1) 
Baseline 
(Day 1) (first 
dose) (V2 
Double-Blind Treatment Period 
(weeks after first dose) 
ET 
SFU b 
3/ 
(4) 
4/ 
(8) 
5/ 
(12) 
6/ 
(16) 
Global Assessment of Arthritis; PGA-PsA=Patient’s Global Assessment of Psoriatic Arthritis; PhGA-arthritis=Physician’s Global Assessment of 
Arthritis; PhGA-PsA=Physician’s Global Assessment of Psoriatic Arthritis; PHQ-9=Patient Health Questionnaire-9; PsA=psoriatic arthritis; 
PsAID=Psoriatic Arthritis Impact of Disease; PsAQoL=Psoriatic Arthritis Quality of Life; PSO=psoriasis; PtAAP=Patient’s Assessment of Arthritis 
Pain; Q4W=every 4 weeks; RF=rheumatoid factor; RNA=ribonucleic acid; SF-36=Short-Form 36-item Health Survey; SFU=Safety Follow-Up; 
SJC=swollen joint count; SPARCC= Spondyloarthritis Research Consortium of Canada; TB=tuberculosis; TJC=tender joint count; V=visit; WPAI-
SHP=Work Productivity and Activity Impairment Questionnaire – Specific Health Problem 
a Visit windows of ±3 days from the first dose at all visits through Week 16. The time between IMP doses should be ≥21 days and ≤35 days during 
the Double-Blind Treatment Period. For the SFU Visit, the visit should occur no more than 3 days prior to the scheduled visit date and within 7 
days after the scheduled visit date (-3 days/+7 days). 
b Safety Follow-Up Visit occurs 20 weeks after the final dose of IMP for all subjects who complete the study and do not enter the OLE study or who 
discontinue early, including those withdrawn from IMP.  
c A complete history of lifestyle (alcohol, drug and nicotine consumption at the time of screening) and infections (fungal skin infections within 12 
months prior to Screening). 
d Confirm there are no significant changes in medical history that would exclude the subject based on the exclusion criteria. 
e The Investigator or designee will measure the height of the subject with shoes removed in meters and the weight of the subject in kilograms. 
f Collect vital signs (pulse rate, BP, and temperature) prior to IMP administration and then approximately at 30 minutes after administration and 
1 hour after administration at Baseline. At all other applicable visits, vital signs will be collected once prior to IMP administration. All other 
procedures are done prior to dosing. 
g Biochemistry testing will include triglycerides, cholesterol, HDL cholesterol, and LDL cholesterol at Baseline, Week 16, and at the ET. 
h After Screening, the hs-CRP data will not be sent to the Investigator to protect the blinded nature of the treatment assignments. 
i Pregnancy testing will consist of serum testing at Screening for all women of childbearing potential. The pregnancy test will be urine at all other 
visits. 
j At dosing visits, all blood samples are taken prior to dosing. Blood samples for bimekizumab and anti-bimekizumab antibody detection will be 
processed as per instructions in the laboratory manual. 
k Includes evaluation of signs and symptoms of active TB and risk for exposure to TB.  
l Any subject with PSO lesions at Baseline will have a BSA-PSO assessment (Section 9.8.1) at each scheduled visit. 
m Only subjects with a BSA of ≥3% at Baseline will be required to have the PASI and IGA assessed at visits post Baseline (Day 1). 
n Only for subjects who have nail PSO at Baseline. 
o Circumference measured in millimeters. The LDI assessment of dactylitis will be obtained for all subjects at all visits after the Screening Visit.  
p If a subject has had a radiograph of the chest within 3 months prior to the Screening Visit, it may be used as the Screening chest x-ray.  
q The x-ray at Screening will be used for CASPAR classification (for inclusion). 
r Adverse events are to be collected beginning at the signing of the Informed Consent form. 
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Table 5-1: 
Schedule of study assessments 
                                                                     Visita/ 
                                                                     Week 
Protocol activity 
Screening 
(V1) 
Baseline 
(Day 1) (first 
dose) (V2 
Double-Blind Treatment Period 
(weeks after first dose) 
ET 
SFU b 
3/ 
(4) 
4/ 
(8) 
5/ 
(12) 
6/ 
(16) 
s The IXRS will be used to register subjects at Screening, to randomize eligible subjects to treatment groups at Day 1 (Baseline) and to register visits. 
t For the full details of bimekizumab and placebo dosing, see Section 7.2.  
 
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5.9 
Schematic diagram 
The study schematic PA0011 is presented in Figure 5-1. 
Figure 5-1: Study schematic diagram 
 
ACR50=American College of Rheumatology 50% response criteria; Q4W=every 4 weeks; SFU=Safety Follow-Up; 
sc=subcutaneous; W=week 
5.10 
Rationale for study design and selection of dose 
Bimekizumab doses of 16mg, 160mg, 160mg with an initial 320mg dose, and 320mg were 
evaluated in PA0008, a Phase 2b multicenter, randomized, double-blind, placebo-controlled, 
parallel group, dose-ranging study. In this study, doses up to 320mg were well tolerated by 
subjects and found to have acceptable safety profile.  
PA0011 will evaluate the efficacy and safety of bimekizumab 160mg sc Q4W in adult subjects 
with active PsA. The dose was selected based on the data from Phase 2b study. In PA0008, both 
ACR50 and PASI90 responder rates saturate at bimekizumab 160mg Q4W, further increase in 
dose does not provide a significant benefit on either ACR50 or PASI90 responder rates. An 
exposure-response analysis was performed on both endpoints which also indicated that 
bimekizumab 160mg Q4W is the optimal dose for these subjects. 
There were no dose-related safety concerns or changes in laboratory values in the preliminary 
data review up to 48 weeks that preclude the use of any of the tested doses in PA0008 for the 
Phase 3 program in PsA. 
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6 
SELECTION AND WITHDRAWAL OF SUBJECTS 
6.1 
Inclusion criteria 
To be eligible to participate in this study, all of the following criteria must be met at Screening 
and be reconfirmed at the Baseline Visit: 
1a. An Institutional Review Board (IRB)/Independent Ethics Committee (IEC) approved written 
Informed Consent form (ICF) is signed and dated by the subject.  
2a. Subject is considered reliable and capable of adhering to the protocol (eg, able to understand 
and complete diaries), visit schedule, or medication intake according to the judgment of the 
Investigator. 
3. Subject is male or female at least 18 years of age. 
4. Female subjects must be: 
− postmenopausal (menopause is defined as 12 consecutive months of amenorrhea, for 
which there is no other obvious pathological or physiological cause),  
− permanently sterilized (eg, tubal occlusion, hysterectomy, bilateral salpingectomy),  
− or, if of childbearing potential (and engaged in sexual activity that could result in 
procreation), must be willing to use a highly effective method of contraception 
throughout the duration of the study until 20 weeks after last administration of IMP, and 
have a negative pregnancy test at Screening and immediately prior to the first dose.  
The following methods are considered highly effective when used consistently and correctly: 
− combined (estrogen and progestogen) hormonal contraception associated with inhibition 
of ovulation (oral, intravaginal, or transdermal)  
− progestogen-only hormonal contraception associated with inhibition of ovulation (oral, 
injectable, or implantable) 
− intrauterine device  
− intrauterine hormone-releasing system 
− vasectomized partner  
− Abstinence as a form of birth control is generally not allowed in the study unless 
abstinence is in accordance with a subject’s preferred and common lifestyle. Study 
personnel must confirm the continued use of abstinence is still in accordance with the 
subject’s lifestyle at regular intervals during the study.  
5. Subject has a documented diagnosis of adult-onset PsA classified and meets the CASPAR 
classification criteria (Table 18-1) for at least 6 months prior to Screening with active PsA 
and must have at Baseline TJC ≥3 out of 68 and SJC ≥3 out of 66 (dactylitis of a digit counts 
as 1 joint each). 
6. Subject must be negative for rheumatoid factor and anti-cyclic citrullinated peptide (CCP) 
antibodies. 
7. Subject must have at least 1 active psoriatic lesion(s) and/or a documented history of PSO. 
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8. Subject has a history of inadequate response (lack of efficacy after at least 3 months of 
therapy at an approved dose) or intolerance to treatment with 1 or 2 TNF(α) inhibitors for 
either PsA or PSO. 
9. Subjects who are regularly taking NSAIDs/COX-2 inhibitors/mild opioid analgesics as part 
of their PsA therapy are required to be on a stable dose/dose regimen for at least 14 days 
before Baseline and should remain on a stable dose through the duration of the study. 
10. Subjects taking oral corticosteroids must be on an average daily dose of ≤10mg/day 
prednisone or equivalent for at least 14 days before Baseline and should remain on a stable 
dose through the duration of the study. 
11. Subjects taking MTX (≤25mg/week) are allowed to continue their medication if started at 
least 12 weeks prior to Baseline, with a stable dose for at least 8 weeks before randomization. 
Dose, dosing schedule and route of administration (oral or sc) should remain stable through 
the duration of the study. It is strongly recommended that subjects taking MTX are also 
taking folic acid supplementation. 
12. Subjects taking LEF (≤20mg/day or an average of 20mg/day if not dosed daily) are allowed 
to continue their medication if started at least 12 weeks prior to Baseline, with a stable dose 
for at least 8 weeks before randomization. Dose and dosing schedule should remain stable 
through the duration of the study. 
13. Subjects taking SSZ (up to 3g/day for arthritis or 4/g per day if in accordance with local 
standard of care), HCQ (up to 400mg/day), or apremilast (up to 60mg/day and dosed as per 
local label) are allowed to continue their medication if started 8 weeks prior Baseline, with a 
stable dose for at least 4 weeks before randomization. 
6.2 
Exclusion criteria 
Subjects are not permitted to enroll in the study if any of the following criteria are met: 
1. Female subjects who are breastfeeding, pregnant, or plan to become pregnant during the 
study or within 20 weeks following final dose of IMP.  
2. Subjects with current or prior exposure to any biologics except TNF inhibitors for the 
treatment of PsA or PSO, including participation in a bimekizumab clinical study who 
received at least 1 dose of IMP (including placebo). 
3. Subject previously participated in another study of a medication (systemic) under 
investigation. Subject must be washed out of the medication for 12 weeks or at least 
5 half-lives prior to the Baseline Visit, whichever is greater, or is currently participating in 
another study of a medication (systemic) under investigation.  
4. Subject previously participated in another study of a medical device under investigation 
within the 4 weeks prior to the Screening Visit or is currently participating in another study 
of a medical device under investigation. 
5. Subject has a known hypersensitivity to any excipients of bimekizumab. 
6. Subject is taking or has taken prohibited PsA or PSO medications without meeting the 
mandatory wash-out period relative to the Baseline Visit (Table 7‒1 and Table 7-2). 
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7. Subject has an active infection or history of infections as follows: 
− Any active infection (except common cold) within 14 days prior to Baseline. 
− A serious infection, defined as requiring hospitalization or iv anti-infectives within 
2 months prior to Baseline. 
− A history of opportunistic, recurrent or chronic infections that, in the opinion of the 
Investigator, might cause this study to be detrimental to the subject. Opportunistic 
infections are infections caused by uncommon pathogens (eg, pneumocystis jirovicii, 
cryptococcosis) or unusually severe infections caused by common pathogens 
(eg, cytomegalovirus, herpes zoster).  
8. Subject has concurrent acute or chronic viral hepatitis B or C or human immunodeficiency 
virus (HIV) infection. Subjects who have evidence of or tested positive for hepatitis B or 
hepatitis C are excluded.  
A positive test for the hepatitis B virus is defined as:  
• positive for hepatitis B surface antigen; or,  
• positive for anti-hepatitis B core antibody  
A positive test for the hepatitis C virus (HCV) is defined as:  
• positive for hepatitis C antibody (anti-HCV antibody), and  
• positive via a confirmatory test for HCV (for example, HCV polymerase chain reaction) 
9. Subject has received any live (includes attenuated) vaccination within the 8 weeks prior to 
the Baseline (eg, inactivated influenza and pneumococcal vaccines are allowed but nasal 
influenza vaccination is not permitted). 
10. Subject has received Bacillus Calmette-Guerin (BCG) vaccinations within 1 year prior to the 
Baseline Visit. 
11. Subject has known tuberculosis (TB) infection, is at high risk of acquiring TB infection, or 
has current or history of nontuberculous mycobacterium (NTMB) infection. A subject with 
latent tuberculosis (LTB) (a positive interferon gamma release assay [IGRA] and diagnosis 
confirmed by TB specialist) may be rescreened once and enrolled after receiving at least 
4 weeks of appropriate LTB infection (LTBI) therapy and if no evidence of therapy-related 
hepatotoxicity has occurred prior to the first injection (alanine aminotransferase 
[ALT]/aspartate aminotransferase [AST] remain ≤3 times upper limit of normal [ULN]).  
Subject has a past history of active TB involving any organ system unless adequately treated 
according to World Health Organization/Center for Disease Control and Prevention 
therapeutic guidance and proven to be fully recovered upon consult with a TB specialist.  
Refer to Section 12.3.6 for details on determining full TB exclusion criteria. 
12. Subject has a history of a lymphoproliferative disorder including lymphoma and/or current 
signs and symptoms suggestive of lymphoproliferative disease. 
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13. Subject has a diagnosis of inflammatory conditions other than PSO or PsA including but not 
limited to RA, sarcoidosis, systemic lupus erythematosus, and reactive arthritis. Subjects 
with a diagnosis of Crohn’s disease, ulcerative colitis, or other inflammatory bowel disease 
(IBD) are allowed as long as they have no active symptomatic disease at Screening or 
Baseline. 
14. Subject had acute anterior uveitis within 6 weeks of Baseline. 
15. Subjects with fibromyalgia or osteoarthritis symptoms that, in the Investigator’s opinion, 
would have potential to interfere with efficacy assessments. 
16. Subject has any active malignancy or history of malignancy within 5 years prior to the 
Screening Visit EXCEPT treated and considered cured cutaneous squamous or basal cell 
carcinoma, or in situ cervical cancer. 
17. Subject has a form of PSO other than chronic plaque-type (eg, pustular, erythrodermic and 
guttate PSO, or drug-induced PSO). 
18. Subject has had major surgery (including joint surgery) within the 3 months prior to 
Baseline, or planned surgery within 6 months after entering the study. 
19. Subject has any systemic disease (cardiovascular, neurological, renal, liver, metabolic, GI, 
hematological, immunological, etc) considered by the Investigator to be uncontrolled, 
unstable or likely to progress to a clinically significant degree during the course of the study. 
20. Subject has had myocardial infarction or stroke within the 6 months prior to the Screening 
Visit. 
21. Subject has laboratory abnormalities at Screening, including any of the following:  
a. ≥3x ULN of any of the following: ALT, AST, alkaline phosphatase (ALP); or >ULN 
total bilirubin (≥1.5xULN total bilirubin if known Gilbert’s syndrome) 
b. White blood cell count (WBC) <3.0x103/μL  
c. Absolute neutrophil count <1.5x103/μL 
d. Lymphocyte count <500 cells/μL 
e. Hemoglobin <8.5g/dL 
f. Creatinine >2mg/dL 
g. Any other laboratory abnormality, which, in the opinion of the Investigator, will prevent 
the subject from completing the study or will interfere with the interpretation of the study 
results.  
Individual screening tests for which the results are in error, borderline, or indeterminate for 
inclusion in the study, can be repeated once for confirmation during the Screening Period. 
Upon retesting, subjects whose results remain outside this threshold should not be 
randomized. 
22. Subject has any other condition including medical or psychiatric which, in the Investigator's 
judgment, would make the subject unsuitable for inclusion in the study. 
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23. Presence of active suicidal ideation, or positive suicide behavior using the “Screening” 
version of the electronic Columbia-Suicide Severity Rating Scale (eC-SSRS) with either of 
the following criteria: 
− Subject has a history of a suicide attempt within the 5 years prior to the Screening Visit. 
Subjects with a history of a suicide attempt more than 5 years ago should be evaluated by 
a mental healthcare professional (eg, locally licensed psychiatrist, psychologist, or 
master’s level therapist) before enrolling into the study. 
− Subject has suicidal ideation in the past month prior to the Screening Visit as indicated by 
a positive response (“Yes”) to either Question 4 or Question 5 of the “Screening” version 
of the eC-SSRS. 
24. Subject has presence of moderately severe major depression, or severe major depression, 
indicated by a score ≥15 using the screening PHQ-9. Medication used to treat depression 
should be stable for 8 weeks prior to Baseline. 
25. Subjects taking PsA medications other than MTX, SSZ, apremilast, HCQ, LEF, 
NSAIDs/COX-2 inhibitors, and oral corticosteroids as outlined in the Inclusion criteria 
(Section 6.1). Stable doses/regimens of analgesics are also permitted. 
26. Subject has a history of chronic alcohol or drug abuse within 6 months prior to Screening 
evaluated by the Investigator based on medical history, site interview, and results of the 
specified urine drug screen.   
27. Subject is a member of Investigator site personnel directly affiliated with this study and/or 
their immediate families. Immediate family is defined as a spouse, parent, child, or sibling, 
whether biological or legally adopted. 
28. Subject is a UCB employee or is an employee of third-party organizations involved in the 
study. 
6.3 
Withdrawal criteria 
Subjects are free to withdraw from the study at any time, without prejudice to their continued 
care. Subjects who withdraw from the study should complete the Early Termination Visit (see 
Section 8.3).  
Subjects should be withdrawn from the study and will be asked to come back for the SFU Visit 
20 weeks after final dose of IMP if the subject withdraws his/her consent. 
Subjects should be withdrawn from IMP and will be asked to come back for all scheduled visits 
(up to Week 16) and the SFU Visit 20 weeks after the final dose of IMP if any of the following 
events occur: 
1. The Sponsor or a regulatory agency requests withdrawal of the subject. 
2. Subject develops an illness that, in the opinion of the Investigator, would interfere with 
his/her continued participation, if the risk of continuing with IMP outweighs the potential 
benefit. 
3. Subject is noncompliant with the study procedures or medications, which may present a risk 
to the safety of the subject, in the opinion of the Investigator. 
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4. Subject uses prohibited concomitant medications, as defined in Section 7.8.2, that may 
present a risk to the safety of the subject in the opinion of the Investigator and the Medical 
Monitor. 
5. Subject has a clinical laboratory value meeting any of the following criteria: 
a. Hepatotoxicity as described in Section 6.3.1. 
b. A laboratory value meeting any of the following criteria: 
− Absolute neutrophil count <1.0x103/μL 
− Absolute lymphocyte count <0.2x103/μL 
Subjects may remain on the IMP if the result is transient. A retest is required within 
1 to 2 weeks at a scheduled or unscheduled visit. If the repeat absolute neutrophil count or 
absolute lymphocyte count is still below the allowable values, the subject must be withdrawn 
from the IMP. If the repeat absolute neutrophil count or absolute lymphocyte count is above 
the allowable values, the subject may continue to receive IMP. 
6. The subject experiences a severe AE, an SAE, or a clinically significant change in a 
laboratory value occurs that, in the opinion of the Investigator, merits the discontinuation of 
the IMP and appropriate measures being taken. 
7. There is confirmation of a pregnancy during the study, as evidenced by a positive pregnancy 
test (see Section 12.1.4 for more information regarding pregnancies). 
8. Subject develops erythrodermic, guttate or generalized pustular form of PSO. 
9. A subject considered as having either a suspected new LTB infection or who develops active 
TB or NTMB infection during the study (including but not limited to, conversion 
demonstrated by IGRA or other diagnostic means) must be immediately discontinued from 
IMP, an ET Visit must be scheduled as soon as possible, but not later than the next regular 
visit. 
The subject must be permanently withdrawn if further examinations result in a diagnosis of 
active TB, or if the subject is diagnosed with LTB infection with no initiation of prophylactic 
treatment, prematurely discontinues prophylactic treatment, or, in the opinion of the 
Investigator or Sponsor, is noncompliant with prophylactic TB therapy. 
Confirmed active TB is an SAE and must be captured in the electronic Case Report Form 
(eCRF) in the SAE Report Form section. As with all SAEs, periodic follow-up reports should 
be completed as per protocol requirements until such time as the TB infection resolves. 
Additional information on TB policies is provided in Section 12.3.6. 
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10. Subjects with newly diagnosed IBD or with IBD flares during the study must: 
− Be referred, as appropriate, to a health care professional treating IBD, such as a 
gastroenterologist 
− Discontinue IMP and be followed-up until resolution of active IBD symptoms 
If IBD flares increase in severity or frequency during the study, the Investigator should use 
clinical judgment in deciding whether the subject should continue on IMP and contact the 
Medical Monitor and UCB study physician to confirm the subject's suitability for continued 
participation in the study. 
11. Subjects must be referred immediately to a mental health care professional and may be 
withdrawn from the study based upon the Investigator’s judgment of benefit/risk for: 
− Active suicidal ideation as indicated by a positive response (“Yes”) to Questions 4 of the 
“Since Last Visit” version of the eC-SSRS 
− Moderately severe major depression as indicated by a PHQ-9 score of 15 to 19 if this 
represents an increase of 3 points compared to last visit 
The mental health consultation must be recorded in the subject’s source documentation.  
12. Subjects must be referred immediately to a mental healthcare professional and must be 
withdrawn in case of: 
− Active suicidal ideation as indicated by a positive response (“Yes”) to Question 5 of the 
“Since Last Visit” version of the eC-SSRS. 
− Any suicidal behavior since the last visit.  
− Severe major depression as indicated by a PHQ-9 score ≥20. 
The mental health consultation must be recorded in the subject’s source documentation. 
13. Any subject who develops a clinically important infection or recurrent infections not 
responsive to standard therapy during the study must discontinue IMP until resolution of the 
infection. The Investigator should use clinical judgement in deciding whether the subject 
should restart IMP and contact the Medical Monitor and UCB study physician to confirm the 
subject’s suitability for continued participation in the study. 
Investigators should contact the Medical Monitor, whenever possible, to discuss the withdrawal 
of a subject from IMP or from the study in advance. 
Subjects withdrawing from the study who are not continuing for all scheduled visits, will 
undergo the ET Visit and the SFU Visit 20 weeks after their final dose of IMP. 
Investigators should attempt to obtain information on subjects in the case of withdrawal or 
discontinuation. For subjects considered as lost to follow-up, the Investigator should make an 
effort (at least 1 phone call and 1 written message to the subject), and document his/her effort 
(date and summary of the phone call and copy of the written message in the source documents), 
to complete the final evaluation. All results of these evaluations and observations, together with a 
narrative description of the reason(s) for removing the subject, must be recorded in the source 
documents. The eCRF must document the primary reason for withdrawal or discontinuation. 
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6.3.1 
Potential drug-induced liver injury IMP discontinuation criteria 
Subjects with potential drug-induced liver injury (PDILI) must be assessed to determine if IMP 
must be discontinued. In addition, all concomitant medications and herbal supplements that are 
not medically necessary should also be discontinued.  
The PDILI criteria below require immediate discontinuation of IMP:  
• Subjects with either of the following: 
− ALT or AST ≥8xULN  
− ALT or AST ≥3xULN and coexisting total bilirubin ≥2xULN  
• - Subjects with ALT or AST ≥3xULN who exhibit temporally associated symptoms of 
hepatitis or hypersensitivity. Hepatitis symptoms include fatigue, nausea, vomiting, right 
upper quadrant pain or tenderness. Hypersensitivity symptoms include fever (without clear 
alternative cause), rash, or eosinophilia (ie, >5%). 
If a nondrug-related cause for the symptoms can be confirmed, these subjects may resume IMP 
administration after discussion with the responsible UCB physician, but only when the 
requirements for rechallenge with IMP as provided in Section 12.2.1.2.1 are followed. 
The PDILI criterion below allows for subjects to continue on IMP at the discretion of the 
Investigator.  
• Subjects with ALT or AST ≥5xULN and <8xULN, total bilirubin <2xULN, and no 
eosinophilia (ie, ≤5%), with no fever, rash, or symptoms of hepatitis (eg, fatigue, nausea, 
vomiting, right upper quadrant pain or tenderness).  
Evaluation of PDILI must be initiated as described in Section 12.2.1 with repeat tests performed 
in 2 weeks. Upon retest, if ALT or AST values have reduced to <5xULN, the subject can 
continue with the study. However, if ALT or AST remains ≥5xULN <8xULN after retest, IMP 
should be temporarily withheld and subject should undergo a repeat test in 2 weeks. The subject 
will continue to be monitored at least twice per week until values normalize, stabilize, or return 
to within baseline values. If ALT or AST values remain ≥5xULN even after the second retest, 
then the subject should be permanently withdrawn from the study and should be followed for 
possible PDILI.  
If subjects are unable to comply with the applicable monitoring schedule, IMP must be 
discontinued immediately. 
Investigators should attempt to obtain information on subjects in the case of IMP discontinuation 
to complete the final evaluation. Subjects with PDILI should not be withdrawn from the study 
until investigation and monitoring are complete. All results of these evaluations and 
observations, as well as the reason(s) for IMP discontinuation and subject withdrawal (if 
applicable), must be recorded in the source documents. The eCRF must document the primary 
reason for IMP discontinuation. 
7 
STUDY TREATMENTS 
7.1 
Description of investigational medicinal products 
The IMPs used in this study are bimekizumab and placebo. 
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Placebo will be supplied as 0.9% sodium chloride aqueous solution (physiological saline, 
preservative-free) of pharmacopoeia (U.S. Pharmacopeia/European Pharmacopeia) quality in a 
1mL PFS for sc injection. 
Further details of the IMPs and their specification will be provided in the IMP Handling Manual. 
7.2 
Treatments to be administered 
Unblinded study staff will be responsible for preparation of the clinical study material, including 
recording the administration information on source documents, and administration of the IMP as 
sc injections. The unblinded personnel will not be involved in the study in any way other than 
assuring the medication is taken from the correct kit and administering the IMP to the subjects. 
Suitable areas for sc injections are the abdominal wall, thigh, or upper outer arm without 
massage. On Day 1 (Baseline) one 160mg injection or one injection of placebo will be 
administered. Injection sites should be rotated between visits and injections should not be given 
in areas where the skin is tender, bruised, red, or hard. 
An IMP Handling Manual will be provided to each site containing instructions regarding drug 
preparation and dosing. 
Double-Blind Treatment Period dosing 
During the Double-Blind Treatment Period, subjects will be randomized 2:1 to receive the 
following blinded IMP regimens: bimekizumab 160mg sc Q4W or placebo. 
All subjects will receive 1 injection sc on Day 1 (Baseline) and 1 injection sc Q4W based on the 
following dosing scheme: 
• Subjects randomized to receive bimekizumab will receive bimekizumab 160mg sc Q4W 
starting on Day 1 (Baseline). 
• Subjects randomized to receive placebo will receive placebo injections sc Q4W starting on 
Day 1 (Baseline).   
7.3 
Packaging 
The IMPs are manufactured, packaged, and labeled according to Good Manufacturing Practice 
(GMP) guidelines and applicable laws or regulations. Investigational medicinal products will be 
suitably packaged in such a way as to protect the IMPs from deterioration during transport and 
storage. 
7.4 
Labeling 
Clinical drug supplies will be labeled in accordance with the current International Council for 
Harmonisation (ICH) guidelines on Good Clinical Practice (GCP) and GMP and will include any 
locally required statements. If necessary, labels will be translated into the local language. 
7.5 
Handling and storage requirements 
Investigational Medicinal Products must be stored under refrigerated conditions (2ºC to 8ºC) 
protected from light. The IMPs must not be frozen. 
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The Investigator (or designee) is responsible for the safe and proper storage of IMP at the site. 
Investigational medicinal product stored by the Investigator is to be kept in a secured area with 
limited access according to the storage conditions mentioned on the label. 
Appropriate storage conditions must be ensured either by controlling the temperature (eg, room, 
refrigeration unit) or by completion of a temperature log in accordance with local requirements 
on a regular basis, showing actual and minimum/maximum temperatures reached over the time 
interval.  
In case an out-of-range temperature is noted, it must be immediately reported as per instructions 
contained in the IMP Handling Manual. 
7.6 
Drug accountability 
A Drug Accountability form will be used to record IMP dispensing and return information on a 
by-subject basis and will serve as source documentation during the course of the study. Details of 
any IMP lost, damaged (due to breakage or wastage), not used, partially used, disposed of at the 
study site, or returned to the Sponsor or designee must also be recorded on the appropriate forms. 
All supplies and pharmacy documentation must be made available throughout the study for UCB 
(or designee) to review. 
The packaging identifies each kit by a unique number that does not correlate to the contents and, 
therefore, does not unblind study site staff. Unblinded study staff will be responsible for 
preparation (eg, breaking tamper proof sticker on kit) of the clinical study material, including 
recording the administration information in the source document. 
The Investigator (or designee) is responsible for retaining all used, unused, and partially used 
containers of IMP until returned or destroyed. 
The Investigator must assign some of the Investigator’s duties for drug accountability at the 
study site to an appropriate pharmacist/designee. 
The Investigator must ensure that the IMP is used only in accordance with the protocol. 
Periodically, and/or after completion of the clinical phase of the study, all used (including empty 
containers)/partially used, unused, damaged, and/or expired IMP must be reconciled and either 
destroyed at the site according to local laws, regulations, and UCB standard operating procedures 
(SOPs), or returned to UCB (or designee). Investigational medicinal product intended for the 
study cannot be used for any other purpose than that described in this protocol. 
7.7 
Procedures for monitoring subject compliance 
Bimekizumab and placebo will be administered in the clinic and compliance will be determined 
at the visit by study personnel. Drug accountability must be recorded on the Drug Accountability 
form. 
7.8 
Concomitant medications/treatments 
All concomitant medications, including over-the-counter products, herbal, traditional remedies, 
vitamin/mineral supplements, other dietary supplements, “nutraceuticals,” and hormones must be 
recorded in the subject’s source documentation (eg, clinical chart) and in the eCRF. This record 
should include the name of the drug, the dose, the route and date(s) of administration, and the 
indication for use. 
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7.8.1 
Permitted concomitant treatments (medications and therapies) 
No medication increases or additions are permitted for medications taken for PsA, apart from the 
protocol allowed background medications at a stable dose. However, a decrease in dose or 
dosing frequency of any agent is permitted for reasons of intolerance/AEs/side-effects at any 
time.  
Subjects are allowed to use acetaminophen/paracetamol and mild opioids as needed, except 
within 24 hours of study visit with disease activity assessment. 
Subjects who are already receiving an established antidepressant regimen should be on a stable 
dose of the antidepressant for 8 weeks prior to Baseline. 
Subjects are allowed to use any other medications, including biologics, after at least 28 days of 
last dose of the IMP. This is applicable for subjects who discontinue from IMP or the study 
early, including those permanently withdrawn from IMP, or subjects who have completed the 
study treatment without entering the extension study and are in the SFU Period. 
7.8.1.1 
Psoriasis treatments 
For treatment of PSO, subjects may continue to use topical moisturizers, emollients, salicylic 
acid preparations, bath oils, and oatmeal bath preparations for skin conditions during the study, 
as needed. Over-the-counter shampoos for the treatment of PSO of the scalp are also permitted. 
Additionally, mild topical steroids are permitted for use limited to the face, axillae, and/or 
genitalia, as needed. Subjects who use prohibited topical medications will be allowed to stay in 
the study but will counseled to not use them further. No other topical preparations are allowed in 
the 2 weeks prior to randomization or during the study unless medically required to treat an AE. 
See Table 7-2 for prohibited PSO medications. 
Use of psoralen and ultraviolet A light (PUVA/UVA) therapy for the treatment of PSO is not 
permitted for the duration of the study. 
7.8.2 
Prohibited concomitant treatments (medications and therapies) 
Prohibited and/or restricted medications are summarized in Table 7‒1 and Table 7-2. 
Table 7‒1: 
Prohibited or restricted medications and required wash-out periods 
Drug class 
Dose 
Exclusion/Washout 
Analgesics, including mild 
opioid analgesics, 
acetaminophen/paracetamol, etc 
Any dose  
Any ad hoc use in the 24 hours prior to any study 
visit.  
 
Stable doses of analgesics are permitted. 
NSAIDs/COX-2 inhibitors  
Any dose 
regimen 
Any change in dose/dose regimen in the 14 days 
prior to the Baseline Visit. For the duration of the 
study, a subject’s NSAIDs/COX-2 inhibitor dose 
must remain stable. 
Oral corticosteroids 
Any dose 
regimen 
Any change in dose/dose regimen in the 14 days 
prior to the Baseline Visit. 
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Table 7‒1: 
Prohibited or restricted medications and required wash-out periods 
Drug class 
Dose 
Exclusion/Washout 
Intramuscular/intravenous 
/intra-articular corticosteroids  
Any dose  
Use in the 28 days prior to the Baseline Visit and 
during the study. 
Intra-articular hyaluronic acid  
Any dose  
Use in the 6 months prior to the Baseline Visit. 
DMARDs: 
-azathioprine,  
-cyclosporine,  
-cyclophosphamide,  
-mycophenolic acid 
-mycophenolate mofetil 
-any other small molecule 
DMARDs (eg, tofacitinib) 
Any dose 
Use within 8 weeks prior to the Baseline Visit and 
during the study. 
-apremilast  
Any dose 
Use within 8 weeks prior to the Baseline Visit 
unless Inclusion Criterion #13 is met.  
-hydroxychloroquine  
Any dose 
Use within 8 weeks prior to the Baseline Visit 
unless Inclusion Criterion #13 is met.  
-sulfasalazine  
Any dose 
Use within 8 weeks prior to the Baseline Visit 
unless Inclusion Criterion #13 is met.  
-methotrexate  
Any dose 
regimen 
Initiation less than 12 weeks prior to the Baseline 
Visit unless Inclusion Criterion #11 is met.   
Administration of LEF and MTX together is not 
permitted at any time during the study. 
-leflunomide  
Any dose 
Use in the 6 months prior to the Baseline Visit, 
unless (1) a cholestyramine washout has been 
performed, in which case, use up to 28 days prior 
to the Baseline Visit is acceptable, or (2) Inclusion 
Criterion #12 is met. 
TNF inhibitor a 
 
-infliximab  
-adalimumab 
-etanercept  
-golimumab  
-certolizumab pegol  
Any dose 
For ADA, IFX, GOL, and CZP any use within the 
3 months prior to the Baseline Visit. 
 
For ETN, use within the 28 days prior to the 
Baseline Visit. 
 
This applies to biosimilar versions of any 
TNF inhibitor 
Any non-TNF biologic 
medications 
Any dose 
Any exposure history. 
ADA=adalimumab; COX-2=cyclooxygenase-2; CZP=certolizumab pegol; DMARD=disease-modifying 
antirheumatic drug; ETN=etanercept; GOL=golimumab; HCQ= hydroxychloroquine; IFX=infliximab; 
LEF=leflunomide; MTX=methotrexate; NSAID=nonsteroidal anti-inflammatory drug; SSZ=sulfasalazine; 
TNF=tumor necrosis factor 
a  Subjects must not have been exposed to more than 2 TNFα inhibitors prior to the Baseline Visit. 
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Table 7-2: 
Additional prohibited psoriasis treatments 
Drug class 
Dose 
Exclusion criteria 
Phototherapy 
Any dose 
Use within the 28 days prior to the Baseline Visit. 
Topical corticosteroids for 
dermatological use except as 
detailed in Section 7.8.1, 
vitamin D analogues, topical 
retinoids, keratolytics, coal tar, 
and fumaric acid esters 
Any dose 
Use within 14 days prior to the Baseline Visit. 
Systemic retinoids 
Any dose 
Use within 3 months prior to the Baseline Visit 
7.8.3 
Vaccines 
Administration of live (including attenuated) vaccines is not allowed during the conduct of the 
study and for 20 weeks after the final dose of the IMP (see Exclusion Criterion #9, Section 6.2). 
Administration of inactivated vaccines is allowed during the study at the discretion of the 
Investigator. 
Administration of inactivated vaccines is allowed during the study at the discretion of the 
Investigator. This includes administration of non-live coronavirus disease 2019 (COVID-19) 
vaccines authorized at the time of issuance of this protocol version (eg, messenger ribonucleic 
acid [mRNA], deoxyribonucleic acid [DNA] viral vector types of vaccines). Considering the 
known mechanism of action and results from a human vaccination response study, bimekizumab 
is not expected to affect the safety and/or efficacy of COVID-19 vaccines.  
7.9 
Blinding 
Due to differences in presentation between the bimekizumab and placebo treatments, special 
precautions will be taken to ensure study blinding and study sites will have blinded and 
unblinded personnel.  
7.9.1 
Procedures for maintaining and breaking the treatment blind 
7.9.1.1 
Maintenance of study treatment blind 
All subject treatment details will be allocated and maintained by the interactive voice or web 
response system (IXRS) system.  
7.9.1.2 
Breaking the treatment blind in an emergency situation 
The integrity of this clinical study must be maintained by observing the treatment blind. In the 
event of an emergency for which the appropriate treatment for a subject cannot be made without 
knowing the treatment assignment, it will be possible to determine to which treatment arm and 
dose the subject has been allocated by contacting the IXRS. All sites will be provided with 
details of how to contact the system for code breaking at the start of the study. The Medical 
Monitor or equivalent should be consulted prior to unblinding, whenever possible. 
The Clinical Project Manager (CPM) will be informed immediately via the IXRS when a code is 
broken but will remain blinded to specific treatment information. Any unblinding of the IMP 
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performed by the Investigator must be recorded in the source documents and on the Study 
Termination eCRF page. 
7.10 
Randomization and numbering of subjects 
An IXRS will be used for assigning eligible subjects to a treatment regimen based on a 
predetermined production randomization and/or packaging schedule provided by UCB (or 
designee). The randomization schedule will be produced by the IXRS vendor. The IXRS will 
generate individual assignments for subject kits of IMP, as appropriate, according to the visit 
schedule. 
To enroll a subject, the Investigator or designee will contact the IXRS and provide brief details 
about the subject to be enrolled. Each subject will receive a 5-digit number assigned at Screening 
that serves as the subject identifier throughout the study. The subject number will be required in 
all communication between the Investigator or designee and the IXRS regarding a particular 
subject. Subject numbers and kit numbers will be tracked via the IXRS. 
Eligible subjects will be randomized to treatment groups at Baseline (Day 1). To randomize a 
subject, the Investigator or designee will contact the IXRS and provide brief details about the 
subject to be randomized. The IXRS will automatically inform the Investigator or designee of the 
subject’s randomization number. The IXRS will allocate kit numbers to the subject based on the 
subject number during the course of the study. The randomization number must be documented 
into the eCRF. 
8 
STUDY PROCEDURES BY VISIT  
The schedule of study assessments (Table 5-1) provides an overview of study assessments. A list 
of procedures to be completed at each visit is described below. Visit windows of ±3 days from 
the first dose at all visits through Week 16 are permissible. For the SFU Visit (20 weeks after the 
final dose), the visit should occur no more than 3 days prior to the scheduled visit date and 
within 7 days after the scheduled visit date (-3 days/+7 days). 
8.1 
Screening Period/Baseline  
8.1.1 
Screening 
The Screening Period will last for a minimum of 14 days and up to a maximum of 35 days. 
Prior to any study-specific activities, subjects will be asked to read, sign, and date an Informed 
Consent form that has been approved by the Sponsor and an IRB/IEC, and that complies with 
regulatory requirements. Subjects will be given adequate time to consider any information 
concerning the study given to them by the Investigator or designee. As part of the informed 
consent procedure, subjects will be given the opportunity to ask the Investigator any questions 
regarding potential risks and benefits of participation in the study. 
Where local regulations permit, subjects will also be given the option to participate in the 
genomics, genetics, and proteomics substudy. Subjects agreeing to participate in the substudy 
will be required to complete a separate Informed Consent form (ICF). The ICF must be signed 
prior to collecting any samples for the substudy. The substudy will only be conducted where 
ethically accepted and authorized by the regulatory agencies. Refusal to participate in the 
substudy will not affect a subject’s ability to participate in the main PA0011 study. 
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The following procedures or assessments will be performed at the Screening Visit: 
• Obtain written informed consent 
• Assessment of eligibility criteria 
• Collect demographic data 
• Collect PsA history 
• Collect significant past medical history and concomitant diseases 
• Record prior medications 
• Record concomitant medications 
• PHQ-9 
• eC-SSRS 
• Vital signs (pulse rate, BP, and temperature) 
• ECG by central reader 
• Collect samples for hematology, biochemistry and urinalysis 
• Collect samples for hs-CRP 
• Pregnancy testing (serum) 
• Urine drug screen 
• Collect samples for Hepatitis B and Hepatitis C testing  
• Collect samples for HIV testing 
• Collect samples for rheumatoid factor and anti-CCP antibodies 
• IGRA TB test 
• TB questionnaire 
• Physical examination 
• BSA affected by PSO 
• PASI 
• IGA 
• Perform TJC and SJC 
• Chest x-ray 
• X-ray of hands and feet 
• AEs 
• IXRS 
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8.1.2 
Baseline (Day 1) 
• Assessment of eligibility criteria 
• Collect significant past medical history and concomitant diseases 
• Record concomitant medications 
• PHQ-9 
• eC-SSRS 
• Height 
• Weight  
• Vital signs (pulse rate, BP, and temperature) 
• Collect samples for hematology, biochemistry (including triglycerides, cholesterol, high 
density lipoprotein [HDL] cholesterol, and low density lipoprotein [LDL] cholesterol), and 
urinalysis 
• Collect samples for hs-CRP 
• Pregnancy testing (urine) 
• Collect sample for HLA-B27 
• Blood sample for bimekizumab plasma concentrations 
• Blood sample for anti-bimekizumab antibody detection 
• Serum and plasma blood samples for exploratory biomarkers (participating subjects only) 
• RNA blood samples for exploratory biomarkers (participating subjects only) 
• Blood samples for genetic/epigenetic analysis (participating subjects only) 
• TB questionnaire 
• Physical examination 
• BSA affected by PSO 
• PASI 
• IGA 
• Perform TJC and SJC 
• HAQ-DI 
• PtAAP 
• PhGA-PsA 
• PhGA-Arthritis 
• PGA-PsA 
• PGA-Arthritis  
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• mNAPSI 
• BASDAI 
• LEI 
• SPARCC 
• LDI 
• PsAQoL 
• PsAID-12 
• FACIT-Fatigue subscale 
• SF-36 
• EQ-5D-3L 
• WPAI-SHP 
• AEs 
• Randomization using IXRS 
• IMP administration (vital signs will be measured 30 minutes and 1 hour after dosing)  
8.2 
Double-Blind Treatment Period 
8.2.1 
Week 4 
• Record concomitant medications 
• PHQ-9 
• eC-SSRS 
• Vital signs (pulse rate, BP, and temperature) 
• Collect samples for hematology, biochemistry and urinalysis 
• Collect samples for hs-CRP 
• Pregnancy testing (urine) 
• Blood sample for bimekizumab plasma concentrations 
• Blood sample for anti-bimekizumab antibody detection 
• BSA affected by PSO 
• PASI 
• IGA 
• Perform TJC and SJC 
• HAQ-DI 
• PtAAP 
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• PhGA-PsA 
• PhGA-Arthritis 
• PGA-PsA 
• PGA-Arthritis  
• BASDAI 
• mNAPSI 
• LEI 
• SPARCC 
• LDI 
• PsAQoL  
• PsAID-12 
• FACIT-Fatigue subscale 
• SF-36 
• EQ-5D-3L 
• AEs  
• IXRS 
• IMP administration  
8.2.2 
Week 8 
• Record concomitant medications 
• PHQ-9 
• eC-SSRS 
• Vital signs (pulse rate, BP, and temperature) 
• Collect samples for hematology, biochemistry and urinalysis 
• Collect samples for hs-CRP 
• Pregnancy testing (urine) 
• Blood sample for bimekizumab plasma concentrations 
• Blood sample for anti-bimekizumab antibody detection 
• BSA affected by PSO 
• PASI 
• IGA 
• Perform TJC and SJC 
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• HAQ-DI 
• PtAAP 
• PhGA-PsA 
• PhGA-Arthritis 
• PGA-PsA 
• PGA-Arthritis  
• BASDAI 
• mNAPSI 
• LEI 
• SPARCC 
• LDI 
• AEs  
• IXRS 
• IMP administration  
8.2.3 
Week 12 
• Record concomitant medications 
• PHQ-9 
• eC-SSRS 
• Vital signs (pulse rate, BP, and temperature) 
• Collect samples for hematology, biochemistry and urinalysis 
• Collect samples for hs-CRP 
• Pregnancy testing (urine) 
• Blood sample for bimekizumab plasma concentrations 
• Blood sample for anti-bimekizumab antibody detection 
• IGRA TB test 
• TB questionnaire 
• BSA affected by PSO 
• PASI 
• IGA 
• Perform TJC and SJC 
• HAQ-DI 
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• PtAAP 
• PhGA-PsA 
• PhGA-Arthritis 
• PGA-PsA 
• PGA-Arthritis  
• BASDAI 
• mNAPSI 
• LEI 
• SPARCC 
• LDI 
• PsAQoL 
• PsAID-12 
• FACIT-Fatigue subscale 
• SF-36 
• EQ-5D-3L 
• WPAI-SHP   
• AEs  
• IXRS 
• IMP administration  
8.2.4 
Week 16 
• Record concomitant medications 
• PHQ-9 
• eC-SSRS 
• Weight  
• Vital signs (pulse rate, BP, and temperature) 
• ECG by central reader 
• Collect samples for hematology, biochemistry (including triglycerides, cholesterol, 
HDL cholesterol, and LDL cholesterol), and urinalysis 
• Collect samples for hs-CRP 
• Blood sample for bimekizumab plasma concentrations 
• Blood sample for anti-bimekizumab antibody detection 
• Serum and plasma blood samples for exploratory biomarkers (participating subjects only) 
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• RNA blood samples for exploratory biomarkers (participating subjects only) 
• Blood samples for genetic/epigenetic analysis (participating subjects only) 
• Pregnancy testing (urine) 
• TB questionnaire 
• Physical examination 
• BSA affected by PSO 
• PASI 
• IGA 
• Perform TJC and SJC 
• HAQ-DI 
• PtAAP 
• PhGA-PsA 
• PhGA-Arthritis 
• PGA-PsA 
• PGA-Arthritis  
• BASDAI 
• mNAPSI 
• LEI 
• SPARCC 
• LDI 
• PsAQoL 
• PsAID-12 
• FACIT-Fatigue subscale 
• SF-36 
• EQ-5D-3L 
• WPAI-SHP 
• AEs  
• IXRS 
At the completion of the Treatment Period, Investigators should discuss treatment options with 
the subject. All subjects who complete the study and do not enter the OLE study or who 
discontinue early, including those withdrawn from IMP, will have a SFU Visit 20 weeks after 
their final dose of IMP. 
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8.3 
Early Termination Visit 
Subjects withdrawing early from the study will undergo the following ET Visit assessments and 
will enter the SFU Period: 
• Record concomitant medications 
• PHQ-9 
• eC-SSRS 
• Weight 
• Vital signs (pulse rate, BP, and temperature) 
• ECG 
• Collect samples for hematology, biochemistry (including triglycerides, cholesterol, 
HDL cholesterol, and LDL cholesterol), and urinalysis 
• Collect samples for hs-CRP 
• Pregnancy testing (urine) 
• Blood sample for bimekizumab plasma concentrations 
• Blood sample for anti-bimekizumab antibody detection 
• TB questionnaire 
• Physical examination 
• BSA affected by PSO 
• PASI 
• IGA 
• Perform TJC and SJC 
• HAQ-DI 
• PtAAP 
• PhGA-PsA 
• PhGA-Arthritis 
• PGA-PsA 
• PGA-Arthritis  
• BASDAI 
• mNAPSI 
• LEI 
• SPARCC 
• LDI 
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• PsAQoL 
• PsAID-12 
• FACIT-Fatigue subscale 
• SF-36 
• EQ-5D-3L 
• WPAI-SHP 
• AEs  
• IXRS 
8.4 
Safety Follow-Up Visit (20 weeks [-3 days/+7 days] after the final 
dose) 
All subjects who complete the study and do not enter the OLE study or who discontinue early, 
including those withdrawn from IMP, will have an SFU Visit 20 weeks after their final dose of 
IMP. 
• Record concomitant medications 
• PHQ-9 
• eC-SSRS 
• Weight 
• Vital signs (pulse rate, BP, and temperature) 
• ECG 
• Collect samples for hematology, biochemistry and urinalysis 
• Collect samples for hs-CRP 
• Pregnancy testing (urine) 
• Blood sample for bimekizumab plasma concentrations 
• Blood sample for anti-bimekizumab antibody detection 
• TB questionnaire 
• Physical examination 
• BSA affected by PSO 
• PASI 
• IGA 
• Perform TJC and SJC 
• HAQ-DI 
• PtAAP 
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• PhGA-PsA 
• PhGA-Arthritis 
• PGA-PsA 
• PGA-Arthritis  
• BASDAI 
• LEI 
• SPARCC 
• LDI 
• PsAQoL 
• SF-36 
• AEs  
• IXRS 
8.5 
Unscheduled Visits 
At the Investigator’s discretion, an Unscheduled Visit may be completed at any time during the 
study but prior to the SFU Visit, if deemed necessary for the subject’s safety and well-being.  
If an Unscheduled Visit is conducted due to safety or efficacy reasons, an eC-SSRS assessment 
will be performed with the subject during the visit. If an Unscheduled Visit is conducted for 
reasons other than safety or efficacy concerns (eg, replacement of lost medication, repeated 
collection of a laboratory specimen due to collection or analysis issues), an eC-SSRS will not be 
required at these visits. 
At this visit, any of the following assessments may be performed, depending on the reason for 
the visit: 
• Record concomitant medication 
• eC-SSRS 
• Vital signs (pulse rate, BP, and temperature) 
• Physical examination 
• ECG  
• If indicated, obtain blood sample(s) for: 
− Standard safety laboratory tests (hematology/biochemistry/urinalysis) 
− Bimekizumab plasma concentrations and anti-bimekizumab antibody detection  
• An IGRA TB test 
• Obtain urine sample for urine pregnancy test 
• AEs 
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9 
ASSESSMENT OF EFFICACY 
The ACR50 response at Week 16 is the primary efficacy variable. In addition, the ACR20 and 
ACR70 responses are secondary or other efficacy variables. Several assessments must be 
completed in order to determine the ACR response. These include the TJC and SJC based on 
68 and 66 joints, respectively, PGA-PsA, PhGA-PsA, PtAAP, HAQ-DI, and hs-CRP. The 
methods for the component measures will be described first, followed by ACR response and 
assessments used in secondary and other efficacy variables.  
The timing for all assessments is specified in the schedule of study assessments (Table 5-1).  
9.1 
Joint assessments 
9.1.1 
68/66 joint evaluation for ACR response and verification of Inclusion 
Criterion 5 
The TJC/SJC, as recommended by ACR in RA, is the 68/66 count and it has since also been used 
in PsA studies; therefore, it will be utilized in this study.  
All joint assessments will be performed by an experienced independent evaluator who has had 
documented training on how to perform these assessments correctly. Preferably, the same 
evaluator should perform these assessments at all visits, as indicated in Table 5-1. The 
independent evaluator will not be involved in any other assessments. The following joints will be 
assessed for tenderness:  
• Upper body (6) - bilateral temporomandibular, sternoclavicular, and acromioclavicular joints 
• Upper extremity (34) - bilateral shoulders, elbows, wrists (includes radiocarpal, and carpal 
and carpometacarpal bones considered as a single unit), metacarpophalangeal (I, II, III, IV, 
and V), thumb interphalangeals, proximal interphalangeal (II, III, IV, and V), and distal 
interphalangeals (II, III, IV, and V). 
• Lower extremity (28) - bilateral hips, knees, ankles, tarsi (includes subtalar, transverse tarsal, 
and tarsometatarsal considered as a single unit), metatarsophalangeals (I, II, III, IV, and V), 
great toe interphalangeals, and proximal interphalangeals (II, III, IV, and V). 
All of these except for the hips are assessed for swelling.  
Artificial and ankylosed joints, as well as missing joints (ie, amputated joints), are excluded from 
both tenderness and swelling assessments.  
One dactylitic digit is to be counted as 1 swollen joint (instead of counting as 3 in the finger or 
2 in the toe). 
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Table 9-1 summarizes the swelling and tenderness grading criteria. 
Table 9-1: 
Swelling and tenderness grading 
Grade 
Tenderness response (68) 
Swelling response (66) 
0 
Not tender 
None 
1 
Tenderness present 
Detectable synovial thickening 
Data mapping from collected data to the grades listed in Table 9-1 will be described in the 
Statistical Analysis Plan (SAP). 
9.1.2 
28 joint evaluation for determination of DAS28(CRP) 
The following 28 joints will be used for calculation of the DAS28(CRP). 
• Upper extremity (26)-bilateral shoulders, elbows, wrists (includes radiocarpal, and carpal and 
carpometacarpal bones considered as a single unit), metacarpophalangeal joints I, II, III, IV, 
and V, thumb interphalangeals, proximal interphalangeal II, III, IV, and V 
• Lower extremity (2)-knees 
9.2 
ACR20, ACR50, and ACR70 response 
The ACR20, ACR50, and ACR70 response rates are based on a 20%, 50%, and 70% or greater 
improvement relative to Baseline in the following measures: 
• TJC based on 68 joints 
• SJC based on 66 joints 
• 3 of the 5 remaining core set measures: 
− PGA-PsA 
− PhGA-PsA 
− PtAAP 
− HAQ-DI 
− hs-CRP 
9.3 
Patient’s Global Assessments  
9.3.1 
Patient’s Global Assessment of Psoriatic Arthritis (PGA-PsA) 
The subject’s global assessment of PsA will be performed using a 100mm VAS scale where 0 is 
“very good, no symptoms” and 100 is “very poor, severe symptoms.” The subject will be asked 
the following question:  
“Considering all the ways your psoriatic arthritis affects you, please mark a vertical line on 
the scale below to show how well you are doing today.” 
The subject should be asked to consider all aspects of their disease (including joint and skin 
components) in their response to this question. 
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9.3.2 
Patient’s Global Assessment of Arthritis (PGA-arthritis) 
The subject’s global assessment of arthritis will be performed using a 100mm VAS scale where 
0 is “very good, no symptoms” and 100 is “very poor, severe symptoms.” The subject will be 
asked the following question: 
“Considering all the ways your arthritis affects you, please mark a vertical line on the scale 
below to show how you are feeling today.” 
The subject should be asked to consider their arthritis symptoms and functional capacity in their 
response to this question. 
9.4 
Physician’s Global Assessments 
These assessments will be performed by the Principal Investigator, another delegated physician, 
or an appropriately trained medical professional (based on local requirements) who has 
documented training on how to perform these assessments correctly. The assessments should be 
made blind to the PGA-PsA and PGA-arthritis assessments. 
9.4.1 
Physician’s Global Assessment of Psoriatic Arthritis (PhGA-PsA) 
The Investigator or delegate will assess the overall status of the subject with respect to their PsA, 
which may include any element of the disease and may include arthritis, PSO, enthesitis, 
dactylitis, or spondylitis. This will be assessed using a 100mm VAS scale where 0 is “very good, 
asymptomatic and no limitation of normal activities” and 100 is “very poor, very severe 
symptoms which are intolerable and inability to carry out all normal activities”. The Investigator 
or delegate will be asked the following question: 
“Considering all the ways the disease affects your patient, mark a vertical line on the scale 
for how well his or her condition is today.”  
9.4.2 
Physician’s Global Assessment of Arthritis (PhGA-Arthritis) 
The Physician or delegate will assess how the subject’s overall arthritis appears at the time of the 
visit. This is an evaluation based on the subject’s disease signs, functional capacity, and physical 
examination using a 100mm VAS scale where 0 is “very good” and 100 is “very poor”. The 
physician will be asked to mark the Patient’s arthritis:  
The Patient’s arthritis at this time is: 
“Please mark a vertical line on the scale below to assess the overall status of the subject's 
arthritis signs and symptoms and the functional capacity of the subject.” 
Very Good--------------------------------------------------------Very Poor 
9.5 
Patient’s Assessment of Arthritis Pain (PtAAP) 
The PtAAP VAS or ‘Pain VAS’ is part of the ACR core set of measures in arthritis 
(Felson et al, 1993). Subjects will assess their arthritis pain using a VAS where 0 is “no pain” 
and 100 is “most severe pain.”  
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9.6 
Health Assessment Questionnaire-Disability Index score 
(HAQ-DI) 
The HAQ-DI contains 20 items divided into 8 domains that measure: dressing and grooming, 
arising, eating, walking, hygiene, reach, grip, and common daily activities. Subjects are required 
to indicate the degree of difficulty they have experienced in each domain in the past week on a 
4-point scale that ranges from 0 (without difficulty) to 3 (unable to do). Any individual score of 
less than 2 is adjusted to 2 if the activity requires assistance from another individual or the use of 
an assistive device. The highest score in each category is then summed (0 to 24) and divided by 
the number of categories scored to give a score that ranges from 0 to 3.  
9.7 
High sensitivity C-reactive protein levels (hs-CRP) 
High sensitivity CRP levels will be analyzed by the central laboratory according to Table 5-1. 
After Screening, the hs-CRP data will not be sent to the Investigator in order to protect the 
blinded nature of the treatment assignments and response. 
9.8 
Evaluation of psoriasis 
9.8.1 
Body surface area psoriasis (BSA-PSO) 
In the BSA-PSO assessment, the subject’s hand (including the palm, fingers, and thumb) is used 
as the reference point for measuring how much of their skin is affected by PSO, representing 
roughly 1% of the body’s surface.  
The BSA palm method will be used for the evaluation of BSA affected by PSO as follows: 
• Head and neck=10% (10 palms) 
• Upper extremities=20% (20 palms) 
• Trunk=30% (30 palms) 
• Lower extremities=40% (40 palms)  
• Total BSA=100% 
9.8.2 
Psoriasis Area and Severity Index (PASI) 
The PASI will be assessed in all subjects with Baseline/Day 1 BSA affected by PSO ≥3% 
determined by the method described in Section 9.8.1 (ie, the BSA palm method).  
The PASI is the most commonly used and validated assessment for grading the severity of PSO 
in clinical studies (Feldman, 2005). The PASI quantifies the severity and extent of the disease 
and weighs these with the percentage of BSA involvement.  
The percent area of involvement (BSA%) is estimated across 4 body areas (head, upper limbs, 
trunk, and lower limbs) and then transferred into a grade (Table 9-2).  
The Investigator assesses the average redness, thickness, and scaliness of lesions in each body 
area (each on a 5-point scale); 0=none, 1=slight, 2=moderate, 3=marked, and 4=very marked.  
The PASI score ranges from 0 to 72 with a higher score indicating increased disease severity.  
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Table 9-2: 
Body areas for calculation of percent BSA for PASI 
Body area 
Details of area 
BSA 
Degree of involvement of 
body area a 
Head 
Face, back of head 
10%  
0 to 6 
Upper limbs 
Left, right, upper lower, flexor 
surface, extensor surface 
20%  
0 to 6 
Trunk 
Front, back, groin 
30%  
0 to 6 
Lower limbs  
Left, right, upper lower, flexor 
surface, extensor surface, including 
buttocks 
40%  
0 to 6 
Total 
 
100%  
 
BSA=body surface area; PASI=Psoriasis Area and Severity Index 
a Where 0=none; 1=1% to <10% affected, 2=10% to <30% affected, 3=30% to <50% affected, 4=50% to <70% 
affected, 5=70% to <90% affected, 6=90% to 100% affected 
The PASI75, PASI90, and PASI100 responses are based on at least 75%, 90%, and 100% 
improvement in the PASI score. The PASI will be assessed at Screening and at Baseline/Day 1. 
Thereafter, the PASI will be assessed for the purposes of determining response only in subjects 
with PSO involving at least 3% of BSA at Baseline/Day 1.  
9.8.3 
Investigator’s Global Assessment (IGA) 
A static IGA for PSO will be used to assess disease severity in all subjects during the study. The 
IGA will be completed at the visits specified in Table 5-1.  
The Investigator will assess the overall severity of PSO using the following 5-point scale 
presented in Table 9-3. 
Table 9-3: 
Five-point IGA 
Score 
Short Descriptor 
Detailed Descriptor 
0 
Clear 
No signs of PSO; post-inflammatory hyperpigmentation may 
be present  
1 
Almost Clear 
No thickening; normal to pink coloration; no to minimal focal 
scaling 
2 
Mild 
Just detectable to mild thickening; pink to light red coloration; 
predominantly fine scaling 
3 
Moderate 
Clearly distinguishable to moderate thickening; dull to bright 
red, moderate scaling  
4 
Severe 
Severe thickening with hard edges; bright to deep dark red 
coloration severe/coarse scaling covering almost all or all 
lesions 
IGA=Investigator's Global Assessment; PSO=psoriasis 
 
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The IGA responder is defined as a subject with a clear (0) or almost clear (1) assessment with at 
least a 2-category improvement from Baseline, meaning that this parameter will be evaluable 
only for subjects with psoriatic skin lesions (IGA score ≥2) at Baseline.    
In this study, only subjects with BSA ≥ 3% at Baseline will have IGA assessed at post-Baseline 
visits. 
9.8.4 
Modified Nail Psoriasis Severity Index (mNAPSI) 
Subjects with psoriatic nail disease will have a target nail selected at the Baseline Visit for 
evaluation using the mNAPSI. The nail selected should be the most affected nail observed at 
Baseline and should be the only one assessed throughout the study. The target nail will be scored 
(0 to 3) for onycholysis/oil drop dyschromia, nail plate crumbling, and pitting and will be scored 
(0 for “no” or 1 for “yes”) for leukonychia, nail bed hyperkeratosis, splinter hemorrhages, and 
red spots in the lunula.  
9.9 
Minimal Disease Activity (MDA) and Very Low Disease Activity 
(VLDA) 
Minimal Disease Activity and VLDA are states of disease activity deemed useful targets of 
treatment by both the subject and physician, given current treatment possibilities and limitations. 
Criteria covering all of the domains of the disease have been developed to determine whether or 
not a subject has reached MDA or VLDA based on key outcome measures in PsA (Mease, 2011; 
Coates et al, 2010).  
A subject is considered as having MDA if 5 or more of the following 7 criteria are fulfilled: 
• Tender joint count ≤1 
• Swollen joint count ≤1 
• PASI ≤1 or BSA ≤3 
• Patient pain VAS ≤15 
• PGA-PsA VAS ≤20 
• HAQ-DI ≤0.5 
• Tender enthesial points ≤1 
A subject is considered as having VLDA if all 7 of the above criteria are fulfilled. 
9.10 
Disease Activity Index for Psoriatic Arthritis (DAPSA) 
Disease Activity Index for Psoriatic Arthritis is a composite score of patient global and pain 
VAS, TJC/SJC, and hs-CRP that incorporates a pattern of peripheral arthritis that often is 
encountered in PsA, and is calculated as follows: 
 DAPSA=SJC (range 0 to 66) + TJC (range 0 to 68) + PGA-Arthritis (VAS range 0 to 10cm; 
0=best, 10=worst) + PtAAP (VAS range 0 to 10cm) + hs-CRP 
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9.11 
Disease Activity Score-28 based on C-reactive protein 
(DAS28[CRP]) 
The components for DAS28(CRP) include the TJC and SJC based on 28 joints (Section 9.11), 
CRP (Section 9.7) and the PGA-arthritis (Section 9.3.2). The DAS28(CRP) is calculated as 
follows:  
𝐷𝐴𝑆28(𝐶𝑅𝑃) = 0.56  √𝑇𝐽𝐶+ 0.28  √𝑆𝐽𝐶+ 0.014   𝑃𝐺𝐴−𝐴𝑟𝑡ℎ𝑟𝑖𝑡𝑖𝑠+ 0.36   𝑙𝑛 (𝐶𝑅𝑃+ 1) + 0.96 
9.12 
Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) 
The BASDAI is the most common instrument used to measure the disease activity of AS from 
the subject’s perspective (Garrett et al, 1994) and is considered useful for evaluating axial 
involvement in subjects with PsA (Fernandez-Sueiro et al, 2009). The BASDAI is a validated 
self-reported instrument which consists of six 10-unit horizontal numeric rating scales to 
measure severity of fatigue, spinal and peripheral joint pain and swelling, enthesitis, and morning 
stiffness (both severity and duration, respectively) over the last week (van Tubergen et al, 2015). 
The final BASDAI score ranges from 0 to 10, with lower scores indicating lower disease 
activity.  
The BASDAI is calculated as follows:  
𝐵𝐴𝑆𝐷𝐴𝐼=
Q1 + Q2 + Q3 + Q4 + (𝑄5 + 𝑄6
2
)
5
 
 
9.13 
Leeds Enthesitis Index (LEI) 
Enthesitis, the inflammation at the bone insertion of tendon, ligament, or joint capsule, is 
common in PsA. The LEI is a new enthesitis index designed for use in PsA (Healy and Helliwell, 
2008) adopted for use in randomized controlled studies involving patients with PsA. Enthesitis 
will be assessed by palpation on the lateral epicondyles of the humerus (elbows), medial femoral 
epicondyles (knees), and Achilles tendons (heels) bilaterally and scored as 0=no pain and 
1=painful for each of the 6 sites, for a score range of 0 to 6. 
9.14 
Spondyloarthritis Research Consortium of Canada (SPARCC) 
The SPARCC is an index that measures the severity of enthesitis through the assessment of 
16 sites (the greater trochanter [right/left [R/L]), quadriceps tendon insertion into the patella 
(R/L), patellar ligament insertion into the patella and tibial tuberosity (R/L), Achilles tendon 
insertion (R/L), plantar fascia insertion (R/L), medial and lateral epicondyles (R/L), and the 
supraspinatus insertion [R/L]) (Maksymowych et al, 2009). Tenderness on examination is 
recorded as either present (1) or absent (0) for each of the 16 sites, for an overall score range of 
0 to 16. 
9.15 
Leeds Dactylitis Index (LDI) 
Dactylitis, the swelling of an entire digit related to articular and periarticular inflammation is a 
characteristic of inflammatory spondyloarthropathies, including PsA. Presence of dactylitis will 
be assessed using the LDI basic. It measures the ratio of the circumference of the affected digit to 
the circumference of the digit on the contralateral hand or foot (millimeters): a minimum 
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difference of 10% is used to define a dactylitic digit (Healy and Helliwell, 2007; 
Helliwell et al, 2005). If the contralateral digit is also dactylitic, a table of normative values 
based on population averages is used to provide the comparison. The ratio is then multiplied by 
the tenderness score, using a simple grading system (0=absent, 1=present). The results from each 
digit with dactylitis are then summed to produce a final score. The digits involved and the 
matching contralateral digit will also be recorded at the same visits. 
9.16 
Psoriatic Arthritis Quality of Life (PsAQoL) 
The use of the PsAQoL is recommended by the health regulatory authorities as 1 of the 
disease-specific HRQoL measures in PsA (CHMP/EWP/438/04). The PsAQoL comprises 
20 items so that the score ranges from 0 to 20 with higher scores indicating worse HRQoL. 
9.17 
Psoriatic Arthritis Impact of Disease-12 (PsAID-12) 
The PsAID-12 is a patient-reported outcome measure for assessing the impact of PsA in 
12 physical and psychological domains, including pain, fatigue, skin problems, work and/or 
leisure activities, functional capacity, discomfort, sleep disturbance, coping, 
anxiety/fear/uncertainty, embarrassment and/or shame, social participation, and depression. Each 
domain is assessed with a single question using a 0 to 10 numerical rating scale. Each domain 
score is multiplied by a weighting factor and the results are then summed to provide the total 
score. The total score ranges from 0 to 10, with higher scores indicating a worse status. The 
PsAID-12 demonstrated satisfactory psychometric properties in an international validation study; 
however, further validation is needed (Gossec et al, 2014). A score below 4 out of 10 is 
considered a patient-acceptable status. A change of 3 or more points is considered relevant 
absolute change.  
9.18 
Functional Assessment of Chronic Illness Therapy (FACIT)-
Fatigue subscale 
The FACIT-Fatigue is a 40-item measure that assesses self-reported fatigue and its impact upon 
daily activities and function over the past 7 days (FACIT.org). The scale consists of 5 subscales 
(physical well-being, social/family well-being, emotional well-being, functional well-being, and 
fatigue). The fatigue subscale is the only one used in this study . It is composed of 13 items, all 
scored from 0 (Not at all) to 4 (Very much). The FACIT-Fatigue subscale score ranges from 0 to 
52 with 0 being the worst possible score and 52 being the best possible score. To obtain a score 
from 0 to 52, all negatively worded questions have to be recoded, so that responses range from 
worst (0) to the best (4) outcome. 
The FACIT–Fatigue subscale has been validated in patients with PsA. The minimum 
clinically-important difference for FACIT-Fatigue subscale in patients with PsA was determined 
to be a 4-point change (Cella et al, 2019). 
9.19 
Short-Form 36-item Health Survey (SF-36) 
The SF-36 (version 2, standard recall) is a 36-item generic HRQoL instrument that uses a recall 
period of 4 weeks. Items are grouped into 8 domains as follows: Physical Functioning (10 items), 
Role Physical (4 items), Bodily Pain (2 items), General Health (5 items), Vitality (4 items), 
Social Functioning (2 items), Role Emotional (3 items), Mental Health (5 items), and 1 item for 
perceived stability or change in health (Health Transition) during the last year. The concepts 
represented by these domains contribute to physical, mental, and social aspects of HRQoL. 
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In addition to domain scores, the PCS and MCS scores are calculated from the 8 domains 
(excluding the Health Transition item). Component scores reflect the impact of each domain on 
physical and mental health status. The norm-based T-scores for the 2 SF-36 component summary 
(PCS and MCS) and the 8 domains are standardized with a mean of 50 and a standard deviation 
(SD) of 10 in the general US population (Maruish, 2011). An individual respondent’s score that 
falls outside the T-score range of 45 to 55 should be considered outside the average range for the 
US general population. When considering group-level data, a score below 47 should be 
considered indicative of impaired functioning within that health domain or dimension. Similar to 
individual respondent data, group mean scores of 47 or greater should be considered average or 
above average as compared to the general US population. Higher scores indicate a better health 
status. 
9.20 
Euro Quality of life 5-Dimensions-3 Level (EQ-5D-3L) 
The EQ-5D-3L is comprised of a 5-item health status dimension and a VAS. The response to 
each of the 5 health status dimensions is divided into 3 levels (no problem, some or moderate 
problems, or extreme problems) and is scored as 1, 2, and 3, respectively. The EQ-5D-3L VAS 
records the respondent’s self-rated health status on a vertical 20cm scale, 0 to 100 graduated 
(0=worst imaginable health status, 100=best imaginable health status). 
9.21 
Work Productivity and Activity Impairment Questionnaire – 
Specific Health Problem (WPAI-SHP) 
The WPAI-SHP V2.0 is a patient-reported questionnaire that assesses subject’s employment 
status, work absenteeism, work impairment while working (presenteeism), overall work, and 
daily activity impairment attributable to a specific health problem (Reilly et al, 1993).  
Five out of 6 items of the WPAI-SHP are regrouped into the 4 dimensions, with scores expressed 
as percentage, where higher numbers indicate greater impairment and less productivity (ie, worse 
outcomes) as described in the WPAI-SHP scoring rules. 
9.22 
Psoriatic Arthritis Response Criteria (PsARC) 
The PsARC is based on the TJC (68 joints) and SJC (66 joints), the PGA-PsA and PhGA-PsA 
VAS.  
The PsARC response is defined as improvement from Baseline in at least 2 of the 4 measures 
(TJC, SJC, PGA-PsA, PhGA-PsA) 1 of which must be TJC or SJC and no worsening from 
Baseline in any of the 4 measures. Improvement for TJC and SJC is defined as a reduction of 
≥30% and worsening is defined as an increase of ≥30%. Improvement of PGA-PsA and 
PhGA-PsA is defined as a reduction of the 100-point VAS of ≥20 points and worsening is 
defined as an increase of the 100-point VAS of ≥20. 
9.23 
Psoriatic Arthritis Disease Activity Score (PASDAS) 
The PASDAS (Coates et al, 2014) is a composite score that includes patient and physician global 
scores of skin and joint disease, SJC, TJC, LEI, tender dactylitis count, the physical component 
of the SF-36 Health Survey, and level of CRP. It was developed by the Group for Research and 
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Assessment of Psoriasis and Psoriatic Arthritis and the European League Against Rheumatism. 
PASDAS is calculated using the following equation: 
PASDAS = (((0.18 × √Physician global VAS) + (0.159 × √Patient global VAS) − 
(0.253 × √SF36 − PCS) + (0.101 × LN (SJC + 1)) + (0.048 × LN (TJC + 1)) + (0.23 × 
LN (LEI + 1)) + (0.377 LN (tender Dactylitis count + 1)) + (0.102 × LN (CRPmg/dL 
+ 1)) +2)*1.5. 
Note: LN=natural logarithm 
The following categories are used to define the level of disease activity (Coates et al, 2018): 
• Remission: PASDAS ≤1.9 
• Low disease activity: PASDAS 1.9 to <3.2 
• Moderate disease activity: PASDAS 3.2 to <5.4 
• High disease activity: PASDAS ≥5.4 
10 
ASSESSMENT OF PHARMACOKINETIC AND 
PHARMACOGENOMIC VARIABLES 
10.1 
Pharmacokinetic variable 
The PK variable is the plasma concentrations of bimekizumab.   
The Investigator or designee will obtain blood samples for these measurements at the time points 
specified in Table 5-1. When these samples are required at a visit during which the subject is 
dosed with IMP, the blood samples will be drawn prior to dosing. Samples should be drawn at 
the same time of the sampling for clinical laboratory tests. The time and date of collection will be 
recorded in the eCRF. Instructions pertaining to sample collection, processing, storage, labeling, 
and shipping are provided in the laboratory manual for this study. Detailed information on 
sample analysis will be provided in a bioanalytical report. 
10.2 Pharmacogenomic variables 
A separate ICF will be required for those subjects who agree to participate in the genomics, 
genetics, and proteomics substudy, and must be signed prior to collection of any samples for the 
substudy. The substudy will only be conducted where ethically accepted and authorized by the 
regulatory agencies. Refusal to participate in the substudy will not affect a subject’s ability to 
participate in the main study. 
These analyses will enable evaluation of biomarkers relative to disease biology and progression, 
drug treatment and inflammatory and immune response processes. The nature and format of 
these tentative analyses will be determined at a later date. 
For individuals consenting to the genomics, genetics, and proteomics substudy, blood samples 
will be drawn for exploratory genetic/epigenetic, genomic, proteomic, and metabolomics 
analysis and for candidate exploratory biomarker analyses. Candidate exploratory biomarker 
evaluations may include, but are not limited to, IL 17A/IL-17F pathway signaling and PsA 
biology (eg, IL-17A, IL-17F, IL-23, IL-6, tumor necrosis factor, dendritic cell-specific 
transmembrane protein, and circulating osteoclast precursors). 
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Collection of these samples will occur at the time points specified in the schedule of study 
assessments (Table 5-1). At dosing visits, blood samples will be drawn prior to dosing, and will 
be drawn at the same time of the sampling for clinical laboratory tests. The time and date of 
collection will be recorded in the eCRF. The samples will be stored at -80°C at the central 
biorepository for up to 20 years. 
Detailed information on the collection, storage, preparation, and shipping of samples for 
potential RNA, proteins, lipids, and metabolites analysis will be presented in the Laboratory 
Manual. 
The nature and format of these tentative analyses will be determined at a later date. Results for 
the exploratory parameters obtained from potential RNA, lipids, proteins and metabolites 
analysis will be described in a separate report. 
11 
ASSESSMENT OF IMMUNOLOGICAL VARIABLES 
Immunological variables are the anti-bimekizumab antibody status, and the treatment-emergent 
antibody positivity derived from anti-drug antibody assays.  
The Investigator or designee will obtain blood samples for these measurements at the time points 
specified in Table 5-1. When these samples are required at a visit during which the subject is 
dosed with IMP, the blood samples will be drawn prior to dosing. Samples should be drawn at 
the same time of the sampling for clinical laboratory tests. The time and date of collection will be 
recorded in the eCRF. Instructions pertaining to sample collection, processing, storage, labeling, 
and shipping are provided in the laboratory manual for this study. The presence of antibodies to 
bimekizumab will be determined using a validated bioanalytical method. Detailed information on 
sample analysis will be provided in a bioanalytical report.  
The presence of anti-bimekizumab antibodies will be determined using a tiered approach of 
screening, confirmatory, and titer assays. Where applicable, a neutralizing-antibody assay will be 
performed. 
12 
ASSESSMENT OF SAFETY 
12.1 
Adverse events 
12.1.1 
Definitions 
12.1.1.1 
Adverse event 
An AE is any untoward medical occurrence in a patient or clinical investigation subject 
administered a pharmaceutical product that does not necessarily have a causal relationship with 
this treatment. An AE can therefore be any unfavorable and unintended sign (including an 
abnormal laboratory finding), symptom, or disease temporally associated with the use of a 
medicinal (investigational) product, whether or not related to the medicinal (investigational) 
product. 
In order to ensure complete safety data collection, all AEs occurring during the study (ie, after 
the signing of the Informed Consent form), including any pretreatment and post-treatment 
periods required by the protocol, must be reported in the eCRF even if no IMP was taken but 
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specific study procedures were conducted. This includes all AEs not present prior to the initial 
visit and all AEs that recurred or worsened after the initial visit. 
Signs or symptoms of the condition/disease for which the IMP is being studied should be 
recorded as AEs only if their nature changes considerably or their frequency or intensity 
increases in a clinically significant manner as compared to the clinical profile known to the 
Investigator from the subject’s history or the Baseline Period. 
12.1.1.2 
Serious adverse event 
Once it is determined that a subject experienced an AE, the seriousness of the AE must be 
determined. An SAE must meet 1 or more of the following criteria: 
• Death 
• Life-threatening 
(Life-threatening does not include a reaction that might have caused death had it occurred in 
a more severe form.) 
• Significant or persistent disability/incapacity 
• Congenital anomaly/birth defect (including that occurring in a fetus) 
• Important medical event that, based upon appropriate medical judgment, may jeopardize the 
patient or subject and may require medical or surgical intervention to prevent 1 of the other 
outcomes listed in the definition of serious 
(Important medical events may include, but are not limited to, potential Hy’s Law [see 
Section 12.1.1.3], allergic bronchospasm requiring intensive treatment in an emergency room 
or at home, blood dyscrasias that do not result in inpatient hospitalization, or the 
development of drug dependency or drug abuse.) 
• Initial inpatient hospitalization or prolongation of hospitalization 
(A patient admitted to a hospital, even if he/she is released on the same day, meets the 
criteria for the initial inpatient hospitalization. An emergency room visit that results in 
admission to the hospital would also qualify for the initial inpatient hospitalization criteria. 
However, emergency room visits that do not result in admission to the hospital would not 
qualify for this criteria and, instead, should be evaluated for 1 of the other criteria in the 
definition of serious [eg, life-threatening adverse experience, important medical event]. 
Hospitalizations for reasons not associated with the occurrence of an AE [eg, preplanned 
surgery or elective surgery for a pre-existing condition that has not worsened or manifested 
in an unusual or uncharacteristic manner] do not qualify for reporting. For example, if a 
subject has a condition recorded on his/her medical history and later has a preplanned surgery 
for this condition, it is not appropriate to record the surgery or hospitalization as an SAE, 
since there is no AE upon which to assess the serious criteria. Please note that, if the 
pre-existing condition has worsened or manifested in an unusual or uncharacteristic manner, 
this would then qualify as an AE and, if necessary, the seriousness of the event would need to 
be determined.) 
Note: Confirmed active TB is an SAE and must be captured on an SAE Report Form and 
provided to the Sponsor in accordance with SAE reporting requirements. 
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12.1.1.2.1 
Anticipated serious adverse events 
The following anticipated SAEs are anticipated to occur in the population studied in this protocol 
at some frequency that is independent of drug exposure. Note that listed events will not be 
regarded as anticipated SAEs if they are life threatening or if they result in the death of the study 
subject. 
This list does not change the Investigator’s obligation to report all SAEs (including anticipated 
SAEs) as detailed in Section 12.1.2.3. 
Table 12-1: Anticipated SAEs for the population of subjects with PsA 
MedDRA system organ class 
MedDRA preferred terms 
Eye disorders 
Uveitis 
Cardiac disorders 
Myocardial infarction 
Atrial fibrillation 
Gastrointestinal disorders 
Crohn's disease 
Hepatobiliary disorders 
Non-alcoholic steatohepatitis 
Metabolism and Nutrition disorders 
Metabolic syndrome 
Diabetes mellitus 
Musculoskeletal and connective tissue disorders 
Psoriatic arthropathy 
Neoplasms benign, malignant and unspecified 
(including cysts and polyps) 
Basal cell carcinoma 
Squamous cell carcinoma 
Nervous system disorders 
Embolic Stroke 
Ischaemic Stroke 
Psychiatric disorders 
Anxiety 
Depression 
Skin and subcutaneous tissue disorders 
Psoriasis 
MedDRA=Medical Dictionary for Regulatory Activities; PsA=psoriatic arthritis; SAE=serious adverse event 
Note: Exception: Listed events will not be regarded as anticipated SAEs if they are life threatening or if they 
result in the death of the study subject. 
12.1.1.3 
Adverse events of special interest 
An AE of special interest is any AE that a regulatory authority has mandated be reported on an 
expedited basis, regardless of the seriousness, expectedness, or relatedness of the AE to the 
administration of a UCB product/compound. 
Potential Hy’s Law, defined as ≥3xULN ALT or AST with coexisting ≥2xULN total bilirubin in 
the absence of ≥2xULN ALP, with no alternative explanation for the biochemical abnormality, 
must ALWAYS be reported to UCB as an AE of special interest (ie, without waiting for any 
additional etiologic investigations to have been concluded). Follow-up information should then 
be reported if an alternative etiology is identified during investigation and monitoring of the 
subject. 
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12.1.1.4 
Other safety topics of interest 
Prespecified safety topics of interest for the study are: infections (serious, opportunistic, fungal, 
and TB), neutropenia, hypersensitivity, suicidal ideation, and behavior, major cardiovascular 
events, liver function test changes/enzyme elevations, malignancies, and inflammatory bowel 
diseases (with gastroenterology referral, as appropriate).  
This is based on findings from the IMP clinical program to date, potential risks generally 
associated with biologic immunomodulators, or findings from other medicines with a related 
mechanism of action. There are no specific AE reporting requirements for these topics; however, 
special monitoring, additional data collection activities, and/or enhanced signal detection 
activities (within UCB) are in place. 
12.1.2 
Procedures for reporting and recording adverse events 
The subject will be given the opportunity to report AEs spontaneously. A general prompt will 
also be given at each study visit to detect AEs. For example: 
“Did you notice anything unusual about your health (since your last visit)?” 
In addition, the Investigator should review any self-assessment procedures employed in the 
study. 
12.1.2.1 
Description of adverse events 
When recording an AE, the Investigator should use the overall diagnosis or syndrome using 
standard medical terminology, rather than recording individual symptoms or signs. The eCRF 
and source documents should be consistent. Any discrepancies between the subject’s own words 
on his/her own records and the corresponding medical terminology should be clarified in the 
source documentation. 
When recording the intensity of an AE in the CRF (ie, mild, moderate, or severe), the 
Investigator should use the following criteria: 
• Mild: the subject is aware of the sign or symptom (syndrome), but it does not interfere with 
his/her usual activities and/or is of no clinical consequence 
• Moderate: the AE interferes with the usual activities of the subject or it is of some clinical 
consequence 
• Severe: the subject is unable to work normally or to carry out his/her usual activities, or the 
AE is of definite clinical consequence 
Details for completion of the AE eCRF (including judgment of relationship to IMP) are 
described in the eCRF Completion Guidelines. 
12.1.2.2 
Rule for repetition of an adverse event 
An increase in the intensity of an AE should lead to the repetition of the AE being reported with: 
• The outcome date of the first AE that is not related to the natural course of the disease being 
the same as the start date of the repeated AE, and the outcome of “worsening” 
• The AE verbatim term being the same for the first and repeated AE, so that the repeated AE 
can be easily identified as the worsening of the first one 
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12.1.2.3 
Additional procedures for reporting serious adverse events 
If an SAE is reported, UCB must be informed within 24 hours of receipt of this information by 
the site. The Investigator must enter the information regarding the SAE into the appropriate 
eCRFs and transmit to UCB via the clinical database, even if the data are incomplete, or if it is 
obvious that more data will be needed in order to draw any conclusions. This information will be 
received by UCB and entered into the global safety database. Any ancillary documentation (eg, 
autopsy or other documentation) that is valid for the SAE can be sent to UCB using the contact 
information (fax/email) for SAE reporting listed in the Serious Adverse Event Reporting section 
at the front of the protocol. 
It is important for the Investigator, when entering the SAE data into the eCRF, to include the 
assessment as to a causal relationship between the SAE and the IMP administration. This insight 
from the Investigator is very important for UCB to consider in assessing the safety of the IMP 
and in determining whether the SAE requires reporting to the regulatory authorities in an 
expedited manner. 
Additional information received by the Investigator must be provided within 24 hours. All 
documents in the local language must be accompanied by a translation in English or the relevant 
information included in the same document must be summarized in the eCRF and transmitted to 
UCB via the clinical database. 
The Investigator is specifically requested to collect and report to UCB (or its representative) any 
SAEs (even if the Investigator is certain that they are in no way associated with the IMP), up to 
30 days from the end of the study for each subject, and to also inform participating subjects of 
the need to inform the Investigator of any SAE within this period. Serious AEs that the 
Investigator thinks may be associated with the IMP must be reported to UCB regardless of the 
time between the event and the end of the study. 
Upon receipt of the electronic transmission of the SAE, UCB will perform as assessment of 
expectedness of the reported SAE. The assessment of expectedness of the SAE is based on the 
IB. 
12.1.3 
Follow up of adverse events 
An AE should be followed until it has resolved, has stable sequelae, the Investigator determines 
that it is no longer clinically significant, or the subject is lost to follow up. This follow-up 
requirement applies to AEs, SAEs, and AEs of special interest; AEs of special monitoring, 
further details regarding follow up of PDILI events is provided in Section 12.2.1.4.  
If an AE is ongoing at the end of the study for a subject, follow up should be provided until 
resolution/stable level of sequelae is achieved, or until the Investigator no longer deems that it is 
clinically significant, or until the subject is lost to follow up. If no follow up is provided, the 
Investigator must provide a justification. The follow up will usually be continued for 20 weeks 
after the subject has discontinued his/her IMP. 
Information on SAEs obtained after clinical database lock will be captured through the Patient 
Safety (PS) database without limitation of time. 
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12.1.4 
Pregnancy 
If the Investigator is notified that a subject has become pregnant after the first intake of any IMP, 
the Investigator must immediately (within 24 hours) notify UCB’s PS department by entering all 
pregnancy information into the eCRF. An automatic notification will be sent to UCB PS. The 
subject should be permanently withdrawn from IMP as soon as pregnancy is known (by positive 
pregnancy test), and the following should be completed: 
• The subject should immediately stop the intake of the IMP. 
• The subject should return for an early ad-hoc study visit. 
• A Safety Follow-Up Visit should be scheduled 20 weeks after the final dose of IMP. 
The Investigator should discuss with the subject the possibility to continue the study by attending 
the scheduled visits for assessments without IMP administration. The tests or assessments, which 
are considered contraindicated during the pregnancy should not be performed. The early ad-hoc 
study visit will be considered as the ET visit if the subject does not wish to pursue the study 
investigations. 
The Investigator must inform the subject of information currently known about potential risks 
and about available treatment alternatives. 
The pregnancy will be documented in the eCRF provided to the Investigator. The progression of 
the pregnancy and the eventual birth (if applicable) must be followed up using the eCRF in 
which the Investigator has to report on the health of the mother and of the child. Every 
reasonable attempt should be made to follow the health of the child for 30 days after birth for any 
significant medical issues. In certain circumstances, UCB may request that follow up is 
continued for a period longer than 30 days. If the subject is lost to follow up and/or refuses to 
give information, written documentation of attempts to contact the subject needs to be provided 
by the Investigator and filed at the site. UCB’s PS department is the primary contact for any 
questions related to the data collection for the pregnancy, eventual birth, and follow up. 
In cases where the partner of a male subject enrolled in a clinical study becomes pregnant, the 
Investigator or designee is asked to contact the subject to request consent of the partner via the 
Partner Pregnancy Consent form that has been approved by the responsible IRB/IEC and should 
be available in the Investigator site file. In case of questions about the consent process, the 
Investigator may contact the UCB/contract research organization (CRO) contract monitor for the 
study. The Investigator will complete the information in the eCRF only after the partner has 
agreed that additional information can be captured and has provided the signed Partner 
Pregnancy Consent form. UCB’s PS department is also the primary contact for any questions 
related to the data collection for partner pregnancy, eventual birth, and follow-up. 
A pregnancy becomes an SAE in the following circumstances: miscarriage, elective abortion, 
medically indicated abortion (eg, when the pregnancy is endangering life or health of woman or 
when fetus will be born with severe abnormalities), unintended pregnancy after hormonal 
contraceptive failure (if the hormonal contraceptive was correctly used), ectopic pregnancy, fetal 
demise, or any congenital anomaly/birth defect of the baby. Those SAEs must be additionally 
reported using the eCRF. 
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12.1.5 
Suspected transmission of an infectious agent via a medicinal 
product 
For the purposes of reporting, any suspected transmission of an infectious agent via a medicinal 
product should be considered as an SAE; such cases must be reported immediately, recorded in 
the AE module of the eCRF, and followed as any other SAE. Any organism, virus, or infectious 
particle (eg, prion protein transmitting transmissible spongiform encephalopathy), pathogenic or 
nonpathogenic, is considered an infectious agent. 
12.1.6 
Overdose of investigational medicinal product 
Excessive dosing (beyond that prescribed in the protocol and including overdose) should be 
recorded in the eCRF. Any SAE or nonserious AE associated with excessive dosing must be 
followed as any other SAE or nonserious AE. These events are only considered AEs or SAEs if 
there are associated clinical signs and symptoms or if the act of taking the excess medicine itself 
is an AE or SAE (eg, suicide attempt). 
12.1.7 
Safety signal detection 
Selected data from this study will be reviewed periodically to detect as early as possible any 
safety concern(s) related to the IMP so that Investigators, clinical study subjects, regulatory 
authorities, and IRBs/IECs will be informed appropriately and as early as possible. 
The Study Physician or medically qualified designee/equivalent will conduct an ongoing review 
of SAEs and perform ongoing SAE reconciliations in collaboration with the PS representative. 
As appropriate for the stage of development and accumulated experience with the IMP, 
medically qualified personnel at UCB may identify additional safety measures (eg, AEs, vital 
signs, laboratory or ECG results) for which data will be periodically reviewed during the course 
of the study. 
In addition, an independent Data Monitoring Committee (DMC) will periodically review and 
monitor the safety data from this study and advise UCB. The DMC membership includes 
clinicians knowledgeable about the disease or the treatment. All members have experience and 
expertise in clinical studies. Board members may not participate in the study as principal or 
co-Investigators, or as study subject care physicians. The duration of membership for the DMC 
will be inclusive of planned analyses for PA0011. The DMC may also be asked to provide a 
review of final study results, as deemed appropriate. The DMC procedures will ensure that data 
remain blind to the study team and Investigators at all times throughout the conduct of the study. 
The detailed role, scope, responsibilities, and complete procedures, as well as the identity of the 
DMC members, will be described in a separate charter document. A Cardiovascular Adjudication 
Committee and a Neuropsychiatric Adjudication Committee will be in place for this study. 
Specific procedures will be outlined in the charters, which will be developed by the committee 
members. 
12.2 
Laboratory measurements 
Clinical laboratory assessments consist of serum biochemistry, hematology, urinalysis and 
pregnancy tests (serum or urine) (Table 5-1). A centralized laboratory will be used to supply all 
laboratory test supplies and analyze all blood and urine samples for hematology and 
biochemistry. Any unscheduled laboratory testing should also be collected using the central 
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laboratory (with the exception of urgent safety laboratory measurements which should be 
performed locally and centrally simultaneously). Testing to rule out hepatitis B, hepatitis C, and 
HIV will be performed at Screening. Rheumatoid factor and anti-CCP testing will also be 
performed at Screening. Testing of HLA-B27 will be performed at Baseline. 
Specific details regarding the handling and processing of serum biochemistry and hematology, 
are provided in the study laboratory manuals. 
Laboratory parameters to be measured are presented in Table 12-2. 
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Table 12-2: Laboratory measurements 
Hematology 
Biochemistry 
Urinalysis  
Basophils 
Calcium 
pH 
Eosinophils 
Chloride 
Albumin (protein) 
Lymphocytes 
Magnesium 
Glucose 
 Monocytes 
Potassium 
Blood 
 Neutrophils 
Sodium 
Leukocyte esterase 
 Hematocrit 
Glucose 
Nitrite 
 Hemoglobin 
BUN 
Urine dipstick for pregnancy testing b 
 MCH 
Creatinine 
Urine drug screen c 
 MCHC 
hs-CRP 
 
 MCV 
AST 
 
 Platelet count 
ALT 
 
 RBC count 
GGT 
 
 WBC count 
ALP 
 
 
Total bilirubin 
 
 
Triglyceridesa 
 
 
Cholesterola 
 
 
HDL cholesterola 
 
 
LDL cholesterola 
 
 
LDH 
 
 
Serum pregnancy testing b 
 
ALP=alkaline phosphatase; ALT=alanine aminotransferase; AST=aspartate aminotransferase; BUN=blood urea 
nitrogen; ET=early termination; GGT=gamma-glutamyltransferase; HDL=high density lipoprotein; hs-
CRP=high sensitivity C-reactive protein; IMP=investigational medicinal product; LDH=lactate dehydrogenase; 
LDL=low density lipoprotein; MCH=mean corpuscular hemoglobin; MCHC=mean corpuscular hemoglobin 
concentration; MCV=mean corpuscular volume; RBC=red blood cell; SFU=Safety Follow-Up; WBC=white 
blood cell 
a Biochemistry will include triglycerides, cholesterol, HDL cholesterol, and LDL cholesterol at Baseline, Week 
16, and at the ET Visit. 
b Pregnancy testing will consist of serum testing at the Screening Visit for all women of childbearing potential. 
The pregnancy test will be urine at all other visits. 
c Urine drug screen will be performed at the Screening Visit. 
12.2.1 
Evaluation of potential drug-induced liver injury 
The PDILI IMP discontinuation criteria for this study are provided in Section 6.3.1, with the 
accompanying required follow-up investigation and monitoring detailed below. All PDILI events 
must be reported as AEs and PDILI events meeting SAE criteria should be reported to the study 
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site and Sponsor within 24 hours of learning of their occurrence. Any PDILI event that meets the 
criterion for potential Hy’s Law must be reported within 24 hours of learning of their occurrence 
as an AE of special interest (see Section 12.1.1.3), and, if applicable, also reported as an SAE 
(see Section 12.1.1.2).  
Evaluation of PDILI consists of the diagnostic testing and continued monitoring included in 
Table 12‒3 (specific tests dependent on laboratory results and corresponding symptoms) and 
consultation with a local hepatologist (if applicable; discussed in Section 12.2.1.1). The local 
hepatologist is the expert usually consulted by the treating physician for assessment and 
management of potential hepatic disease. This would usually be a hepatologist but may be a 
gastroenterologist. Additional investigation and monitoring may be required and adapted based 
on the diagnosis after the cause of the liver injury/abnormality is confirmed (details in 
Section 12.2.1.4).  
The results of all monitoring, including laboratory testing and other testing, should be made 
available to the study site and Sponsor. 
All initial tests resulting in abnormal hepatic laboratory values need to be repeated, but 
appropriate medical action must not be delayed waiting for the repeat result. 
If tests are done locally for more rapid results, a concurrent sample should also be sent to the 
central laboratory whenever possible. Medical care decisions are to be made initially using the 
most rapidly available results and a conservative approach must be taken if the results from the 
2 laboratory tests are significantly different. Data from the local and central laboratory are to be 
recorded on the applicable eCRF pages. 
When IMP is discontinued, all concomitant medications and herbal supplements that are not 
medically necessary should also be discontinued. In these cases, the Investigator should also 
consider dose reduction for medically necessary concomitant medication and consider changing 
any medically required concomitant medication known to be hepatotoxic to a suitable 
alternative. 
When IMP is stopped due to PDILI (as described in Section 6.3.1), IMP must be permanently 
discontinued unless a subsequent alternative diagnosis fully explains the hepatic findings. If a 
subsequent alternative diagnosis fully explains the hepatic findings, and the requirements 
provided in Section 12.2.1.2.1 are met, rechallenge with IMP may be appropriate. 
The approach to investigate PDILI is summarized in Table 12‒3. 
 
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Table 12‒3: Required investigations and follow-up for PDILI 
Laboratory value 
 
Immediate 
Follow up 
ALT or 
AST 
Total 
bilirubin 
Symptomsa of 
hepatitis of 
hypersensitivity 
Consultation 
requirements 
Actions 
Testing 
Evaluation 
≥3xULN 
≥2xULNb NA 
Hepatology consultc 
Medical Monitor must 
be notified within 
24 hours (eg, by 
laboratory alert) and 
subject discussed with 
Medical Monitor 
ASAP. 
 
Immediate IMP 
discontinuation.d 
 
 
 
Essential: Must have 
repeat liver 
chemistry values 
and additional 
testing completed 
ASAP (see 
Section 12.2.1.3); 
recommended to 
occur at the site with 
HCP. 
Monitoring of liver 
chemistry values at least 
twice per week until 
values normalize, 
stabilize, or return to 
within baseline values.e 
≥3xULN 
NA 
Yes 
≥8xULN 
NA 
NA 
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Table 12‒3: Required investigations and follow-up for PDILI 
Laboratory value 
 
Immediate 
Follow up 
ALT or 
AST 
Total 
bilirubin 
Symptomsa of 
hepatitis of 
hypersensitivity 
Consultation 
requirements 
Actions 
Testing 
Evaluation 
≥5xULN 
(and ≥2x 
baseline) 
and 
<8xULN  
<2xULN 
No 
Discussion with 
Medical Monitor 
required. 
Consider need for 
hepatology consult if 
there is no evidence of 
resolution (see Follow 
up requirements).c 
Further investigation 
– immediate IMP 
discontinuation not 
required (see 
Section 12.2.1.2). 
 
IMP discontinuation 
required if any of the 
following occur: 
• 
Subject cannot 
comply with 
monitoring 
schedule. 
• 
Liver chemistry 
values continue 
to increase. 
• 
Liver chemistry 
values remain 
≥5xULN (and 
≥2x baseline) 
after 4 weeks of 
monitoring 
without evidence 
of resolution. 
Essential: Every 
attempt must be 
made to have repeat 
liver chemistry 
values and 
additional testing 
completed within 
48 hours at the site 
with HCP (see 
Section 12.2.1.3). 
Monitoring of liver 
chemistry values at least 
twice per week for 
2 weeks.e 
• 
Immediate IMP 
discontinuation 
required if liver 
chemistry values 
continue to increase. 
After 2 weeks of 
monitoring liver 
chemistry values: 
• 
ALT or AST remains 
≥5xULN <8xULN, 
IMP should be 
temporarily withheld 
and subject should 
undergo repeat test in 
2 weeks. 
• 
Continue IMP if ALT 
or AST values 
<5xULN; continue to 
monitor at least twice 
per week until values 
normalize, stabilize, 
or return to within 
baseline values. 
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Table 12‒3: Required investigations and follow-up for PDILI 
Laboratory value 
 
Immediate 
Follow up 
ALT or 
AST 
Total 
bilirubin 
Symptomsa of 
hepatitis of 
hypersensitivity 
Consultation 
requirements 
Actions 
Testing 
Evaluation 
• 
If ALT or AST 
remains ≥5xULN 
after second re-test, 
immediate IMP 
discontinuation 
required. 
Continue to monitor until 
values normalize, 
stabilize, or return to 
within baseline values.e 
ALP=alkaline phosphatase; ALT=alanine aminotransferase; ASAP=as soon as possible; AST=aspartate aminotransferase; HCP=healthcare practitioner; 
IMP=investigational medicinal product; NA=not applicable; PDILI=potential drug-induced liver injury; ULN=upper limit of normal 
a Hepatitis symptoms include fatigue, nausea, vomiting, and right upper quadrant pain or tenderness; hypersensitivity symptoms include eosinophilia (>5%), 
rash, and fever (without clear alternative cause). 
b If the subject also has ≥2xULN ALP, the possibility of an indication of biliary obstruction should be discussed with the Medical Monitor. 
c Details provided in Section 12.2.1.1. The local hepatologist is the expert usually consulted by the treating physician for assessment and management of 
potential hepatic disease. This would usually be a hepatologist but may be a gastroenterologist. 
d Details are provided in Section 12.2.1.2.  
e Unless an alternative monitoring schedule is agreed by the Investigator and UCB responsible physician. Determination of stabilization is at the discretion of the 
Investigator in consultation with the hepatologist (as applicable) and UCB responsible physician, as needed. 
 
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12.2.1.1 
Consultation with Medical Monitor and local hepatologist  
Potential drug-induced liver injury events require notification of the Medical Monitor within 
24 hours (eg, by laboratory alert), and the subject must be discussed with the Medical Monitor as 
soon as possible. If required, the subject must also be discussed with the local hepatologist. The 
local hepatologist is the expert usually consulted by the treating physician for assessment and 
management of potential hepatic disease. This would usually be a hepatologist but may be a 
gastroenterologist. If determined necessary, this discussion should be followed by a full 
hepatology assessment (see Section 12.2.1.3) and SAE report (if applicable). 
12.2.1.2 
Immediate action: determination of IMP discontinuation 
All PDILI events require immediate action, testing, and monitoring.  
The immediate action is dependent on the laboratory values and symptoms of hepatitis or 
hypersensitivity and ranges from continuation of IMP (followed by immediate investigation) to 
immediate and permanent discontinuation (see Section 6.3.1 and Table 12‒3 for details). 
When IMP is discontinued, all concomitant medications and herbal supplements that are not 
medically necessary should also be discontinued. The Investigator should also consider dose 
reduction for medically necessary concomitant medication and consider changing any medically 
required concomitant medication known to be hepatotoxic to a suitable alternative. 
12.2.1.2.1 
IMP restart/rechallenge  
Subjects who are immediately discontinued from IMP due to having met certain criteria for 
PDILI (as described in Section 6.3.1 and Table 12‒3), but for whom an alternative diagnosis is 
confirmed, ie, drug-induced liver injury is excluded, can rarely restart IMP. Rechallenge with 
IMP can occur only if ALL of the following requirements are met at the time of the rechallenge: 
• The results of additional testing and monitoring described in Section 12.2.1.3 and 
Section 12.2.1.4 confirm a nondrug-related cause for the abnormal hepatic laboratory 
parameters and any associated symptoms (ie, a subsequent alternative diagnosis fully 
explains the hepatic findings).  
• No alternative treatment options are available to the subject. 
• The subject has shown clear therapeutic benefit from the IMP. 
• Subject’s ALT or AST elevations do not exceed ≥3xULN. 
• Subject’s total bilirubin is <1.5xULN. 
• Subject has no signs or symptoms of hypersensitivity.  
• The rechallenge is approved by the UCB responsible physician and a hepatologist. The 
hepatologist must be external to UCB. It is recommended that the hepatologist be a local 
hepatology expert or the hepatologist treating the subject. 
• Subject agrees to the investigator-recommended monitoring plan and understands their 
individual benefit/risk for restarting IMP and this is adequately documented.  
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12.2.1.3 
Testing: identification/exclusion of alternative etiology 
The measurements and additional information required for the assessment of PDILI events when 
there is a reasonable possibility that they may have been caused by the IMP are detailed in 
Table 12-4 (laboratory measurements) and Table 12-5 (additional information). Results of the 
laboratory measurements and information collected are to be submitted to the Sponsor on the 
corresponding eCRF. If the medical history of the subject indicates a requirement for other 
assessments not included below, these additional assessments should be completed and 
submitted, as applicable. 
All blood samples should be stored, if possible. If tests are done locally for more rapid results, a 
concurrent sample must also be sent to the central laboratory. 
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The following measurements are to be assessed: 
Table 12-4: PDILI laboratory measurements 
Virology-
related 
Hepatitis A IgM antibody 
HBsAg 
Hepatitis E IgM antibody 
HBcAb-IgM 
Hepatitis C RNA 
Cytomegalovirus IgM antibody 
Epstein-Barr viral capsid antigen IgM antibody (if unavailable, obtain heterophile 
antibody or monospot testing) 
Immunology 
Anti-nuclear antibody (qualitative and quantitative) 
Anti-smooth muscle antibody (qualitative and quantitative) 
Type 1 anti-liver kidney microsomal antibodies (qualitative and quantitative) 
Hematology 
Eosinophil count 
Urinalysis 
Toxicology screena 
Chemistry 
Amylase 
Sodium, potassium, chloride, glucose, BUN, creatinine 
Total bilirubin, ALP, AST, ALT, GGT, total cholesterol, albumin 
If total bilirubin ≥1.5xULN, obtain fractionated bilirubin to obtain % direct bilirubin 
Serum CPK and LDH to evaluate possible muscle injury causing transaminase 
elevation 
Additional 
Prothrombin time/INRb 
Serum pregnancy test 
PK sample 
ALT=alanine aminotransferase; CPK=creatine phosphokinase; HBcAb-IgM=hepatitis B core antibody-IgM; 
HBsAg=hepatitis B surface antigen; IgM=immunoglobulin M; INR=international normalized ratio; 
LDH=lactate dehydrogenase; PDILI=potential drug-induced liver injury; PK=pharmacokinetic; 
RNA=ribonucleic acid; ULN=upper limit of normal 
a For detecting substances (ie, amphetamines, benzodiazepines, opioids, marijuana, cocaine, phencyclidine, and 
tricyclic antidepressants), additional tests may be performed based on the Investigator’s medical judgment and 
subject’s history. 
b Measured only for subjects with ALT >8xULN, elevations in total bilirubin, and symptoms of hepatitis or 
hypersensitivity. Hepatitis symptoms include fatigue, nausea, vomiting, and right upper quadrant pain or 
tenderness; hypersensitivity symptoms include eosinophilia (>5%), rash, and fever (without clear alternative 
cause). 
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Additional information to be collected is presented in Table 12-5.  
Table 12-5: PDILI information to be collected 
New or updated information 
Concomitant prescription and over-the-counter medications (eg, acetaminophen, herbal remedies, 
vitamins); dosages and dates should be included. 
Pertinent medical history, including the following: 
• 
History of liver disease (eg, autoimmune hepatitis, nonalcoholic steatohepatitis or other “fatty 
liver disease”) 
• 
Adverse reactions to drugs 
• 
Allergies 
• 
Relevant family history or inheritable disorders (eg, Gilbert’s syndrome, alpha-1 antitrypsin 
deficiency) 
• 
Recent travel  
• 
Progression of malignancy involving the liver (Note: Metastatic disease to the liver, by itself, 
should not be used as an explanation for significant AST and/or ALT elevations.) 
The appearance or worsening of clinical symptoms of hepatitis or hypersensitivity (eg, fatigue, nausea, 
vomiting, right upper quadrant pain or tenderness, decreased appetite, abdominal pain, jaundice, fever, 
or rash) 
Recent clinically significant hypotension or hypoxemia with compromised cardiopulmonary function 
Alcohol and illicit drug use 
Results of liver imaging or liver biopsy, if done 
Results of any specialist or hepatology consult, if done 
Any postmortem/pathology reports 
ALT=alanine aminotransferase; AST=aspartate aminotransferase; PDILI=potential drug-induced liver injury 
12.2.1.4 
Follow-up evaluation 
Potential drug-induced liver injury events require follow-up monitoring as described in 
Table 12‒3. Monitoring should continue until liver chemistry values normalize, stabilize, or 
return to baseline. Determination of stabilization is at the discretion of the Investigator in 
consultation with the hepatologist (as applicable) and UCB responsible physician, as needed. 
12.3 
Other safety measurements 
12.3.1 
Vital signs 
The Investigator or designee should measure all vital signs (BP, temperature [oral, axillary, or 
otic], and pulse rate) after the subject has been sitting for at least 5 minutes, and the subject 
should remain seated during the measurements. At Baseline, vital signs will be measured prior to 
IMP administration and then at approximately 30 minutes and 1 hour after dosing. At all other 
administrations of IMP, vital signs will be measured only once prior to dosing. 
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12.3.2 
Body weight and height 
The Investigator or designee will measure the height of the subject with shoes removed in meters 
and the weight of the subject in kilograms. The same scale should be utilized throughout the 
study where possible. 
12.3.3 
Physical examination 
The physical examination should be conducted by the Investigator or designee at the time points 
listed in Table 5-1 and will include general appearance; ear, nose, and throat; eyes, hair, and 
skin; respiratory; cardiovascular; gastrointestinal; musculoskeletal; hepatic; neurological 
(including limb reflexes); and mental status. Findings considered clinically significant changes 
since the physical examination at the Screening Visit will be recorded as AEs. 
12.3.4 
12-lead electrocardiogram 
The Investigator or designee will perform the ECGs which will be read centrally. Full details of 
ECG recording will be provided in the ECG Manual. 
12.3.5 
Patient Health Questionnaire-9 (PHQ-9)  
The PHQ-9 is a multipurpose instrument for screening, diagnosing, monitoring, and measuring 
the severity of depression. The PHQ-9 scores for depression range from 0 to 27 with higher 
scores indicating worse state. A score of 5 to 9 is considered to be minimal symptoms of 
depression. A score of 10 to 14 is considered minor depression, dysthymia, or mild major 
depression. A score of 15 to 19 is considered to indicate moderately severe major depression, 
and a score >20 is considered to be severe major depression.  
The PHQ-9 will be assessed at the visits specified in Table 5-1.  
Refer to Section 6.3 for PHQ-9-related withdrawal criteria. 
12.3.6 
Assessment and management of TB and TB risk factors 
All subjects will be assessed for TB at Screening and at the time points specified in the schedule 
of study assessments (Table 5-1) through physical examination for signs and symptoms of TB, 
chest x-ray (Section 12.3.6.2), laboratory testing (Section 12.3.6.1), and subject questionnaire 
(Section 12.3.6.3).  
At Screening, all subjects will have an IGRA test (QuantiFERON TB Test is recommended), a 
chest x-ray (unless already performed within 3 months of Screening) and examination for signs 
and symptoms of TB. In addition, each subject will complete a TB questionnaire directed at 
potential exposure to TB and symptoms of TB.  
For the purposes of this study, TB definitions are as follows: 
a. Known TB infection: 
− Active TB infection or clinical signs and symptoms suspicious for TB (pulmonary or 
extra-pulmonary). 
− History of active TB infection involving any organ system or findings in other organ 
systems consistent with TB infection, unless adequately treated and proven to be fully 
recovered upon consult with a TB specialist. 
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− Any evidence by radiography or other imaging modalities consistent with previously 
active TB infection that is not reported in the subject’s medical history. 
b. High risk of acquiring TB infection: 
− Known close exposure to another person with active TB infection within the 3 months 
prior to Screening. 
− Time spent in a healthcare delivery setting or institution where individuals infected with 
TB are housed and where the risk of transmission of infection is high. 
c. Latent TB infection (unless appropriate prophylaxis is initiated at least 4 weeks prior to IMP 
dosing and continued to completion of prophylaxis): 
− The absence of signs, symptoms, or physical findings suggestive of TB infection with a 
positive IGRA test (or 2 indeterminate IGRA test results) and a chest x-ray (or other 
imaging) without evidence of TB infection. If the result of the IGRA test is 
indeterminate, the particular IGRA test previously performed may be repeated once; if 
positive or indeterminate on retest, the subject may not be randomized to IMP without 
further evaluation by a TB specialist and discussion with the Study Physician, if LTB 
infection is identified. The retest must be done during the protocol-defined Screening 
window. 
− Note: If available, respiratory or other specimens must also be smear and culture negative 
for TB (Center for Disease Control diagnosis of LTBI; http://www.cdc.gov/TB/topic 
/testing/default.htm). 
d. NTMB infection is defined as a clinical infection caused by mycobacterial species other than 
those belonging to the Mycobacterium tuberculosis complex. 
e. Tuberculosis test conversion: 
− A positive IGRA result for the current test when previous IGRA test results were 
negative. All subjects with TB test conversion must immediately stop IMP administration 
and be referred to a TB specialist for further evaluation. Confirmed TB test conversions 
should be classified as due to LTBI, active TB infection, or NTMB, and reported to the 
UCB PS function. 
Subject eligibility, retesting requirements, and treatment requirements are presented in 
Figure 12-1. A schematic diagram of TB test results during the study is presented in Figure 12‒2. 
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Figure 12-1: Schematic diagram of TB test results and study eligibility 
 
CDC=Center for Disease Control; IGRA-interferon-gamma release assay; LTBI= latent tuberculosis infection; 
TB=tuberculosis; WHO=World Health Organization 
a IGRA retest must be done during the protocol-defined Screening window. 
b Subject has a past history of active TB involving any organ system unless adequately treated according to 
WHO/CDC therapeutic guidance and proven to be fully recovered upon consult with a TB specialist. Subjects who 
have recently (no more than 12 months prior to Screening) completed full treatment course of prophylaxis for 
LTBI are allowed. Prophylaxis should be in accordance with WHO/CDC guidelines and TB specialist judgment 
based on the origin of infection.  
c Subjects with LTBI may enter the study only after they have completed at least 4 weeks of appropriate 
prophylactic therapy and thereafter, will continue and complete the entire regimen. 
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Figure 12‒2: Schematic diagram of TB test results during the study 
 
ASAP=as soon as possible; IGRA-interferon-gamma release assay; LTBI=latent tuberculosis infection; 
TB=tuberculosis;  
a IGRA retest must be done ASAP and prior to the next dose. 
b Subjects with LTBI may continue the study only after they have completed at least 4 weeks of appropriate 
prophylactic therapy and thereafter, will continue and complete the entire regimen.  
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12.3.6.1 
Tuberculosis assessment by IGRA 
During conduct of the study, the TB assessment by IGRA (QuantiFERON-TB Test is 
recommended) will be performed as described in Table 5-1 for all subjects. The test results will 
be reported as positive, negative, or indeterminate. Positive and indeterminate TB test results that 
occur during the course of the study must be reported as an AE and appropriately updated once 
the final diagnosis is known (eg, active TB, latent TB, or false positive TB test). UCB also 
recommends that a TB specialist be consulted where TB (latent or active) is suspected or if there 
are doubts regarding test results. If latent or active TB is identified, subjects must undergo 
appropriate study-specified withdrawal procedures. The retest during Screening must be done 
during the protocol-defined Screening window. 
12.3.6.2 
Chest x-ray for tuberculosis 
A plain posteroanterior chest x-ray must be performed in the Screening Period unless one has 
been performed within 3 months prior to the Screening Visit. The chest x-ray (or, if done, 
Computed Axial Tomography of the chest) must be clear of signs of TB infection (previous or 
current) before first IMP administration. All chest imaging (particularly x-rays) should be 
available for review by the Investigator before randomization of the subject. The chest x-ray 
reading should be repeated if the TB test was confirmed positive. If the second read of the 
pretreatment chest x-ray is confirmed to be clear, the subject may be included in the study 
4 weeks after the start of the TB prophylactic treatment. If the pretreatment chest x-ray is not 
available for a re-read, it should be repeated after notification to the radiologist that this subject 
is IGRA positive and confirmed to be clear for signs of TB. 
The chest imaging must be negative for any old or recent TB infection as determined by a 
qualified radiologist and/or pulmonary physician. Any new clinically significant findings post 
Baseline on chest x-ray must be documented in the source documents and the eCRF as an AE. 
12.3.6.3 
Tuberculosis questionnaire 
The questionnaire “Evaluation of signs and symptoms of tuberculosis” should be used as a 
source document. The questionnaire will be completed as described in Table 5-1. The 
questionnaire will assist with the identification of subjects who may require therapy for TB. A 
subject who answers “Yes” to the question 
 
 at Screening 
is excluded. A “Yes” response to any of the other questions within the questionnaire at Screening 
should trigger further careful assessment to determine if subject has LTB or active TB (see 
Exclusion Criterion #11 in Section 6.2). A “Yes” response to any of the questions during the 
study should trigger further assessments to determine if the subject has either LTB or active TB 
infection.   
12.3.6.4 
Tuberculosis management 
LTB infection and active TB identified during study 
During the study, subjects who develop evidence of LTB infection or active TB must 
immediately stop further administration of IMP and will be referred to an appropriate TB 
specialist (pulmonologist or infectious disease specialist) for further evaluation. Evidence of 
LTB infection is defined as subject’s IGRA test converts to positive or indeterminate (and 
confirmed indeterminate on repeat), or the subject’s questionnaire or history and physical 
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indicates that TB infection or exposure may have occurred. Evidence of active TB includes, in 
addition to the aforementioned tests, signs and symptoms of organ involvement. In either 
situation, the subject should be carefully assessed by a TB specialist for active TB. Subjects 
diagnosed with active TB should be withdrawn from the study and receive appropriate TB or 
prophylaxis therapy.  
If a TB specialist excludes an active TB infection, the subject can proceed with the IMP no 
earlier than 4 weeks after the start of an appropriate prophylactic therapy. 
Any presumptive diagnosis or diagnosis of a TB infection is a reportable event. Confirmed active 
TB must be reported as an SAE. The Investigator is to complete and submit the TB follow-up 
form provided. 
The subject should be transferred to the care of his/her physician and managed according to the 
best available standard of care. Subjects identified as having converted to active TB during the 
study must be withdrawn and scheduled to return for the ET Visit as soon as possible but no later 
than the next scheduled study visit and complete all ET Visit assessments.  
The subject should be encouraged to complete a SFU Visit (20 weeks after the final dose of 
IMP). 
If infection with NTMB is identified during the study, the same procedure as for active TB 
acquired during the study must be followed. 
12.3.7 
Pregnancy testing 
Pregnancy testing will consist of serum testing at Screening for all women of childbearing 
potential. The pregnancy test will be urine at all other visits. 
The Screening Visit serum pregnancy testing results must be negative and received and reviewed 
prior to randomization. A negative urine pregnancy test result should be obtained immediately 
prior to each administration of IMP at the visits specified in Table 5-1. Pregnancy tests should be 
administered to all female subjects of childbearing potential, regardless of their use of birth 
control.  
12.3.8 
Assessment of suicidal ideation and behavior 
Suicidal ideation and behavior will be assessed by trained study personnel using the eC-SSRS. 
This scale will be used to assess suicidal ideation and behavior that may occur during the study. 
The visits at which the eC-SSRS assessments will be performed are specified in the schedule of 
study assessments (Table 5-1). 
The eC-SSRS is a standardized and validated instrument developed for the assessment of the 
severity and frequency of suicidal ideation and behavior (Posner et al, 2011; Mundt et al, 2010). 
Subjects respond to standardized clinical questions that are presented in a uniform fashion. The 
eC-SSRS defines 5 subtypes of suicidal ideation and behavior in addition to self-injurious 
behavior with no suicidal intent. The eC-SSRS takes approximately 3 to 10 minutes to complete. 
Refer to Section 6.3 for eC-SSRS-related withdrawal criteria.  
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13 
STUDY MANAGEMENT AND ADMINISTRATION  
13.1 
Adherence to protocol 
The Investigator should not deviate from the protocol. However, the Investigator should take any 
measure necessary in deviation from or not defined by the protocol in order to protect clinical 
study subjects from any immediate hazard to their health and safety. In this case, this action 
should be taken immediately, without prior notification of the regulatory authority, IRB/IEC, or 
Sponsor. 
After implementation of such measure, the Investigator must notify the CPM of the Sponsor 
within 24 hours and follow any local regulatory requirements. 
13.2 
Monitoring 
UCB (or designee) will monitor the study to meet the Sponsor’s monitoring SOPs, ICH-GCP 
guideline, and applicable regulatory requirements, and to ensure that study initiation, conduct, 
and closure are adequate. Monitoring of the study may be delegated by UCB to a CRO or a 
contract monitor. 
The Investigator and his/her staff are expected to cooperate with UCB (or designee) and to be 
available during the monitoring visits to answer questions sufficiently and to provide any 
missing information. The Investigator(s)/institution(s) will permit direct access to source 
data/documents for study-related monitoring, audits, IRB/IEC review, and regulatory 
inspection(s). 
The Investigator will allow UCB (or designee) to periodically review all eCRFs and 
corresponding source documents (eg, hospital and laboratory records for each study participant). 
Monitoring visits will provide UCB (or designee) with the opportunity to evaluate the progress 
of the study, verify the accuracy and completeness of eCRFs, ensure that all protocol 
requirements, applicable authorities’ regulations, and Investigator’s obligations are being 
fulfilled, and resolve any inconsistencies in the study records. 
13.2.1 
Definition of source data 
All source documents must be accurate, clear, unambiguous, permanent, and capable of being 
audited. They should be made using some permanent form of recording (ink, typing, printing, 
optical disc). They should not be obscured by correction fluid or have temporary attachments 
(such as removable self-stick notes). Photocopies and/or printouts of eCRFs are not considered 
acceptable source documents. 
Source documents are original records in which raw data are first recorded. These may include 
hospital/clinic/general practitioner records, charts, diaries, x-rays, laboratory results, printouts, 
pharmacy records, care records, ECG or other printouts, completed scales, or QoL 
questionnaires, for example. Source documents should be kept in a secure, limited access area. 
Source documents that are computer generated and stored electronically must be printed for 
review by the monitor (eg, ECG reports). Once printed, these copies should be signed and dated 
by the Investigator and become a permanent part of the subject’s source documents. The 
Investigator will facilitate the process for enabling the monitor to compare the content of the 
printout and the data stored in the computer to ensure all data are consistent. 
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Electronic data records, such as Holter monitor records or electroencephalogram records, must 
be saved and stored as instructed by UCB (or designee). 
Electronic Patient-Reported Outcome (ePRO) measures (eg, PtAAP, EQ-5D-3L, SF-36, 
PGA-PsA, and PGA-arthritis) will be completed by each subject and will be collected 
electronically. 
The data collection and database management system will be supplied by a vendor and will be 
compliant with the relevant regulations. The data collected on the ePROs will be uploaded to a 
central server database and will be sent electronically to UCB (or a designated CRO). 
13.2.2 
Source data verification 
Source data verification ensures accuracy and credibility of the data obtained. During monitoring 
visits, reported data are reviewed with regard to being accurate, complete, and verifiable from 
source documents (eg, subject files, recordings from automated instruments, tracings [ECG], 
x-ray films, laboratory notes). All data reported on the eCRF should be supported by source 
documents, unless otherwise specified in Section 13.2.1. 
13.3 
Data handling 
13.3.1 
Case Report form completion 
This study will use electronic data capture (EDC); the Investigator is responsible for prompt 
reporting of accurate, complete, and legible data in the eCRFs and in all required reports. 
Any change or correction to the eCRF should be dated, initialed, and explained (if necessary) 
and should not obscure the original entry.  
Corrections made after the Investigator’s review and signature of the completed eCRF will be 
resigned and dated by the Investigator. 
The Investigator should maintain a list of personnel authorized to enter data into the eCRF. The 
Investigator is responsible for prompt reporting of accurate, complete, and legible data in the 
electronic eCRFs and in all required reports.  
Detailed instructions on the use of the EDC will be provided in the eCRF Completion 
Guidelines. 
Any change or correction to the eCRF after saving must be accompanied by a reason for the 
change. Corrections made after the Investigator’s review and approval (by means of a 
password/electronic signature) will be reapproved by the Investigator. 
13.3.2 
Database entry and reconciliation 
Case Report forms/external electronic data will be entered/loaded into a validated electronic 
database using a clinical data management system (CDMS). Computerized data cleaning checks 
will be used in addition to manual review to check for discrepancies and to ensure consistency of 
the data. Case Report form data are entered into the clinical database using independent, 
double-data entry, with the exception of comment fields, which are verified by a second person. 
The data are entered into the eCRFs once and are subsequently verified if the study is performed 
using electronic data capture. 
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An electronic audit trail system will be maintained within the CDMS to track all data changes in 
the database once the data have been saved initially into the system or electronically loaded. 
Regular backups of the electronic data will be performed. 
13.3.3 
Subject Screening and Enrollment log/Subject Identification Code list 
The subject’s screening and enrollment will be recorded in the Subject Screening and Enrollment 
Log. 
The Investigator will keep a Subject Identification Code list. This list remains with the 
Investigator and is used for unambiguous identification of each subject. 
The subject’s consent and enrollment in the study must be recorded in the subject’s medical 
record. These data should identify the study and document the dates of the subject’s 
participation. 
13.4 
Termination of the study 
UCB reserves the right to temporarily suspend or prematurely discontinue this study either at a 
single site, multiple sites, or at all sites at any time for reasons including, but not limited to, 
safety or ethical issues, inaccurate or incomplete data recording, noncompliance, or 
unsatisfactory enrollment with respect to quality or quantity. 
If the study is prematurely terminated or suspended, UCB (or its representative) will inform the 
Investigators/institutions and the regulatory authority(ies) of the termination or suspension and 
the reason(s) for the termination or suspension, in accordance with applicable regulatory 
requirement(s). The IRB/IEC should also be informed and provided with reason(s) for the 
termination or suspension by the Sponsor or by the Investigator/institution, as specified by the 
applicable regulatory requirement(s). In addition, arrangements will be made for the return of all 
unused IMP and other material in accordance with UCB procedures for the study. 
13.5 
Archiving and data retention 
The Investigator will maintain adequate records for the study, including eCRFs, medical records, 
laboratory results, Informed Consent documents, drug dispensing and disposition records, safety 
reports, information regarding participants who discontinued, and other pertinent data. 
All essential documents are to be retained by the Investigator until at least 2 years after the last 
approval of a marketing application in an ICH region and until there are no pending or 
contemplated marketing applications in an ICH region, or at least 2 years have elapsed since the 
formal discontinuation of clinical development of the IMP. These documents should be retained 
for a longer period, however, if required by the applicable regulatory requirement(s) or by an 
agreement with UCB (CPMP/ICH/135/95, 2002 [Section 4.9.5]). The Investigator will contact 
UCB for authorization prior to the destruction of any study records or in the event of accidental 
loss or destruction of any study records. The Investigator will also notify UCB should he/she 
relocate or move the study-related files to a location other than that specified in the Sponsor’s 
trial master file. 
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13.6 
Audit and inspection 
The Investigator will permit study-related audits mandated by UCB, after reasonable notice, and 
inspections by domestic or foreign regulatory authorities. 
The main purposes of an audit or inspection are to confirm that the rights and well-being of the 
subjects enrolled have been protected, that enrolled subjects (ie, signing consent and undergoing 
study procedures) are appropriate for the study, and that all data relevant for the evaluation of the 
IMP have been processed and reported in compliance with the planned arrangements, the 
protocol, investigational site, and IRB/IEC SOPs, ICH-GCP, and applicable regulatory 
requirements. 
The Investigator will provide direct access to all study documents, source records, and source 
data. If an inspection by a regulatory authority is announced, the Investigator will immediately 
inform UCB (or designee). 
13.7 
Good Clinical Practice 
Noncompliance with the protocol, ICH-GCP, or local regulatory requirements by the 
Investigator, institution, institution staff, or designees of the Sponsor will lead to prompt action 
by UCB to secure compliance. Continued noncompliance may result in the termination of the 
site’s involvement in the study. 
14 
STATISTICS 
A description of statistical methods follows and will be described in more detail in the SAP. 
14.1 
Definition of analysis sets 
The following analysis sets were defined: 
• The Enrolled Set (ES) consists of all subjects who have given informed consent. 
• The Randomized Set (RS) consists of all randomized subjects.  
• The Safety Set (SS) consists of all randomized subjects who received at least 1 dose of the 
IMP. 
• The Full Analysis Set (FAS) consists of all randomized subjects who received at least 1 dose 
of the IMP and have valid measurement of the components of the primary efficacy variable 
at Baseline. 
• The Per-Protocol Set (PPS) will consist of all subjects in the RS who had no important 
protocol deviations affecting the primary efficacy variable. Important protocol deviations 
will be predefined and subjects with important protocol deviations will be evaluated during 
ongoing data cleaning meetings prior to unblinding of the data. Exclusions from the FAS will 
be considered important protocol deviations that also result in exclusion from the PPS. 
• The Pharmacokinetic Per-Protocol Set (PK-PPS) consists of all randomized subjects who 
received at least one dose of the IMP and provided at least one quantifiable plasma 
concentration post-dose without important protocol deviations that would affect the 
concentration. Exclusions from the FAS will be considered important protocol deviations that 
also result in exclusion from the PK-PPS. 
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• The COVID-19-free Set will consist of all subjects in the RS who had no COVID-19 impact 
up to the primary efficacy endpoint. This will be defined as subjects not having a COVID-19 
related important protocol deviation, nor having an impact based on the COVID-19 eCRF 
nor having an AE related to COVID-19, nor discontinuing due to COVID-19 up to the time 
of the primary endpoint. 
14.2 
General statistical considerations 
Summary statistics will consist of frequency tables for categorical variables. For continuous 
variables, summary statistics will consist of number of available observations, arithmetic mean, 
SD, median, minimum, and maximum unless stated otherwise. 
All statistical tests will be performed 2-sided at a 5% level of significance unless stated 
otherwise. 
14.3 
Planned efficacy analyses 
14.3.1 
Analysis of the primary and secondary efficacy variables 
A fixed sequence testing procedure will be applied for the primary and selected secondary 
variables. The testing procedure will control the family-wise type-I-error and will account for 
multiplicity. The family-wise error will be set to α=0.05 (2-sided).  
For each test, on each binary efficacy endpoint, the null hypothesis is that the conditional odds 
ratio is equal to one.  
H0: ORT1T2 = 1 
The alternative hypothesis is that the conditional odds ratio is not equal to one. 
HA: ORT1T2≠ 0  
For each test, on each continuous efficacy endpoint, the null hypothesis is that there is no 
difference between treatment groups.   
H0: T1 – T2 = 0 
The alternative hypothesis is that there is a difference between treatment groups. 
HA: T1 – T2 ≠ 0  
For the primary and secondary variables, the primary comparison is the bimekizumab 160mg sc 
Q4W vs placebo. Point estimates and 95% confidence intervals (CI) will be calculated. 
The testing starts with H1. If H1 can be rejected at α=0.05 (2-sided), the corresponding α will be 
passed on to the next test in the sequence and testing will continue. The testing will be stopped if 
a hypothesis cannot be rejected at α=0.05 (2-sided). 
The fixed sequence testing procedure of primary and secondary efficacy endpoints is shown in 
Figure 14-1. 
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Figure 14-1: Sequential testing procedure of primary/secondary efficacy 
endpoints (fixed sequence testing procedure) 
 
ACR50=American College of Rheumatology 50% response criteria; BKZ=bimekizumab; CfB=change from 
Baseline; H=hypothesis; HAQ-DI=Health Assessment Questionnaire-Disability Index; MDA=Minimal Disease 
Activity; PASI90=Psoriasis Area and Severity Index 90; PCS=Physical Component Summary; Q4W=every 
4 weeks; SF-36= Short-Form 36-item Health Survey; W=Week 
14.3.1.1 
Analysis of the primary efficacy variable 
The primary efficacy variable will be analyzed for all subjects in the RS. 
The primary endpoint is the ACR50 response at Week 16. The primary efficacy analysis will 
evaluate the composite estimand in the RS. The composite estimand combines the clinically 
meaningful improvement from Baseline in ACR50 response and not discontinuing treatment 
early. This composite estimand is similar to nonresponder imputation (NRI). 
The following 4 attributes describe the estimand that will be used to define the treatment effect 
of interest for the primary efficacy analysis: 
1. Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP 
2. Subject-level outcome = ACR50 at Week 16 
3. Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment prior to Week 16. A composite strategy will be implemented in which a positive 
clinical outcome is defined as achieving ACR50 at Week 16 and not discontinuing study 
treatment through Week 16.  
4. Population-level summary measure = Conditional odds ratio comparing bimekizumab to 
placebo. 
As the ACR response is based on 7 different component scores, it is necessary to consider 
various data scenarios that could impact the calculation of response. The rules described here are 
applicable in the context of the calculation of ACR response and may differ from the rules 
applied for calculating and summarizing the components individually (some values may need to 
be imputed for component analysis but are not required here to evaluate ACR response).  
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The following rules will be applied prior to invoking any imputation analysis at the variable 
level: 
• If a subject has a component value that is equal to 0 at Baseline and the post-Baseline 
value is greater than or equal to 0, then the percent improvement for that component will 
be treated as 0 for purposes of ACR response calculations.  
• If a subject has component values that are missing at Baseline, then the percent 
improvement for that component will be treated as missing for purposes of ACR response 
calculations 
Observed data will be used to calculate ACR response where possible. In case of partial missing 
data where an observed response may be calculated, imputed data will not change the result. 
Missing data at Week 16 that are not preceded by an intercurrent event, and any data after an 
intercurrent event will be imputed as nonresponders. 
The statistical hypothesis for the ACR50 response at Week 16 is that the conditional odds ratio 
for ACR50 response in the bimekizumab treatment compared with placebo is equal to 1.  
A logistic regression model will be used to assess the treatment effect on ACR50 response at 
Week 16. The model will include fixed effects for treatment. The suitability of including the 
randomization stratification variables, prior TNFα exposure and region will be assessed, and will 
be added to the model if appropriate. Comparisons will be made using the 2-sided Wald test at a 
significance level of α=0.05 (ie, H1 Figure 14-1). The odds ratio vs placebo, p-value and the 
95% CI will be calculated. 
Any use of prohibited or rescue medications through Week 16 would constitute an important 
protocol deviation which would be accounted for when the sensitivity analysis based on the PPS 
is performed (see Section 14.3.1.1.1). 
14.3.1.1.1 
Supportive analyses 
Supportive analyses for the primary efficacy variable will be conducted: 
1. The analysis will be repeated based on the PPS to evaluate the effect of important protocol 
deviations on the analysis.  
2. The analyses will be repeated for all subjects in the FAS to evaluate the consistency between 
the RS and the more restrictive FAS. This analysis will only be performed if the number of 
subjects in RS and FAS are different. 
3. The primary comparison will also be repeated for all individual components of the 
ACR50 response to explore the effect of the signs and symptoms of the individual 
components on the composite endpoint. Since all ACR components are continuous variables 
(eg, change from Baseline in TJC), an analysis of covariance (ANCOVA) with treatment, 
prior TNFα exposure and region, as fixed effects and the Baseline value as covariate will be 
used for the analysis. Note as outlined above, some additional values may need to be imputed 
for component analysis which are not required to evaluate the overall ACR response. 
4. The analysis will be repeated using a modified composite estimand where intercurrent events 
are defined only as discontinuation due to AE or lack of efficacy. 
5. The analysis will be repeated using a treatment policy approach. 
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6. The analysis will be repeated using observed cases only. 
7. The analysis will be repeated using the COVID-free Set. 
Additional sensitivity and supportive analyses to evaluate varying assumptions related to the 
handling of missing data will also be performed and are described in Section 14.7. 
14.3.1.2 
Analyses of the secondary efficacy variables 
The secondary efficacy variables will be analyzed for all subjects in the RS.  
All binary variables that are part of the testing hierarchy are given below: 
• PASI90 responders at Week 16 will be analyzed to evaluate the composite estimand. The 
composite estimand combines the clinically meaningful improvement from Baseline in 
PASI90 response and not discontinuing treatment early. 
• The proportion of subjects achieving MDA status at Week 16 will be analyzed to evaluate 
the composite estimand. The composite estimand combines (1) achieving the MDA status 
with (2) not discontinuing treatment early. 
The statistical hypothesis for the binary variables at Week 16 is that the conditional odds ratio for 
binary variable in the bimekizumab treatment compared with placebo groups is equal to 1. 
The binary variables will be analyzed using the same analysis methods as used for the primary 
variable (Section 14.3.1.1). 
All continuous variables that are part of the testing hierarchy are given below: 
• Change from Baseline in HAQ-DI at Week 16.   
• Change from Baseline in SF-36 PCS score at Week 16.   
Continuous variables will be analyzed to evaluate the hypothetical estimand as defined below: 
1. Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP 
2. Subject level outcome = variable as stated in Section 4.2.1  
3. Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment prior to Week 16. A hypothetical strategy for addressing intercurrent events will be 
implemented. This estimand targets the treatment difference in a scenario where withdrawal 
from study treatment does not occur, such that outcomes for subjects without an intercurrent 
event are as observed, and outcomes for subjects with an intercurrent event are treated as 
though they had completed the randomized study treatment through Week 16. A multiple 
imputation strategy will be used to impute data following an intercurrent event. 
4. Population-level summary measure = the difference in the adjusted means between 
bimekizumab 160mg Q4W and placebo.  
Any missing data at Week 16 that is not preceded by an intercurrent event (ie, discontinuation of 
study medication) will also be imputed based on a predefined MI model. In MI, the missing 
value is replaced by a set of plausible values, where each value is a Bayesian draw from the 
conditional distribution of the missing data given the observed data. Intermittent missing data 
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will be imputed using the MCMC method, followed by monotone regression for monotone 
missing data. 
The statistical model for continuous endpoints for the comparison of bimekizumab and placebo 
will be an ANCOVA model with treatment, prior TNFα exposure and region as fixed effects and 
the Baseline value as covariate. The statistical hypothesis for the continuous variables at 
Week 16 is that the treatment difference between the bimekizumab treatment group and placebo 
is equal to 0. 
All secondary efficacy variables will also be summarized based on observed case data as well as 
multiple imputation using the modified composite estimand for binary variables. 
Variables that are included in the hierarchy will additionally be rerun using the COVID-free Set. 
14.3.2 
Analyses of the other efficacy variables 
All other efficacy variables will be analyzed for all subjects in the RS.  
Generally, the estimand structure for binary other efficacy variables is as described below. Note 
that further details will be provided in the SAP. 
1. Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP. 
2. Subject-level outcome = The given variable and time point being summarized (eg, ACR20 at 
Week 8) 
3. Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment prior to the time point being summarized. A composite strategy will be 
implemented in which a positive clinical outcome is defined as achieving the given variable 
at the specified time point and not discontinuing study treatment through that time point.   
4. Population-level summary measure = Unadjusted proportion of responders 
Any missing data that are not preceded by an intercurrent event as described above will be 
imputed based on NRI as described for the primary and secondary efficacy variables. 
Continuous variables will be summarized using descriptive statistics by treatment group and by 
each visit. Generally, the estimand structure for continuous other efficacy variables is as 
described below. Note that further details will be provided in the SAP. 
1. Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP 
2. Subject-level outcome = The given variable and time point being summarized (eg, change 
from Baseline in HAQ-DI at Week 8) 
3. Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment prior to the time point being summarized. A hypothetical strategy will be 
implemented in which outcomes for subjects without an intercurrent event are as observed at 
the given time point, and outcomes for subjects with an intercurrent event are treated as 
though they had completed the randomized study treatment through the time point being 
summarized. A multiple imputation strategy will be used to impute data following an 
intercurrent event.  
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4. Population-level summary measure = Unadjusted mean. 
Any missing data that are not preceded by an intercurrent event as described above will be 
imputed based on a predefined multiple imputation model as described for continuous secondary 
efficacy variables. 
Other binary and continuous efficacy variables will also be summarized based on observed case 
(OC) data (ie, subjects with missing data or who have prematurely discontinued study treatment 
are treated as missing). Further, binary outcomes will be summarized using the modified 
composite estimand. 
The time to ACR20/50/70 response will be estimated and presented using the Kaplan Meier 
product limit method for each treatment. Time to a given response will be defined as the time in 
days from Baseline until the first date when the response is achieved. Subjects who discontinue 
study treatment prior to achieving a response will be censored at the date of study treatment 
discontinuation. The median time to response, including the 2-sided 95% CI, will be calculated 
for each treatment. Between group differences will be analyzed using a log-rank statistic. 
The time to ACR20/50/70 endpoints will be analyzed using OC data. All other efficacy variables 
will be analyzed based on imputed and on OC data. 
14.3.3 
Subgroup analyses 
Subgroup analyses will be performed on the ACR50 response and the PASI90 response at 
Week 16. The following variables for subgroup analyses will be defined:  
• Age (<45 years of age, ≥45 years of age) 
• Gender (male, female) 
• Disease duration (<1 years, ≥1 years) 
• Region (eg, Asia, Eastern Europe, North America, Western Europe) 
• Race 
• Weight at Baseline (≤100kg, >100kg)  
• hs-CRP at Baseline (<6mg/L, ≥6mg/L) 
• Prior TNF exposure (intolerance to TNFα, inadequate response to 1 TNFα, inadequate 
response to 2 TNFα inhibitors) 
• Prior conventional disease-modifying antirheumatic drugs (cDMARDs) (0, 1, ≥2) 
• Concomitantly receiving cDMARDs versus no concomitant cDMARDs  
• Concomitantly receiving MTX versus no concomitant MTX 
• PSO affected BSA at Baseline (<3%, ≥3% to ≤10%, >10%) 
• BASDAI at Baseline (≤4, >4) 
• Anti-bimekizumab antibody status (positive, negative) 
• HLA-B27 status (positive, negative) 
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14.4 
Planned safety analyses 
14.4.1 
Safety analyses 
Safety variables will be analyzed for all subjects in the SS. 
Adverse events will be coded according to the Medical Dictionary for Regulatory Activities 
(MedDRA® 19.0). Adverse events with an onset date on or after the date of first IMP 
administration and up to 20 weeks after the last (most recent) dose of IMP will be defined as 
TEAEs. Treatment-emergent AEs will be summarized descriptively by treatment group, primary 
system organ class, high-level term, and preferred term. Additional tables will summarize 
TEAEs leading to withdrawal from IMP, TEAEs by intensity and relationship to IMP. 
Treatment-emergent AEs leading to withdrawal from both IMP or the study, serious TEAEs, 
TEAEs of special interest, TEAEs of special monitoring and deaths will be also be tabulated and 
listed. TEAEs adjusted for exposure will also be presented.  
When analyzing categorical data, the number and percentage of subjects in each category will be 
presented by treatment group. In addition, shift tables may be used to evaluate the number and 
percentage of subjects having a different post-Baseline status when compared to their baseline 
status. 
Laboratory value (including markedly abnormal values), urinary values, vital signs, ECGs, 
eC-SSRS, and extent of exposure will be presented descriptively by treatment group. Definitions 
for markedly abnormal laboratory values will be provided in the SAP. 
14.5 
Other planned analyses 
14.5.1 
Pharmacokinetics analyses 
Pharmacokinetic variables will be analyzed for all subjects in the PK-PPS.  
Bimekizumab plasma concentrations will be summarized for each treatment at each scheduled 
visit. 
The relationship between bimekizumab plasma concentrations and efficacy response (for 
example ACR20/50/70) and/or safety endpoints may be explored via a graphical and/or a model 
based (PK-PD) approach. The data may also be combined with that from other bimekizumab 
studies. The details of such analysis will be described separately in a data analysis plan, and the 
analysis itself will be reported separately from the CSR.   
14.5.2 
Immunological analyses 
Anti-bimekizumab antibodies will be assessed using a tiered approach: screening, confirmatory, 
and titer assays will be used. Anti-bimekizumab antibodies (including positivity) will be 
summarized by treatment at each scheduled visit at which samples are collected.  
14.6 
Handling of protocol deviations 
Important protocol deviations are deviations from the protocol which potentially could have a 
meaningful impact on study conduct or on the primary efficacy, key safety, or PK outcomes for 
an individual subject. The criteria for identifying important protocol deviations will be defined 
within the appropriate protocol-specific document. Important protocol deviations will be 
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reviewed as part of the ongoing data cleaning process, and all important deviations will be 
identified and documented prior to unblinding to confirm exclusion from analysis sets. 
14.7 
Handling of dropouts or missing data 
The primary method for assessing the efficacy variables will be the composite estimand 
approach to handling missing data that is similar to NRI. The sensitivity of results to the 
approach for handling missing data will be evaluated via supportive analyses using different 
missing data mechanisms. 
In instances where MI is used, the missing value is replaced by a set of plausible values, where 
each value is a Bayesian draw from the conditional distribution of the missing data given the 
observed data. Intermittent missing data will be imputed using the MCMC method, followed by 
regression for monotone missing data. The multiple imputation procedures planned for efficacy 
analyses are based on an assumption of data missing at random (MAR).  
The following sensitivity analyses for the primary efficacy variable and for those secondary 
efficacy variables that are part of the hierarchical testing will be conducted: 
1.  Multiple imputation as described above will be performed using the modified composite 
estimand. The definition of an intercurrent event is changed from all treatment 
discontinuation, to discontinuation of treatment due to AE or lack of efficacy.  
2. A tipping point analysis will be performed to evaluate missingness assumptions. The tipping 
point analysis will be performed on the monotone missing data and only if the primary 
analysis is significant at α=0.05. Various delta adjustments will be made to the assumed 
responses on the monotone missing data in each treatment group independently with various 
degrees of plausibility. It will include scenarios where subjects who have missing data and 
are randomized to bimekizumab have a lower probability of response compared to subjects 
who have missing data and were randomized to placebo. For binary variables this includes 
the worst case scenario where subjects who have missing data and are randomized to 
bimekizumab are considered nonresponders. The goal of the tipping point analysis is to 
systematically vary assumptions until there is no evidence of a treatment effect (if possible). 
The plausibility of such required delta adjustment will then be assessed. Details will be 
provided in the SAP.  
3. The treatment policy strategy for addressing intercurrent events will be considered. This will 
be based on an analysis in which all available data at Week 16 regardless of the occurrence 
of intercurrent events will be considered. This analysis will use the same models specified for 
the primary and secondary analyses where subjects are analyzed according to their 
randomized treatment, even if they discontinued study treatment for any reason prior to 
Week 16 and were no longer on the randomized study treatment when the assessment was 
performed at Week 16. Even though efforts will be made to collect the primary outcome data 
for all subjects at Week 16, there may still be some subjects for whom Week 16 efficacy data 
cannot be obtained. In this case, missing data will be imputed using MI under the assumption 
of MAR. Results will be combined into a single inference using Rubin's rule. It should be 
noted that this measures something different from the primary analysis and could be 
confounded by placebo subjects who withdraw and are subsequently on another active 
medication at the time of the Week 16 assessment. Therefore, the results of this analysis 
should be interpreted in the appropriate context. 
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4. An additional sensitivity analysis will be based on observed data only for subjects who are 
still on the randomized treatment at Week 16. Subjects with missing data or who have 
prematurely discontinued study treatment will be treated as missing. The same analysis 
procedure described in the main efficacy analysis will be used. 
Additional details on these sensitivity analyses will be provided in the SAP. 
14.8 
Planned interim analysis and data monitoring 
14.8.1 
Data monitoring 
A DMC will be reviewing safety data on an ongoing basis. The DMC membership includes 
experienced clinicians and a statistician, all of whom have expertise in clinical studies. Further 
details are specified in the DMC Charter.  
Cardiovascular and Neuropsychiatric Adjudication Committees will also periodically review 
data from this study. Details are provided in the Cardiovascular Adjudication Committee and 
Neuropsychiatric Adjudication Committee charters. 
Other adjudication committees may be added as necessary. 
Both Data Monitoring and Adjudication Committee members may not participate in the study as 
principal or co-Investigators, or as study subject care physicians and must not be members of the 
study team at UCB or the conducting CRO. The duration of membership for the committees will 
be inclusive of planned analyses for PA0011. 
14.8.2 
Interim analysis 
One interim analysis will be performed after all randomized subjects have completed the 
Double-Blind Treatment Period at Week 16.  
The purpose of the Week 16 interim analysis is to perform a comprehensive evaluation of all 
available double-blind data for the 2 treatment arms and to prepare a regulatory submission for a 
marketing authorization application based on this analysis. 
For the Week 16 interim analysis, the database will be locked, and the treatment codes will be 
made available to UCB personnel with exception of operational staff working on the study. An 
interim report will be written. The Investigators and subjects will remain blind to the assigned 
bimekizumab dosing regimen until the final analysis is completed. 
The interim analysis will evaluate the primary and secondary efficacy variables, as well as all 
other efficacy, safety, and PK variables up to Week 16 according to the statistical methods 
specified in the SAP. No formal alterations to the further study conduct (eg, stopping rules, 
sample size re-estimation, or changes to eligibility criteria) are planned for this interim analysis. 
To ensure blinding of Investigators and subjects, a blinding plan will be written to evaluate the 
potential bias of the Active Treatment-Blind period, define blinded and unblinded teams, and 
describe the process of interim results generation and dissemination. The plan will be finalized 
prior to the lock of the database at the interim analysis. 
14.9 
Determination of sample size 
Approximately 390 subjects will be randomly assigned in a 2:1 ratio to the following treatment 
groups: bimekizumab 160mg sc Q4W (260 subjects) and placebo (130 subjects).  
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The primary efficacy analysis is based on the primary comparison of bimekizumab versus 
placebo for ACR50 response at Week 16. 
All sample size and power calculations were done at a significance level of 0.05. 
All sample size and power calculations were performed using the software nQuery Advisor® 7.0. 
14.9.1 
Power calculation for primary endpoint 
The sample size assumptions for bimekizumab vs placebo are based on the ACR50 response data 
in the subgroup of TNFα-IR patients from the Phase 2b bimekizumab study in a mixed prior 
TNFα therapy population of subjects with moderate to severe PsA (PA0008). Sample size 
calculations for a TNFα-IR population are also based on ACR50 responses at Week 16 in the 
SPIRIT-P2 study.  
Observed ACR50 at Week 12 results in the PA0008 TNFα-IR populations were in a small 
number of subjects; bimekizumab 160mg (n=7), 320mg (n=8), and 320mg (initial dose) plus 
160mg (n=8) and ranged from 14.3% to 37.5%.  
The ixekizumab Phase 3 study SPIRIT–P2 is conducted on a similar patient population to that in 
this study and showed a 35% (n=122) ACR50 response at Week 16. Therefore, taking into 
account the range of ACR50 responses at Week 12 in PA0008, the estimated ACR50 response at 
Week 16 in the bimekizumab 160mg sc Q4W group is conservatively assumed to be 26%.  
For placebo, a similar approach as above is used. In the PA0008 TNFα-IR population, an 
ACR50 response of 11.1% (n=9) was observed at Week 12. The observed placebo 
ACR50 response at Week 16 was less than 10% in the SPIRIT-P2 study (n=118). Therefore, the 
estimated ACR50 response at Week 16 in the placebo group is assumed to be 10%. 
The sample size for showing statistical superiority of bimekizumab vs placebo was calculated 
using a 2-sided 2-sample Chi-square test with continuity correction (Fleiss et al, 1980). 
Assuming 260 subjects in the bimekizumab group and 130 subjects in the placebo group, the test 
for detecting statistical superiority of bimekizumab 160mg vs placebo based on ACR50 response 
at Week 16 has 96% power to detect a true treatment difference of 16% (odds ratio of 3.16).  
14.9.2 
Power calculations for secondary endpoints 
The assumptions for power calculations of the secondary endpoints included in the hierarchy and 
for which supporting data are available, in the TNFα-IR population are based on the results of 
PA0008 and the SPIRIT-P2 studies. All power calculations for binary endpoints were performed 
using a 2-sided 2-sample Chi-square test with continuity correction (Fleiss et al, 1980). All 
power calculations for continuous endpoints were performed using a 2-sided 2-group 
Satterthwaite t-test (Moser et al, 1989). 
For PASI90 response at Week 16, a PASI90 response at Week 12 of 38% (N=122), from the 
SPIRIT-P2 study is assumed. The PASI90 response at Week 12 in the bimekizumab 160mg 
group is 50.0% (n=8) in the subgroup analysis of the TNFα-IR patients. Placebo PASI90 
response at Week 16 is based on SPIRIT-P2 data (6.0% at Week 12). However, for this endpoint 
the placebo response is rounded to 10%. With those assumptions, the endpoint has 99% power to 
detect a treatment difference of 28% (odds ratio 5.52) at an assumed 50% of subjects with 
BSA ≥3% of the planned sample size. 
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For the change from Baseline in HAQ-DI at Week 16, based on data from the TNFα-IR 
population in SPIRIT-P2 Week 12 as well as Week 12 and Week 16 data from the PA0008 and 
PsA001 studies respectively, estimates of the SD in the active treatment and placebo groups 
are 0.71. A 2-group Satterthwaite t-test with a 0.050 2-sided significance level will have 85% 
power to detect a difference of 0.23 in the mean change from Baseline in HAQ-DI at Week 16 
between bimekizumab treatment and placebo assuming a sample size of 390 subjects 
randomized 2:1. 
For the change from Baseline in PCS score of SF-36 at Week 16, based on data from the TNFα-
IR population in SPIRIT-P2 where estimates of the SD in the active treatment and placebo 
groups at Week 12 are ixekizumab Q4W (SD=11.95) and placebo (SD=12.15). A two-group 
Satterthwaite t-test with a 0.050 2-sided significance level will have 89% power to detect a 
difference in means of 4.4 change from Baseline in SF-36 PCS score at Week 16 between the 
bimekizumab and placebo treatment groups with a sample size of 390 subjects randomized 2:1. 
For MDA at Week 16, it is assumed that 5% of the placebo subjects achieve MDA at Week 16 
(SPIRIT-P2 Week 12). Given the planned sample size and using a 2-sided 2-sample Chi-square 
test with continuity correction this study has 92% power to detect an absolute difference in MDA 
response at Week 16 of 12% (odds ratio of 3.892) with a total sample size of 390 patients. 
15 
ETHICS AND REGULATORY REQUIREMENTS 
15.1 
Informed consent 
Subject’s informed consent must be obtained and documented in accordance with local 
regulations, ICH-GCP requirements, and the ethical principles that have their origin in the 
principles of the Declaration of Helsinki. 
Prior to obtaining informed consent, information should be given in a language and at a level of 
complexity understandable to the subject in both oral and written form by the Investigator (or 
designee). Each subject will have the opportunity to discuss the study and its alternatives with 
the Investigator. 
Prior to participation in the study, the Informed Consent form should be signed and personally 
dated by the subject and by the person who conducted the informed consent discussion 
(Investigator or designee). The subject must receive a copy of the signed and dated Informed 
Consent form. As part of the consent process, each subject must consent to direct access to 
his/her medical records for study-related monitoring, auditing, IRB/IEC review, and regulatory 
inspection. 
If the Informed Consent form is amended during the study, the Investigator (or the Sponsor, if 
applicable) must follow all applicable regulatory requirements pertaining to the approval of the 
amended Informed Consent form by the IRB/IEC and use of the amended form. 
All studies conducted at centers in the US must include the use of a Health Insurance Portability 
and Accountability Act Authorization form. 
The subject may withdraw his/her consent to participate in the study at any time. A subject is 
considered as enrolled in the study when he/she has signed the Informed Consent form. An eCRF 
must not be started, nor may any study specific procedure be performed for a given subject, 
without having obtained his/her written consent to participate in the study. 
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15.2 
Subject identification cards 
Upon signing the Informed Consent form, the subject will be provided with a subject 
identification card in the language of the subject. The Investigator will fill in the subject 
identifying information and medical emergency contact information. The Investigator will 
instruct the subject to keep the card with him/her at all times. 
15.3 
Institutional Review Boards and Independent Ethics 
Committees 
The study will be conducted under the auspices of an IRB/IEC, as defined in local regulations, 
ICH-GCP, and in accordance with the ethical principles that have their origin in the Declaration 
of Helsinki. 
The Investigator/UCB will ensure that an appropriately constituted IRB/IEC that complies with 
the requirements of the current ICH-GCP version or applicable country-specific regulations will 
be responsible for the initial and continuing review and approval of the clinical study. Prior to 
initiation of the study, the Investigator/UCB will forward copies of the protocol, Informed 
Consent form, IB, Investigator’s curriculum vitae (if applicable), advertisement (if applicable), 
and all other subject-related documents to be used for the study to the IRB/IEC for its review and 
approval. 
Before initiating a study, the Investigator will have written and dated full approval from the 
responsible IRB/IEC for the protocol. 
The Investigator will also promptly report to the IRB/IEC all changes in the study, all 
unanticipated problems involving risks to human subjects or others, and any protocol deviations, 
to eliminate immediate hazards to subjects. 
The Investigator will not make any changes in the study or study conduct without IRB/IEC 
approval, except where necessary to eliminate apparent immediate hazards to the subjects. For 
minor changes to a previously approved protocol during the period covered by the original 
approval, it may be possible for the Investigator to obtain an expedited review by the IRB/IEC as 
allowed. 
As part of the IRB/IEC requirements for continuing review of approved studies, the Investigator 
will be responsible for submitting periodic progress reports to the IRB/IEC (based on IRB/IEC 
requirements), at intervals appropriate to the degree of subject risk involved, but no less than 
once per year. The Investigator should provide a final report to the IRB/IEC following study 
completion. 
UCB (or its representative) will communicate safety information to the appropriate regulatory 
authorities and all active Investigators in accordance with applicable regulatory requirements. 
The appropriate IRB/IEC will also be informed by the Investigator or the Sponsor, as specified 
by the applicable regulatory requirements in each concerned country. Where applicable, 
Investigators are to provide the Sponsor (or its representative) with evidence of such IRB/IEC 
notification. 
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15.4 
Subject privacy 
UCB staff (or designee) will affirm and uphold the subject’s confidentiality. Throughout this 
study, all data forwarded to UCB (or designee) will be identified only by the subject number 
assigned at Screening. 
The Investigator agrees that representatives of UCB, its designee, representatives of the relevant 
IRB/IEC, or representatives of regulatory authorities will be allowed to review that portion of the 
subject’s primary medical records that directly concerns this study (including, but not limited to, 
laboratory test result reports, ECG reports, admission/discharge summaries for hospital 
admissions occurring during a subject’s study participation, and autopsy reports for deaths 
occurring during the study). 
15.5 
Protocol amendments 
Protocol changes may affect the legal and ethical status of the study and may also affect the 
statistical evaluations of sample size and the likelihood of the study fulfilling its primary 
objective. 
Significant changes to the protocol will only be made as an amendment to the protocol and must 
be approved by UCB, the IRB/IEC, and the regulatory authorities (if required), prior to being 
implemented. 
16 
FINANCE, INSURANCE, AND PUBLICATION 
Insurance coverage will be handled according to local requirements. 
Finance, insurance, and publication rights are addressed in the Investigator and/or CRO 
agreements, as applicable. 
17 
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Reilly MC, Zbronzek AS, Dukes EM. The Validity and Reproducibility of a Work Productivity 
and Activitiy Impairment Instrument. PharmacoEconomics. 1993:4(5):353-365. 
Salaffi F, Carotti M, Gasparini S, INtorcia M, Grassi W. The health-related quality of life in 
rheumatoid arthritis, ankylosing spondylitis, and psoriatic arthritis: a comparison with a selected 
sample of healthy people. Health Qual Life Outcomes. 2009;7:25. 
van Tubergen A, Black PM, Coteur G. Are patient-reported outcome instruments for ankylosing 
spondylitis fit-for-purpose for the axial spondyloarthritis patient? A Qualitative and 
Psychometric Analysis. Rheum. 2015;54:1842-51. 
Watanabe H, Kawaguchi M, Fujishima S, Ogura M, Matsukura S, Takeuchi H, et al. Functional 
characterization of IL-17F as a selective neutrophil attractant in psoriasis. J Invest Dermatol. 
2009;129:650-6. 
Woodworth T, Furst DE, Alten R, Bingham C, Yocum D, Sloan V, et al. Standardizing 
assessment and reporting of adverse effects in rheumatology clinical trials II: the Rheumatology 
Common Toxicity Criteria v.2.0. J Rheumatol. 2007;34:1401-14. 
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18 
APPENDICES 
18.1 
Classification Criteria for Psoriatic Arthritis  
Inflammatory articular disease (joint, spine, or entheseal) AND at least 3 points of the following 
5 categories: 
Table 18-1: CASPAR Criteria 
Category 
Definition 
Points 
1) Evidence of psoriasis:  
(Score for 1 of the following a) 
 
 
Current psoriasis 
Psoriatic skin or scalp disease present today as 
judged by a dermatologist or rheumatologist 
2 points 
Personal history of psoriasis 
A history of psoriasis that may be obtained from the 
subject, family physician, dermatologist, 
rheumatologist, or other qualified health care 
provider 
1 point 
Family history of psoriasis 
A history of psoriasis in a first- or second-degree 
relative according to subject report 
1 point 
2) Psoriatic nail dystrophy 
Typical psoriatic nail dystrophy, including 
onycholysis, pitting, and hyperkeratosis, observed on 
current physical examination 
1 point 
3) A negative test for rheumatoid 
factor 
By any method except latex, but preferably by 
enzyme-linked immunosorbent assay (ELISA) or 
nephelometry, according to the local laboratory 
reference range 
1 point 
4) Dactylitis:  
(Score for 1 of the following) 
 
 
Current dactylitis 
Swelling of an entire digit 
1 point 
History of dactylitis 
A history of dactylitis recorded by a rheumatologist 
1 point 
5) Radiologic evidence of 
juxta-articular new bone 
formation 
Ill-defined ossification near joint margins (but 
excluding osteophyte formation) on plain radiographs 
of the hand or foot 
1 point 
CASPAR=Classification Criteria for Psoriatic Arthritis  
a “Score for 1 of the following” means that only 1 of the 3 criteria is applicable (either current psoriasis [scores 2 
points], personal history [scores 1 point], or family history [scores 1 point]). 
 
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18.2 
Protocol Amendment 1 
The main purpose of this protocol amendment was to update the completed and ongoing studies 
information, clarify study procedures, add re-screening rules, update the description of the IMP, 
change the statistical hierarchy, and update the statistical section. 
Modifications and changes 
Global changes: 
The following changes were made throughout the protocol and are not included in specific 
changes table that follows:  
• The company name was changed from UCB Biopharma SPRL to UCB Biopharma SRL 
• The term “legal representative” was deleted from protocol, as it is not applicable to PA0011 
• Minor spelling, editorial, and formatting changes were made throughout the document  
 
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Specific changes: 
Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 1: Administrative section 
Study contact details 
 
UCB PHARMA Ltd 
208 Bath Road 
Slough SL1 3WE 
 
 
UCB BIOSCIENCES GmbH 
Alfred-Nobel-Str. 10 
40789 Monheim 
GERMANY 
 
The Sponsor Study Physician has 
changed. 
 
UCB BIOSCIENCES Inc. 
8010 Arco Corporate Drive 
Raleigh, NC 27617 
UNITED STATES 
 
 
UCB BIOSCIENCES GmbH 
Alfred-Nobel-Str. 10 
40789 Monheim 
GERMANY 
 
The Clinical Project Manager has 
changed.  
 
UCB PHARMA Ltd 
Alfred-Nobel-Strasse 10 
40789 Monheim am Rhein 
GERMANY 
 
 
UCB BIOSCIENCES Inc. 
8010 Arco Corporate Drive 
Raleigh, NC 27617 
UNITED STATES 
 
The Clinical Trial Biostatistician 
has changed. 
Change 2: Abbreviations added 
List of abbreviations 
Abbreviations and definitions are added for the following: HS, OC, and UC 
Abbreviations used in text. 
Change 3: Updated text in bimekizumab section 
Section 2.2 
Furthermore, a proof-of-concept study 
with bimekizumab in subjects with 
moderate-to-severe PsA demonstrated 
a strong efficacy signal that warrants 
further exploration of bimekizumab in 
Furthermore, a proof-of-concept study 
(PA0007) with bimekizumab in 
subjects with moderate to severe PsA 
demonstrated a strong efficacy signal 
that warrants further exploration of 
Added PA0007 study number and 
updated PA0008 sentence since the 
study is now completed. Also, 
corrected error in statement about 
PA0011. 
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PA0011 
 
 
 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
this indication. A Phase 2b, dose-
ranging study (PA0008) is an ongoing 
study that was designed to investigate 
the efficacy and safety of various 
bimekizumab dose regimens in 
subjects with active PsA. The current 
Phase 3, randomized, double-blind, 
placebo-controlled, and active-
controlled confirmatory study 
(PA0011) is designed to investigate the 
efficacy and safety of bimekizumab in 
subjects with active PsA. 
bimekizumab in this indication. A 
Phase 2b, dose-ranging study 
(PA0008) is an ongoing study that was 
designed to investigate the efficacy 
and safety of various bimekizumab 
dose regimens in subjects with active 
PsA. The current Phase 3, randomized, 
double-blind, placebo-controlled, and 
active controlled confirmatory study 
(PA0011) is designed to investigate the 
efficacy and safety of bimekizumab in 
subjects with active PsA. 
Change 4: Updated text in nonclinical studies section 
Section 2.2.1 
Preliminary results from the 
embryofetal and postnatal study 
conducted in the Cynomolgus monkey 
indicate no effects of bimekizumab on 
the gestation, gestation duration, or the 
parturition of pregnant females. 
Preliminary rResults from the 
embryofetal and postnatal study 
conducted in the Cynomolgus monkey 
indicate no effects of bimekizumab on 
the gestation, gestation duration, or the 
parturition of pregnant females. 
This nonclinical study is now 
completed. 
Change 5: Updated text in clinical studies section 
Section 2.2.2.1 
This section was updated to reflect the studies that have completed as of 02 Dec 
2019. Detailed study descriptions for non-PsA studies were deleted and cross-
reference to the bimekizumab IB was added for detail of these studies. Psoriatic 
arthritis PA0007 summary remains, and a summary of the recently completed 
PA0008 was added. 
More studies have completed, and 
additional studies have started since 
the original protocol was written. 
Section 2.2.2.2 
This section was updated to reflect studies that are ongoing as of 02 Dec 2019. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 6: Updated secondary efficacy variables 
Section 4.2.1 
The secondary efficacy variables for 
this study are as follows: 
• 
PASI90 response at Week 4 and 
Week 16 in the subgroup of 
subjects with PSO involving at 
least 3% BSA at Baseline 
• 
Change from Baseline in Health 
Assessment Questionnaire—
Disability Index (HAQ-DI) at 
Week 16 
• 
Change from Baseline in the 
Short-Form 36-item Health Survey 
(SF-36) Physical Component 
Summary (PCS) at Week 16 
• 
etc  
The secondary efficacy variables for 
this study are as follows: 
• 
Change from Baseline in Health 
Assessment Questionnaire—
Disability Index (HAQ-DI) at 
Week 16 
• 
PASI90 response at Week 4 and 
Week 16 in the subgroup of 
subjects with PSO involving at 
least 3% BSA at Baseline 
• 
Change from Baseline in Health 
Assessment Questionnaire—
Disability Index (HAQ-DI) at 
Week 16 
• 
Change from Baseline in the 
Short-Form 36-item Health Survey 
(SF-36) Physical Component 
Summary (PCS) score at Week 16 
• 
etc 
The HAQ-DI variable was 
promoted in the testing hierarchy. 
Section 14.3.1 
Figure 14-1 
In Figure 14-1 Sequential testing procedure of primary/secondary efficacy 
endpoints (fixed sequence testing procedure), the variable of Change from 
Baseline HAQ-DI at Week 16 superior to placebo was moved from the 3rd 
position in the sequential testing hierarchy to the 2nd position (after the primary 
variable). 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 7: Made minor update to secondary safety variables 
Section 4.2.2 
Secondary safety variables to be 
assessed are as follows: 
• 
Incidence of treatment-emergent 
adverse events (TEAEs) 
• 
Incidence of SAEs 
• 
Adverse events leading to 
withdrawal from IMP 
 
Secondary safety variables to be 
assessed are as follows: 
• 
Incidence of treatment-emergent 
adverse events (TEAEs) 
• 
Incidence of treatment-emergent 
SAEs 
• 
Treatment-emergent adverse 
events leading to withdrawal from 
IMP 
Clarified variables. 
Change 8: Updated PsAID-12 variables 
Section 4.3.1  
• Change from Baseline PsAID-12 
• 
Change from Baseline in 
PsAID-12 total score 
• 
Change from Baseline in the 
individual domain scores of 
PsAID-12 
• 
Proportion of subjects achieving 
PsAID-12 total score ≤4 
• Change from Baseline in PsAID-
12 total score ≥3 (PsAID-12 
responders) 
The variables were updated for 
consistency with the SAP. 
Change 9: Updated Other efficacy variables 
Section 4.3.1 
• 
Change from Baseline in the 
Psoriatic Arthritis Quality of Life 
(PsAQoL) 
• 
Change from Baseline in the SF-
36 PCS and Mental Component 
Summary (MCS), as well as the 8 
domain scores (Physical 
Functioning, Role Physical, Bodily 
Pain, General Health, Vitality, 
• 
Change from Baseline in the 
Psoriatic Arthritis Quality of Life 
(PsAQoL) global score 
• 
Change from Baseline in the 
SF-36 PCS and SF-36 Mental 
Component Summary (MCS) 
scores, as well as the 8 domain 
scores (Physical Functioning, Role 
Physical, Bodily Pain, General 
Minor editorial changes and 
variables were updated for 
consistency with the SAP. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Social Functioning, Role 
Emotional, and Mental Health) 
• 
Change from Baseline in 
Functional Assessment of Chronic 
Illness Therapy—Fatigue 
(FACIT-F) 
• 
Change from Baseline in Work 
Productivity and Activity 
Impairment Questionnaire–
Specific Health Problem (WPAI-
SHP) v2.0 adapted to PsA scores 
• 
Responses to the EuroQol-5D-3-
Level (EQ-5D-3L) dimensions 
• 
Change from Baseline in the EQ-
5D-3L utility score 
• 
Change from Baseline in EQ-5D-
3L Visual Analog Scale (VAS) 
scores 
Health, Vitality, Social 
Functioning, Role Emotional, and 
Mental Health) 
• 
Change from Baseline in 
Functional Assessment of Chronic 
Illness Therapy—Fatigue 
(FACIT-F) score 
• 
Change from Baseline in Work 
Productivity and Activity 
Impairment Questionnaire–
Specific Health Problem (WPAI-
SHP) v2.0 adapted to PsA scores 
• 
Responses to the EuroQol-5D-3-
Level (EQ-5D-3L) dimensions 
• 
Change from Baseline in the EQ-
5D-3L utility score 
• 
Change from Baseline in EQ-5D-
3L Visual Analog Scale (VAS) 
scores 
• 
Change from Baseline in 
Physician’s Global Assessment 
of Arthritis (PhGA-Arthritis) 
• 
Change from Baseline in 
Patient’s Global Assessment of 
Arthritis (PGA-Arthritis) 
Change 10: Moved PHQ-9 variable 
Section 4.3.1 
Section 4.3.2 
• Change from Baseline in Patient 
Health Questionnaire-9 (PHQ-9)   
Was in Section 4.3.1 Other efficacy 
variables 
• Change from Baseline in Patient 
Health Questionnaire-9 (PHQ-9)  
Is now in Section 4.3.2 Other safety 
variables 
PHQ-9 is a safety variable. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 11: Made minor update to study design section 
Section 5.1 
Subjects completing Week 16 are 
eligible for enrollment in an OLE 
study to continue to receive 
bimekizumab. 
Subjects completing Week 16 and 
meeting eligibility criteria are 
eligible for enrollment in an OLE 
study to continue to receive 
bimekizumab. 
Clarification of procedure. 
Change 12: Added text regarding rescreening and retesting requirements 
Section 5.2 
The following new section was added in Section 5.2: 
5.2.1  Within-study rescreening/retesting requirements  
Clarified rules for when rescreening 
and/or retesting is allowed. 
Change 13: Made minor updates to Schedule of study assessments 
Table 5-1 
a Visit windows of ±3 days from the first 
dose at all visits through Week 16. The 
time between IMP doses should be ≥21 
days and ≤35 days during the Double-
Blind Treatment Period. The Safety 
Follow-Up Visit window is -3 and +7 
days from the final dose. 
a Visit windows of ±3 days from the first 
dose at all visits through Week 16. The 
time between IMP doses should be ≥21 
days and ≤35 days during the Double-
Blind Treatment Period. The Safety 
Follow-UpFor the SFU Visit window is, 
the visit should occur no more than 3 
days prior to the scheduled -3visit date 
and +within 7 days from the final 
dose.after the scheduled visit date (-3 
days/+7 days). 
Clarification of the SFU Visit 
timing. 
o 
Circumference measured in 
millimeters. 
o Circumference measured in 
millimeters. The LDI assessment of 
dactylitis will be obtained for all 
subjects at all visits after the 
Screening Visit. 
Clarification of the LDI assessment 
timing. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 14: Made minor updates to Inclusion criteria  
Section 6.1 
1. An Institutional Review Board 
(IRB)/Independent Ethics 
Committee (IEC) approved written 
Informed Consent form is signed 
and dated by the subject or legal 
representative. 
2. Subject/legal representative is 
considered reliable and capable of 
adhering to the protocol (eg, able to 
understand and complete diaries), 
visit schedule, or medication intake 
according to the judgment of the 
Investigator. 
1a. An Institutional Review Board 
(IRB)/Independent Ethics 
Committee (IEC) approved written 
Informed Consent form is signed 
and dated by the subject or legal 
representative. 
2a. Subject/legal representative is 
considered reliable and capable of 
adhering to the protocol (eg, able to 
understand and complete diaries), 
visit schedule, or medication intake 
according to the judgment of the 
Investigator. 
Numbering of these inclusion 
criteria needed to change due to 
change in wording.  
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 15: Made updates to potential drug-induced livery injury (PDILI) IMP discontinuation criteria 
Section 6.3.1 
Section 12.2.1.2 
The PDILI criteria below require 
immediate and permanent 
discontinuation of IMP:  
• 
Subjects with either of the 
following: 
− 
ALT or AST ≥8xULN  
− 
ALT or AST ≥3xULN and 
coexisting total bilirubin 
≥2xULN  
The PDILI criterion below requires 
immediate discontinuation of IMP for: 
• 
Subjects with ALT or AST 
≥3xULN who exhibit temporally 
associated symptoms of hepatitis 
or hypersensitivity. Hepatitis 
symptoms include fatigue, nausea, 
vomiting, right upper quadrant 
pain or tenderness. 
Hypersensitivity symptoms 
include fever (without clear 
alternative cause), rash, or 
eosinophilia (ie, >5%). 
The PDILI criteria below require 
immediate and permanent 
discontinuation of IMP:  
• 
Subjects with either of the 
following: 
− 
ALT or AST ≥8xULN  
− 
ALT or AST ≥3xULN and 
coexisting total bilirubin 
≥2xULN  
The PDILI criterion below requires 
immediate discontinuation of IMP for: 
• 
Subjects with ALT or AST 
≥3xULN who exhibit temporally 
associated symptoms of hepatitis 
or hypersensitivity. Hepatitis 
symptoms include fatigue, nausea, 
vomiting, right upper quadrant 
pain or tenderness. 
Hypersensitivity symptoms 
include fever (without clear 
alternative cause), rash, or 
eosinophilia (ie, >5%). 
Requirements for IMP 
discontinuation were clarified, and 
the requirement for permanent 
discontinuation of IMP was 
removed. 
Section 12.2.1, 
Table 12-3 
The table was simplified and criteria for IMP discontinuation was updated in line 
with changes made to Section 6.3.1. 
In addition, a table footnote with cross-reference to Section 12.2.1.2 was added 
as footnote d and the previous footnote d became footnote e. 
Section 12.2.1.2.1 
Subjects who are immediately 
discontinued from IMP due to having 
met certain criteria for PDILI (as 
described in Section 6.3.1 and Table 
12‒3), but for whom an alternative 
Subjects who are immediately 
discontinued from IMP due to having 
met certain criteria for PDILI (as 
described in Section 6.3.1 and Table 
12‒3), but for whom an alternative 
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Protocol section 
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Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
diagnosis is confirmed, ie, drug-
induced liver injury is excluded, can 
rarely restart IMP. Rechallenge with 
IMP can occur only if ALL of the 
following requirements are met: 
diagnosis is confirmed, ie, drug-
induced liver injury is excluded, can 
rarely restart IMP. Rechallenge with 
IMP can occur only if ALL of the 
following requirements are met at the 
time of the rechallenge: 
Change 16: Updated description of IMP 
Section 7.1 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Updated to be consistent with other 
studies in bimekizumab clinical 
development program. 
Change 17: Updated prohibited concomitant treatments section  
Section 7.8.2, 
Table 7-1 
Exclusion/washout for oral 
corticosteroids: 
Any change in dose/dose regimen in 
the 28 days prior to the Baseline Visit. 
Exclusion/washout for oral 
corticosteroids: 
Any change in dose/dose regimen in 
the 28 14 days prior to the Baseline 
Visit. 
Updated washout timing 
requirements. 
Exclusion/washout for methotrexate: 
Use within 8 weeks prior to the 
Baseline Visit unless Inclusion 
Criterion #11 is met.   
Exclusion/washout for methotrexate: 
Use within 8Initiation less than 
12 weeks prior to the Baseline Visit 
unless Inclusion Criterion #11 is met.   
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 18: Updated text in IGA section  
Section 9.8.3 
Added the following text under Table 9-3: 
The IGA responder is defined as a subject with a clear (0) or almost clear 
(1) assessment with at least a 2-category improvement from Baseline, 
meaning that this parameter will be evaluable only for subjects with 
psoriatic skin lesions (IGA score ≥2) at Baseline. 
In this study, only subjects with BSA ≥ 3% at Baseline will have IGA 
assessed at post-Baseline visits. 
The section needed a definition of 
IGA responder added to assessment 
description. 
Change 19: Updated DAPSA formula  
Section 9.10 
SJC (range 0 to 66) + TJC (range 0 to 
68) + PGA-Arthritis and patient’s pain 
assessment (VAS range 0 to 10; 
0=best, 10=worst) + hs-CRP 
DAPSA=SJC (range 0 to 66) + TJC 
(range 0 to 68) + PGA-Arthritis and 
patient’s pain assessment (VAS range 
0 to 10cm; 0=best, 10=worst) + 
PtAAP (VAS range 0 to 10cm) + hs-
CRP 
Corrected formula. 
Change 20: Updated DAS28(CRP) formula  
Section 9.11 
DAS28(CRP)=0.56 √TJC+0.28 
√SJC+0.014 PGA-Arthritis+0.36 
ln(hs-CRP+1)+0.96 
DAS28(CRP)=0.56 √TJC+0.28 
√SJC+0.014 PGA-Arthritis+0.36 
ln(hs-CRP+1)+0.96 
Corrected formula. 
Change 21: Moved PHQ-9 assessment section from efficacy assessments to safety assessments  
Old Section 9.22 
moved to  
New Section 12.3.5 
12.3.5 Assessment and management of 
TB and TB risk factors 
12.3.6 Pregnancy testing 
12.3.7 Assessment of suicidal ideation 
and behavior  
12.3.5 Patient Health 
Questionnaire-9 (PHQ-9) 
12.3.6 Assessment and management of 
TB and TB risk factors 
12.3.7 Pregnancy testing 
12.3.8 Assessment of suicidal ideation 
and behavior 
The PHQ-9 is a safety variable and 
was moved to Other safety 
variables from Other efficacy 
variables in the current amendment. 
The assessment description section 
was moved to align with the 
variable change. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 22: Updated text in pregnancy section  
Section 12.1.4 
If the Investigator is notified that a 
subject has become pregnant after the 
first intake of any IMP, the 
Investigator must immediately notify 
UCB’s PS department by entering all 
pregnancy information into the eCRF. 
An automatic notification will be sent 
to UCB PS. The subject should be 
withdrawn from the study as soon as 
pregnancy is known (by positive 
pregnancy test), and the following 
should be completed: 
• 
The subject should return for the 
ET Visit. 
• 
The subject should immediately 
stop the intake of the IMP. 
• 
A Safety Follow-Up Visit should 
be scheduled 20 weeks after the 
final dose of IMP. 
The Investigator must inform the 
subject of information currently known 
about potential risks and about 
available treatment alternatives. 
 
If the Investigator is notified that a 
subject has become pregnant after the 
first intake of any IMP, the 
Investigator must immediately (within 
24 hours) notify UCB’s PS 
department by entering all pregnancy 
information into the eCRF. An 
automatic notification will be sent to 
UCB PS. The subject should be 
permanently withdrawn from the 
study IMP as soon as pregnancy is 
known (by positive pregnancy test), 
and the following should be 
completed: 
• 
The subject should return for the 
ET Visit. 
• 
The subject should immediately 
stop the intake of the IMP. 
• 
The subject should return for an 
early ad-hoc study visit. 
• 
A Safety Follow-Up Visit should 
be scheduled 20 weeks after the 
final dose of IMP. 
The Investigator should discuss with 
the subject the possibility to 
continue the study by attending the 
Clarified pregnancy instructions. 
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Protocol section 
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Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
scheduled visits for assessments 
without IMP administration. The 
tests or assessments, which are 
considered contraindicated during 
the pregnancy should not be 
performed. The early ad-hoc study 
visit will be considered as the ET 
visit if the subject does not wish to 
pursue the study investigations. 
The Investigator must inform the 
subject of information currently known 
about potential risks and about 
available treatment alternatives. 
Section 12.1.4 
Last paragraph regarding the “option to enroll in a separate observational 
pregnancy follow-up study” was deleted. 
There is no pregnancy registrational 
study. 
Change 23: Updated text in analysis of the primary efficacy variable section 
Section 14.3.1.1 
Provided additional detail regarding the statistical approach to be used for 
analyzing ACR response. 
Updated protocol to be consistent 
with SAP. 
Section 14.3.1.1.1 
Added clarification regarding sensitivity analyses to be used. 
Change 24: Updated text in analysis of the secondary efficacy variables section 
Section 14.3.1.2 
Provided additional detail regarding the statistical approach to be used for 
analyzing secondary efficacy variables. 
Updated protocol to be consistent 
with SAP. 
Change 25: Updated text in analysis of the other efficacy variables section 
Section 14.3.2 
Provided additional detail regarding the statistical approach to be used for 
analyzing the other efficacy variables. 
Updated protocol to be consistent 
with SAP. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 26: Updated subgroup analyses section 
Section 14.3.3 
Added the following subgroup: 
• 
Concomitantly receiving MTX versus no concomitant MTX 
Added subgroup consistent with 
SAP. 
Change 27: Updated text in handling of dropouts or missing data section 
Section 14.7 
Added some detail regarding the statistical approach to be used for missing data 
for composite endpoints and the supportive analyses based on OC and NRI. 
Updated protocol to be consistent 
with SAP. 
Change 28: Updated text in data monitoring section 
Section 14.8.1 
Added the following statement: 
Other adjudication committees may be added as necessary. 
Allowing the possibility for 
additional committees to be utilized 
during study. 
 
 
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18.3 
Protocol Amendment 2 
The main purpose of this protocol amendment was to modify the secondary variables and fixed 
sequence testing procedure, update the statistical section, and make other procedural 
clarifications. 
Modifications and changes 
Global changes: 
Throughout the protocol, FACIT-F has been corrected to FACIT-Fatigue subscale, as it is the 
fatigue subscale that is being assessed in this study. In addition, minor spelling, editorial, and 
formatting changes were made throughout the protocol. These global changes are not included in 
specific changes table that follows.  
 
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PA0011 
 
 
 
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Specific changes: 
Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 1: Administrative section 
Study contact details 
 
UCB BIOSCIENCES GmbH 
Alfred-Nobel-Str. 10 
40789 Monheim 
GERMANY 
 
 
 
UCB Celltech Ltd 
208 Bath Road 
Slough SL1 3WE 
 
The Sponsor Study Physician has 
changed. 
 
UCB BIOSCIENCES GmbH 
Alfred-Nobel-Str. 10 
40789 Monheim 
GERMANY 
 
 
UCB Biopharma SRL 
Chemin du Foriest 
Brain-l’Alleud B-1420 
BELGIUM 
 
The Sponsor Clinical Project 
Manager has changed. 
 
UCB BIOSCIENCES Inc.  
8010 Arco Corporate Drive 
Raleigh, NC 27617 
UNITED STATES 
 
 
UCB BIOSCIENCES Inc.  
4000 Paramount Pkwy, 
 
Morrisville, NC 27560 
UNITED STATES 
 
The address of the North Carolina, 
US office has changed. 
Change 2: Abbreviations added 
List of abbreviations 
Abbreviations and definitions added for the following: COVID-19, DNA, 
mRNA, LN, PsARC, PASDAS 
Abbreviations used in text. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 3: Updated text in clinical studies section 
Section 2.2.2.1 
The list of completed studies was updated consistent with the current 
bimekizumab IB.  
More studies have completed, and 
additional studies have started, 
since the last protocol amendment. 
Section 2.2.2.2 
The list of ongoing studies was updated consistent with the current bimekizumab 
IB. 
Change 4: Added 6 new Other efficacy variables 
Section 4.3.1 
Added the following variables:  
• 
Composite endpoint composed of ACR50 and PASI100 response in 
subjects with PSO involving at least 3% BSA at Baseline 
• 
Proportion of Psoriatic Arthritis Response Criteria (PsARC) responders 
• 
Psoriatic Arthritis Disease Activity Score (PASDAS) categories 
• 
Change from Baseline in the PASDAS  
• 
Proportion of subjects with a decrease of HAQ-DI from Baseline of at 
least 0.35 in those subjects with HAQ-DI >0.35 at Baseline 
• 
Proportion of FACIT-Fatigue subscale responders (subjects with a 
minimum clinically important difference for FACIT-Fatigue subscale 
score, defined as an increase of ≥4) in subjects with FACIT-Fatigue 
subscale score ≤48 at Baseline 
Updated to be consistent with 
variables added to the SAP 
Change 5: Updated wording in other efficacy variables 
Section 4.3.1 
• 
Disease Activity Index for 
Psoriatic Arthritis (DAPSA) score 
• 
Disease Activity Index for Psoriatic 
Arthritis (DAPSA) score categories 
Corrected wording  
• 
Change from Baseline in PsAID-
12 total score ≥3 (PsAID-12 
responders) 
• 
Proportion of PsAID-12 
responders (decrease Change from 
Baseline in PsAID-12 total score 
≥3) (PsAID-12 responders) in 
subjects with PsAID-12 total 
score >3 at Baseline 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
• 
Change from Baseline in the 
Psoriatic Arthritis Quality of Life 
(PsAQoL) global score 
• 
Change from Baseline in the 
Psoriatic Arthritis Quality of Life 
(PsAQoL) global total score 
• 
Change from Baseline in 
Functional Assessment of 
Chronic Illness Therapy—Fatigue 
(FACIT-F) 
• 
Change from Baseline in 
Functional Assessment of Chronic 
Illness Therapy—Fatigue 
(FACIT-F) subscale score 
Change 6: Updated the planned number of sites 
Section 5.6 
Approximately 390 subjects will be 
randomly assigned in a 2:1 ratio to the 
following treatment groups: 
bimekizumab 160mg sc Q4W (260 
subjects) and placebo (130 subjects). 
The planned number of study sites is 
approximately 89. 
Approximately 390 subjects will be 
randomly assigned in a 2:1 ratio to the 
following treatment groups: 
bimekizumab 160mg sc Q4W (260 
subjects) and placebo (130 subjects). 
The planned number of study sites is 
approximately 89120. 
The planned number of sites was 
adjusted. 
Change 7: Added a withdrawal criterion 
Section 6.3 
Added the following to the list of withdrawal criteria: 
13. Any subject who develops a clinically important infection or recurrent 
infections not responsive to standard therapy during the study must 
discontinue IMP until resolution of the infection. The Investigator should 
use clinical judgement in deciding whether the subject should restart IMP 
and contact the Medical Monitor and UCB study physician to confirm the 
subject’s suitability for continued participation in the study. 
In line with the exclusion 
criterion 11 regarding infections, a 
specific infection-related 
withdrawal criterion was added to 
clarify that patients with serious or 
recurrent infections not responding 
to standard therapies are not 
exposed to immunomodulatory 
therapies until their infection is 
resolved. This is in line with most 
biologic therapies, including other 
anti-IL17s. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 8: Updated the permitted concomitant treatments section 
Section 7.8.1 
Added the following paragraph to the section:  
Subjects are allowed to use any other medications, including biologics, after at 
least 28 days of last dose of the IMP. This is applicable for subjects who 
discontinue from IMP or the study early, including those permanently withdrawn 
from IMP, or subjects who have completed the study treatment without entering 
the extension study and are in the SFU period.  
Clarification of permitted 
concomitant medications. 
Change 9: Updated the vaccines section 
Section 7.8.3 
Added the following paragraph to the section: 
Administration of inactivated vaccines is allowed during the study at the 
discretion of the Investigator. This includes administration of non-live 
coronavirus disease 2019 (COVID-19) vaccines authorized at the time of 
issuance of this protocol version (eg, messenger ribonucleic acid [mRNA], 
deoxyribonucleic acid [DNA] viral vector types of vaccines). Considering the 
known mechanism of action and results from a human vaccination response 
study, bimekizumab is not expected to affect the safety and/or efficacy of 
COVID-19 vaccines. 
Clarification that administration of 
COVID-19 vaccines are allowed at 
the discretion of the Investigator. 
Change 10: Updated FACIT-Fatigue assessment section 
Section 9.18 
The FACIT–F scale (Cella et al, 
2005) will be used to assess fatigue in 
PsA patients. The FACIT-F has been 
validated in the general population, in 
patients with RA, and in patients with 
PsA. The minimum clinically 
important difference for FACIT-F in 
patients with RA was determined to 
be a 3 to 4-point change; this 
minimum clinically important 
difference will be used in evaluating 
The FACIT–F scale (Cella et al, 2005) 
will be used to assess fatigue in PsA 
patients. The FACIT-Fatigue is a 
40-item measure that assesses 
self-reported fatigue and its impact 
upon daily activities and function 
over the past 7 days (FACIT.org). 
The scale consists of 5 subscales 
(physical well-being, social/family 
well-being, emotional well-being, 
functional well-being, and fatigue). 
The fatigue subscale is the only one 
Added a reference for FACIT-
Fatigue subscale use in PsA. 
Wording changes implemented for 
consistency with the user manuals 
and to reflect precise description of 
the patient-reported outcomes 
(PRO) tool and scoring (change in 
terminology but no change in the 
method). 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
clinically meaningful changes in 
fatigue for patients with PsA. 
used in this study. It is composed of 
13 items, all scored from 0 (Not at all) 
to 4 (Very much). The 
FACIT-Fatigue subscale score ranges 
from 0 to 52 with 0 being the worst 
possible score and 52 being the best 
possible score. To obtain a score from 
0 to 52, all negatively worded 
questions have to be recoded, so that 
responses range from worst (0) to the 
best (4) outcome. 
The FACIT-Fatigue subscale has been 
validated in the general population, in 
patients with RA, and in patients with 
PsA. The minimum clinically important 
difference for FACIT-Fatigue subscale 
in patients with RAPsA was determined 
to be a 3   to 4-point change (Cella et 
al, 2019); this minimum clinically 
important difference will be used in 
evaluating clinically meaningful 
changes in fatigue for patients with 
PsA. 
Change 11: Updated SF-36 assessment section 
Section 9.19 
In addition to domain scores, the PCS 
and MCS scores are calculated from 
the 8 domains (excluding the Health 
Transition item). Component scores 
appreciate the impact of each domain 
on physical and mental health status 
(Maruish, 2011). Each of the 8 
domain scores and the component 
summary scores range from 0 to 100, 
In addition to domain scores, the PCS 
and MCS scores are calculated from the 
8 domains (excluding the Health 
Transition item). Component scores 
appreciate reflect the impact of each 
domain on physical and mental health 
status (Maruish, 2011). Each of the 8 
domain scores and the component 
summary scores range from 0 to 100, 
Wording changes implemented for 
consistency with the user manuals 
and to reflect precise description of 
the PRO tools and scoring (change 
in terminology but no change in the 
method). 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
with a higher score indicating a better 
health status. The 2 component 
summary scores are standardized with 
a mean of 50 and a standard deviation 
(SD) of 10 in the general US 
population. 
with a higher score indicating a better 
health status. The norm-based T-
scores for the 2 SF-36 component 
summary scores (PCS and MCS) and 
the 8 domains are standardized with a 
mean of 50 and a standard deviation 
(SD) of 10 in the general US population 
(Maruish, 2011). An individual 
respondent’s score that falls outside 
the T-score range of 45 to 55 should 
be considered outside the average 
range for the US general population. 
When considering group-level data, a 
score below 47 should be considered 
indicative of impaired functioning 
within that health domain or 
dimension. Similar to individual 
respondent data, group mean scores 
of 47 or greater should be considered 
average or above average as 
compared to the general US 
population. Higher scores indicate a 
better health status. 
Change 12: Added 2 new sections to describe the PsARC and PASDAS efficacy assessments added in new Other efficacy variables 
New Section 9.22 
Section 9.22 Psoriatic Arthritis Response Criteria (PsARC) added to describe the 
PsARC efficacy assessment 
The PsARC was added in a new 
Other efficacy variable 
New Section 9.23 
Section 9.23 Psoriatic Arthritis Disease Activity Score (PASDAS) added to 
describe the PASDAS efficacy assessment 
The PASDAS was added in 2 new 
Other efficacy variables. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 13: Updated Other safety topics of interest section 
Section 12.1.1.4 
Prespecified safety topics of interest 
for the study are: infections (serious, 
opportunistic, fungal and TB), 
neutropenia, hypersensitivity, suicidal 
ideation and behavior, depression, 
major cardiovascular events, liver 
function test changes/enzyme 
elevations, malignancies, and 
inflammatory bowel diseases (with 
gastroenterology referral, as 
appropriate). 
Prespecified safety topics of interest for 
the study are: infections (serious, 
opportunistic, fungal and TB), 
neutropenia, hypersensitivity, suicidal 
ideation and behavior, depression, 
major cardiovascular events, liver 
function test changes/enzyme 
elevations, malignancies, and 
inflammatory bowel diseases (with 
gastroenterology referral, as 
appropriate). 
With progressive development of 
bimekizumab and based on the 
ongoing review of emerging safety 
data, depression has been removed 
as a safety topic of interest. 
Nevertheless, depression will 
continue to be monitored as a safety 
parameter by the PHQ-9 and will 
be captured via routine AE 
reporting during the study. This 
update is considered a procedural 
change. 
Change 14: Updated Evaluation of PDILI section 
Section 12.2.1 
The PDILI IMP discontinuation 
criteria for this study are provided in 
Section 6.3.1, with the accompanying 
required follow-up investigation and 
monitoring detailed below. All PDILI 
events must be reported as AEs and 
reported to the study site and Sponsor 
within 24 hours of learning of their 
occurrence. Any PDILI event that 
meets the criterion for potential Hy’s 
Law must be reported as an AE of 
special interest (see Section 12.1.1.3), 
and, if applicable, also reported as an 
SAE (see Section 12.1.1.2). 
The PDILI IMP discontinuation criteria 
for this study are provided in Section 
6.3.1, with the accompanying required 
follow-up investigation and monitoring 
detailed below. All PDILI events must 
be reported as AEs and reported to the 
study site PDILI events meeting SAE 
criteria should be reported to the 
Sponsor within 24 hours of learning of 
their occurrence. Any PDILI event that 
meets the criterion for potential Hy’s 
Law must be reported within 24 hours 
of learning of their occurrence as an 
AE of special interest (see 
Section 12.1.1.3), and, if applicable, 
also reported as an SAE (see 
Section 12.1.1.2). 
Clarified PDILI event reporting 
procedure. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Section 12.2.1.2 
The immediate action is dependent on 
the laboratory values and symptoms 
of hepatitis or hypersensitivity and 
ranges from continuation of IMP 
(followed by immediate investigation) 
to immediate discontinuation (see 
Section 6.3.1 and Table 12‒3 for 
details). 
The immediate action is dependent on 
the laboratory values and symptoms of 
hepatitis or hypersensitivity and ranges 
from continuation of IMP (followed by 
immediate investigation) to immediate 
and permanent discontinuation (see 
Section 6.3.1 and Table 12‒3 for 
details). 
Clarify the range of potential 
actions. 
Change 15: Updated the analysis set definition section 
Section 14.1 
• 
The Per-Protocol Set (PPS) will 
consist of all subjects in the RS 
who had no important protocol 
deviations affecting the primary 
efficacy variable. Important 
protocol deviations will be 
predefined and subjects with 
important protocol deviations will 
be evaluated during ongoing data 
cleaning meetings prior to 
unblinding of the data. 
• 
The Pharmacokinetic Per-
Protocol Set (PK-PPS) consists of 
all randomized subjects who 
received at least one dose of the 
IMP and provided at least one 
quantifiable plasma concentration 
post-dose without important 
protocol deviations that would 
affect the concentration.  
 
• 
The Per-Protocol Set (PPS) will 
consist of all subjects in the RS 
who had no important protocol 
deviations affecting the primary 
efficacy variable. Important 
protocol deviations will be 
predefined and subjects with 
important protocol deviations will 
be evaluated during ongoing data 
cleaning meetings prior to 
unblinding of the data. Exclusions 
from the FAS will be considered 
important protocol deviations 
that also result in exclusion from 
the PPS. 
• 
The Pharmacokinetic Per-Protocol 
Set (PK-PPS) consists of all 
randomized subjects who received 
at least one dose of the IMP and 
provided at least one quantifiable 
plasma concentration post-dose 
without important protocol 
deviations that would affect the 
Clarified PPS and PK-PPS 
definitions. 
Added COVID-19-free analysis set 
to determine if COVID-19 has an 
impact on analyses. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
concentration. Exclusions from the 
FAS will be considered important 
protocol deviations that also 
result in exclusion from the PK-
PPS. 
• 
The COVID-19-free Set will 
consist of all subjects in the RS 
who had no COVID-19 impact up 
to the primary efficacy endpoint. 
This will be defined as subjects 
not having a COVID-19 related 
important protocol deviation, nor 
having an impact based on the 
COVID-19 eCRF, nor having an 
AE related to COVID-19, nor 
discontinuing due to COVID-19 
up to the time of the primary 
endpoint. 
Change 16: Updated text in analysis of the primary efficacy variables section 
Section 14.3.1.1 
Updated text regarding the statistical approach to be used for analyzing primary 
efficacy variable. 
Updated statistical methods based 
on feedback from the FDA. 
Change 17: Updated title and text in former Sensitivity analyses section 
Section 14.3.1.1.1 
Updated title of this section from Sensitivity analyses to SensitivitySupportive 
analyses. Also, updated text regarding the statistical approach to be used for the 
supportive analyses. 
Updated statistical methods based 
on feedback from the FDA. 
Change 18: Updated text in analysis of the secondary efficacy variables section 
Section 14.3.1.2 
Updated text regarding the statistical approach to be used for analyzing 
secondary efficacy variables. 
Updated statistical methods based 
on feedback from the FDA. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
Change 19: Updated text in analysis of the other efficacy variables section 
Section 14.3.2 
Updated text regarding the statistical approach to be used for analyzing the other 
efficacy variables. 
Updated statistical methods based 
on feedback from the FDA. 
Change 20: Updated text in handling of dropouts or missing data section 
Section 14.7 
Updated the statistical approach to be used for missing data. 
Updated statistical methods based 
on feedback from the FDA. 
Change 21: Updated reference list 
References 
Deleted the following 2 references due to updates made in Section 14.7 Handling 
of dropouts or missing data: 
Mallinckrodt CH, Lin Q, Lipkovich I, Molenberghs G. A structured approach 
to choosing estimands and estimators in longitudinal clinical trials. Pharm 
Stat. 2012;11:456-61. 
Mallinckrodt CH. Preventing and Treating Missing Data in Longitudinal 
Clinical Trials: A Practical Guide. New York, NY: Cambridge University 
Press; 2013. 
Added the following 3 references, 1 for FACIT-Fatigue subscale and 2 for 
PASDAS: 
Cella D, Wilson H, Shalhoub H, et al. Content validity and psychometric 
evaluation of Functional Assessment of Chronic Illness Therapy-Fatigue in 
patients with psoriatic arthritis. J Patient Rep Outcomes. 2019;3(1):5. 
Coates LC, FitzGerald O, Mease PJ, et al. Development of a disease activity 
and responder index for psoriatic arthritis – Report of the Psoriatic Arthrits 
Module at OMERACT 11. J Rheumatol 2014;41:782-91. 
Coates LC, Gladman DD, Nash P, et al. Secukinumab provides sustained 
PASDAS-defined remission in psoriatic arthritis and improves health-related 
quality of life in patients achieving remission: 2-year results from the Phase 
Deleted Mallinckrodt references, as 
they are no longer applicable due to 
statistical updates. 
Additional references were 
deleted/added to support the 
assessments of FACIT-Fatigue 
subscale and PASDAS. 
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Protocol section 
impacted 
Key components of previous 
protocol text 
Key components of revised protocol 
text 
Rationale 
III FUTURE 2 study. Arthritis Res Ther. 2018;20(1):272. doi: 
10.1186/s13075-018-1773-y. 
Deleted the following FACIT reference because it was superseded by the Cella 
et al, 2019 reference: 
Cella D, Yount S, Sorensen M, Chartash E, Sengupta N, Grober J. Validation 
of the Functional Assessment of Chronic Illness Therapy Fatigue Scale 
relative to other instrumentation in patients with rheumatoid arthritis. J 
Rheumatol. 2005;32:811–19. 
 
 
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19 
DECLARATION AND SIGNATURE OF INVESTIGATOR 
I confirm that I have carefully read and understood this protocol and agree to conduct this 
clinical study as outlined in this protocol, according to current Good Clinical Practice and local 
laws and requirements. 
I will ensure that all subinvestigators and other staff members read and understand all aspects of 
this protocol. 
I have received and read all study-related information provided to me. 
The objectives and content of this protocol as well as the results deriving from it will be treated 
confidentially and will not be made available to third parties without prior authorization by UCB. 
All rights of publication of the results reside with UCB, unless other agreements were made in a 
separate contract. 
Investigator: 
 
  
Printed name 
 Date/Signature 
 
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20 
SPONSOR DECLARATION 
I confirm that I have carefully read and understand this protocol and agree to conduct this 
clinical study as outlined in this protocol and according to current GCP. 
 
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Approval Signatures
Name:
PA0011-protocol-amend-2
Version:
1. 0
Document Number:
CLIN-000171699
Title:
PA0011 Protocol-Amendment-2-Phase 3 - Placebo - controlled - Double-blind
Approved Date:
12 Apr 2021
Document Approvals
Approval
Verdict: Approved
Name: 
Capacity: Clinical
Date of Signature: 08-Apr-2021 13:33:04 GMT+0000
Approval
Verdict: Approved
Name: 
Capacity: Clinical
Date of Signature: 08-Apr-2021 17:24:32 GMT+0000
Approval
Verdict: Approved
Name: 
Capacity: Medical
Date of Signature: 12-Apr-2021 08:08:01 GMT+0000
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SAP_001.pdf: 
UCB 
 
09 Nov 2021 
Statistical Analysis Plan 
Bimekizumab 
PA0011 
 
 
 
 
Confidential 
Page 1 of 192 
 
 
STATISTICAL ANALYSIS PLAN  
Study: PA0011  
Product: Bimekizumab  
A MULTICENTER, PHASE 3, RANDOMIZED, DOUBLE-BLIND, 
PLACEBO-CONTROLLED STUDY EVALUATING THE 
EFFICACY AND SAFETY OF BIMEKIZUMAB IN THE 
TREATMENT OF SUBJECTS WITH ACTIVE PSORIATIC ARTHRITIS 
SAP/Amendment Number Date 
Final SAP 
24 May 2019  
Amendment 1 
Amendment 2 
02 Jul 2021 
09 Nov 2021 
Confidentiality Statement 
Confidential 
This document is the property of UCB and may not – in full or in part – be passed on, 
reproduced, published, or otherwise used without the express permission of UCB. 
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TABLE OF CONTENTS 
LIST OF ABBREVIATIONS .................................................................................................... 9 
1 
INTRODUCTION ........................................................................................................... 14 
2 
PROTOCOL SUMMARY ............................................................................................... 14 
2.1 
Study objectives ........................................................................................................... 14 
2.1.1 
Primary objective ................................................................................................. 14 
2.1.2 
Secondary objectives ........................................................................................... 14 
2.1.3 
Other objectives ................................................................................................... 14 
2.2 
Study variables ............................................................................................................. 15 
2.2.1 
Efficacy variables ................................................................................................ 15 
2.2.1.1 
Primary efficacy variable .......................................................................... 15 
2.2.2 
Secondary variables ............................................................................................. 15 
2.2.2.1  
Secondary efficacy variables ..................................................................... 15 
2.2.2.2 
Secondary safety variables ........................................................................ 15 
2.2.3 
Other variables ..................................................................................................... 16 
2.2.3.1 
 Other efficacy variables ............................................................................ 16 
2.2.3.2 
Other safety variables ................................................................................ 18 
2.2.3.3 
Pharmacokinetic variable .......................................................................... 18 
2.2.3.4 
Pharmacogenomic variables ...................................................................... 18 
2.2.3.5 
Immunological variables ........................................................................... 18 
2.3 
Study design and conduct ............................................................................................ 18 
2.3.1 
Study description ................................................................................................. 18 
2.3.2 
Study periods ....................................................................................................... 20 
2.4 
Determination of sample size ....................................................................................... 21 
2.4.1 
Power calculation for primary endpoint .............................................................. 21 
2.4.2 
Power calculation for secondary endpoints ......................................................... 22 
3 
DATA ANALYSIS CONSIDERATIONS ...................................................................... 23 
3.1 
General presentation of summaries and analyses ........................................................ 23 
3.2 
General study level definitions .................................................................................... 26 
3.2.1 
Relative day ......................................................................................................... 26 
3.2.2 
Mapping of assessments performed at Early Termination Visit ......................... 27 
3.3 
Definition of Baseline values ....................................................................................... 27 
3.4 
Study treatment discontinuation and intercurrent event .............................................. 28 
3.5 
Protocol deviations....................................................................................................... 28 
3.6 
Analysis sets................................................................................................................. 28 
3.6.1 
Enrolled Set ......................................................................................................... 29 
3.6.2 
Randomized Set ................................................................................................... 29 
3.6.3 
Safety Set ............................................................................................................. 29 
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3.6.4 
Full Analysis Set .................................................................................................. 29 
3.6.5 
Per Protocol Set ................................................................................................... 29 
3.6.6 
Pharmacokinetic Per-Protocol Set ....................................................................... 29 
3.6.7 
COVID-19-free Set .............................................................................................. 29 
3.7 
Treatment assignment and treatment groups ............................................................... 30 
3.8 
Center pooling strategy ................................................................................................ 30 
3.9 
Coding dictionaries ...................................................................................................... 30 
3.10 
Changes to protocol-defined analyses ......................................................................... 30 
3.11 
Changes related to COVID-19 ..................................................................................... 31 
4 
STATISTICAL/ANALYTICAL ISSUES ....................................................................... 31 
4.1 
Adjustments for covariates .......................................................................................... 31 
4.2 
Handling of dropouts or missing data .......................................................................... 32 
4.2.1 
Strategy for handling missing data for efficacy analyses .................................... 32 
4.2.1.1 
Primary analysis of binary endpoints that are part of the testing hierarchy 
(primary and secondary endpoints) ........................................................... 33 
4.2.1.2 
Primary analysis of continuous endpoints that are part of the testing 
hierarchy (secondary endpoints) ............................................................... 34 
4.2.1.3 
Supportive analyses of primary efficacy endpoint .................................... 34 
4.2.1.4 
Supportive analyses of endpoints that are part of the testing hierarchy 
(secondary endpoints) ................................................................................ 34 
4.2.1.5 
Analyses of secondary endpoints that are not part of the testing hierarchy 
and other efficacy endpoints ...................................................................... 35 
4.2.1.6 
Summary table of missing data handling approaches for efficacy analyses35 
4.2.2 
Methods for handling missing data for efficacy analyses.................................... 36 
4.2.2.1 
Non-responder imputation ......................................................................... 36 
4.2.2.2 
MI – MCMC/Monotone Regression ......................................................... 37 
4.2.2.3 
MI – MCMC/Reference-Based imputation ............................................... 43 
4.2.2.4 
Tipping Point analysis ............................................................................... 44 
4.2.2.5 
Treatment Policy Strategy ......................................................................... 46 
4.2.3 
Handling of missing data for AE ......................................................................... 47 
4.2.4 
Handling of missing data for prior and concomitant medications ....................... 48 
4.3 
Interim analyses and data monitoring .......................................................................... 49 
4.3.1 
Interim analysis .................................................................................................... 49 
4.3.2 
Data Monitoring Committee ................................................................................ 50 
4.4 
Multicenter studies ....................................................................................................... 50 
4.5 
Multiple comparisons/multiplicity ............................................................................... 50 
4.6 
Use of an efficacy subset of subjects ........................................................................... 51 
4.7 
Active-control studies intended to show equivalence .................................................. 51 
4.8 
Examination of subgroups ........................................................................................... 51 
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5 
STUDY POPULATION CHARACTERISTICS ............................................................. 52 
5.1 
Subject disposition ....................................................................................................... 52 
5.2 
Impact of COVID-19 ................................................................................................... 53 
5.3 
Protocol deviations....................................................................................................... 53 
6 
DEMOGRAPHICS AND OTHER BASELINE CHARACTERISTICS ........................ 54 
6.1 
Demographics .............................................................................................................. 54 
6.2 
Baseline characteristics ................................................................................................ 54 
6.2.1 
Baseline values for primary efficacy variable components ................................. 54 
6.2.2 
Other baseline characteristics .............................................................................. 55 
6.2.3 
History of psoriatic arthritis and psoriasis ........................................................... 56 
6.3 
Medical history and concomitant diseases ................................................................... 57 
6.4 
Prior and concomitant medications .............................................................................. 57 
6.5 
Prohibited concomitant medications ............................................................................ 58 
7 
MEASUREMENTS OF TREATMENT COMPLIANCE ............................................... 58 
8 
EFFICACY ANALYSES ................................................................................................ 58 
8.1 
Statistical analysis of the primary efficacy variable .................................................... 58 
8.1.1 
Derivation of ACR50 response ............................................................................ 58 
8.1.1.1 
Derivation of tender joint count (TJC) and swollen joint count (SJC)...... 60 
8.1.1.2 
Patient and physician reported clinical outcomes on psoriatic arthritis .... 62 
8.1.1.3 
Derivation of the health assessment questionnaire disability index score 
(HAQ-DI) .................................................................................................. 62 
8.1.1.4 
High-sensitivity C-Reactive Protein (hs-CRP) .......................................... 63 
8.1.2 
Primary analysis of the primary efficacy variable ............................................... 63 
8.1.3 
Subgroup analyses of the primary efficacy variable ............................................ 64 
8.1.4 
Supportive analyses of the primary efficacy variable .......................................... 66 
8.1.4.1 
Analysis on the PPS .................................................................................. 66 
8.1.4.2 
Analysis on the FAS .................................................................................. 66 
8.1.4.3 
Analysis using modified composite estimand where intercurrent events 
are defined as discontinuation due to AE or Lack of efficacy .................. 66 
8.1.4.4 
Analysis on individual components of the ACR ....................................... 67 
8.1.4.5 
Analyses using treatment policy strategy imputation for missing data ..... 68 
8.1.4.6 
Analysis on Observed cases ...................................................................... 69 
8.1.4.7 
Tipping point analysis ............................................................................... 69 
8.1.4.8 
Analyses including COVID-19 impact ..................................................... 69 
8.2 
Statistical analysis of the secondary efficacy variables ............................................... 70 
8.2.1 
Derivation of secondary efficacy variables ......................................................... 70 
8.2.1.1 
HAQ-DI: Change from Baseline at Week 16 ............................................ 70 
8.2.1.2 
Psoriasis Area and Severity Index 90 (PASI90) at Week 16 (in subjects 
with PSO involving at least 3% of BSA at Baseline) ................................ 70 
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8.2.1.3 
SF-36 PCS: Change from Baseline at Week 16 ........................................ 71 
8.2.1.4 
MDA at Week 16 ...................................................................................... 72 
8.2.1.5 
ACR20 and ACR70 response at Week 16 ................................................. 73 
8.2.1.6 
Proportion of subjects with an Investigator’s Global Assessment (IGA) 
score of 0 (clear) or 1 (almost clear) AND at least a 2-grade reduction 
from Baseline at Week 4 and Week 16 in the subset of subjects with 
psoriatic skin lesions at Baseline ............................................................... 73 
8.2.1.7 
Change from Baseline in the Patient’s Assessment of Arthritis Pain 
(PtAAP) ..................................................................................................... 74 
8.2.1.8 
Change from Baseline in PsAID-12 total score at Week 16 ..................... 74 
8.2.1.9 
Psoriasis Area Severity Index 90 (PASI90) at Week 4 (in subjects with 
PSO involving at least 3% of BSA at Baseline) ........................................ 74 
8.2.2 
Primary analysis of secondary efficacy variables ................................................ 74 
8.2.3 
Supportive analyses of the secondary efficacy variables..................................... 76 
8.3 
Statistical analysis of other efficacy variables ............................................................. 76 
8.3.1 
Derivation of other efficacy variables ................................................................. 76 
8.3.1.1 
Time to ACR20, ACR50, ACR70 response from Baseline ...................... 76 
8.3.1.2 
ACR20, ACR50 and ACR70 response ...................................................... 76 
8.3.1.3 
PASI75, PASI90, and PASI100 response (in subjects with PSO involving 
at least 3% of BSA at Baseline) ................................................................ 77 
8.3.1.4 
Composite endpoints composed of ACR50/PASI90 and ACR50/PASI100 
response (in subjects with PSO involving at least 3% of BSA at Baseline)77 
8.3.1.5 
Proportion of Psoriatic Arthritis Response Criteria (PsARC) responders. 77 
8.3.1.6 
Psoriatic Arthritis Disease Activity Score (PASDAS) categories ............. 77 
8.3.1.7 
MDA response ........................................................................................... 78 
8.3.1.8 
Very Low Disease Activity (VLDA) response ......................................... 78 
8.3.1.9 
Proportion of subjects with an IGA score of 0 (clear) or 1 (almost clear) 
AND at least a 2-grade reduction from Baseline in the subset of subjects 
with psoriatic skin lesions at Baseline ....................................................... 78 
8.3.1.10 
Disease Activity Index for Psoriatic Arthritis (DAPSA) score categories, 
state and change from Baseline in DAPSA score ..................................... 79 
8.3.1.11 
Change from Baseline in the Disease Activity Score -28 based on C-
reactive protein (DAS28[CRP]) ................................................................ 79 
8.3.1.12 
Change from Baseline in all individual ACR core components................ 80 
8.3.1.13 
Enthesitis-free state based on the LEI and change in LEI from Baseline in 
the subgroup of subjects with enthesitis at Baseline ................................. 80 
8.3.1.14 
Enthesitis-free state based on the SPARCC index and change in SPARCC 
index from Baseline in the subgroup of subjects with enthesitis at Baseline81 
8.3.1.15 
Dactylitis-free state based on the LDI and change in LDI from Baseline in 
the LDI in the subgroup of subjects with dactylitis at Baseline ................ 81 
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8.3.1.16 
Change from Baseline in the Bath Ankylosing Spondylitis Disease 
Activity Index (BASDAI) in the subgroup of subjects with axial 
involvement defined by a score of ≥4 at Baseline ..................................... 83 
8.3.1.17 
Change from Baseline in the modified Nail Psoriasis Severity Index 
(mNAPSI) score at Week 4, 8, 12 and 16 in the subgroup of subjects with 
psoriatic nail disease at Baseline ............................................................... 83 
8.3.1.18 
Change from Baseline in PsAID-12 total score ........................................ 84 
8.3.1.19 
Change from Baseline in the Psoriatic Arthritis Quality of Life (PsAQoL) 
total score .................................................................................................. 84 
8.3.1.20 
Change from Baseline in the SF-36 PCS and MCS scores, as well as the 8 
domain scores (Physical Functioning, Role Physical, Bodily Pain, General 
Health, Vitality, Social Functioning, Role Emotional, and Mental Health)85 
8.3.1.21 
Change from Baseline in Functional Assessment of Chronic Illness 
Therapy (FACIT) – Fatigue subscale score............................................... 85 
8.3.1.22 
Change from Baseline in Work Productivity and Activity Impairment 
Questionnaire–Specific Health Problem (WPAI-SHP) v2.0 adapted to 
PsA scores ................................................................................................. 86 
8.3.1.23 
Responses to the EuroQol-5D-3-Level (EQ-5D-3L) dimensions, change 
from Baseline in VAS score ...................................................................... 87 
8.3.1.24 
Change from Baseline in Patient’s Global Assessment of Arthritis (PGA-
arthritis) and Physician’s Global Assessment of Arthritis (PhGA-Arthritis)88 
8.3.1.25 
Proportion of subjects with a decrease of HAQ-DI from Baseline of at 
least 0.35 in the subgroup of subjects with Baseline HAQ-DI≥0.35 ........ 88 
8.3.2 
Analyses of other efficacy endpoints ................................................................... 88 
8.3.2.1 
Time to ACR20/50/70 response ................................................................ 88 
8.3.2.2 
Other endpoints (excluding time to ACR20/50/70 response) ................... 89 
8.3.2.3 
Additional statistical analysis for other efficacy endpoints ....................... 90 
9 
PHARMACOKINETICS AND IMMUNOLOGICAL (IMMUNOGENICITY) 
ANALYSES ..................................................................................................................... 91 
9.1 
Pharmacokinetics ......................................................................................................... 91 
9.2 
Immunological (immunogenicity) analyses ................................................................. 93 
9.2.1 
Anti-bimekizumab antibody ................................................................................ 93 
9.2.2 
Neutralizing anti-bimekizumab antibodies .......................................................... 98 
10 SAFETY ANALYSES ..................................................................................................... 99 
10.1.1 
Extent of exposure and time at risk ................................................................... 100 
10.1.2 
Time at risk in subject-years by COVID-19 pandemic period .......................... 101 
10.1.2.1 
Time at Risk in the pre-COVID-19 pandemic period ............................. 101 
10.1.2.2 
Time at Risk in the COVID-19 pandemic period .................................... 101 
10.1.2.3 
Time at Risk in the post COVID-19 pandemic period ............................ 102 
10.2 
Adverse events ........................................................................................................... 102 
10.2.1 
Standard AE summaries .................................................................................... 103 
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10.2.2 
Exposure duration of AEs .................................................................................. 104 
10.2.3 
Exposure adjusted incidence rate (EAIR) and exposed adjusted event rate 
(EAER) .............................................................................................................. 105 
10.2.4 
Other safety topics of interest ............................................................................ 106 
10.2.4.1 
Infections (serious, opportunistic, fungal and TB) .................................. 106 
10.2.4.2 
Malignancies ........................................................................................... 106 
10.2.4.3 
Major adverse cardiac events (MACE) ................................................... 107 
10.2.4.4 
Neutropenia ............................................................................................. 108 
10.2.4.5 
Suicidal Ideation and Behavior Neuropsychiatric events ........................ 108 
10.2.4.6 
Inflammatory bowel disease .................................................................... 109 
10.2.4.7 
Hypersensitivity (including Anaphylaxis) ............................................... 110 
10.2.4.8 
Hepatic events and DILI .......................................................................... 110 
10.2.5 
COVID-19 impact ............................................................................................. 110 
10.3 
Clinical laboratory evaluations .................................................................................. 111 
10.4 
Vital signs, physical findings, and other observations related to safety .................... 115 
10.4.1 
Vital signs, weight and physical findings .......................................................... 115 
10.4.2 
Electrocardiograms ............................................................................................ 116 
10.5 
Other safety variables ................................................................................................ 117 
10.5.1 
Electronic Columbia Suicide Severity Rating Scale (eC-SSRS) ....................... 117 
10.5.2 
Assessment of tuberculosis ................................................................................ 118 
10.5.3 
Change from Baseline in the Patient Health Questionnaire-9 (PHQ-9) ............ 118 
11 REFERENCES .............................................................................................................. 119 
12 APPENDICES ............................................................................................................... 120 
12.1 
Appendix1: MedDRA algorithmic approach to anaphylaxis..................................... 120 
12.2 
Appendix2: UCB-defined search criteria for identifying Opportunistic infections ... 121 
13 AMENDMENT(S) TO THE STATISTICAL ANALYSIS PLAN (SAP) .................... 123 
13.1 
Amendment 1 ............................................................................................................. 123 
13.2 
Amendment 2 ............................................................................................................. 182 
14 STATISTICAL ANALYSIS PLAN SIGNATURE PAGE ........................................... 192 
 
 
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LIST OF TABLES 
Table 7‒1: 
List of decimals for continuous efficacy endpoints ......................................... 24 
Table 3-2: 
Region definitions ............................................................................................ 30 
Table 4-1: 
List of non-composite continuous endpoints ................................................... 32 
Table 4-2: 
Missing data handling approaches for efficacy endpoints ............................... 35 
Table 4-3: 
Tipping point analysis: Delta parameters for each ACR component .............. 45 
Table 4-4: 
Sequential testing procedure of primary/ secondary efficacy endpoints 
(fixed sequence testing procedure) (All efficacy endpoints at Week 16) ........ 50 
Table 8-1: 
Swelling and tenderness grading ..................................................................... 61 
Table 8-2:  
Aid or device associated with HAQ-DI category ............................................ 63 
Table 8-3: 
Five-point IGA ................................................................................................. 73 
Table 8-4: 
Normative values for LDI ................................................................................ 82 
Table 10-1: 
Type of extended MACE events .................................................................... 107 
Table 10-2: 
Laboratory measurements .............................................................................. 111 
Table 10-3: 
Definitions of markedly abnormal biochemistry values ................................ 112 
Table 10-4: 
Definitions of markedly abnormal hematology values .................................. 113 
Table 10-5: 
Definitions of markedly abnormal liver enzyme elevation values ................ 114 
Table 10-6: 
Definitions of markedly abnormal blood pressure values ............................. 116 
 
 
LIST OF FIGURES 
Figure 2-1: 
Study schematic design .................................................................................... 19 
 
 
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LIST OF ABBREVIATIONS 
ACR 
American College of Rheumatology 
ACR20,50,70 
American College of Rheumatology 20, 50, 70% response criteria 
ADAb 
anti-drug antibody 
ADR 
adverse drug reaction 
AE 
adverse event  
ANCOVA 
analysis of covariance  
ATC 
anatomical therapeutic chemical classification  
BASDAI 
Bath Ankylosing Spondylitis Disease Activity Index 
BKZ 
bimekizumab 
BLQ 
below the limit of quantification  
BMI 
body mass index 
BP 
blood pressure 
BSA 
body surface area 
CASPAR 
Classification Criteria for Psoriatic Arthritis  
CCP 
cyclic citrullinated peptide 
cDMARD 
conventional disease modifying antirheumatic drug 
CI 
confidence Interval 
COVID-19 
Coronavirus Disease 2019 
CRF 
case report form 
CRP 
C-reactive protein 
CV 
coefficient of variation 
DAPSA 
disease activity index for psoriatic arthritis  
DAS28[CRP] 
disease activity score-28 based on C-reactive protein 
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DILI 
drug-induced liver injury 
DMC 
data monitoring committee 
DMARDs 
disease modifying antirheumatic drugs 
ECG 
electrocardiogram 
eC-SSRS 
electronic Columbia-Suicide Severity Rating Scale 
EQ-5D-3L 
Euro-Quality of Life 5-Dimensions 3 Level version 
ET 
early termination 
EAER 
exposure adjusted event rate 
EAIR 
exposure adjusted incidence rate 
FACIT 
Functional Assessment of Chronic Illness Therapy 
FAS 
full analysis Set 
FDA  
Food and Drug Administration 
HAQ-DI 
Health Assessment Questionnaire - Disability Index  
HLA-B27  
human leukocyte antigen B27 
HLT 
high level term 
hs-CRP 
high sensitivity C-reactive protein  
ICH 
International Council for Harmonisation of Technical Requirements 
for Pharmaceuticals for Human Use  
IE 
intercurrent event 
IGA 
Investigator’s Global Assessment 
IMP 
investigational medicinal product 
IPD 
important protocol deviation 
IWRS 
interactive web response system 
KM 
Kaplan-Meier 
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LCL 
lower confidence limit 
LDI 
Leeds Dactylitis Index 
LEI 
Leeds Enthesitis Index 
LLOQ 
lower limit of quantification 
LN 
natural logarithm 
LSM 
least square means 
MACE 
major adverse cardiac events 
MAR 
missing at random 
MCMC 
Markov-Chain Monte Carlo 
MCS 
Mental Component Summary 
MDA 
minimal disease activity 
MedDRA 
medical dictionary for regulatory activities  
MI 
multiple imputation 
mNAPSI 
modified Nail Psoriasis Severity Index 
MTX 
methotrexate 
NAb 
neutralizing anti-bimekizumab antibodies 
NRI 
nonresponder imputation 
NRS 
numeric rating scale 
NSAID 
nonsteroidal anti-inflammatory drug 
OC 
observed cases 
OLE 
open label extension 
OR 
odds ratio 
PASDAS 
psoriatic arthritis disease activity score 
PASI 
psoriasis area and severity index 
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PASI75, PASI90, PASI100 
psoriasis area and severity index 75%, 90%, 100% 
PCS 
Physical Component Summary  
PGA-Arthritis 
Patient’s Global Assessment of arthritis 
PGA-PsA 
Patient’s Global Assessment of Psoriatic Arthritis 
PhGA-Arthritis 
Physician’s Global Assessment of arthritis 
PhGA-PsA 
Physician’s Global Assessment of Psoriatic Arthritis 
PHQ-9 
Patient Health Questionnaire-9  
PK-PPS 
pharmacokinetics per-protocol set 
PPS 
per-protocol set 
PsA  
psoriatic arthritis 
PsAID-12 
Psoriatic Arthritis Impact of Disease-12 
PsARC 
psoriatic arthritis response criteria 
PsAQoL 
Psoriatic Arthritis Quality of Life  
PSO 
psoriasis 
PT 
preferred term 
PtAAP 
Patient’s Assessment of Arthritis Pain 
Q4W 
every 4 weeks 
RS 
randomized set 
SAE 
serious adverse event 
SAP 
statistical analysis plan 
SC 
subcutaneously  
SD 
standard deviation 
SF-36 
Short-Form 36-item Health Survey  
SFU 
safety follow-up 
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SOC 
system organ class 
SPARCC 
Spondyloarthritis Research Consortium of Canada 
SJC 
swollen joint count 
SMQ 
standardized MedDRA query 
SS 
safety set 
TB 
tuberculosis 
TEAE 
treatment emergent adverse event 
TESAE 
treatment emergent serious adverse event 
TFLs 
tables, figures, and listings 
TJC 
tender joint count 
TNF 
tumor necrosis factor 
TNFα 
tumor necrosis factor alpha  
TNFα-IR 
TNFα -inadequate responders  
UCL 
upper confidence limit 
ULN 
upper limit of normal 
VAS 
visual analog scale 
WHO-DD 
World Health Organization Drug Dictionary 
VLDA 
very low disease activity  
WPAI-SHP 
Work Productivity and Activity Impairment questionnaire - Specific 
Health Problem 
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1 
INTRODUCTION 
This statistical analysis plan (SAP) provides the necessary information to perform the final 
statistical analysis as well as the interim analysis for study PA0011. It also defines the summary 
tables, figures, and listings (TFLs) to be generated for the final clinical study report. 
The SAP is based on Protocol Amendment 2 (1 APR 2021). All references to study protocol 
hereafter refer to this version of the protocol, and, unless otherwise specified, the study will be 
analyzed as described in this version of the protocol. If a future protocol amendment necessitates 
a substantial change to the statistical analysis of the study data, or if analysis definitions must be 
modified or updated, this SAP will be amended accordingly.  
The content of this SAP is compatible with the International Council for Harmonisation of 
Technical Requirements for Pharmaceuticals for Human Use (ICH)/Food and Drug 
Administration (FDA) E9 Guidance documents (ICH E9, 1998). 
2 
PROTOCOL SUMMARY 
2.1 
Study objectives 
2.1.1 
Primary objective 
The primary objective is to demonstrate the clinical efficacy of bimekizumab (BKZ) 
administered subcutaneously (sc) every 4 weeks (Q4W) for 16 weeks compared with placebo in 
the treatment of prior tumor necrosis factor alpha-inadequate responders (TNFα-IR) subjects 
with active psoriatic arthritis (PsA), as assessed by the American College of Rheumatology 50% 
(ACR50) response. 
2.1.2 
Secondary objectives 
The secondary objectives are as follows: 
• To assess the efficacy of bimekizumab compared with placebo 
• To assess the safety and tolerability of bimekizumab 
• To assess the impact of bimekizumab on patient-reported quality of life 
• To assess the impact of bimekizumab on skin psoriasis (PSO) in the subgroup of affected 
subjects at Baseline. 
• To assess the impact of bimekizumab on functional improvement 
2.1.3 
Other objectives 
Other objectives are as follows: 
• To assess the immunogenicity of bimekizumab 
• To assess the impact of bimekizumab on extra-articular disease manifestations (dactylitis, 
enthesitis) 
• To assess nail PSO in the subgroup of affected subjects at Baseline 
• To explore the exposure-response relationship of bimekizumab 
• To assess the impact of bimekizumab treatment on axial disease 
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• To assess the effect of bimekizumab on gene and protein expression, and explore the 
relationship between genomic, genetic, and proteomic biomarkers and disease biology, drug 
treatment and inflammatory and immune responses (from consenting subjects who agree to 
participate in the biomarkers sub-study) 
• To assess the impact of bimekizumab on social life and work productivity 
2.2 
Study variables 
2.2.1 
Efficacy variables 
2.2.1.1 
Primary efficacy variable 
The primary efficacy variable is the ACR50 response at Week 16. 
2.2.2 
Secondary variables 
2.2.2.1 
Secondary efficacy variables 
The secondary efficacy variables are as follows: 
• Change from Baseline in Health Assessment Questionnaire - Disability Index (HAQ-DI) at 
Week 16 
• Reduction of 90% from Baseline in Psoriasis Area and Severity Index (PASI90 response) at 
Week 4 and Week 16 in the subgroup of subjects with PSO involving at least 3% body 
surface area (BSA) at Baseline 
• Change from Baseline in the Short-Form 36-item Health Survey (SF-36) Physical 
Component Summary (PCS) score at Week 16 
• Minimal Disease Activity (MDA) response at Week 16 
• ACR20 response at Week 16 
• ACR70 response at Week 16 
• Proportion of subjects with an Investigator Global Assessment (IGA) score of 0 (clear) or 1 
(almost clear) AND at least a 2-grade reduction from Baseline at Week 4 and Week 16 in the 
subset of subjects with psoriatic skin lesions at Baseline 
• Change from Baseline in the Patient’s Assessment of Arthritis Pain (PtAAP) at Week 16 
• Change from Baseline in Psoriatic Arthritis Impact of Disease-12 (PsAID-12) total score at 
Week 16 
2.2.2.2 
Secondary safety variables 
Secondary safety variables to be assessed are as follows: 
• Incidence of treatment-emergent adverse events (TEAEs) 
• Incidence of treatment-emergent serious adverse events (TESAEs) 
• TEAEs leading to withdrawal from Investigational Medicinal Product (IMP) 
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2.2.3 
Other variables 
2.2.3.1 
 
Other efficacy variables 
The following other efficacy variables will be assessed (all time points not specified in Section 
2.2.1.1 or Section 2.2.2.1 are exploratory): 
• Time to ACR20, ACR50, and ACR70 response from Baseline (Day 1)  
• ACR20, ACR50 and ACR70 response  
• PASI75, PASI90 and PASI100 response in the subgroup of subjects with PSO involving at 
least 3% BSA at Baseline 
• Composite endpoint composed of ACR50 and PASI90 response in subjects with PSO 
involving at least 3% BSA at Baseline 
• Composite endpoint composed of ACR50 and PASI100 response in subjects with PSO 
involving at least 3% BSA at Baseline 
• Proportion of Psoriatic Arthritis Response Criteria (PsARC) responders  
• Psoriatic Arthritis Disease Activity Score (PASDAS) categories  
• Change from Baseline in the PASDAS 
• MDA response  
• Very Low Disease Activity (VLDA) response  
• Proportion of subjects with an IGA score of 0 (clear) or 1 (almost clear) AND at least a 2-
grade reduction from Baseline in the subset of subjects with psoriatic skin lesions at Baseline 
• Disease Activity Index for Psoriatic Arthritis (DAPSA) score categories, 
• Change from Baseline in DAPSA score 
• Change from Baseline in the Disease Activity Score-28 based on C-reactive protein (DAS28 
[CRP]) 
• Change from Baseline in all individual ACR core components: 
− Swollen Joint Count (SJC) 
− Tender Joint Count (TJC) 
− HAQ-DI 
− PtAAP 
− Physician’s Global Assessment for Psoriatric Arthritis (PhGA-PsA) 
− Patient’s Global Assessment for Psoriatric Arthritis (PGA-PsA) 
− High sensitivity C-reactive protein (hs-CRP) 
• Enthesitis-free state based on the Leeds Enthesitis Index (LEI) in the subgroup of subjects 
with enthesitis at Baseline (ie, LEI>0 at Baseline) 
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• Change from Baseline in the LEI in the subgroup of subjects with enthesitis at Baseline (ie, 
LEI>0 at Baseline) 
• Enthesitis-free state based on the Spondyloarthritis Research Consortium of Canada 
(SPARCC) index in the subgroup of subjects with enthesitis at Baseline (ie, SPARCC>0 at 
Baseline) 
• Change from Baseline in SPARCC index in the subgroup of subjects with enthesitis at 
Baseline (ie, SPARCC>0 at Baseline) 
• Dactylitis-free state based on the Leeds Dactylitis Index (LDI) in the subgroup of subjects 
with dactylitis at Baseline (LDI>0) 
• Change from Baseline in the LDI in the subgroup of subjects with dactylitis at Baseline 
(LDI>0) 
• Proportion of subjects with a decrease of HAQ-DI from Baseline of at least 0.35 in the 
subgroup of subjects with Baseline HAQ-DI≥0.35 
• Change from Baseline in the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) 
in the subgroup of subjects with axial involvement defined by a score of ≥4 at Baseline  
• Change from Baseline in the modified Nail Psoriasis Severity Index (mNAPSI) score in the 
subgroup of subjects with psoriatic nail disease at Baseline (mNAPSI score>0) 
• Change from Baseline in PsAID-12 total score 
• Change from Baseline in the individual domain scores of PsAID-12 
• Proportion of subjects achieving PsAID-12 total score ≤4 
• Proportion of PsAID-12 responders (decrease from Baseline in PsAID-12 total score ≥3) in 
subjects with PsAID-12 total score ≥3 at Baseline  
• Change from Baseline in the Psoriatic Arthritis Quality of Life (PsAQoL) total score  
• Change from Baseline in the SF-36 PCS and SF-36 Mental Component Summary (MCS), as 
well as the 8 domain scores of the SF-36 (Physical Functioning, Role Physical, Bodily Pain, 
General Health, Vitality, Social Functioning, Role Emotional, and Mental Health)  
• Change from Baseline in Functional Assessment of Chronic Illness Therapy (FACIT)-
Fatigue subscale score 
• Proportion of FACIT-Fatigue subscale responders (subjects with a minimum clinically-
important difference for FACIT-Fatigue subscale score, defined as an increase of ≥4) in 
subjects with FACIT-Fatigue subscale score ≤48 at Baseline 
• Change from Baseline in Work Productivity and Activity Impairment Questionnaire–Specific 
Health Problem (WPAI-SHP) v2.0 adapted to PsA scores 
• Responses to the EuroQol-5D-3-Level (EQ-5D-3L) dimensions 
• Change from Baseline in EQ-5D-3L Visual Analog Scale (VAS) scores 
• Change from Baseline in Physician’s Global Assessment of Arthritis (PhGA-Arthritis)  
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• Change from Baseline in Patient’s Global Assessment of Arthritis (PGA-Arthritis)  
2.2.3.2 
Other safety variables 
Other safety variables to be assessed are: 
• Change from Baseline in vital signs (blood pressure [BP], temperature, and pulse rate) 
• Standard 12-lead electrocardiogram (ECG) results 
• Change from Baseline in clinical laboratory values (hematology, biochemistry and 
urinalysis) 
• Change from Baseline in Patient Health Questionnaire-9 (PHQ-9) 
Physical examination findings considered clinically significant changes since the physical 
examination at the Screening Visit will be recorded as AEs. 
2.2.3.3 
Pharmacokinetic variable 
The pharmacokinetic (PK) variable is the plasma concentration of BKZ. Blood samples for these 
measurements will be obtained at all visits except Screening.  
2.2.3.4 
Pharmacogenomic variables 
Additional blood samples will be collected from subjects who consent to participate in the sub 
study at specific time points and stored at -80°C for up to 20 years. 
Genomic, genetic, epigenetic, proteins, and metabolite biomarkers may be measured to evaluate 
the relationship with response to treatment with BKZ, PsA disease biology, and inflammatory 
and immune response processes. The nature and format of these tentative sub study analyses will 
be determined when the results of the main study are made available. 
The candidate exploratory variables are the blood or blood derivative (eg, serum) concentrations 
of cytokines and chemokines of relevance to IL-17A/F signaling pathway and PsA biology. 
Additional variables may include but will not be limited to serum complement concentrations.  
2.2.3.5 
Immunological variables 
The immunological variables allow evaluation of immunogenicity. The immunological variables 
are:  
• The anti- BKZ antibody status 
• The treatment-emergent antibody status derived from antidrug antibody (ADAb) assays 
• The neutralizing antidrug antibody (NAb) status 
These 3 variables will be assessed at all visits except Screening.  
2.3 
Study design and conduct 
2.3.1 
Study description 
PA0011 is a Phase 3, multicenter, randomized, double-blind, placebo-controlled study. To be 
eligible to participate in this study, subjects must be adults with a diagnosis of PsA based on the 
Classification Criteria for Psoriatic Arthritis (CASPAR) criteria and have disease with TJC ≥3 
and SJC ≥3, as well as an inadequate response (lack of efficacy after at least 3 months of therapy 
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at an approved dose) or intolerance to treatment with 1 or 2 TNFα inhibitors for either PsA or 
PSO. Study entrance criteria are described in the protocol. 
The study consists of the following periods (see Figure 7‒1 for a schematic diagram). 
• a Screening Period (≥14 days to ≤35 days),  
• a 16-week placebo-controlled Double-Blind Treatment Period,  
• and a Safety Follow-Up (SFU) Period, 20 weeks after the final dose of IMP (for subjects who 
complete the study and do not enter the open-label extension (OLE) study or for subjects 
who discontinue early, including those withdrawn from IMP). 
The maximum study duration per subject will be up to 37 weeks. The end of the study is defined 
as the date of the last visit of the last subject in the study.  
Approximately 390 subjects will be randomized in a 2:1 ratio, stratified by region (North 
America, Western Europe, Eastern Europe, and Asia) and prior TNFα inhibitor exposure 
(inadequate response to 1 prior TNFα inhibitor, inadequate response to 2 prior TNFα inhibitors, 
or intolerance to TNFα inhibitor) to receive one of the two following blinded treatment groups:  
• Bimekizumab 160mg sc Q4W,  
• Placebo 
Subjects discontinuing IMP during the Double-Blind Treatment Period will be encouraged to 
return for all scheduled visits through Week 16 and the SFU Visit, as applicable. 
At the completion of the Double-Blind Treatment Period, subjects completing the study (ie, 
performing all visits up to Week 16 and not having permanently discontinued IMP) and who did 
not meet any of the withdrawal criteria will be given the opportunity to enter an OLE study at 
Week 16. 
Figure 7‒1: Study schematic diagram 
 
  
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Refer to the clinical study protocol for more detailed information on the study assessments and 
schedule of procedures. 
2.3.2 
Study periods 
The following study periods are defined for the classification by study period: 
Screening Period (≥14 days to ≤35 days) 
 
Starts at time of the informed consent date (Screening Visit -Visit 1) and ends the day before the 
first dose administration of IMP (Baseline Visit – Visit 2) (ie, generally the day before Visit 2 
date). This period should last between 14 to 35 days and will involve obtaining laboratory data 
and verifying that the doses of nonsteroidal anti-inflammatory drugs (NSAIDs) or permitted 
DMARDs, if used to treat PsA, are stable. The Screening Period will also enable washout of any 
medications not permitted for use during the study. 
 
Double-Blind Treatment Period (16 weeks) 
Starts on the day of first dose administration of study drug (Visit 2). This period should last 16 
weeks maximum. During the Double-Blind Treatment Period, subjects will be randomized 2:1 
(stratified by region and prior TNFα inhibitor exposure [inadequate response to 1 or 2 prior 
TNFα inhibitors, or intolerance to TNFα inhibitors]) to receive 1 of 2 blinded treatment 
regimens: 
• Bimekizumab 160mg sc Q4W,  
• Placebo 
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Visit windows of ±3 days are allowed from the first dose at all visits through Week 16. The visit 
window is relative to the Day 1 (Baseline) Visit.  
Bimekizumab and placebo will be administered sc by unblinded study personnel at the clinical 
site. 
The time between IMP doses should be ≥21 days and ≤35 days during the Double-Blind 
Treatment Period.  
Subjects discontinuing IMP during the Double-Blind Treatment Period will return for all 
scheduled visits through Week 16 and the SFU Visit (20 weeks after the final dose of IMP) as 
applicable. Subjects withdrawing from the study will have an Early Termination (ET) Visit and a 
SFU Visit 20 weeks after the final dose of IMP, as applicable. 
 
The end of the 16-week Double-Blind Treatment Period will be either the date of Week 16 visit 
(Visit 6) for subjects completing the treatment period, or the date of the early termination (ET) 
visit for subjects who discontinued during the Treatment Period. 
If a subject does not have a Visit 6 or ET visit, then either the date of the last scheduled or 
unscheduled visit during the Treatment Period or the date of last known dose of study drug 
during the Treatment Period, whichever is later, will define the end date of the Treatment Period. 
 
Safety Follow-Up 
The SFU Period will be defined for all subjects who complete the study and do not enter the 
OLE study, or for subjects who discontinue early including those withdrawn from IMP. This 
period should last 20 weeks from the final dose. 
• For subjects who complete the study and do not enter the OLE study, the SFU Period starts 
the day after Visit 6 date and ends on the day of the SFU Visit.  
• For subjects who discontinue early, the SFU Period starts the day after the ET date and ends 
on the day of the SFU Visit 
A subject will be considered to have completed a study period if they complete the last scheduled 
study visit for that period. Note that subjects who previously discontinued IMP and are 
continuing for all scheduled visits through Week 16 will also be considered as completed the 
Double-Blind Treatment Period. 
2.4 
Determination of sample size 
Approximately 390 subjects will be randomly assigned in a 2:1 ratio to the following treatment 
groups: BKZ 160mg sc Q4W (260 subjects) and placebo (130 subjects).  
The primary efficacy analysis is based on the primary comparison of BKZ versus placebo for 
ACR50 response at Week 16.  
All sample size and power calculations were done at a significance level of 0.05. 
All sample size and power calculations were performed using the software nQuery Advisor® 
7.0. 
2.4.1 
Power calculation for primary endpoint 
The sample size assumptions for BKZ vs placebo are based on the ACR50 response data in the 
subgroup of TNFα-IR patients from the Phase 2b BKZ study in a mixed prior TNFα therapy 
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population of subjects with moderate-to-severe PsA (PA0008). Sample size calculations for a 
TNFα-IR population are also based on ACR50 responses at Week 16 in the SPIRIT-P2 study. 
Observed ACR50 at Week 12 results in the PA0008 TNFα-IR populations were in a small 
number of subjects; BKZ 160mg (n=7), 320mg (n=8), and 320mg (initial dose) plus 160mg 
(n=8) and ranged from 14.3% to 37.5%. 
The ixekizumab Phase 3 study SPIRIT–P2 is conducted on a similar patient population to that in 
this study and showed a 35% (n=122) ACR50 response at Week 16. Therefore, taking into 
account the range of ACR50 responses at Week 12 in PA0008, the estimated ACR50 response at 
Week 16 in the BKZ 160mg sc Q4W group is conservatively assumed to be 26%. 
For placebo, a similar approach as above is used. In the PA0008 TNFα-IR population, an ACR50 
response of 11.1% (n=9) was observed at Week 12. The observed placebo ACR50 response at 
Week 16 was less than 10% in the SPIRIT-P2 study (n=118). Therefore, the estimated ACR50 
response at Week 16 in the placebo group is assumed to be 10%. 
The sample size for showing statistical superiority of BKZ vs placebo was calculated using a 2-
sided 2-sample Chi-square test with continuity correction (Fleiss et al, 1980). Assuming 260 
subjects in the BKZ group and 130 subjects in the placebo group, the test for detecting statistical 
superiority of BKZ 160mg vs placebo based on ACR50 response at Week 16 has 96% power to 
detect a true treatment difference of 16% (odds ratio (OR) of 3.16). 
2.4.2 
Power calculation for secondary endpoints 
The assumptions for power calculations of the secondary endpoints included in the hierarchy and 
for which supporting data are available, in the TNFα-IR population are based on the results of 
PA0008 and the SPIRIT-P2 studies. All power calculations for binary endpoints were performed 
using a 2-sided 2-sample Chi-square test with continuity correction (Fleiss et al, 1980). All 
power calculations for continuous endpoints were performed using a 2-sided 2-group 
Satterthwaite t-test (Moser et al, 1989). 
For the change from Baseline in HAQ-DI at Week 16, based on data from the TNFα-IR 
population in SPIRIT-P2 Week 12 as well as Week 12 and Week 16 data from the PA0008 and 
PsA001 studies respectively, estimates of the SD in the active treatment and placebo groups are 
0.71. A two-group Satterthwaite t-test with a 0.050 2-sided significance level will have 85% 
power to detect a difference of 0.23 in the mean change from Baseline in HAQ-DI at Week 16 
between BKZ treatment and placebo assuming a sample size of 390 subjects randomized 2:1. 
For PASI90 response at Week 16, a PASI90 response at Week 12 of 38% (N=122), from the 
SPIRIT-P2 study is assumed. The PASI90 response at Week 12 in the BKZ 160mg group is 
50.0% (n=8) in the subgroup analysis of the TNFα-IR patients. Placebo PASI90 response at 
Week 16 is based on SPIRIT-P2 data (6.0% at Week 12). However, for this endpoint the placebo 
response is rounded to 10%. With those assumptions, the endpoint has 99% power to detect a 
treatment difference of 28% (OR of 5.52) at an assumed 50% of subjects with BSA ≥3% of the 
planned sample size. 
For the change from Baseline in PCS score of SF-36 at Week 16, based on data from the TNFα-
IR population in SPIRIT-P2 where estimates of the SD in the active treatment and placebo 
groups at Week 12 are ixekizumab Q4W (SD=11.95) and placebo (SD=12.15). A 2-group 
Satterthwaite t-test with a 0.050 2-sided significance level will have 89% power to detect a 
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difference in means of 4.4 change from Baseline in SF-36 PCS score at Week 16 between the 
bimekizumab and placebo treatment groups with a sample size of 390 subjects randomized 2:1. 
For MDA at Week 16, it is assumed that 5% of the placebo subjects achieve MDA at Week 16 
(SPIRIT-P2 Week 12). Given the planned sample size and using a 2-sided 2-sample Chi-square 
test with continuity correction this study has 92% power to detect an absolute difference in MDA 
response at Week 16 of 12% (OR of 3.892) with a total sample size of 390 subjects. 
3 
DATA ANALYSIS CONSIDERATIONS 
3.1 
General presentation of summaries and analyses 
Statistical analysis and generation of tables, figures, subject data listings, and statistical output 
will be performed using SAS® Version 9.3 or higher unless otherwise specified. All tables and 
listings will use Courier New font size 9. 
Descriptive statistics will be displayed to provide an overview of the study results.  
For categorical parameters, the number and percentage of subjects in each category will be 
presented. Unless otherwise noted, the denominator for percentages will be based on the number 
of subjects included in the respective analysis set. Subjects with missing data can generally be 
accounted for using one of the 2 following approaches:  
• Percentages will be summarized based on all subjects in the analysis set and a “Missing” 
category (corresponding to subjects with missing data for the variable being summarized) 
will be included as the last row in the list of categories being summarized (this approach will 
be used when reporting demographics and Baseline characteristics, some ADAb and NAb 
tables and some shift tables from Baseline for laboratory data).   
• Percentages will be based only on those subjects with observed data for the variable being 
summarized. As the denominator may be different from the number of subjects in the 
analysis set being considered, the denominator should be displayed in the table. The general 
format for displaying this will be “n/Nsub (%)”. 
Unless otherwise noted, all percentages will be displayed to one decimal place. No percentage 
will be displayed for zero counts, and no decimal will be presented when the percentage is 100%.  
Unless stated otherwise, continuous endpoints will be expressed as a change from Baseline 
which will be calculated as the value at a specific timepoint minus the value at Baseline.  
For continuous parameters, descriptive statistics will include number of subjects with available 
measurements (n), arithmetic mean, standard deviation (SD), median, minimum, and maximum 
(unless otherwise stated).  
For hs-CRP variable, the summary statistics should contain arithmetic mean, geometric mean, 
geometric coefficient of variation (CV), median, first and third quartile (Q1 and Q3), minimum 
and maximum (for the value and ratio to Baseline). The geometric CV (%) will be calculated 
using the following formula: 
𝐶𝑉= √𝑒𝑆𝐷𝑙𝑛
2 −1 
where 𝑆𝐷𝑙𝑛 represents the standard deviation of the ln-transformed hs-CRP values. 
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For BKZ PK concentrations, geometric mean, geometric CV, 95% confidence intervals (CIs) for 
geometric mean (assuming log-normally distributed data) will be calculated if at least ⅔ of the 
values of interest are above the lower limit of quantification (LLOQ). If this is not the case, only 
median, minimum and maximum will be presented.  
Decimal places for descriptive statistics will always apply the following rules: 
• “n” will be an integer.  
• Mean, SD, SE, and median (Q1 and Q3 where applicable) will use 1 additional decimal place 
compared to the original data (for a derived score, number of decimals of the original data 
considered is the one obtained where deriving the score in the absence of missing data).  
• Coefficient of variance (CV [%]) will be presented with 1 decimal place.  
• Minimum and maximum will have the same number of decimal places as the original raw 
value. 
If the number of decimal places reported in the original data is varied then either the maximum 
raw number of reported decimal places or 3 will be used, whichever is the lowest, as a guide for 
the descriptive statistics. 
Table 7‒1: 
List of decimals for continuous efficacy endpoints  
Continuous efficacy endpoint 
Decimal place used 
for minimum and 
maximum 
Decimal places used 
for Mean, SD (or 
SE) and median 
BASDAI  
1 
2  
DAPSA  
1 
2  
DAS28[CRP]  
2 
3  
EQ-5D-3L dimension scores  
0 
1  
EQ-5D-3L (VAS)  
0 
1  
FACIT-Fatigue subscale score  
1 
2  
HAQ-DI  
3 
4  
hs-CRP  
2 
3 
LDI  
1 
2  
LEI  
1 
2  
mNAPSI  
0 
1  
PASDAS  
1 
2  
PASI  
1 
2  
PGA-Arthritis /PhGA-Arthritis  
0 
1  
PGA-PsA / PhGA-PsA  
0 
1  
PsAID-12  
1 
2  
PsAQoL  
1 
2  
PsARC  
1 
2 
PtAAP  
0 
1  
SF-36  
2 
3  
SPARCC  
1 
2  
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TJC / SJC  
1 
2  
WPAI-SHP  
1 
2 
BASDAI=Bath Ankylosing Spondylitis Disease Activity Index; DAPSA=disease activity index for psoriatic arthritis; 
DAS28[CRP]=disease activity score-28 based on C-reactive protein; EQ-5D-3L=Euro-Quality of Life 5-Dimensions 3 Level 
version; FACIT=Functional Assessment of Chronic Illness Therapy; HAQ-DI=Health Assessment Questionnaire – Disability 
Index; hs-CRP=High sensitivity C-reactive protein; LDI=Leeds Dactylitis Index; LEI=Leeds Enthesitis Index; 
mNAPSI=Modified Nail Psoriasis Severity Index; PASDAS= Psoriatic Arthritis Disease Activity Score; PASI=Psoriasis Area 
and Severity Index;  PGA-Arthritis=Patient’s Global Assessment of Arthritis; PGA-PsA=Patient’s Global Assessment of 
Psoriatic Arthritis; PhGA-Arthritis=Physician’s Global Assessment of Arthritis; PhGA-PsA=Physician’s Global Assessment of 
Psoriatic Arthritis;   PHQ-9=Patient Health Questionnaire-9; PSAID-12=Psoriatic Arthritis impact of disease-12; 
PsAQoL=Psoriatic Arthritis Quality of Life; PsARC= Psoriatic Arthritis Response Criteria; PtAAP=Patient’s assessment of 
Arthritis Pain;  SF-36=Short-Form 36-item Health Survey; SJC= Swollen Joint Count; SPARCC= Spondyloarthritis Research 
Consortium of Canada ; TJC=Tender Joint Count; WPAI-SHP=Work Productivity and Activity Impairment questionnaire – 
Specific Health Problem  
Unless stated otherwise, statistical tests of efficacy variables will be performed 2-sided and p-
values will be rounded to 3 decimal places. P-values less than 0.001 will be presented as 
“<0.001” and p-values greater than 0.999 will be presented as “>0.999.” Statistical comparison 
will be performed at the 0.05 level of significance. Least square means (LSM), odds-ratios (OR) 
and corresponding confidence intervals (CI) will be presented using 3 decimals. 
UCB uses SAS in a 64-bit Windows environment, and it is well-documented that in this 
environment the maximum accuracy of any numeric value is 15 significant digits. However, SAS 
by default does not limit the accuracy of numeric values to 15 significant digits which, in certain 
instances, may result in inaccurate representation of the data and cause errors when used in 
subsequent calculations, particularly when comparing a value to a chosen threshold. This, in 
turn, could potentially result in a change in classification of a subject from a responder to a 
nonresponder (and vice versa) if these values occur on a threshold used in the evaluation of 
response (or a critical laboratory value for example). 
Therefore, in order to avoid issues caused by inaccurate floating point representation of numeric 
values, temporary variables are created (ie, for absolute values, change and percentage change 
from Baseline) during programming which are rounded to 12 decimal places prior to comparison 
to a specific threshold in the derivation of a response parameter. This does not imply inherent 
rounding on the analysis variables for absolute value, change or percentage of change which are 
retained unrounded in the final analysis dataset. Thus, rounding is applied exclusively during the 
derivation of new response parameters or critical value variables, and the rounded values are 
created on a temporary basis only. 
The SAS® outputs supportive of any inferential statistics that are part of the hierarchical testing 
procedure (ie, all inferential statistics associated with the endpoints in Table 7‒4 will be provided 
as a separate PDF document in addition to TFLs. These outputs will be included in the 
‘Documentation of Statistical Methods’ section of the clinical study report. 
The order of treatment groups to be presented in tables from left to right will be: 
• Placebo 
• Bimekizumab 160mg Q4W 
Selected tables may also include columns for all subjects (regardless of study treatment). 
The abbreviation for bimekizumab is BKZ and will be used in tables and listings headers. In the 
TLFs subjects randomized to bimekizumab 160mg will be labeled as “BKZ 160mg Q4W”.  
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Per protocol, visit windows of ±3 days from the first dose at all visits through Week 16 are 
permissible. For the SFU Visit, the visit should occur no more than 3 days prior to the scheduled 
visit date and within 7 days after the scheduled visit date. Only data collected at the scheduled 
visit will be included in the analysis. The only deviation may concern unscheduled vendor data 
as explained in Section 10.5. 
All by-visit summaries will contain nominal (ie, scheduled) visits only. Unscheduled visits will 
not be mapped to scheduled visits except for some assessments that may occur within 3-day time 
window of a scheduled visit. In that case, the assessment will be mapped to the corresponding 
scheduled visit and will be used for the analysis unless the data are present for that scheduled 
visit.  
Assessments collected at unscheduled visits will only be listed, except in the case of determining 
treatment-emergent markedly abnormal criteria for laboratory and vital sign parameters where all 
post-Baseline (scheduled and unscheduled) values will be summarized. For PK, immunological 
and immunogenicity analyses, SFU data will be a part of the data reported in some tables 
(Section 9).   
For by-visit tables summarizing efficacy data, the SFU visit will not be included, but SFU 
efficacy data will be listed. By-visit tables summarizing safety will however include the SFU 
visit. 
A complete set of data listings containing all documented data and all derived data (eg, change 
from Baseline) will be generated. 
Repeated visits will not be summarized but listed. 
Unless otherwise stated, listings will be sorted by treatment, subject number within each 
treatment group (not randomization number), variable (if applicable) and visit (if applicable, 
including timing relative to dosing if applicable). For listings including nonrandomized subjects, 
the nonrandomized subjects will be shown first in the listing, ordered by subject number. All 
listings will include repeat and unscheduled measurements; such measurements will appear in 
chronological order together with the scheduled visits, ie, a repeated measurement will appear 
directly after the visit and time relative to dosing for which the repeat measurement was 
performed. In all the listings dates will be presented in the format ‘YYYY-MM-DD’ and times 
will be presented in 24h clock format as ‘hh:mm’. 
3.2 
General study level definitions 
3.2.1 
Relative day 
The relative day will be included in some listings. The way that relative day is calculated 
depends on when the given event occurs relative to the date of first study drug administration.  
• If the event starts (stops) on or after the first dose of study drug administration, but prior to 
the study drug stop date, relative day is calculated as start (stop) date of the event minus first 
dose date of study drug dose + 1.  
Relative day 1 is the date of first study drug administration. 
• If the event starts (stops) after the last dose of study drug administration, the relative day is 
calculated as start (stop) date of the event minus most recent study drug dose date. The 
relative day in this situation should be preceded by a ‘+’ 
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• If the event starts (stops) before the first dose of study drug administration, the relative day is 
calculated as start (stop) date of the event minus first dose date of study drug dose. The 
relative day in this situation should be preceded by a ‘-’. 
Relative day will only be computed for fully completed dates and will be left blank for partial 
dates. 
For AEs, relative days for start and stop dates will be calculated as the number of days since the 
first injection of the medication. For non-treatment emergent AEs, relative day of onset will be 
negative if the event started before the date of first dose. A complete date must be established in 
order to correctly identify the AEs. Section 4.2.3 describes imputation rules in case of missing 
data for AEs. 
3.2.2 
Mapping of assessments performed at Early Termination Visit 
If the early termination visit occurs at a scheduled visit as outlined in the schedule of 
assessments, then no mapping is necessary, and any early withdrawal assessments should 
correspond to that scheduled visit. Early termination visit assessments that do not have a 
scheduled visit with a matching date will be assigned a visit based on the protocol defined visit 
windows (±3 days from first dose to Week 16, and -3 to +7 days from the final dose for the SFU 
Visit).  For early discontinuation visits that fall between protocol defined visit windows and not 
within them, the later of the 2 visits will be assigned. 
If there is an existing scheduled site visit in the window, then the assessments at the ET visit will 
be mapped to the next scheduled site visit. 
The ADAb assessments and PK are exceptions to this rule:  
• ADAb levels, PK from an ET visit will be mapped to the next visit where antibody levels / 
PK are measured. 
3.3 
Definition of Baseline values 
A Baseline value for a subject is defined as the latest measurement for that subject up to and 
including the day of administration of first study medication (ie, generally Visit 2 by default), 
unless otherwise stated.   
By default, for randomized subjects for which no start date of treatment is available, the Baseline 
value will be considered as the last available value prior to the randomization date.   
If a Baseline assessment is taken on the same day as first administration of study medication, it is 
eligible to be used as the Baseline value, even in the case that the time of the assessment is 
recorded as taking place after the time of first study medication administration. This is 
considered acceptable as this measurement is still the best representation of the Baseline value of 
the given assessment since it is highly unlikely that the study medication could have an impact 
on any measurement in such a short period of time. However, such cases should be rare as study 
center personnel are instructed to do all assessments at the Baseline visit prior to administering 
study medication. One exception to this rule is plasma concentration. If Baseline plasma 
concentration is measured at a time after the first administration of study medication, then it 
should not be eligible to be considered as a Baseline plasma concentration. Such cases should be 
discussed with the quantitative clinical pharmacologist.  
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If a Baseline measurement is missing or not collected, and a Screening value is available, the 
Screening value will be utilized as Baseline instead. If no measurement is available prior to 
receiving study medication, then the Baseline value is treated as missing.  
Baseline values for component scores should be computed using components from the same visit 
where the relevant measurements were recorded prior to dosing. For example, if the Screening 
Visit has all of the components, and the Baseline visit is missing one or more components, the 
Baseline value for the component score should be calculated using the Screening Visit values. 
When the time of first dose is derived, it should be based on the first injection of study treatment, 
regardless of whether or not it is an active treatment. 
Chest x-ray performed within 3 months before the Screening Visit is considered as Baseline 
measurement. 
3.4 
Study treatment discontinuation and intercurrent event 
The concept of intercurrent event is one of the estimand attributes. 
 
Unless otherwise noted, treatment discontinuation due to any reason will be considered as an 
intercurrent event (IE). Since there is no treatment discontinuation date collected, the treatment 
discontinuation date is defined as: 
• 
Treatment end date + 31 days. 
3.5 
Protocol deviations 
Important protocol deviations (IPD) are deviations from the protocol which potentially could 
have a meaningful impact on study conduct or on the primary efficacy, key safety, or PK 
outcomes for an individual subject. The criteria for identifying IPD will be defined within the 
appropriate protocol-specific document. All protocol deviations (PDs) will be reviewed as part of 
the ongoing data cleaning process and data evaluation. The IPD will be identified and 
documented prior to unblinding to confirm exclusion from Per-Protocol Set (PPS) and 
Pharmacokinetics Per-Protocol Set (PK-PPS).  
Also, an IPD will not always necessitate the removal of a subject from the PPS. Depending on 
the type of protocol deviation, the subject may remain in the PPS. The IPD document developed 
by the clinical study team should clearly state which deviations will result in a removal from the 
PPS.  
In addition to IPDs resulting in the exclusion from the PPS, subjects who reduce the dose or 
dosing frequency of certain medications due to intolerance, AE, side-effects or receive new 
prohibited medication for AE will be removed from the PPS. While this is not an IPD, as it is 
allowed per protocol for safety reasons, these subjects will be removed from the PPS as this non-
PD could have an effect on the primary efficacy outcome in the same way as flagged IPDs 
resulting in exclusion from the PPS. 
A specific category of PD, as a consequence of the Coronavirus Disease 2019 (COVID-19) 
pandemic, called COVID-19 related PD will be assessed based especially on the information 
collected on a dedicated eCRF page (and other available sources).  
3.6 
Analysis sets 
The analysis sets are described below. 
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3.6.1 
Enrolled Set 
The Enrolled Set (ES) consists of all subjects who have given informed consent. 
Subject dispositions will be summarized on the ES. 
3.6.2 
Randomized Set 
The Randomized Set (RS) consists of all enrolled subjects who have been randomized.  
Demographic tables, primary, secondary, and other efficacy variables will be presented on the 
RS. 
3.6.3 
Safety Set 
The Safety Set (SS) consists of all subjects who received at least 1 dose of the IMP. 
Demographic tables, study treatment compliance and exposure and safety variables will be 
presented on the SS. The anti-BKZ antibody will also be analyzed on the SS for subjects 
receiving BKZ. 
3.6.4 
Full Analysis Set 
The Full Analysis Set (FAS) consists of all randomized subjects who received at least 1 dose of 
the IMP and have a valid measurement of all components of the primary efficacy variable at 
Baseline. 
Supportive analysis of the primary efficacy variable will be performed on the FAS.  
3.6.5 
Per Protocol Set 
The Per-Protocol Set (PPS) consists of all subjects in the RS who had no IPD or non-PD related 
to prohibited medications (along with subjects with a reduced frequency/dosing of a drug) 
affecting the primary efficacy variable. The deviations will be predefined and subjects with 
deviations will be evaluated during ongoing data cleaning meetings prior to unblinding of the 
data. See Section 3.5 for further details. Exclusion from the FAS will be considered as an IPD 
that also result in exclusion from the PPS. 
Supportive analysis of the primary efficacy variable will be performed on the PPS. 
3.6.6 
Pharmacokinetic Per-Protocol Set 
The Pharmacokinetic Per Protocol Set (PK-PPS) consists of all randomized subjects who 
received at least 1 dose of the IMP and provided at least 1 quantifiable plasma concentration 
post-dose without important protocol deviations that would affect the concentration.  
PK variables will be analyzed for all subjects in the PK-PPS. 
3.6.7 
COVID-19-free Set 
The COVID-19-free Set will consist of all subjects in the RS who had no COVID-19 impact up 
to the primary efficacy endpoint. This will be defined as subjects: 
• not having a COVID-19 related IPD 
• not having an impact based on the COVID-19 eCRF. 
• not having an AE related COVID-19 (Section 10.2.5 ) 
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• not discontinuing due to COVID-19 
The disposition data, the primary efficacy endpoint and the secondary efficacy endpoints 
included in the testing hierarchy will be analyzed on the COVID-19-free Set. 
3.7 
Treatment assignment and treatment groups 
It is expected that subjects receive treatment as randomized and hence safety analyses will be 
based on the SS, as randomized. However, if after unblinding it is determined that subjects 
randomized to placebo received BKZ at any time, then for safety analyses these subjects will be 
reallocated to the BKZ treatment group. Subjects randomized to BKZ will only be reallocated to 
the placebo treatment group if they never received BKZ. 
Efficacy analyses will be performed according to randomization and not actual treatment 
received. Data collected after study treatment discontinuation will be listed only and not reported 
in table (except in the context of the treatment policy analysis performed on the primary efficacy 
endpoint in Section 8.1.4.5).  
3.8 
Center pooling strategy 
Geographic regions have been categorized as North America, Western Europe, Eastern Europe, 
and Asia. Below table displays the geographic regions with corresponding countries.  
Table 7‒2: 
Region definitions 
Region 
Countries 
North America 
Canada, United States 
Western Europe 
Germany, Italy, United Kingdom 
Eastern Europe 
Czech Republic, Poland, Russia, Hungary 
Asia 
Australia, Japan 
The above regions will be the ones used when considering the region as factor in the efficacy 
analyses.  
3.9 
Coding dictionaries 
Medical history and AEs will be coded using the Medical Dictionary for Regulatory Activities 
(MedDRA®) version 19.0. Medications will be coded using the World Health Organization Drug 
Dictionary (WHO-DD) version MAR2021. Medical procedures will not be coded. 
To maintain consistency across studies in the bimekizumab development program, the dictionary 
versions will be held constant to support consistency of coding in the regulatory submissions. 
3.10 
Changes to protocol-defined analyses 
The following changes from the protocol will be considered: 
• The subgroup analysis on BASDAI will be performed on the categories: <4 vs. ≥4 rather than 
≤4 vs. >4. 
• Proportion of subjects with a decrease of HAQ-DI from Baseline of at least 0.35 (HAQ-DI 
responders) in those subjects with HAQ-DI ≥0.35 instead of >0.35. 
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• Proportion of PsAID-12 responders (decrease from Baseline in PsAID-12 total score ≥3) in 
subjects with PsAID-12 total score ≥3 at Baseline instead of >3 at Baseline. 
• An additional supportive analysis for primary endpoint based on the analysis of the 
individual components of ACR will be performed using the Reference-Based imputation 
method. 
• The main analyses of the secondary continuous variables included in the testing hierarchy 
will be performed using the Reference-Based imputation method. 
• Additional subgroup analyses will be performed for HAQ-DI responders at Week 16. 
• Additional subgroups based on the combination of concomitant methotrexate (MTX) and 
baseline conventional disease modifying antirheumatic drug (cDMARD). 
3.11 
Changes related to COVID-19 
The impact of the COVID-19 pandemic on study procedures/conduct as well as the efficacy and 
safety endpoints will be investigated, and additional analysis outputs will be provided as 
appropriate. These additional analyses were not planned as part of the original protocol as the 
pandemic was not ongoing at the time of protocol finalization. These additional analyses will 
include analyses by period of the COVID-19 pandemic (pre/during/post) as defined below: 
• Pre COVID-19 pandemic period: Period prior to COVID-19 pandemic start date defined as 
11-Mar-2020. 
• COVID-19 pandemic period: Period from 11-Mar-2020 though the COVID-19 pandemic end 
date which is currently not defined at the time of approval of the SAP. 
• Post COVID-19 pandemic period: Period after the declaration of the end of the pandemic 
The additional analyses are described in the following sections: 
• Subject disposition (Section 5.2) 
• Protocol deviations (Section 5.3) 
• Efficacy analyses related to the hierarchy endpoints (Section 8.1.4.8  and Section 8.2.3) 
• Adverse events (Section 10.2.5) 
4 
STATISTICAL/ANALYTICAL ISSUES 
4.1 
Adjustments for covariates 
The primary efficacy analysis will investigate the treatment effect, adjusting on the 2 
randomization stratification variables: 
• Region  
− North America, Western Europe, Eastern Europe, Asia  
or 
− North America, Eastern Europe, Western Europe + Asia if the percentage of randomized 
subjects is less than 10% in either of the Asia or Western Europe regions  
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• Prior TNFα inhibitor exposure (inadequate response to 1 prior TNFα inhibitor, inadequate 
response to 2 prior TNFα inhibitors, intolerance to TNFα inhibitors) 
When adjusting on these 2 variables, a statistical model might not converge (ie, in case the 
likelihood maximization algorithm failed to converge). In that case, the statistical model will be 
run after dropping stratification variables in their order of appearance, successively region (one 
first and the other after) and prior TNFα inhibitor exposure.  
In the event that a subject is stratified in the incorrect stratum (ie, the stratum recorded in the 
Interactive voice or web Response System (IXRS) differs from the actual stratum the subject 
belongs to), the actual stratum will be used for the analysis.  
The secondary analyses will be adjusted on the same categorical factors as the primary analysis. 
For continuous variables, Baseline value (of the variable of interest) will also be included as 
covariate where appropriate.  
4.2 
Handling of dropouts or missing data 
4.2.1 
Strategy for handling missing data for efficacy analyses 
Different approaches will be used to handle missing data including how the intercurrent events 
will be considered (Section 3.4).  
In this section, 3 terms will be defined for binary endpoints:  
• Non-composite binary endpoint: Binary endpoints derived based on 1 continuous 
measurement (eg, PASI90).  
• Composite binary endpoint: Binary endpoints derived based on several continuous 
measurements (eg, ACR50).  
• Composite continuous endpoint: Continuous endpoint derived based on several continuous 
measurements (eg, PASDAS).  
The table below summarizes all continuous endpoints (excluding composite continuous 
endpoints) along with their observed ranges and indicate whether they are represented by an 
integer value. These endpoints will be analyzed and / or used in the derivation of composite or 
non-composite endpoints: 
Table 7‒1: 
List of non-composite continuous efficacy endpoints 
Efficacy endpoint 
Minimum 
Maximum 
Integer 
Value 
BASDAI 
0 
10 
 
EQ-5D-3L dimension scores 
1 
3 
Yes 
EQ-5D-3L (VAS) 
0 
100 
Yes 
FACIT-Fatigue subscale score 
0 
52 
 
HAQ-DI 
0 
3 
 
hs-CRP 
LLOQ/2 where 
LLOQ=0.10mg/L 
No maximum 
 
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Efficacy endpoint 
Minimum 
Maximum 
Integer 
Value 
IGA 
0 
4 
Yes 
LDI 
0 
No maximum 
 
LEI 
0 
6 
 
Tender dactylitis count 
0 
20 
Yes 
mNAPSI 
0 
13 
Yes  
PASI 
0 
72 
 
PGA-Arthritis /PhGA-Arthritis 
0 
100 
Yes 
PGA-PsA / PhGA-PsA 
0 
100 
Yes 
PsAID-12 
0 
10 
 
PsAQoL 
0 
20 
 
PtAAP 
0 
100 
Yes 
SF-36a  
Physical Functioning (PF) 
Role Physical (RP) 
Bodily Pain (BP) 
General Health (GH) 
Vitaly (VT) 
Social Functioning (SF) 
Role Emotional (RE) 
Mental Health (MH) 
Physical component summary (PCS) 
Mental component summary (MCS) 
 
19.26 
21.23 
21.68 
18.95 
22.89 
17.23 
14.39 
11.63 
5.02 
-3.33 
 
57.54 
57.16 
62.00 
66.50 
70.42 
57.34 
56.17 
63.95 
79.78 
80.09 
 
SPARCC 
0 
16 
 
TJC / SJC 
0 
68/66 
 
WPAI-SHP 
0 
100 
 
BASDAI=Bath Ankylosing Spondylitis Disease Activity Index; EQ-5D-3L=Euro-Quality of Life 5-Dimensions 3 Level version; 
FACIT=Functional Assessment of Chronic Illness Therapy; HAQ-DI=Health Assessment Questionnaire – Disability Index; hs-
CRP=High sensitivity C-reactive protein; IGA=Investigator Global assessment; LDI=Leeds Dactylitis Index; LEI=Leeds 
Enthesitis Index; LLOQ=lower limit of quantification; mNAPSI=Modified Nail Psoriasis Severity Index; PASI=Psoriasis Area 
and Severity Index;  PGA-Arthritis=Patient’s global assessment of Arthritis; PGA-PsA=Patient’s Global assessment of 
Psoriatic Arthritis; PhGA-Arthritis=Physician’s Global Assessment of Arthritis;  PhGA-PsA=Physician’s Global 
Assessment of Psoriatic Arthritis;  PHQ-9=Patient Health Questionnaire-9; PSAID-12=Psoriatic Arthritis Impact of Disease-
12; PsAQoL=Psoriatic Arthritis Quality of Life; PtAAP=Patient’s Assessment of Arthritis Pain;  SF-36=Short-Form 36-item 
Health Survey; SJC= Swollen Joint Count; SPARCC= Spondyloarthritis Research Consortium of Canada ; TJC=Tender Joint 
Count; WPAI-SHP=Work Productivity and Activity Impairment questionnaire – Specific Health Problem 
a minimum and maximum of the norm-based scores – Normal range for SF-36 scores is 0-100 
4.2.1.1 
Primary analysis of binary endpoints that are part of the testing 
hierarchy (primary and secondary endpoints) 
All binary endpoints (composite & non-composite) are based on continuous component 
variables. 
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The primary analysis of binary efficacy endpoints that are part of the testing hierarchy is 
considered under a framework estimand in which missing data (due to study treatment 
discontinuation) is considered indicative of failed treatment and imputed to nonresponse. Further 
data missing while on treatment, or data observed while not on treatment, will also be imputed to 
nonresponse. 
This composite estimand approach to handling missing data which is the primary analysis 
method for binary efficacy endpoints is similar to the non-responder imputation (NRI) method.  
 
4.2.1.2 
Primary analysis of continuous endpoints that are part of the testing 
hierarchy (secondary endpoints) 
For continuous efficacy endpoints that are part of the testing hierarchy, the primary analysis 
method is based on the hypothetical estimand approach as follows:  
• If subjects have missing data regardless whether the missing data is preceded by an IE, then 
missing data will be imputed based on the MI-MCMC/Reference-Based imputation method 
(Section 4.2.2.3 ). 
• If subjects have non-missing data after IE, then such data will be set to missing prior to 
running MI. 
4.2.1.3 
Supportive analyses of primary efficacy endpoint 
For the primary endpoint, which is a composite binary endpoint, several supportive analyses 
assuming different missing data mechanisms will be conducted: 
• The modified composite estimand approach: the IE is changed from all treatment 
discontinuation to discontinuation of treatment due to AE or lack of efficacy. The same as the 
primary method will be used with the difference that only data after discontinuation due to 
AE or lack of efficacy is set to nonresponse. All other imputed data will be used.  
• For the analysis of individual components of ACR, under the hypothetical estimand approach 
using the Reference-Based imputation method (Section 4.2.2.3).  
• The tipping point approach implemented within the MI framework, but only if the primary 
endpoint analysis result is statistically significant at alpha=0.05. (Section 4.2.2.4).  
• The treatment policy strategy (Section 4.2.2.5). 
• The observed case (OC) analysis that will only include the observed data.  For subjects who 
had treatment discontinuation, only observed data prior to treatment discontinuation date will 
be analyzed.  For visits with missing data without treatment discontinuation, the data will 
remain missing.  For observed data after treatment discontinuation, the corresponding visit 
data and subsequent visit data will be treated as missing. 
4.2.1.4 
Supportive analyses of endpoints that are part of the testing 
hierarchy (secondary endpoints) 
The following supportive analysis methods will be performed for the secondary and the other 
efficacy variables that are part of the testing hierarchy:  
For binary endpoints:  
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• The modified composite estimand approach: the IE is changed from all treatment 
discontinuation to discontinuation of treatment due to AE or lack of efficacy. For composite 
or non-composite binary endpoints, the standard MI approach) will be implemented 
(similarly as in Section 4.2.1.3) on the raw continuous score(s) (eg, PASI for the PASI90 
endpoint) before deriving the binary endpoint based on the imputed score(s).  
• The OC analysis.  
For continuous endpoints: 
• The hypothetical estimand approach:  
− If subjects have missing data regardless whether the missing data is preceded by an IE, 
then missing data will be imputed based on the MI-MCMC/Monotone regression method 
(Section 4.2.2.2). 
− If subjects have non-missing data after IE, then such data will be set to missing prior to 
running MI. 
• The OC analysis.  
4.2.1.5 
Analyses of secondary endpoints that are not part of the testing 
hierarchy and other efficacy endpoints 
The other efficacy endpoints including the secondary efficacy endpoints that are not part of the 
testing hierarchy will be analyzed as the secondary efficacy endpoints (with the exclusion of the 
MI-MCMC/reference-based imputation method for continuous variables) but with no designated 
priority. 
For a combined binary endpoint based on the combination of a non-composite and a composite 
binary endpoint (as with the ACR50 and PASI90 combined endpoint), each binary endpoint will 
be derived independently, as described above, before deriving the combined endpoint.  
 
4.2.1.6 
Summary table of missing data handling approaches for efficacy 
analyses 
The below table summarizes which missing data handling approaches will be used for each type 
of efficacy endpoint.  
Table 7‒2: 
Missing data handling approaches for efficacy endpoints 
Efficacy Endpoint 
Priority 
Variable Type 
Missing data handling approach 
Composite 
estimand 
(NRI) 
Modified 
Composite 
estimand 
(MI) 
Hypothetical 
estimand 
(MI) 
 
Hypothetical 
estimand 
Reference-
Based 
(MI) 
OC 
Tipping 
Point 
analysis 
(MI) 
Treatment 
Policy 
(MI) 
Primary endpoints 
Composite 
Binary 
P 
 Sa 
 
 
S 
Sa 
Sa 
Binary  
P 
Sa 
 
 
S 
 
 
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Efficacy Endpoint 
Priority 
Variable Type 
Missing data handling approach 
Composite 
estimand 
(NRI) 
Modified 
Composite 
estimand 
(MI) 
Hypothetical 
estimand 
(MI) 
 
Hypothetical 
estimand 
Reference-
Based 
(MI) 
OC 
Tipping 
Point 
analysis 
(MI) 
Treatment 
Policy 
(MI) 
Secondary 
endpoints included 
in the testing 
hierarchy 
Continuous 
 
 
S 
P 
S 
 
 
Other Secondary 
endpoints (not 
included in the 
testing hierarchy 
Binary 
X 
Xa 
 
 
X 
 
 
Continuous 
 
 
X 
 
X 
 
 
Other endpoints 
Binary  
X 
Xa,b 
 
 
X 
 
 
Continuous 
 
 
X b 
x d  
X 
 
 
Categorical 
X c 
X c 
 
 
X 
 
 
P=Primary method, S=Supportive method, X=Method to be used (no priority designated) MI=multiple imputation, NRI=non-
responder imputation, OC=observed cases. 
Note: Composite estimand (NRI) refers to the approach in which data preceded by the intercurrent event of study treatment 
discontinuation are imputed as nonresponse, and other missing data are also imputed as nonresponse. 
Note: Modified Composite Estimand (MI) refers to the approach in which data preceded by the intercurrent event of study 
treatment discontinuation due to AE or lack of efficacy are imputed as nonresponse (or worst category for categorical variable), 
and other missing data are imputed via a MI model.  
Note: Hypothetical Estimand (MI) refers to the approach where outcomes for subjects without an intercurrent event of study 
treatment discontinuation are as observed, and outcomes for subjects with the intercurrent event are imputed via a MI model. 
Note: Referenced Based imputation refers to the approach in which it is assumed that the statistical behavior of the bimekizumab 
and placebo-treated subjects after discontinuing study medication becomes that of the placebo-treated subjects that remain in the 
study. 
a  Imputation method is applied on continuous data, and binary variable is derived from the continuous variable based on 
complete imputed data set. 
b MI will be used to provide point estimates at each timepoint only.  
c Missing data to be imputed to the worst category. 
d For ACR components analysis at Week 16. 
 
4.2.2 
Methods for handling missing data for efficacy analyses 
The sections below describe the method to be used for missing efficacy data handling. 
Note: For a specific endpoint, if analyzed subjects in a one or several treatment groups have no 
missing data, then analysis of observed cases will be performed in the concerned treatment 
group(s). 
4.2.2.1 
Non-responder imputation  
For binary endpoints, the non-responder imputation (NRI) analysis, also described above as the 
primary composite estimand, will consider the following subjects as “non-responders” for the 
timepoint of interest: 
• Subjects with missing data at the timepoint of interest. In the case of ACR50, nonresponse is 
imputed if ACR50 cannot be derived (ie, derived as “missing”) based on available ACR 
components. (Section 8.1.1). 
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• Subjects remaining in the study at the timepoint of interest but discontinuing study treatment 
before the timepoint of interest (data after IE). 
• Subjects with missing Baseline value (for composite or non-composite binary variables based 
on change(s) from Baseline of continuous endpoint(s)). 
4.2.2.2 
MI – MCMC/Monotone Regression 
In instances where MI is used, the missing value is replaced by a set of plausible values, where 
each value is a Bayesian draw from the conditional distribution of the missing data given the 
observed data. Intermittent missing data will be imputed using the MCMC method, followed by 
regression for monotone missing data (called “MI-MCMC/Monotone regression” method in this 
SAP). The MI procedures planned for efficacy analyses are based on an assumption of data 
missing at random (MAR). 
 
This section describes the algorithms to be implemented for the MI – MCMC/Monotone 
Regression procedures for non-composite binary endpoints, composite binary endpoints, and 
continuous endpoints. These descriptions focus on the MI procedure itself and do not specifically 
account for dealing with intercurrent events which is addressed in Section 4.2.1.  
4.2.2.2.1 
Non-Composite binary endpoints 
For non-composite binary endpoints, the MI method will be applied as follows based on raw 
values: 
• Step 1: Imputation of missing data using MI: 
Create datasets, one for each treatment group, of subjects with observed values and missing 
values (needing estimation by MI). For the imputation step, missing values will be separated into 
2 categories: intermittent missing values (ie, missing values for a given subject that has available 
data before and after the missing timepoint, including missing value at Baseline) and monotone 
missing values (ie, where all subject data is missing after a given time point). Datasets should be 
designed in a horizontal structure meaning that each subject should be present in a single 
observation, with a set of values, one for each scheduled visit where the endpoint is supposed to 
be collected according to the protocol (this excludes the unscheduled visits).  
Datasets should also be sorted by subject number before proceeding with the MI process.  
a. For the intermittent missing values, the missing value in each dataset will be filled in using 
the Markov-Chain Monte Carlo (MCMC) method with multiple chains, monotone missing 
data imputing pattern, and non-informative priors for all parameters. Unless specified 
differently, the first 200 iterations will not be used (the ‘burn-in’ option). A total of 100 sets 
of imputations will be performed. The seed used for these imputations will be 2017 and all 
other MI procedures described in this SAP will use this same seed as well.  The procedure 
will be performed for each treatment group separately. 
The resulting 100 imputed data sets will have a monotone missing pattern and will be imputed 
using a method for monotone missingness: 
b. For monotone missing data, one monotone regression will be used to impute missing data. 
A separate regression model is estimated for each variable with missing values (ie, 
measurement at each time point). Based on the resulting model, a new regression model is 
then drawn and is used to impute the missing values for the variable. Since the data set has a 
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monotone missing data pattern, the process is repeated sequentially for variables with 
missing values. The procedure will be based on the 100 imputed datasets generated from the 
MCMC procedure and will be performed for each treatment group separately by imputation.  
The SAS® PROC MI procedure will be used for the imputation.  
In both cases, the imputation model will include the randomization strata as stratification 
variables (region and prior TNFα inhibitor exposure), the value at Baseline and at each post-
Baseline visit (up to the week of interest). The imputation model based on the MCMC method 
will only allow joint multivariate normal variables. For the MCMC method (when imputing 
intermittent missing values), randomization strata will be re-coded as indicator variables, and 
will be always specified in the following order if they are retained in the model: 
− North America region (1 for North America, 0 otherwise) 
− Western Europe region (1 for Western Europe, 0 otherwise) 
− Eastern Europe region (1 for Eastern Europe, 0 otherwise)  
− Prior TNFα 1 (1 for inadequate response to 1 prior TNFα inhibitor) 
− Prior TNFα 2 (1 for inadequate response to 2 prior or more TNFα inhibitors) 
No variable needs to be created for the 3rd category of prior TNFα inhibitors (intolerance 
to TNFα inhibitors) or the 4th region (Asia) which is covered when all above variables are 
“0”.    
The randomization strata (region and prior TNFα inhibitor exposure) may be dropped from the 
imputation model to facilitate model convergence if required (this will be the case for all 
imputation models) as described below: 
− If the MI fails to converge when adjusting on the stratification variables specified above, 
or if the percentage of randomized subjects is less than 10% in either of the Asia or 
Western Europe regions, then the Western Europe and Asia region will be combined and 
the binary variables for region that will be left in the MI will then be for North America 
and Eastern Europe regions.  
− If after doing that, the MI still fails to converge then all region factors will be removed 
from the MI.  
− If the MI still does not converge after dropping the regions, the remaining stratification 
variables (Prior TNFα 2,1) will also be removed. 
− If a variable is dropped in order to allow convergence for one model in the study, that 
variable does not have to be dropped from other models in the study of the model 
converges without dropping the variable. That is, model convergence should be evaluated 
for each efficacy table independently. Furthermore, this means that a table based on a 
single timepoint may have different variables in the imputation model than a separate by-
visit table for the same variable. 
The post-Baseline values will need to be specified in chronological order after the Baseline value 
in the imputation model so that the SAS® PROC MI imputes variables from left to right (ie, the 
Week 4 value will be first imputed using regression based on Baseline value, and then the Week 
8 value will be imputed using regression based on Baseline and Week 4 values, etc.). The 
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resulting datasets for each treatment arm will be combined into 1 complete dataset containing 
100 times the number of subjects analyzed.  
Note: When imputing missing hs-CRP values, missing values due to values below LLOQ (0.10 
mg/L) will be replaced by the midpoint value between 0 and LLOQ prior to running MI. 
• Step 2: Standard rounding rules will be applied to the imputed values after each SAS® 
PROC MI. If an imputed value falls outside of the range for the given variable (as listed in 
Table 7‒1), the value will be updated to be within the predefined range. For example, the 
imputed value for PASI will be updated to 0 or 72 in the case of an imputed value less than 0 
or greater than 72, respectively. For endpoints that can take only integer values (eg,: IGA as 
listed in Table 7‒1), the imputed values will be rounded to the closest integer after each 
SAS® PROC MI. 
Note: For hs-CRP, the lower limit used the midpoint value between 0 and LLOQ. For some 
parameters, there is not necessarily an upper limit to the imputed value (ie, LDI) 
• Step 3: On the dataset obtained from Step 2, the binary responder variable will be derived. In 
practice, the value at the week of interest (eg, Week 16) in the imputed data sets will be used 
to categorize the subject as a responder or not.  If subjects have an IE, then the endpoint at all 
subsequent visits will be set to “nonresponse” and the following will be performed: 
− When date of visit is available: by comparing IE date vs. date of visit 
− When the date of visit is missing in case of fully imputed data at a visit: by comparing the 
next visit number after the visit where the last study medication occurs vs. the visit 
number where data are imputed 
• Step 4: At each timepoint the (unadjusted) proportion of responders will be calculated by 
treatment group from the imputed datasets using SAS® PROC FREQ. 
• Step 5: (For primary and secondary efficacy endpoints only): For each value of the 
imputation number from 1 to 100, the adjusted proportion of responders will be analyzed 
using a logistic regression model with a fixed effect for treatment. The suitability of 
including region and prior TNFα inhibitor exposure as fixed effects will be assessed using 
goodness-of-fit tests (Deviance and Pearson’s and Hosmer-Lemeshow) and added, if 
appropriate, if it allows model convergence. Covariates kept in the modelling should also be 
the same as the ones previously used for the MI. Comparisons will be made using 2-sided 
Wald test level of significance of 5%. The results obtained from the 100 logistic regression 
analyses (ie, the adjusted proportion of responders for each treatment group, the OR and the 
difference of proportions for the BKZ-placebo comparison and corresponding 95% CI) will 
be combined for overall inference using Rubin’s rules, which account for the uncertainty 
associated with the imputed values (Rubin, 1987). This will be done using SAS® PROC 
MIANALYZE.  
4.2.2.2.2 
Composite binary endpoints 
For composite binary endpoints, the MI method will be applied as follows: 
• Step1: The MCMC/monotone regression approach described above in Step 1 for non-
composite binary endpoints will be performed separately for each individual component 
variable.   
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• Step 2: The same rounding rules described in Step 2 above for non-composite binary 
endpoints will be performed for each component. 
• Step 3: Based on the multiple imputed data sets obtained for each component, the binary 
response will be derived as follows: 
− The dataset obtained for each component will be merged by imputation number and 
subject number 
− On the dataset obtained, the binary endpoint will be derived for each subject/visit based 
on the component values. 
− If subjects have an IE, then the endpoint at all subsequent visits (from the day after the 
intercurrent event date, whether the data were observed or not) will be set to “non-
response”. 
• Steps 4 and 5: Same as Steps 4 and 5 above for non-composite binary endpoints (Section 
4.2.2.2.1).   
For the primary endpoint, the ‘burn-in’ option in SAS® PROC MI may be set higher than the 
default value. The goodness-of-fit tests to assess convergence of the MCMC will be provided in 
a SAS® output.  
4.2.2.2.3 
Calculation of adjusted responder rates, odds ratio and CIs for 
binary endpoints. 
Estimates of the adjusted responder rates for each treatment group and the associated standard 
errors are obtained from the logistic regression in Step 5 on the logit scale and as such are 
assumed to follow a normal distribution. These estimates will be combined using Rubin’s rules 
and the combined estimates and associated SEs will be used to construct 95% CIs on the logit 
scale. The combined estimates and 95% CIs on the logit scale will be back transformed using the 
inverse logit link function to obtain the adjusted responder rates (%) and associated 95% CIs. 
Some key points to consider relative to the calculation of the odds ratios and corresponding 
confidence intervals. As the estimates of the odds ratios from the logistic regression model in 
step 5 follow a lognormal distribution, a log transformation is needed to normalize these 100 
odd-ratio estimates since the procedures for combining results from multiple imputed datasets 
are based on the assumption that the statistics estimated from each imputed dataset are normally 
distributed. Therefore, the log of the odds ratio estimates from the logistic regression model are 
used when combining into a single inference (step 3). Additionally, the standard errors (SE) for 
the odds ratios are transformed as follows: 
𝑆𝐸= log(𝑈𝐶𝐿) −log(𝐿𝐶𝐿)
2𝑍𝛼/2
 
where UCL and LCL are the upper and lower confidence limit, respectively, for the CI of the 
odds ratio from the logistic regression model, and 𝑍𝛼/2 is the relevant critical value from the 
standard normal distribution (1.96 for a 95% CI). The estimates of the log odds ratio for BKZ 
relative to placebo and the corresponding upper and lower confidence limits will be provided. 
The odds ratio will be then estimated by exponentiating the estimate of the log odds ratio. The 
odds ratio and the confidence limits of the odds ratio will be estimated as follows: 
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𝑂𝑅= exp(𝐿𝑜𝑔 𝑜𝑑𝑑𝑠 𝑟𝑎𝑡𝑖𝑜 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒 ) 
𝐿𝐶𝐿= 𝑂𝑅∗exp(−𝑆𝐸∗𝑍𝛼/2 ) 
𝑈𝐶𝐿= 𝑂𝑅∗exp(𝑆𝐸∗𝑍𝛼/2 ) 
where OR is the back-transformed estimate of the odds ratio just described, SE is the standard 
error of the log odds ratio and 𝑍𝛼/2 is the relevant critical value from the standard normal 
distribution (1.96 for a 95% CI). These calculations will be done such that odds ratios and 
corresponding CIs are calculated for the odds ratio of BKZ versus placebo. 
In addition to calculating the odds ratio, associated CIs, and p-values for the comparisons of 
BKZ vs. placebo, the estimated proportion of responders (ie, estimated responder rate) and the 
difference in the proportion of responders between BKZ and placebo will be estimated, along 
with 2-sided 95% CIs. The creation of the estimates of this difference will be completed using 
the process detailed below: 
1. Use the logistic regression model to calculate: 
Least squares mean (LSM) estimates of the log odds of BKZ (GB) and placebo (GP), as well 
as their corresponding standard errors (SB and SP, respectively). 
Standard error of the LSM estimate of the log odds ratio (SR) 
2. Compute estimates for predicted proportions using the following transformations: 
PB = exp(GB)/(1 + exp(GB)) 
PP = exp(GP)/(1 + exp(GP)) 
The difference in proportions is then given by: 
D = PB – PP 
3. Estimate the standard error of D by: 
SD = sqrt[PB2(1-PB)2SB2 + PP2(1-PP)2SP2 + PB(1-PB)PP(1-PP)SR2 – PB(1-PB)PP(1-PP)(SB2 + 
SP2]) 
The MI/MCMC monotone regression method, as previously outlined, will be used to account for 
missing values. The calculation steps described above will be based on the results provided from 
the logistic regression model of the multiple imputed datasets. An estimate for the difference in 
proportions, D, and corresponding standard error, SD, will be computed for each of these 
datasets. The results from these analyses will be combined into a single estimate of the difference 
in predicted proportion of response and a 2-sided 95% CI interval using SAS PROC 
MIANALYZE. 
4.2.2.2.4 
Continuous efficacy endpoints 
For secondary and other continuous efficacy endpoints, the same methods as the ones described 
above for the non-composite binary endpoints will apply based on the values at the timepoint(s) 
of interest, with the following differences:  
• Step 1: The same imputation procedure as the described in step 1 for the non-composite 
binary endpoints will be used.  
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• Step 2: The same rounding rules described in step 2 above for non-composite binary 
endpoints will be performed.   
• Step 3: On the dataset obtained with the imputation number from 1 to 100; change from 
Baseline will be derived. Simple means and standard errors will be calculated using Rubin’s 
rules (via SAS® PROC MIANALYZE) for each timepoint(s) of interest. For calculation of 
other descriptive statistics such as the median, min and max, Rubin's rules do not apply. MI 
estimates will be computed by simply averaging the estimates from the multiple repetitions 
of the imputation algorithm. For CRP data (that will be presented using the geometric mean 
and corresponding 95% CI, arithmetic mean, median, Q1, Q3, minimum and maximum). The 
change from Baseline will be expressed as the ratio to Baseline (value at the visit divided by 
value at Baseline) in the by-visit summaries. The following approach will be applied: 
− Following the MI procedure, the ratio to Baseline will be calculated for any of the 
imputed values  
− The natural logarithm of the absolute values and of the ratios to Baseline will be 
calculated 
− The logged values will be summarized by treatment, visit and imputation  
− The datasets will be combined using PROC MIANALYZE in order to get the mean from 
the absolute values and ratios to Baseline across imputations 
− The estimates of the mean will be back transformed to obtain the geometric mean on the 
original scale 
− For the median, Q1, Q3, minimum and maximum the procedure outlined above for the 
other endpoints will be followed 
• Step 4: (for primary and secondary efficacy variables): For each value of the imputation 
number from 1 to 100, the change from Baseline will be analyzed using an ANCOVA model 
with treatment group, region, and prior TNFα inhibitor exposure as fixed effects and the 
Baseline value as covariate. The results obtained from the 100 ANCOVA analyses (ie, the 
LSM for the treatment difference and the 95% CI for the contrasts) will be combined using 
Rubin’s rules (via SAS® PROC MIANALYZE). 
For composite continuous endpoints, the MI will be applied on each component the same way as 
for composite binary endpoint. The datasets obtained for each component will be merged by 
imputation number and subject number. On the dataset obtained, the endpoint will be derived for 
each subject/visit based on the component values. The endpoint obtained will be analyzed as 
above. 
4.2.2.2.5 
Ordinal efficacy endpoints 
For ordinal efficacy endpoints, the MI method will be applied as for the continuous efficacy 
endpoints with the following exceptions:  
• After the imputation of the intermittent and monotone missing data , the rounding rules will 
be performed to align the data with the possible responses for the respective endpoint (eg, If 
the variable can take the value 1, 2 or 3, the imputed values will be rounded to the closest 
possible value).   
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• If the ordinal efficacy endpoint is used to derive a binary endpoint, the same analysis strategy 
as described above for the binary endpoints will be used.    
• If the ordinal efficacy endpoint is not used to derive a binary endpoint, the unadjusted 
proportions of subject by categories will be presented. 
• If subjects have an IE, then the ordinal endpoint at all subsequent visits (from the day after 
the IE date, whether the data were observed or not) will be set to the value used for the worst 
category. 
4.2.2.3 
MI – MCMC/Reference-Based imputation 
For the primary analysis of the secondary continuous efficacy variable included in the testing 
hierarchy and the individual components of the ACR response, the Reference-Based multiple 
imputation method will be used. In this imputation method, the missing data will be imputed 
based on data from the placebo group only (Mallinckrodt, 2013).  
Reference-Based MI assumes that the statistical behavior of the BKZ and placebo-treated 
subjects after discontinuing study medication becomes that of the placebo-treated subjects. All 
time points after study treatment discontinuation for BKZ and placebo groups will be considered 
missing. MIs are used to replace missing outcomes for BKZ- and placebo-treated subjects who 
discontinued using multiple draws from the posterior predictive distribution estimated from the 
placebo arm.  
Note: SAS 9.4 may be used for this analysis where equivalent steps to those outlined below will 
be used to perform the imputation. 
In the case of continuous endpoints, the procedure will be implemented as follows on the raw 
values: 
1. Data will be processed sequentially, one timepoint (visit) at a time, by repeatedly calling 
SAS® PROC MI to impute missing outcome data at visits t=1,…, Week 16 (Week 16 being 
the time point of interest) using data from the placebo-treated subjects arm only. 
a. Initialization. Set t=1 (Baseline visit). Create a dataset combining all records from all 
subjects with columns for covariates (prior TNFα exposure and region) and outcome at 
Baseline. Impute missing values at Baseline using prior TNFα exposure at Baseline and 
region. 
b. Iteration. Set t=t+1. Create a dataset combining records from BKZ- (subjects with missing 
data at visit t) and all placebo-treated subjects with columns for covariates (prior TNFα 
exposure and region) and outcomes at visits 1 to t. In this dataset, outcomes for BKZ-
randomized subjects are missing at visit t and observed or previously imputed at visits 1 to t-
1. Outcomes for placebo-treated subjects are observed or missing at visit t and observed or 
previously imputed at visits 1 to t-1. The outcomes should be sorted in chronological order in 
the model.  
c. Imputation. Impute missing values for visit t using previous outcomes for visits 1 to t-1, prior 
use of TNFα inhibitor, and region. Note that only placebo data will be used to estimate the 
imputation model since no outcome is available for BKZ- treated subjects at visit t. As a 
consequence, the input dataset should include all subjects from placebo but only subjects 
from the BKZ arm that have values at timepoint t missing.  
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d. Repeat steps 1b-1c for all timepoints, 100 times with different seed values (seeds ranging 
from 201 to 300) to create 100 imputed complete datasets. Subjects whose missing values 
were imputed in the last PROC MI call will be included in the input dataset for the next 
PROC MI call. Standard rounding rules will be applied to the imputed values. If the MI 
procedure yields a value outside of the pre-defined range for the given variable, the value 
will be updated to be within the predefined range of values for the endpoint of interest. For 
example, the imputed value for TJC will be updated to 0 or 68 in the case of an imputed 
value less than 0 or greater than 68, respectively.  
2. The analysis will be done on the change from Baseline, and the model will be an ANCOVA 
model with treatment group, region, and prior TNFα inhibitor exposure classification as fixed 
effects and the Baseline value as covariate.  
For generation of summary statistics, the 100 imputed datasets will be combined, and simple 
means and standard errors will be calculated using Rubin’s rules (via SAS® PROC 
MIANALYZE). For calculation of other descriptive statistics (median, Q1, Q3, minimum 
and maximum), Rubin’s rules do not apply. Multiple imputation estimates will be computed 
by calculating arithmetic means of the estimates from the multiple repetitions of the 
imputation algorithm. Thus, for median, Q1, Q3, minimum and maximum the following 
approach will apply: 
• The data will be summarized by treatment, visit and imputation and the summary 
statistics will be computed.  
• Results will be summarized by taking the mean value of each summary statistic at 
each visit across all imputations.  
• The number of decimal places will remain the same as the original for display 
purposes (ie, if the mean was presented to 1 decimal place, the mean of the means 
will also be presented to 1 decimal place). 
3. The results obtained from the 100 ANCOVA analyses in Step 4 (i.e. the Least Square Means 
for the treatment difference and the 95% CI for the contrasts) will be combined with Rubin’s 
rules.  
4.2.2.4 
Tipping Point analysis 
Tipping point analyses will also be implemented as a supportive analysis for the primary efficacy 
endpoint. 
The objective of the tipping point analyses is to identify assumptions about the missing data 
under which the conclusions from the main analysis change (ie, under which there is no longer 
evidence of a treatment effect. These tipping point analyses will only be performed if the primary 
efficacy analysis results in a statistically significant treatment effect (p<0.05). 
As a first step, the worst-case scenario will be evaluated. Specifically, all BKZ-randomized 
subjects with a missing ACR50 at Week 16 (or non-missing ACR50 after study treatment 
discontinuation) will be imputed as non-responders, while all placebo-randomized subjects with 
a missing ACR50 at Week 16 will be imputed as responders. While there is little justification for 
such an approach, it makes the most putative assumption possible against a BKZ treatment 
effect. After applying this imputation approach, a logistic regression model consistent with the 
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one described for the primary analysis will be applied. If the p-value for the odds ratio of BKZ 
versus placebo is less than 0.05, then no further tipping point analyses are needed. 
If this analysis based on the worst-case scenario results in a p-value greater than 0.05, then 
additional tipping point analyses will be performed. In practice, it implies different delta 
adjustments will be made to the assumed responses on the missing data (where missing values 
include observations after the intercurrent event date and any other missing values) in each 
treatment group independently with various degrees of plausibility with the goal to find for each 
treatment group the “tipping point” that will significantly reverse the primary result which 
yielded a p-value less than 0.05. These delta adjustments will be done on each component of 
ACR50 as follows: 
• Step 1: The same MCMC method described in Section 4.2.2.2 will be implemented for non-
monotone (intermittent) missing pattern values, using the same imputation model. This will 
be based on 100 imputations. 
• Step 2: Based on the dataset obtained in Step 1, a monotone regression model will be applied 
(using the same imputation model as in Step 1) and as described in Section 4.2.2.2 . This will 
be based on 1 imputation.  
• Step 3: Imputed values will be shifted using a delta adjustment independently in each 
treatment group.   
Once defined, the same delta adjustment value will be applied on the imputed values for the 
Week 16 visit only. The selected scenario will assume that subjects randomized to BKZ and who 
have missing data have a lower probability of response compared to subjects randomized to 
placebo with missing data. 
- For ACR components for which high scores are associated with a less favorable outcome, it 
will mean that:  
▪ A positive shift is applied to the imputed value for subjects randomized to BKZ in order 
to increase the imputed value. 
▪ A negative shift is applied to the imputed value for subjects randomized to placebo in 
order to decrease the imputed value. 
A set of possible values will be first pre-defined for the delta parameter as follows: 
-  For all ACR components, the value of the initial delta parameter will be equivalent to a 
specific percentage of the possible range of each component (ie, 5%). For hs-CRP, the range 
will be based on the log-transformed values at Week 16. The delta parameters for each 
endpoint are listed in the Table 7‒3 .  
Table 7‒3: 
Tipping point analysis: Delta parameter for each ACR component  
ACR component1 
Range 
Delta 
SJC 
0-66 
3.3 
TJC 
0-68 
3.4 
HAQ-DI 
0-3 
0.15 
PtAAP, PhGA-PsA, PGA-PsA 
0-100 
5 
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ACR component1 
Range 
Delta 
hs-CRP2 
Observed range  
of the loge transformed values for all subjects 
at Week 16 
 
5% of the observed 
range 
1The shifted imputed value should not exceed the range for the ACR component. 
2The delta adjustment will be applied on the loge transformed imputed and observed values which will then be exponentiated 
prior to deriving endpoint.   
• Step 4: Standard rounding rules will be applied to the imputed values. If the SAS® PROC 
MI yields a value outside of the range for the given component, the value will be updated 
after the imputation has been performed to be within the predefined range.  
• Step 5: Repeat steps 1 to 4 for each ACR component. The composite binary endpoint 
(ACR50) will then be derived based on the multiple shifted imputed data sets obtained for 
each component. 
• Step 6: Additionally, as the primary endpoint is derived using NRI, subjects randomized to 
BKZ with missing data (where missing values include observations after the IE date and any 
other missing values) should be set to non-response, after applying the delta adjustment 
outlined in Step 3 above. This ensures subjects randomized to BKZ do not have a higher 
probability of response in the tipping point analyses compared to the primary analysis (ie, a 
subject randomized to BKZ who is non-responder in the primary analysis cannot become a 
responder in the tipping point analyses). 
• Step 7: In the data obtained, for each value of the imputation number, ACR50 will be 
analyzed using a logistic regression model with factors of treatment group, region, and prior 
TNFα inhibitor exposure at Baseline as fixed effects. 
• Step 8: The results obtained from the 100 logistic regression analyses in Step 6 will be 
combined for overall inference using Rubin’s rules, and the results obtained for each shift 
parameter will be presented in a single table.  
• Step 9: Step 3 to Step 8 will be repeated so that, at each iteration, missing values are adjusted 
with a larger shift than at the previous iteration. Depending on the results obtained, delta 
parameters with more granularity (eg, 2 times, 3 times the initial delta) will be investigated. 
The process will go on until the p-value for the odds ratio between BKZ and placebo is no 
longer statistically significant (ie, ≥ 0.05). The odds ratio, 95% CI, and p-values obtained for 
each value of delta will be combined in one single table.  
4.2.2.5 
Treatment Policy Strategy  
Another supportive analysis will be performed on the primary efficacy endpoint to address 
intercurrent events.  
The treatment policy strategy will include all available data observed at the week of interest 
(Week 16) regardless of the occurrence of intercurrent events. This means the analysis includes 
on- and off-treatment values collected after subjects prematurely discontinued study treatment 
but agreed to remain on the study and continued to attend visits and provide assessments at those 
visits. Those observed values will be analyzed according to the subject’s randomized treatment. 
Subjects for whom efficacy data cannot be obtained at the week of interest, despite attempts to 
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retain them in the study, will have their data imputed using MI-MCMC/monotone regression 
(Section 4.2.2.2).  
4.2.3 
Handling of missing data for AE 
For analyses of AEs, a complete date must be established to correctly identify the AE as 
occurring during treatment or not. For purposes of imputing missing components of partially 
reported start and stop dates for AEs, the algorithms listed below will be followed. In the event 
of ambiguity or incomplete data which makes it impossible to determine whether the AE was 
treatment emergent, the AE will be considered treatment emergent. 
Although the algorithms for treatment-emergence depend on the onset date, imputation rules are 
provided for stop date as well, as these may be needed for certain statistical analyses, such as an 
analyses of AE prevalence or AE duration. 
Start and stop dates of AEs will be displayed as reported in the subject data listings (ie, no 
imputed values will be displayed in data listings). 
Imputation of Partial AE Start Dates 
• If only the month and year are specified: 
− if the month and year of first dose of IMP is not the same as the month and year of the 
start date, then use the 1st of the month, 
− if the month and year of first dose of IMP is the same as the month and year of the start 
date, then use the date of first dose of IMP, 
• If only the year is specified: 
− if the year of first dose is not the same as the year of the start date, then use January 1 of 
the year of the start date. 
− if the year of first dose is the same as the year of the start date, then use the date of first 
dose. 
• If the date is completely unknown: 
− use the date of first dose of IMP if the stop date is unknown or not prior to the onset date.  
 
Imputation of Partial Stop Dates: 
• if only the month and year are specified, then use the last day of the month 
• if only the year is specified, then use December 31st of that year 
• if the stop date is completely unknown, then do not impute the stop date 
If the imputed stop date is prior to the imputed start date:  
• For missing start day and start month:  
− if the year of start date is the same as the year of first dose and the imputed stop date is on 
or after the date of first dose then set the start date to the date of first dose 
− otherwise set to the 1st January of the year of the start date 
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• For missing start day only 
− if the month and year of the start date is the same as the month and year of first dose and 
the imputed stop date is on or after the date of first dose, then set the start date to the date 
of first dose 
− if the month and year of the start date is the same as the month and year of first dose and 
the imputed stop date is before the date of first dose, then set the start date to the 1st of 
that month 
In the event of ambiguity or incomplete data which makes it impossible to determine whether an 
AE is treatment emergent, the AE will be considered as treatment emergent. 
Other imputations 
In addition, the following will apply for presenting AE in summary tables: 
• if the intensity of an AE is unknown, it will be considered as severe.  
• if the relationship to study drug is missing, it will be considered as related.  
For missing seriousness, no imputation rule will be applied. 
4.2.4 
Handling of missing data for prior and concomitant medications 
Any medications with incomplete start and end dates/times will be handled according to the 
following rules for classification as prior and concomitant and for the calculation of relative 
study days. In the event of ambiguity or incomplete data which makes it impossible to determine 
whether a medication was concomitant or not, the medication will be considered as concomitant. 
Such imputations will only be performed for these classifications and calculations; in the listings 
all data will be shown as recorded on the electronic case report form (eCRF). 
Imputation of Partial Start Dates 
• If only the month and year are specified: 
− if the month and year of first dose of IMP is not the same as the month and year of the 
start date, then use the 1st of the month. 
− if the month and year of first dose of IMP is the same as the month and year of the start, 
then use the date of first dose of IMP. 
• If only the year is specified: 
− if the year of first dose of IMP is not the same as the year of the start date, then use the 
1st of January of the year of the start date. 
− if the year of first dose of IMP is the same as the year of the start date, then use the date 
of first dose of IMP. 
• If the start date is completely unknown: 
−  if the stop date is unknown or not prior to the date of first dose of IMP, then use the date 
of first dose of IMP. 
− if the stop date is prior to the date of first dose of IMP, then set the start date to the 1st of 
January of the year of the end date. 
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Imputation of Partial Stop Dates: 
• If only the month and year are specified, then use the last day of the month, 
• If only the year is specified, then use December 31st of that year. 
• If the stop date is completely unknown, do not impute the stop date. There will be no 
imputation of any other missing data. 
If the imputed stop date is prior to the imputed start date:  
• For missing start day and start month:  
− if the year of start date is the same as the year of first dose and the imputed stop date is on 
or after the date of first dose, then set the start date to the date of first dose 
− otherwise set to the 1st January of the year of the start date 
• For missing start day only 
− if the month and year of the start date is the same as the month and year of first dose and 
the imputed stop date is on or after the date of first dose, then set the start date to the date 
of first dose 
− if the month and year of the start date is the same as the month and year of first dose and 
the imputed stop date is before the date of first dose, then set the start date to the 1st of 
that month 
In the event of ambiguity or incomplete data which makes it impossible to determine whether a 
medication was concomitant, the medication will be considered as concomitant. 
4.3 
Interim analyses and data monitoring 
4.3.1 
Interim analysis 
One interim analysis will be performed after all randomized subjects have completed the 
Double-Blind Treatment Period at Week 16.  
The purpose of the Week 16 interim analysis is to perform a comprehensive evaluation of all 
available double-blind data for the BKZ and placebo treatment arms to prepare a regulatory 
submission for a Marketing Authorization Application based on this analysis.  
The interim analysis will evaluate the primary and secondary efficacy variables as well as all 
other efficacy, safety and PK variable results up to Week 16. In addition, disposition, 
demographics and other Baseline characteristics, protocol deviations and compliance will be 
described. All available data at the time of the snapshot will be included (ie, even SFU data 
available beyond the Week 16 timepoint). Events on-going at the time of the interim analysis 
(eg, concomitant medications, adverse events) will be analyzed as they are collected to date, and 
analyses based on these events will be up to date at time of the final analysis.  
For the interim analysis, the database will be locked, and the treatment codes will be made 
available to UCB personnel. An interim report will be written. The investigators and subjects 
will remain blinded to the assigned BKZ dosing regimen until the final analysis is completed. A 
blinding maintenance plan will be written to evaluate the potential bias in data reporting and 
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describe the process of interim results generation and dissemination. The plan will be finalized 
prior to the lock of the database at the interim analysis. 
No formal alterations to the further study conduct (eg, stopping rules, sample size re-estimation, 
or changes to eligibility criteria) are planned for the interim analysis. 
No separate SAP for the interim analysis will be provided. The TFL shells for the interim and 
final analyses will be provided in the same document. The final analysis will consist of a re-run 
of all analyses, including new data occurring during the SFU Period that were not available for 
the interim Week 16 analysis.  
4.3.2 
Data Monitoring Committee 
An independent Data Monitoring Committee (DMC) will be formed to monitor the ongoing 
safety of the study through periodic review. The general scope of DMC activities is presented in 
the protocol, and the composition and operation of the DMC will be defined in the DMC charter. 
The presentation and analysis of data for the DMC meetings will be described within a separate 
DMC SAP. 
4.4 
Multicenter studies 
The data from all centers will be pooled for the purposes of the analysis. However, the effect of 
center (using a pooling of centers by region) on results will be evaluated as mentioned in Section 
3.8.  
4.5 
Multiple comparisons/multiplicity 
A fixed sequence testing procedure will be applied for the primary endpoint and the key 
secondary endpoints. The testing procedure will account for multiplicity and control the family-
wise type I error rate at alpha=0.05 (2-sided).  
For each test, on each binary efficacy endpoint, the null hypothesis is that the conditional odds 
ratio is equal to one (H0: ORT1T2 = 1). The alternative hypothesis is that the conditional odds ratio 
is not equal to one (HA: ORT1T2≠ 1). 
For each test, on each continuous efficacy endpoint, the null hypothesis is that there is no 
difference between treatment groups (H0: T1 – T2 = 0). The alternative hypothesis is that there is 
a difference between treatment groups (HA: T1 – T2 ≠0). 
T1 refers to BKZ and T2 to placebo.  
According to this strategy, the statistical testing of an endpoint can be investigated only if the 
null hypothesis for the previous endpoint has been rejected (ie, if p<0.05). Table 7‒4 shows the 
testing order for these endpoints. 
Table 7‒4: 
Sequential testing procedure of primary/secondary efficacy 
endpoints (fixed testing procedure procedure) (All efficacy endpoints 
at Week 16) 
BKZ 160mg Q4W 
H1 
ACR50 Response superior to Placebo 
H2 
Change from Baseline HAQ-DI superior to Placebo  
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H3 
PASI90 Response superior to Placebo in subjects with PSO BSA ≥3% at Baseline 
H4 
Change from Baseline SF-36 PCS superior to Placebo 
H5 
MDA superior to Placebo 
   ACR50=American College of Rheumatology 50% response crtiteria; BKZ=bimekizumab; H=hypothesis; HAQ-DI=Health 
Assessment Questionnaire - Disability Index; MDA=Minimal Disease Activity; PASI90=Psoriasis Area and Severity Index 90; 
PCS=Physical Component Summary; Q4W=every 4 weeks; SF-36=Short-Form 36-item Health Survey; W=week.  
4.6 
Use of an efficacy subset of subjects 
The RS will be the primary analysis set for efficacy analyses, but analyses will also be repeated 
on the FAS and the PPS for the primary efficacy endpoint. The FAS analysis will evaluate 
whether there are differences in the efficacy analysis between randomized subjects and 
randomized subjects with a Baseline assessment; while the PPS analysis will evaluate the effect 
of IPD on the analysis.  
4.7 
Active-control studies intended to show equivalence 
Efficacy outcomes are based on superiority comparisons of the BKZ 160mg sc Q4W to placebo, 
this section is then not applicable for this study. 
4.8 
Examination of subgroups 
Subgroup analyses will be performed on the variables below. They are all assessed at Baseline,  
except concomitant cDMARDs, concomitant Methotrexate (MTX) and ADAb status which will 
be assessed during the 16-week period. Subgroup analyses will be performed on the ACR50 
response, the PASI90 response and the HAQ-DI response (subjects with a decrease of HAQ-DI 
from Baseline of at least 0.35) at Week 16. The ADAb status will also be used for subgroup 
analysis for the PK endpoints.  
The variables for subgroup analyses will be:   
• Age (<45 years of age, ≥45 years of age), 
• Gender (male, female), 
• Disease duration (<1 year, ≥1 year), 
• Region (eg, North America, Western Europe, Eastern Europe, Asia. Western Europe will be 
combined with Asia if any of these 2 regions have less than 10% of the randomized subjects), 
• Race (White, Black, and Other), 
• Body weight at Baseline (≤100kg, >100kg), 
• Prior TNFα exposure (intolerance to TNFα inhibitor, inadequate response to at least 1 TNFα 
inhibitor, inadequate response to 2 prior or more TNFα inhibitors), 
• hs-CRP at Baseline (<6mg/L, ≥6mg/L),  
• Prior conventional disease-modifying antirheumatic drugs (cDMARDs) (0, 1, ≥2) (taken 
prior to Baseline). Such medications will be classified using an adjudicated spreadsheet. 
• Concomitantly receiving cDMARDs versus no concomitant cDMARDs,  
• Concomitantly receiving MTX versus no concomitant MTX,  
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• Concomitantly receiving MTX at Baseline vs. other cDMARDs at Baseline (MTX at 
Baseline, no MTX at Baseline and cDMARDs at Baseline, no MTX at Baseline and no 
cDMARDs at Baseline), 
• PSO affected BSA at Baseline (<3%, ≥3% to 10%, >10%), 
• BASDAI at Baseline (<4, ≥4), 
• ADAb status (positive, negative) (See Section 9.2) for the BKZ 160mg Q4W group only, 
• Human leukocyte antigen B27 (HLA-B27) (positive, negative). 
Note: In the context of submission for Japanese health authorities, a subset of tables, listings and 
figures will be provided for the subgroup of subjects randomized in Japan. 
5 
STUDY POPULATION CHARACTERISTICS 
5.1 
Subject disposition 
Subject disposition will be summarized for all subjects screened overall, by region and by site. In 
this summary, the dates of first subject screened and date of last subject last visit (end of study), 
number of screened subjects, and the number of subjects included in each analysis set (RS, SS, 
FAS, PPS, PK-PPS, COVID-19-free Set) will be presented.  
The disposition of subjects into treatments groups and analysis sets will also be summarized on 
the RS. 
Reasons for screen failures (as collected on the Study Termination Screen Failure CRF page) 
will be summarized for all screened subjects who failed to be randomized.  
The number and percentage of randomized subjects who completed the study, completed the 
study not on randomized treatment, who discontinued IMP, overall and by reason, and who 
discontinued the study, with the primary reason for study discontinuation (as collected on the 
Study Termination CRF page), will be tabulated overall and by treatment group. The numbers 
and percentage of randomized subjects entering the SFU Period will additionally be presented. 
The numbers and percentages of these subjects who either complete the SFU visit or not will 
additionally be presented. The numbers and percentages of randomized subjects entering the 
Open Label Extension (OLE) study and those not entering the OLE study will also be presented. 
A subject will be said to have completed the study if she/he had completed the last scheduled 
study visit, not including SFU visits. (The SFU visit is typically 140 days post last dose of IMP, 
which is roughly equivalent to 5 half-lives of BKZ).For subjects who previously discontinued 
IMP, the primary reason for discontinuation as collected on the Study Medication termination 
CRF page will be summarized in a separate table. 
Finally, the number of randomized subjects who discontinued the study due to AEs by type of 
AEs (serious fatal, non-fatal, other) will be summarized. 
Study disposition and termination details will be listed for all subject screened. Additional 
listings will be created on study discontinuation, subject analysis sets and visit dates (both actual 
visit and visit remapped for analysis). A listing will also be provided for subjects who did not 
meet the study eligibility criteria. 
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To assess subject disposition (entry and periods in the study) during the COVID-19 pandemic, 
subject disposition will be assessed by period of the COVID-19 pandemic (pre – during – post) 
(Section 3.6.7 ), by comparing the dates of visits (or events) to the dates of the COVID-19 
pandemic period. 
5.2 
Impact of COVID-19 
A listing of visits affected by COVID-19 will be presented based on the ES including the visit, 
date of visit, relationship to COVID-19, impact category, and a narrative (short description) of 
the event. These data will be summarized for non-randomized subjects and by treatment group 
and overall, for enrolled subjects. 
A summary of study visits by COVID-19 pandemic period (pre – during – post) will be 
presented for subjects enrolled prior, during and after the pandemic.  
In addition, in order to assess the potential impact of COVID-19 on the collection and reporting 
of efficacy data, a separate summary on the RS will be presented to display missing data as well 
as data collected via an alternative modality (eg, phone, video call) for efficacy endpoints 
included in the hierarchy (Table 7‒4). For these displays, missing data will be presented only for 
visits affected by COVID-19, as reported on the dedicated eCRF page. Missing data at other 
visits and for other reasons will not be included. 
For visits conducted remotely, it was not possible to assess some endpoints (eg, TJC, SJC, LDI, 
LEI, PASI, etc.) and therefore these assessments will be missing for those visits. In addition, for 
any missed visit or visit conducted remotely, the CRP assessment will also be missing. Such 
assessments will be considered missing as a result of the COVID-19 pandemic. For these visits, 
it will therefore not be possible to assess composite endpoints like ACR response. For this 
summary table, based on the RS, only visits at which efficacy assessments are scheduled will be 
included. 
5.3 
Protocol deviations 
The definition of an IPD is given in Section 3.5. 
A summary displaying the number and percentage of subjects with an important protocol 
deviation will be provided for the RS by treatment group. This will include a summary of 
subjects excluded from the PPS and PK-PPS. The summary will be provided overall and by type 
of deviation (inclusion criteria deviation, exclusion criteria deviation, withdrawal criteria 
deviation, prohibited concomitant medication, incorrect treatment or dose, treatment non-
compliance, procedural non-compliance, COVID-19 related IPD) as well as the number and 
percentage of subjects excluded from the PPS due to reason other than PD. Criteria for exclusion 
of subjects from the PPS or PK-PPS will be defined in a separate document.  
A listing of important protocol deviations will be provided for all subjects in the RS. 
A listing of COVID-19 related PDs will be provided for all subjects in the RS. 
A listing of subjects excluded from the PPS for reasons other than IPD will be provided. 
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6 
DEMOGRAPHICS AND OTHER BASELINE 
CHARACTERISTICS 
Unless otherwise specified, all summaries will be based on the SS and repeated using the RS 
(unless the SS and RS analysis sets are identical).  
6.1 
Demographics 
The following demographic variables measured at Baseline will be summarized overall and by 
treatment group: age (years), gender, country, geographic region, country, race, ethnicity, height 
(cm), body weight (kg) and body mass index (BMI) (kg/m2).  
Age, body weight and BMI will be summarized as continuous variables and as categorical 
variables based on the categories specified below.  
For age, 3 sets of categories will be defined: 
• ≤18, 19 to <65, ≥65 years (clinicaltrials.gov requirement),  
• 18 to <65, 65 to <85, ≥85 years (EudraCT requirement),  
• 18 to <45, ≥45 to <65, ≥65 years.  
Body weight categories will be: ≤100, >100 kg. 
Even if BMI is available in the database, BMI (in kg/m2) will be recalculated during analysis 
based on height (in m) and weight (in kg) values collected in the database, and the calculated 
values will be used in the statistical analysis since they are considered more accurate. The 
formula for BMI (kg/m2) calculation is: 
BMI = Weight (kg)
(Height (m))2 
BMI categories will be: <25, 25 to <30, ≥30 to <35, ≥35 kg/m2. 
A separate frequency table will summarize the subject’s lifestyle on the SS.  
By-subject listings on demographics and female subjects’ childbearing potential and birth control 
data will be provided for all screened subjects. Listing on lifestyle will be provided on the RS.  
To understand the study population during the different periods of the COVID-19 pandemic, the 
reporting of Baseline demographics will be repeated by COVID-19 pandemic period (pre - 
during as determined by the Baseline visit date) on the SS. 
6.2 
Baseline characteristics 
6.2.1 
Baseline values for primary efficacy variable components 
Baseline values for the 7 components for primary efficacy variable will be summarized by 
treatment group and overall. The following variables will be summarized: 
• TJC,  
• SJC,  
• PGA-PsA, 
• PhGA-PsA, 
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• PtAAP, 
• HAQ-DI, 
• hs-CRP (mg/L).  
For hs-CRP, SJC, and TJC the following rule will be applied: If Baseline value is missing, then 
take the most recent value (taken at previous unscheduled visit or at Screening); If value is still 
missing, the Baseline value will be considered missing. hs-CRP will be summarized using 
descriptive statistics   and in classes (≥6mg/L, <6mg/L). 
Efficacy variables not listed above will not be presented in the Baseline characteristics section. 
They will be presented in by-visit tables in the context of the analysis of secondary and other 
efficacy variables. 
To understand the study population during the different periods of the COVID-19 pandemic, the 
reporting of Baseline demographics will be repeated by COVID-19 pandemic period (pre-,  
during, and post- as determined by the Baseline visit date) on the SS. 
6.2.2 
Other baseline characteristics  
The following variables will be summarized by treatment group and overall:  
• Prior TNFα exposure (Intolerance to TNFα inhibitor, Inadequate response to 1 TNFα 
inhibitor, Inadequate response to 2 TNFα inhibitors) – IXRS randomization strata 
• Prior TNFα exposure (Intolerance to TNFα inhibitor, Inadequate response to at least 1 TNFα 
inhibitor, Inadequate response to 2 prior or more TNFα inhibitors) – actual randomization 
strata 
• % of BSA affected by PSO (<3%, ≥3% to ≤10%, >10%) 
• PASI score at Baseline (for subjects with PSO involving at least 3% of BSA at Baseline). 
This variable will be summarized as a continuous variable and in classes (<10, 10 to 20,>20)  
• BASDAI (<4, ≥4) 
• Rheumatoid factor (positive, negative). A rheumatoid factor value < 30 IU/mL is defined as 
negative and a value ≥ 30 IU/mL is defined as positive. (Chemistry results / Proteins / 
Test=RF). 
• Anti-cyclic citrullinated peptide (CCP) antibodies (Positive, Negative).  Anti-CCP antibodies 
negative is a value < 20 U/mL and a value ≥ 20 U/mL is defined as positive. 
• Nail psoriasis (yes, no) 
• Dactylitis (“yes” if LDI score>0, “no” if LDI score=0 or missing) 
• Enthesitis based on LEI (“yes” if LEI score>0, “no” if LEI score=0 or missing) 
• Enthesitis based on SPARCC (“yes” if SPARCC>0, “no” if SPARCC=0 or missing) 
• Prior NSAID (yes, no)  
• NSAID at Baseline (yes, no)  
• Past cDMARDs therapy (yes, no) 
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• Prior cDMARDs (0, 1, ≥2) (see Section 4.8 ) 
• cDMARDs at Baseline (yes, no) 
• HLA-B27 status (positive, negative) 
• Methotrexate at Baseline (yes, no)  
• Prior oral corticosteroids (yes, no)  
• Oral corticosteroids at Baseline (yes, no) 
The above data including extra-articular assessments will also be listed.  
Efficacy variables not listed above will not be presented in the Baseline characteristics section. 
They will be presented in by-visit tables in the context of the analysis of secondary and other 
efficacy variables. 
To understand the study population during the different periods of the COVID-19 pandemic, the 
reporting of Baseline demographics will be repeated by COVID-19 period (pre-, during, and 
post- as determined by the Baseline visit date) on the SS. 
6.2.3 
History of psoriatic arthritis and psoriasis 
The following PsA history variables will be summarized overall and by treatment group: 
• Time since first diagnosis of PsA (years). Time since first diagnosis will be summarized as a 
continuous variable and as categorical variables based on following categories: <1, 1 to <2, 
≥2 years. 
• Time since first diagnosis of PSO (years),  
Time since first diagnosis of PsA/PSO (years) will be calculated as follows: 
𝐷𝑎𝑡𝑒 𝑜𝑓 𝑖𝑛𝑓𝑜𝑟𝑚𝑒𝑑 𝑐𝑜𝑛𝑠𝑒𝑛𝑡−𝐷𝑎𝑡𝑒 𝑜𝑓 𝑑𝑖𝑎𝑔𝑛𝑜𝑠𝑖𝑠
365.25
 
 
• Age at first diagnosis of PsA (years),  
Age at first diagnosis (years) of PsA will be calculated as: 
 𝐷𝑎𝑡𝑒 𝑜𝑓 𝑑𝑖𝑎𝑔𝑛𝑜𝑠𝑖𝑠 𝑜𝑓 𝑃𝑠𝐴−𝐷𝑎𝑡𝑒 𝑜𝑓 𝑏𝑖𝑟𝑡ℎ
365.25
 
If the date of diagnosis is partial, it should be imputed to the most recent feasible date (ie, last 
day of the month if only day is missing, or the last day of the year if day and month are missing). 
Partial dates should not be imputed later than the subject’s screening date. For subjects enrolled 
at German sites, only the year of birth may be entered into the eCRF for this study. For these 
subjects age will be calculated after imputing their date of birth to be on January 1st. 
• PsA subtype (Polyarticular – symmetric arthritis, Oligoarticular – asymmetric arthritis, Distal 
interphalangeal joint predominant, Spondylitis predominant, Arthritis mutilans) 
The data on history of psoriasis and psoriatic arthritis will be listed for all screened subjects. 
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6.3 
Medical history and concomitant diseases 
Medical history conditions are defined as conditions that have resolved prior to study entry.  
Ongoing medical conditions are defined as conditions that are ongoing at the time of study entry. 
Medical history and on-going medical conditions will be summarized on the SS by MedDRA 
System Organ Class (SOC) and Preferred Term (PT), by treatment and overall including the 
number and percentage of subjects with each condition. Psoriatic arthritis history will not be 
included in this table as it will be presented separately (Section 6.2.3). The denominator of the 
percentages will be the number of subjects in the population considered. The table summaries 
will be ordered alphabetically for SOC and in terms of decreasing frequency for PT within SOC 
in the BKZ treatment group. In the event of ties, PT will be ordered alphabetically.  
Medical history and ongoing medical conditions will be listed by treatment and subject including 
the reported term, PT, and SOC for the RS. The start date (month and year only) and the end date 
(or ongoing if applicable) will be included in the listing. Partial dates will not be imputed. A 
glossary of all medical history conditions will be presented including the reported term, PT and 
SOC. Concomitant medical procedures will be listed on the RS. 
6.4 
Prior and concomitant medications 
Prior medications include any medications that started prior to the start date of the first IMP 
administration. 
Concomitant medications are medications taken at least one day in common with the study 
medication dosing period.  
The IMP dosing period corresponding to the combined Double-Blind Treatment Period will be 
calculated as follows: 
• The study medication dosing period start date is defined as the date of first dose. 
The study medication dosing period stop date is defined as follows: 
• For subjects who are ongoing at the time of the clinical data cut (not including subjects who 
are in SFU) use date of last clinical contact 
• For subjects who died prior to last visit (not including those who died during SFU), use the 
minimum of the following: 
− Date of death 
− Date of last dose of any study medication + 28 days 
• For subjects who complete the study as planned, the dosing period ends at the later of the 
following two dates: 
− Date of last administration of IMP + 28 days 
− The last scheduled visit date not including SFU 
• For all other subjects, use the maximum of the following: 
− Date of last dose of any study medication + 28 days 
− Date of last visit (not including SFU) 
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In the case of missing data, the classification of medications as prior or concomitant will be 
performed as described in Section 4.2.4. Imputations of missing data will be performed before 
calculation of relative study days. 
The number and percentage of subjects taking prior medications and prior Anti-TNFs (excluding 
past psoriasis medications) will be summarized on the SS by treatment group, overall and by 
ATC class, presenting Anatomical Main Group (ATC Level 1), Therapeutical/Pharmacological 
Subgroup (ATC level 3), and preferred term (PT).  
The table summary will be ordered alphabetically for the ATC class and in terms of decreasing 
frequency for PT within ATC class in the BKZ treatment group. In the event of ties, PT will be 
ordered alphabetically. 
A by-subject listing of all prior medications and prior Anti-TNFs and concomitant medications 
on the SS as well as glossary of all medical medications will be provided. 
6.5 
Prohibited concomitant medications  
Prohibited or restricted medications are defined in the protocol section 7.8.2. 
Prohibited medications will be listed on SS. 
7 
MEASUREMENTS OF TREATMENT COMPLIANCE 
Treatment compliance summaries will be performed based on the SS, by randomized treatment 
and for all subjects. 
Due to the method of administration of the treatments, compliance will be examined in terms of 
completed injections. Treatment compliance will be calculated as: 
Total number of actual (completed) injections
 Total number of expected injections
 ×  100% 
The total number of expected injections is derived relative to when the subject finishes treatment.  
If a subject completes treatment, 4 injections are expected (at Baseline, Week 4, Week 8 and 
Week 12).  
If a subject discontinues early, then the number of expected injections is based on the time of 
early discontinuation relative to the dosing visits. This number will be calculated by determining 
the number of expected dosing visits prior to the date of early discontinuation. If the early 
discontinuation coincides with an expected dosing visit, this visit will used to determine the 
number of expected injections. 
A summary of percent treatment compliance categorized as <75% and ≥75% will be provided by 
treatment group, as well as a by-subject listing of treatment compliance. 
8 
EFFICACY ANALYSES 
8.1 
Statistical analysis of the primary efficacy variable 
8.1.1 
Derivation of ACR50 response 
The ACR50 response at Week 16 is the primary efficacy variable.  
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This is a composite endpoint and represents at least 50% improvement from Baseline at Week 16 
for each of the following: 
• TJC (based on 68 joint count) 
• SJC (based on 66 joint count) 
• At least 3 of the 5 remaining core set measures: 
– PGA-PsA 
– PhGA-PsA 
– PtAAP  
– HAQ-DI 
– hs-CRP 
Prior to deriving ACR50, the percent of change for each component will be calculated as:  
Percent improvement from Baseline = 100 × Baseline Value −Week 16 value 
Baseline Value
 
 
As the ACR response is based on 7 different component scores, it is necessary to consider 
various data scenarios that could impact the calculation of ACR response. The rules described 
here are applicable in the context of the calculation of ACR response and may differ from the 
rules applied for calculating and summarizing the components, individually (some values may 
need to be imputed for component for component analysis but are not required here to evaluate 
the ACR response). 
 
The following rules will be applied prior to invoking any imputation analysis at the variable 
level: 
• If a subject has a component value that is equal to 0 at Baseline and the post-Baseline value 
is greater than or equal to 0, then the percentage of improvement for that component will be 
treated as 0 for purposes of ACR response calculations. 
• If a subject has a component value that is missing at Baseline, then the percentage of 
improvement for that component will be treated as missing for purpose of ACR response 
calculations.   
Observed data will be used to calculate ACR response where possible. In case of partial missing 
data where an observed response may be calculated, imputed data will not change the result.  
To address possible missing data in ACR components, ACR50 will be derived as below:  
• Positive response on ACR50 
o Improvement at Week 16 of at least 50% from baseline on SJC and TJC and at least 3 
out of the 5 remaining ACR components (regardless of whether the two remaining 
components are missing or not) 
• Negative response on ACR50 
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o No improvement at Week 16 of at least 50% from baseline on SJC (regardless of 
whether the remaining components are missing or not) 
o No improvement at Week 16 of at least 50% from baseline on TJC (regardless of 
whether the remaining components are missing or not) 
o No improvement for at least 3 out of the 5 ACR components (PGA-PsA, PhGA-PsA, 
PtAAP, HAQ-DI, hs-CRP) regardless of whether the remaining components are 
missing or not 
• Missing ACR50 response 
o For all other situations that are not specified above. 
For the OC analysis: if a given visit falls after the treatment discontinuation date, the endpoint at 
this visit and all subsequent visits (whether the data were observed or not) will be derived but 
reported as missing (Section 8.1.4.6). 
For the MI analysis: if a given visit falls after the treatment discontinuation date, the endpoint at 
this visit and all subsequent visits (whether the data were observed or not) will be imputed. 
Responses falling after an IE (defined as treatment discontinuation due to AE or lack of efficacy 
for the modified composite estimand) will be set to nonresponse (Section 8.1.4.3). 
 
8.1.1.1 
Derivation of tender joint count (TJC) and swollen joint count (SJC) 
Tender and swollen joints are assessed based on the 68 and 66 joints for tenderness and swelling, 
respectively. The 68/66 joints that are assessed are:   
• Upper body (6) - bilateral temporomandibular, sternoclavicular, and acromioclavicular joints. 
• Upper extremity (34) - bilateral shoulders, elbows, wrists (includes radiocarpal, carpal and 
carpometacarpal bones considered as a single unit), metacarpophalangeal (I, II, III, IV, and 
V), thumb interphalangeals, proximal interphalangeal (II, III, IV, and V), and distal 
interphalangeals (II, III, IV, and V). 
• Lower extremity (28) - bilateral hips, knees, ankles, tarsi (includes subtalar, transverse tarsal, 
and tarsometatarsal considered as a single unit), metatarsophalangeals (I, II, III, IV, and V), 
great toe interphalangeals, and proximal interphalangeals (II, III, IV, and V). 
The assessment on swelling exclude the hips.  
Each of the joints can be graded as follows by the assessor:  
• Permanently not assessable 
• Temporarily not assessable 
• Asymptomatic 
• Tender only 
• Swollen only 
• Tender and swollen 
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Permanently non-evaluable joints will be considered missing for both tender and swollen joint 
counts at the visit at which the grading was recorded and all subsequent visits. The asymptomatic 
joints will be included in the joint count analysis with scores of 0. 
For the statistical analysis, swelling and tenderness will be each graded on a 2-point scale as 
described below in Table 8‒1. 
Table 8‒1: 
Swelling and Tenderness grading 
Present 
Tenderness response (68) 
Swelling response (66) 
No (0) 
Not tender 
None 
Yes (1) 
Positive response to questioning (tender), 
spontaneous response elicited (tender and winced) 
or withdrawal by subject on examination (tender, 
winced, and withdrew) 
Detectable synovial thickening 
with or without loss of bony 
contours, or bulging synovial 
proliferation with or without 
cystic characteristics 
The joint graded by the assessor will then have its grade mapped as follows: 
• The “Tender only” joints will correspond to a tenderness response of 1, and a swelling 
response of 0.  
• The “Swollen only” joints will correspond to a swelling response of 1, and a tenderness 
response of 0. 
• The “Tender and swollen” joints will correspond to a swelling and tenderness response of 1. 
Dactylitic digits will be identified as follows and the joints will be counted as follows: 
• Fingers 2-5: Swelling Distal Interphalangeal Joint x (side), Swelling Proximal 
Interphalangeal Joint x (side), Swelling Metacarpophalangeal Joint x (side) – if they are in 
any of the gradings ‘swollen only’ or ‘tender and swelling’ or ‘injected’ then only 1 finger 
will be added to the swollen joint count 
• Toes 1-5: Swelling Interphalangeal Joint x (side), Swelling Metatarsophalangeal Joint x 
(side) – if they were in any of gradings ‘swollen’ or ‘tender and swollen’ or ‘injected’ then 
only 1 toe will be added to the swollen joint count 
The tender joint count (TJC) and swollen joint count (SJC) are weighted joint counts. If there are 
missing observations in the tender or swollen joint assessments (TJ and SJ, respectively), then 
the remaining observations will be assessed and weighted by the number of the assessed 
joints (AJ) as shown below: 
𝑇𝐽𝐶= 𝑛× ∑
𝑇𝐽
𝑛
𝑖=1
∑
𝐴𝐽
𝑛
𝑖=1
 
𝑆𝐽𝐶= 𝑛× ∑
𝑆𝐽
𝑛
𝑖=1
∑
𝐴𝐽
𝑛
𝑖=1
 
Where n represents the number of total joints.  
However, if a joint is missing at Baseline, then that joint will be set to missing throughout the 
study. If more than 50% of the planned tender joint assessments (ie, more than 34) or 50% of the 
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planned swollen joint assessments (ie, more than 33) are missing at any post-Baseline visit, then 
no imputation will be done and the total TJC or SJC will be set to missing for that visit. 
8.1.1.2 
Patient and physician reported clinical outcomes on psoriatic 
arthritis 
The physician’s global assessment of psoriatic arthritis (PhGA-PsA), the patient’s global 
assessment of psoriatic arthritis (PGA-PsA) and the patient’s assessment of arthritis pain 
(PtAAP) are clinical outcomes based on visual analog scales (VAS) ranged from 0 to 100 (in 
mm).  
• PhGA-PsA: The investigator will assess the overall status of the subject with respect to their 
PsA signs and symptoms using a numerical rating scale where 0 is “very good, asymptomatic 
and no limitation of normal activities” and 100 is “very poor, very severe symptoms which 
are intolerable and inability to carry out all normal activities”. This assessment will be based 
through the following question “Considering all the ways the disease affects your patient, 
mark a vertical line on the scale for how well his or her condition is today.”  
• PGA-PsA: Subjects will assess the impact of PsA in answering the following question 
“Considering all the ways your psoriatic arthritis affects you, please mark a vertical line on 
the scale below to show how well you are doing today.” The subject should be asked to 
consider all aspects of their disease (including joint and skin components) in their response to 
this question. Subjects will score PGA-PsA in using a VAS where 0 is “very good, no 
symptoms” and 100 is “very poor, severe symptoms.” 
• PtAAP: Subjects will assess their arthritis pain through the PtAAP using a VAS where 0 is 
“no pain” and 100 is “most severe pain.” 
8.1.1.3 
Derivation of the health assessment questionnaire disability index 
score (HAQ-DI) 
The HAQ-DI contains 20 items that measure the degree of difficulty experienced in the 
following 8 categories of the daily living activities: dressing and grooming (2 items), arising (2 
items), eating (3 items), walking (2 items), hygiene (3 items), reach (2 items), grip (3 items), and 
common daily activities (3 items). 
For each question/item, subjects should indicate the level of difficulty (from 0 to 3) in the past 
week as follows: 
• 0: ‘without any difficulty’ 
• 1: ‘with some difficulty’ 
• 2: ‘with much difficulty’ 
• 3: ‘unable to do’ 
Each category is given a score by taking the maximum value for each question. 
For each question related to a specific daily living activity, subjects can specify whether an aid or 
devices is usually used. 
If a category score equals 0 or 1, but a device related to that category is used, or help from 
another person is provided for that category, then the category score is increased to 2.  
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If a category score already equals 2, and a device related to that category is used, or help from 
another person is provided for that category, the score for that category remains 2.  
Table 8‒2 details how each aid and device is associated with the category scores. Aid or device 
considered as ‘other’ than the ones listed will not be considered in the analysis.  
Table 8‒2: 
Aid and device associated with HAQ-DI category 
Aid or device 
Will be associated with category score 
Walking  
Dressing and grooming 
Eating 
Arising 
Hygiene 
Hygiene 
Grip 
Hygiene 
Reach  
Hygiene 
If all questions within a given category are unanswered, no score will be provided for that 
category (this rule applies even if aids and devices are non-missing).  
The HAQ-DI score will be calculated by dividing the sum of the highest category scores (0 to 
24) by the number of categories with at least 1 question answered. If fewer than 6 categories 
have responses, no HAQ-DI score will be calculated (ie, HAQ-DI score will be considered 
missing).  
The HAQ-DI score ranges from 0 to 3. A lower HAQ-DI score indicates an improvement in 
function. 
8.1.1.4 
High-sensitivity C-Reactive Protein (hs-CRP) 
In the summary tables presenting hs-CRP values, the observed values and ratio to Baseline 
values will be displayed.  
hs-CRP values which are below the lower limit of quantification (LLOQ) should be set to the 
midpoint between 0 and the LLOQ prior to the analysis. Listing will show values below the 
LLOQ. The LLOQ for hs-CRP is 0.10mg/L. 
8.1.2 
Primary analysis of the primary efficacy variable 
The primary efficacy variable will be analyzed for all subjects in the RS.  
The primary endpoint is the ACR50 response at Week 16. The primary efficacy analysis will 
evaluate the composite estimand in the RS. The composite estimand combines the clinically 
meaningful improvement from Baseline in ACR components as assessed using the ACR50 
response at Week 16 and not discontinuing study treatment prior to Week 16.  
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The following 4 attributes describe the estimand that will be used to define the treatment effect 
of interest for the primary efficacy analysis: 
• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP 
• Subject-level outcome = ACR50 at Week 16  
• Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment prior to Week 16. A composite strategy will be implemented in which a positive 
clinical outcome is defined as achieving ACR50 at Week 16 and not discontinuing study 
treatment through Week 16. 
• Population-level summary measure = Conditional odds ratio comparing BKZ to placebo and 
difference of response rate between BKZ and placebo. 
Missing data at Week 16 that are not preceded by an IE and any data after an IE will be imputed 
as non-responders. This results in a more traditional NRI approach and will be labeled as such 
throughout the SAP. 
The statistical hypothesis for the ACR50 response at Week 16 is that the conditional OR for 
ACR50 response in the BKZ treatment compared to placebo treatment is equal to 1.   
A logistic regression model will be used to assess the treatment effect on ACR50 response at 
Week 16. The model will include fixed effects for treatment, and prior TNFα inhibitor exposure 
and region as stratification factors. The suitability of including these variables in the model will 
be assessed using Pearson and Deviance and the Hosmer-Lemeshow Goodness-of-Fit Tests 
(Hosmer and Lemeshow, 2000).  
P-values below 0.05 would lead to a reconsideration of the model to be used and if the logistic 
regression model is unable to converge the stratification variables will be dropped (Section 4.1). 
In that case, all supportive analyses as well as imputation models conducted for the primary 
endpoint will disregard these exploratory factors from their models.  
The country-specific analyses performed on subjects randomized in Japan will not consider the 
region factor as a covariate for the modelling. Considering that the number of subjects 
randomized in Japan is low (less of 10% of the RS), statistical models might not converge. If a 
model (logistic Model or mixed model) is not converging, all related adjusted statistics and p-
value will not be presented: “NE” for “Not Evaluable” will be displayed instead. 
The SAS® PROC LOGISTIC will be used to run the logistic regression.  
The summary table results will present the adjusted responder rates and the associated 95% CI 
for BKZ and placebo, the adjusted odds ratio and 95% CI for the comparison of BKZ versus 
placebo, and the p-value that the OR=1 and the difference of response rate between BKZ and 
placebo and associated 95% CI. The treatment comparison will be made using the 2-sided Wald 
test at a significance level of α=0.05 (ie, H1 in Table 7‒4).  
8.1.3 
Subgroup analyses of the primary efficacy variable 
Subgroup analyses will be performed on the primary efficacy variable on the RS.  
The variables for subgroup analyses are defined in Section 4.8.  
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For each subgroup analysis (except for the analysis by prior TNFα exposure, by region, and by 
ADAb status), a logistic regression will be fitted involving the same terms that were retained 
when running the primary analysis model, plus a term for the subgroup and the subgroup by 
treatment interaction as detailed below:  
• Fixed effect for treatment  
• Prior TNFα 1 (1 for inadequate response to at least 1 prior TNFα inhibitor) 
• Prior TNFα 2 (1 for inadequate response to 2 prior or more TNFα inhibitors) 
• Region  
• Term for subgroup  
• Terms for subgroup by treatment interaction(s).  
 
For subgroup analyses by Prior TNFα exposure, the terms that will be retained will be:  
• Fixed effect for treatment  
• Prior TNFα 1 (1 for inadequate response to 1 prior TNFα inhibitor) 
• Prior TNFα 2 (1 for inadequate response to 2 prior TNFα inhibitors) 
• Region  
• Terms for Prior TNFα inhibitor exposure by treatment interaction  
For subgroup analyses by region, the terms that will be retained will be:  
• Fixed effect for treatment  
• Prior TNFα 1 (1 for inadequate response to 1 prior TNFα inhibitor) 
• Prior TNFα 2 (1 for inadequate response to 2 prior TNFα inhibitors) 
• Region  
• Terms for region by treatment interaction  
For subgroup analyses by ADAb status, the terms that will be retained will be:  
• prior TNFα exposure at Baseline   
• Region  
• ADAb Status (Positive, Negative) 
For all subgroup analyses, the terms for the subgroups will coded as below: 
• For Yes/No or positive /negative variables, the category “yes” or “positive” will be coded 
“1”. 
• For continuous variables in 2 classes, the highest category will be coded “1”. 
• For continuous variables in 3 classes (or more), 2 (or more) binary variables will be created 
and coded “1” for the 2 (or more) top categories. 
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• For gender, “male” will be the category coded “1”. 
The same estimand approach as the one used for the primary analysis will be used to handle 
missing data (NRI).  
For each subgroup category and each treatment group (subgroup analysis on the ADAb status for 
only BKZ group), the mean proportion of responders on imputed datasets, the adjusted responder 
rates with associated 95% CI will be provided. The adjusted OR (for the comparison BKZ and 
placebo) and the corresponding 95% CI will also be provided. In addition, the difference in 
response rates between BKZ and placebo and the corresponding 95% CI will also be presented 
(except for the subgroup analysis on the ADAb status). The results obtained for each subgroup 
will be presented in one single table. The ORs and associated 95% CIs for each subgroup 
category will also be displayed on a single forest-plot.  
The observed rates of responses by subgroup categories will be also provided along with the 
results obtained on imputed data. 
In addition, the mean proportion of ACR50 responders at Week 16 separated by the 6 pre-
defined ADAb subcategories (as defined in Section 9.2) will be presented graphically for the 
BKZ-randomized subjects.  
8.1.4 
Supportive analyses of the primary efficacy variable 
Unless otherwise specified, the following supportive analyses planned for the primary efficacy 
endpoint will be conducted on the RS (except analyses described in Sections 8.1.4.1, 8.1.4.2 and 
8.1.4.8 ). For the below analyses, unless specified: 
• the same model as the one specified for the primary analysis will be used 
• the same statistics will be provided: the mean proportion of responders (on imputed datasets 
when applicable) the adjusted responder rates for each treatment group, the adjusted ORs for 
the comparison BKZ versus placebo and its 95% CI, the p-value for the comparison between 
BKZ and placebo and the difference of response rates between BKZ and placebo and its 
corresponding 95% CI 
The adjusted OR and 95% CI for the comparison BKZ versus placebo obtained from the primary 
analysis and from the supportive analyses described below (except for Section 8.1.4.4) will be 
displayed in a forest-plot. 
8.1.4.1 
Analysis on the PPS 
The primary analysis described in Section 8.1.2 will be repeated based on the PPS to evaluate the 
effect of IPD on the analysis. 
8.1.4.2 
Analysis on the FAS 
The primary analysis described in Section 8.1.2 will be repeated for all subjects in the FAS to 
evaluate the consistency between the RS and the more restrictive FAS. This analysis will only be 
produced if the number of subjects in the RS and FAS differs.  
8.1.4.3 
Analysis using modified composite estimand where intercurrent 
events are defined as discontinuation due to AE or Lack of efficacy  
The modified composite estimand for this analysis is detailed below  
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• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP. 
• Subject-level outcome = ACR50 at Week 16. 
• Intercurrent event handling = An intercurrent event is defined as discontinuation due to AE 
or lack of efficacy. A composite strategy will be implemented in which a positive clinical 
outcome is defined as achieving ACR50 at Week 16 and not discontinuing study treatment 
due to an AE or lack of efficacy through Week 16.  
• Population-level summary measure = Conditional OR comparing BKZ to placebo.  
Any missing data at Week 16 that is not preceded by an IE will be imputed based on a 
predefined MI model (MI/MCMC - Monotone Regression) (Section 4.2.2.2).  
The following categories of subjects will enter the MI/MCMC – Monotone regression process 
for each ACR component:  
• Subjects with all post-Baseline values missing.  
• Subjects withdrawn from the study treatment (data collected prior to the treatment 
withdrawal will be retained) - Those subjects will have values imputed for missing 
assessments and non missing assessment falling after study treatment discontinuation (falling 
after or before the study withdrawal). 
• Subjects with missing value at Baseline. MI will be applied for each of the components 
separately before deriving the response.  
In the case of partial missing data, ACR will be derived as in Section 8.1.1. 
If an IE occurred prior to or at week 16 (or for any other intermittent missing data at Week16), 
the subjects will be considered as “non-responders”. 
In MI, the missing value is replaced by a set of plausible values, where each value is a Bayesian 
draw from the conditional distribution of the missing data given the observed data. 
8.1.4.4 
Analysis on individual components of the ACR 
The primary comparison (BKZ vs. placebo) will also be repeated for all individual components 
of the ACR50 response to explore the effect of the signs and symptoms of the individual 
components on the composite endpoint. Since all ACR components are continuous variables (eg, 
change from Baseline in TJC), an analysis of covariance (ANCOVA) with treatment, region, and 
Prior TNFα inhibitor exposure as fixed effects and the Baseline value as covariate will be used 
for the analysis. Missing data imputation described in Section 4.2.2 will be successively applied 
for each component. 
The following 4 attributes describe the hypothetical estimand that will be used to define the 
treatment effect of interest for each of the 7 ACR components: 
• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP 
• Subject level outcome = Change from Baseline in the ACR components at Week 16 
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• Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment prior to Week 16. This estimand targets the treatment difference in a scenario 
where withdrawal from study treatment does not occur, such that outcomes for subjects 
without an intercurrent event are as observed, and outcomes for subjects with an intercurrent 
event are treated successively according to the 2 following hypothetical strategies: 
− (a) as they had completed treatment through Week 16. In that strategy, missing data or 
non missing data after IE (reset as missing) will be imputed using MI as though they had 
completed the randomized study treatment through Week 16.  
− (b) as they had completed the randomized study treatment through Week 16 but on 
placebo. In that strategy, missing data or non missing data after IE (reset as missing) will 
be imputed using Reference-Based MI, in which the MI model is based on data from the 
Placebo group. 
• Population-level summary measure = The difference in the adjusted means between BKZ and 
placebo. 
For the results obtained using the 2 MI methods, the SAS® PROC MIXED will be used to run 
the ANCOVA model. The inferential statistics obtained from each model will be displayed in a 
single table. 
For all variables, the following statistics will be presented: 
− the adjusted least-square means (LSM) and standard error (SE) by treatment group, 
− for the comparison between placebo and BKZ: the difference between the LSM, the 
associated 95% CI for the contrasts, and the corresponding p-value. 
An additional table will present the descriptive statistics for the 2 treatment groups for each ACR 
component variable at Week16. Those statistics will be the mean and SE, median, minimum, and 
maximum after MI. 
8.1.4.5 
Analyses using treatment policy strategy imputation for missing data 
The treatment policy strategy for addressing the intercurrent events will be considered. In this 
analysis, all available data at Week 16 will be considered regardless of the occurrence of 
intercurrent events. This analysis will use the same models specified for the primary analyses 
where subjects are analyzed according to their randomized treatment, even if they discontinued 
study treatment for any reason prior to Week 16 and were no longer on the randomized study 
treatment when the assessment was performed at Week 16.  
In the context of this analysis, in addition to the statistics provided in the context of MI, the 
number of observed ACR50 responses regardless of the existence of IE will be also reported. 
The following 4 attributes describe the treatment policy strategy analysis is detailed below: 
• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP 
• Subject-level outcome = ACR50 at Week 16 
• Intercurrent event handling = Discontinuation of study medication for any reason will be 
handled by using the data as observed irrespective of the intercurrent event occurring.  
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• Population-level summary measure = Conditional odds ratio comparing ‘BKZ and other 
medication as needed’ to ‘placebo and other medication as needed’. 
8.1.4.6 
Analysis on Observed cases  
An observed case (OC) analysis will additionally be conducted, where only observed data for 
subjects who are still on the randomized treatment at Week 16 are included. Subjects with 
missing data at Week 16 or who have prematurely discontinued study treatment at or prior to 
Week 16 will be treated as missing and missing data will not be replaced. 
The following 4 attributes describe the estimand that will be used to define the treatment effect 
of interest for the OC analysis: 
• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP 
• Subject-level outcome = ACR50 at Week 16 while on randomized treatment 
• Intercurrent event handling = A “while on randomized treatment” strategy will be 
implemented.  
• Population-level summary measure = Conditional OR comparing BKZ to placebo. 
The same analysis model as used for the primary efficacy analysis will be conducted on the RS. 
8.1.4.7 
Tipping point analysis 
The degree of the departure from the MAR assumption to overturn conclusions from the primary 
analysis will be investigated in a tipping point analysis. This analysis will be performed on the 
monotone missing data and only if the primary analysis is significant at α=0.05. Intermittent 
missing data will be imputed using the MCMC method. In this analysis, it will be assumed that 
subjects who have missing data and are randomized to BKZ have a lower probability of response 
compared to subjects who have missing data and are randomized to placebo.  
The analysis will be primarily conducted on the binary response endpoint itself in considering 
the worst-case scenario that subjects who have missing ACR50 response will be set as non-
responders if they are randomized to BKZ, and as responders if they are randomized to Placebo. 
If the result tips, then the tipping point analysis will be reconducted on the ACR50 endpoint after 
having delta-adjusted each individual component of the ACR50 endpoint. For both analyses, the 
same model as used for the primary efficacy analysis will be conducted on the RS. If the delta 
parameter value for which the study conclusion under MAR is reversed is plausible, the 
conclusion under MAR will then be questionable.  
Refer to Section 4.2.2.4 for more details on the methodology.  
 
8.1.4.8 
Analyses including COVID-19 impact 
To assess the impact of the COVID-19 pandemic on the primary efficacy endpoint, 2 sensitivity 
analyses will be conducted using the same analysis method as the primary analysis (Section 
8.1.2):  
• on the COVID-19-free Set 
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• by COVID-19 period (pre- during -post as determined by the Week 16 date). 
8.2 
Statistical analysis of the secondary efficacy variables 
8.2.1 
Derivation of secondary efficacy variables  
The primary and supportive analysis methods of secondary efficacy variables for which the 
derivation method is provided below are described in Section 8.2.2 and Section 8.2.3. 
For the other secondary variables which are not part of the testing hierarchy, there is no priority 
designated between methods described as primary and supportive analysis methods. 
8.2.1.1 
HAQ-DI: Change from Baseline at Week 16 
The derivation for HAQ-DI is described in Section 8.1.1.3 (The analysis of this variable is 
already covered in Section 8.1.4.4).   
Change from Baseline at Week 16 in HAQ-DI is the 2nd endpoint in the sequential testing 
hierarchy (Table 7‒4).  
8.2.1.2 
Psoriasis Area and Severity Index 90 (PASI90) at Week 16 (in 
subjects with PSO involving at least 3% of BSA at Baseline) 
PASI scoring of psoriatic plaques is based on 3 criteria:  
• redness (R),  
• thickness (T),  
• scaliness (S).  
Severity is rated for each index (R, S, T) on a 0-4 scale (0 = none, 1 = slight, 2 = moderate, 3 = 
marked, and 4 = very marked)).  
The body is divided into 4 areas comprising: 
• head (h),  
• upper extremities (u),  
• trunk (t),  
• lower extremities (l).  
In each of these areas, the fraction of total surface area affected is graded on a 0-6 scale (where 0 
= 0% [clear], 1 = >0% to <10%, 2 = 10% to <30%, 3 = 30% to <50%, 4 = 50% to <70%, 5 = 
70% to <90%, and 6 = 90% to 100%). 
The various body regions are weighted to reflect their respective proportion of BSA. The 
composite PASI score is then calculated by multiplying the sum of the individual-severity scores 
for each area by the weighted area-of-involvement score for that respective area, and then 
summing the 4 resulting quantities as follows:  
𝑃𝐴𝑆𝐼= (0.1 × (𝑅ℎ + 𝑇ℎ + 𝑆ℎ ) × 𝐴ℎ) 
+ (0.2 × (𝑅𝑢 + 𝑇𝑢 + 𝑆𝑢 ) × 𝐴𝑢) 
  +(0.3 × (𝑅𝑡 + 𝑇𝑡 + 𝑆𝑡 ) × 𝐴𝑡)  
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  +(0.4 × (𝑅𝑙 + 𝑇𝑙 + 𝑆𝑙 ) × 𝐴𝑙)  
where  
Rh, Ru, Rt, Rl = redness score of plaques on the head, upper extremities, trunk, and lower 
extremities, scored 0-4 respectively;  
Th, Tu, Tt, Tl = thickness score of plaques on the head, upper extremities, trunk, and lower 
extremities, scored 0-4 respectively;  
Sh, Su, St, Sl = scaliness score of plaques on the head, upper extremities, trunk, and lower 
extremities, scored 0-4 respectively;  
Ah, Au, At, Al = numerical value translation of % area of psoriatic involvement score for the 
head, upper extremities, trunk, and lower extremities, scored from 0-6 respectively. 
The highest potential PASI score is 72 for severe disease; the lowest is 0 for no psoriasis lesions. 
PASI scores are treated as continuous If a subject is missing 1 or 2 severity measurements for a 
certain region, the average of the remaining non-missing severity measurement(s) within that 
region will be utilized to substitute for the missing severity measurement(s) in that region. If the 
area of affected skin and/or all severity measurements for up to 2 regions are missing, then the 
missing (R+T+S) x A for a region will be substituted by the average of the available (R+T+S) x 
A. Otherwise, the PASI score will be set to missing. 
The percent improvement in PASI scores from Baseline will be then computed as:  
Percent improvement from Baseline = 100 × Baseline PASI −Post Baseline PASI
Baseline PASI
 
If a subject has experienced an improvement, this measure will be positive. If a subject has 
experienced a worsening in their condition, this measure will be negative.  
PASI90 is a binary variable equal to 1 if the percentage improvement from Baseline in the PASI 
scores is 90% or greater and 0 if the percentage improvement from Baseline is less than 90%. 
PASI90 is the 3rd endpoint in the sequential testing hierarchy (Table 7‒4). 
8.2.1.3 
SF-36 PCS: Change from Baseline at Week 16 
The SF-36 (Version 2, standard recall) is a 36-items generic health-related quality of life 
instrument that uses a recall period of 4 weeks.  Items are grouped into 8 domains as follows:  
• Physical Functioning (10 items) 
• Role Physical (4 items) 
• Bodily Pain (2 items) 
• General Health (5 items) 
• Vitality (4 items) 
• Social Functioning (2 items) 
• Role Emotional (3 items) 
• Mental Health (5 items) 
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 The concepts represented by these domains contribute to 
physical, mental, and social aspects of health-related quality of life. 
 In addition to domain scores, the PCS and MCS scores are calculated from the 8 domains 
(excluding the Health Transition item). Component scores reflect the impact of each domain on 
physical and mental health status. 
The norm-based T-scores for the 2 SF-36 component summary (PCS and MCS) and the 8 
domains are standardized with a mean of 50 and a standard deviation (SD) of 10 in the general 
US population (Maruish, 2011). An individual respondent’s score that falls outside the T-score 
range of 45 to 55 should be considered outside the average range for the US general population. 
When considering group-level data, a score below 47 should be considered indicative of 
impaired functioning within that health domain or dimension. Similar to individual respondent 
data, group mean scores of 47 or greater should be considered average or above average as 
compared to the general US population. Higher scores indicate a better health status. 
For the calculation of the SF-36 norm-based T-scores for the 8 domains and the PCS and MCS, 
the scoring software Optum’s PRO CoRE (version 1.4) will be used. The software uses updated 
2009 U.S. population norms and applies a Full Missing Score Estimation method as follows: 
• A health domain score (except the Physical Functioning domain) will be estimated provided 
that at least one 1 non-missing response is available within that domain.  
• For the Physical Functioning domain, item response theory will be used to develop a model 
for estimates of the missing score. 
• Regression methods will then be applied to estimate the PCS and MCS on the basis of the 
available domains. 
Change from Baseline at Week 16 in SF-36 PCS score is the 4th endpoint in the sequential testing 
hierarchy (Table 7‒4). 
8.2.1.4 
MDA at Week 16 
MDA is a state of disease activity deemed a useful target of treatment by both the subject and 
physician, given current treatment possibilities and limitations. The criteria that need to be met 
are based on key outcome measures in PsA and are shown below: 
• Tender Joint Count ≤1 
• Swollen Joint Count ≤1 
• PASI ≤1(for subjects with PSO involving at least 3% of BSA at Baseline) or BSA ≤3% 
• PtAAP (VAS) ≤15 mm  
• PGA-PsA (VAS) ≤20 mm  
• HAQ-DI ≤0.5 
• Tender enthesial points ≤1(LEI≤1) 
A subject has achieved MDA if 5 or more of the 7 above criteria are fulfilled. 
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The enthesitis instrument of the study (ie,: LEI) will be used to determine whether a subject has 
≤1 tender enthesial point.  
The following rule will be applied for subjects with BSA <3 at Baseline: Subjects with BSA <3 
at Baseline will always meet the criteria PASI ≤1 or BSA ≤3 except in the cases where a post-
Baseline BSA score >3 is observed.  
MDA at Week 16 is the 5th endpoint in the sequential testing hierarchy (Table 7‒4). 
8.2.1.5 
ACR20 and ACR70 response at Week 16 
The ACR20 and ACR70 responses are defined based on respectively 20% and 70% or greater 
improvement from Baseline in the same measures than the primary endpoint. See Section 8.1.1 
for details.  
8.2.1.6 
Proportion of subjects with an Investigator’s Global Assessment 
(IGA) score of 0 (clear) or 1 (almost clear) AND at least a 2-grade 
reduction from Baseline at Week 4 and Week 16 in the subset of 
subjects with psoriatic skin lesions at Baseline 
A static IGA for psoriasis will be used to assess disease severity in all subjects during the study. 
Investigator will assess the overall severity of PSO using the following 5-point scale specified in 
Table 8‒3 .  
Table 8‒3: 
Five-point IGA 
Score 
Short description 
Definition 
0 
Clear 
No signs of PSO; post-inflammatory hyperpigmentation may be 
present 
1 
Almost clear 
No thickening; normal to pink coloration; no to minimal focal 
scaling 
2 
Mild 
Just detectable to mild thickening; pink to light red coloration; 
predominately fine scaling 
3 
Moderate 
Clearly distinguishable to moderate thickening; dull to bright red, 
moderate scaling 
4 
Severe 
Severe thickening with hard edges; bright to deep dark red 
coloration; severe/coarse scaling covering almost all or all lesions 
    IGA=Investigator’s Global Assessment; PSO=psoriasis 
The IGA response is defined as clear [0] or almost clear [1] assessment with at least a two-grade 
category improvement from Baseline, meaning that this parameter will be only evaluable for 
subjects with psoriatic skin lesions (IGA score ≥2) at Baseline.  
Note that per protocol and device setting, only subjects with BSA ≥ 3% at Baseline will have 
IGA assessed at post-Baseline visits.  
For some subjects with BSA ≥ 3% at Baseline, IGA data have not been captured at Week 4 and 
Week 16 visits when BSA<3% at those visits. To address that, additional supportive analyses 
will be performed in which these subjects will be considered as IGA responders at the respective 
visit. 
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8.2.1.7 
Change from Baseline in the Patient’s Assessment of Arthritis Pain 
(PtAAP)  
The change from Baseline at Week 16 in PtAAP will be analyzed as described in Section 8.1.4.4. 
8.2.1.8 
Change from Baseline in PsAID-12 total score at Week 16 
The PsAID questionnaires measure the impact of disease on the subject. The impact of PsA is 
measured by weighting 12 different domains of health to derive a weighted summary score. The 
domains are pain, fatigue, skin problems, work and/or leisure activities, functional capacity, 
discomfort, sleep disturbance, coping, anxiety/fear/uncertainty, embarrassment and/or shame, 
social participation, and depression. The PsAID score is based on the relative importance of 
each of the domains. Each domain is answered based on a Numeric Rating Scales (NRS) scale 
ranging from 0 to 10.  
The equation for the PsAID-12 scores is as follows: 
𝑃𝑠𝐴𝐼𝐷−12 = 1
20 (3 × 𝑃𝑎𝑖𝑛+ 2 × 𝐹𝑎𝑡𝑖𝑔𝑢𝑒+ 2 × 𝑆𝑘𝑖𝑛+ 2 × 𝑊𝑜𝑟𝑘𝐿𝑒𝑖𝑠𝑢𝑟𝑒
⁄
+ 2 × 𝐹𝑢𝑛𝑐𝑡𝑖𝑜𝑛𝑛𝑎𝑙
+ 2 × 𝐷𝑖𝑠𝑐𝑜𝑚𝑓𝑜𝑟𝑡+ 2 × 𝑆𝑙𝑒𝑒𝑝+ 𝐶𝑜𝑝𝑖𝑛𝑔+ 𝐴𝑛𝑥𝑖𝑒𝑡𝑦+ 𝐸𝑚𝑏𝑎𝑟𝑟𝑎𝑠𝑠𝑚𝑒𝑛𝑡+ 𝑆𝑜𝑐𝑖𝑎𝑙
+ 𝐷𝑒𝑝𝑟𝑒𝑠𝑠𝑖𝑜𝑛) 
 
The total score ranges from 0 to 10 with higher scores indicating a worse impact of the disease. 
A score below 4 out of 10 is considered a subject-acceptable status. A change of 3 or more points 
is considered relevant absolute change. 
If one value (from the 12 domains) is missing, the missing value will be imputed in taking the 
mean value of the remaining (non-missing) domains, and the imputed value will be used to 
calculate the PsAID with the formula above. If two or more of the domains are missing, the 
PsAID score will be set to missing. 
8.2.1.9 
Psoriasis Area Severity Index 90 (PASI90) at Week 4 (in subjects with 
PSO involving at least 3% of BSA at Baseline) 
This variable will be derived as described in Section 8.2.1.2 .   
8.2.2 
Primary analysis of secondary efficacy variables 
The secondary efficacy variables will be analyzed for all subjects in the RS. 
As indicated in Table 7‒4, there are 4 secondary endpoints included in the testing hierarchy that 
will be tested in a chronological order until one is failed to be statistically significant.  
For the other secondary endpoints (which are not part of the testing hierarchy), the p-values 
produced by the statistical models will be considered nominal since these endpoints are not 
controlled for multiplicity. 
For the secondary composite and non-composite binary endpoints, the same estimand structure 
(composite estimand) as the one defined for the primary efficacy analysis of the primary efficacy 
endpoint (Section 8.1.2) will be used. The NRI approach for handling missing data and the same 
analysis model will be considered, and the analysis results will be presented similarly.  
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The statistical hypothesis for the binary variables at Week 16 is that the conditional odds ratio in 
the BKZ group compared with placebo treatment group is equal to 1. For the secondary 
continuous endpoints, the analysis will evaluate the hypothetical estimand as defined below: 
• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP.  
• Subject level outcome = variable as stated in Section 2.2.2     
• Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment prior to Week 16. A hypothetical strategy for addressing intercurrent events will be 
implemented. This estimand targets the treatment difference in a scenario where withdrawal 
from study treatment does not occur, such that outcomes for subjects without an IE are as 
observed, and outcomes for subjects with an IE are treated as though they had completed 
treatment through Week 16 but on placebo. A MI strategy will be used to impute any missing 
data and observed data after IE which will be set to missing prior to running MI. Such data 
will be imputed using Reference-Based MI, in which the MI model is based on data from the 
placebo group.  
• Population-level summary measure = the difference in the adjusted means between BKZ 
160mg Q4W and placebo. 
The same analysis model and imputation strategy for handling missing data as in Section 8.1.4.4 
will also be considered. The analysis results will be presented similarly as for this analysis on the 
individual ACR components. 
In the case of MDA as the response is based on 7 different component scores, it is necessary to 
consider various data scenarios that could impact the calculation of response. The rules described 
here are applicable in the context of the calculation of MDA response and may differ from the 
rules applied for calculating and summarizing the components individually (some values may 
need to be imputed for component analysis but are not required here to evaluate MDA response).  
The following rules will be applied to complete the derivation of MDA response based on the 
composite estimand definition: 
• If a given visit has been preceded by an IE (treatment discontinuation): 
o The endpoint at all subsequent visits (whether the data were observed or not) will be set 
to “nonresponse” as the subject has not met the criteria for response. 
• If a given visit has not been preceded by an intercurrent event: 
o If a subject satisfies at least 5 of the 7 MDA criteria, the subject is considered as MDA 
responder 
o If a subject does not satisfy at least 3 MDA criteria, the subject is considered as non- 
responder 
o In all other cases, the NRI approach will be applied.  
An overview table will combine the results of the primary analysis for the primary and secondary 
efficacy endpoints included in the testing hierarchy.  
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For the country specific analyses performed on subjects randomized in Japan, the region factor 
will net be considered as a covariate for the modelling. 
8.2.3 
Supportive analyses of the secondary efficacy variables  
As mentioned in Table 7‒2, the supportive analyses for all secondary variables will be performed 
using the modified composite estimand for binary variables (using MI-MCMC/monotone 
regression as in Section 8.1.4.3) and on OC.  
For PASI90, the MI will be run on the PASI score on subjects involving at least 3% of BSA at 
Baseline. 
For the MDA (and VLDA) MI analysis, subjects with BSA <3 at Baseline will always meet the 
criteria PASI ≤1 or BSA ≤3 except in the cases where a BSA score >3 is observed.  Subjects 
involving at least 3% of BSA at Baseline will have their BSA values imputed using MI when 
deriving MDA (VLDA). 
Additionally, subgroup analyses will be performed on the PASI90 response at Week 16 (in 
subjects with PSO involving at least 3% of BSA at Baseline) endpoint. Refer to Section 4.8 for 
the list of subgroups of interest. The same analysis method than the one used for the subgroup 
analysis of the primary endpoint will be performed. The results will be presented similarly.  
To assess the impact of the COVID-19 pandemic, the analysis of secondary efficacy endpoints 
with be repeated on the COVID-19-free Set using the primary analysis method. 
8.3 
Statistical analysis of other efficacy variables 
8.3.1 
Derivation of other efficacy variables 
The analysis of other efficacy variables will be performed in the two randomized treatment 
groups.  
8.3.1.1 
Time to ACR20, ACR50, ACR70 response from Baseline 
Time to a given response will be defined as the length in days from Baseline until the first date 
when the response is achieved.  
Time from Baseline to censoring will be considered for the following subjects:  
• Subjects who discontinue study treatment prior to achieving a response will be censored at 
the date of study treatment discontinuation.  
• Subjects who reach the end of treatment period visit without achieving the given response 
will be censored at the date of the end of treatment period visit (for the interim analysis, 
subjects who reached Week 16 without achieving the given response will be censored at that 
visit).   
8.3.1.2 
ACR20, ACR50 and ACR70 response 
Method for derivation of ACR50 can be found in Section 8.1.1. ACR20 and ACR70 will be 
derived similarly except that they will be based on a 20% and on 70% improvement from 
Baseline.  
ACR20, ACR50 and ACR70 responses will be analyzed at Week 4, 8, 12, and 16. 
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8.3.1.3 
PASI75, PASI90, and PASI100 response (in subjects with PSO 
involving at least 3% of BSA at Baseline) 
Method for derivation of PASI score can be found in Section 8.2.1.2. 
PASI75, PASI90, and PASI100 are binary variables equal to 1 if the percentage improvement 
from Baseline in the PASI scores is ≥ 75%, ≥90%, 100% and 0 if the percentage improvement 
from Baseline is < 75%, 90%, 100% respectively. 
For PASI75, PASI90, and PASI100, the PASI score and the change from Baseline for subjects 
with PSO involving at least 3% of BSA at Baseline will be analyzed at Week 4, 8, 12 and 16. 
8.3.1.4 
Composite endpoints composed of ACR50/PASI90 and 
ACR50/PASI100 response (in subjects with PSO involving at least 3% 
of BSA at Baseline) 
Composite endpoint composed of ACR50 and PASI90 is a binary variable equal to 1 for subjects 
responding to both ACR50 (ACR50=1) and PASI90 (PASI90=1). 
The composite endpoint will be equal to 0 if ACR50=0 or PASI90=0 regardless of whether any 
of the two endpoints is missing.  
The same rules as above will be applicable for the composite endpoint between ACR50 and 
PASI100. 
The composite endpoints will be missing if both endpoints are missing or if any of the two is 
missing and the other one equal to 1. Each endpoint (ACR50 and PASI90 or PASI100) will be 
imputed separately before deriving the composite endpoint. The composite endpoints for subjects 
with PSO involving at least 3% BSA at Baseline will be analyzed at Week 4, 8, 12 and 16. 
8.3.1.5 
Proportion of Psoriatic Arthritis Response Criteria (PsARC) 
responders 
The PsARC is based on the TJC (68 joints) and SJC (66 joints), the PGA-PSA and PhGA-PSA.  
The PsARC response is defined as improvement from Baseline in at least 2 of the 4 measures 
(TJC, SJC, PGA-PSA, PhGA-PSA) 1 of which must be TJC or SJC and no worsening from 
Baseline in any of the 4 measures:  
• improvement for TJC and SJC is defined as a reduction of ≥30%. Improvement of PGA-PSA 
and PhGA-PSA is defined as a reduction of the 100-point VAS of ≥20 points and, worsening 
is defined as an increase of and, 
• worsening for TJC and SJC is defined as an increase of ≥30%. Worsening for PGA-PsA and 
PhGA-PsA is defined as an increase of the 100-point VAS of ≥20. 
PsARC response will be analyzed at Week 4, 8, 12, and 16. 
8.3.1.6 
Psoriatic Arthritis Disease Activity Score (PASDAS) categories 
The PASDAS is a composite score that includes patient and physician global scores of skin and 
joint disease, SJC, TJC, LEI, tender dactylitis count (sum of tenderness scores), the physical 
component of the SF-36 Health Survey, and level of hs-CRP. PASDAS is calculated using the 
following equation:  
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𝑃𝐴𝑆𝐷𝐴𝑆= ((0.18 × √Physician global VAS) + (0.159 × √Patient global VAS )
− (0.253 × √SF36 PCS ) + (0.101 × LN(SJC + 1)) + (0.048 × LN(TJC + 1))
+ (0.23 × LN(LEI + 1)) + (0.377 × LN (Tender dactylitis count + 1))
+ (0.102 x LN(hs −CRP + 1) + 2)) × 1.5 
Note: LN=natural logarithm  
If Tender Dactylitis count is missing because LDI=0 at Baseline, Tender Dactylitis count will be 
replaced by 0 in the formula. 
If for any other reason a PASDAS component is missing, PASDAS will be set to missing. 
The following categories are used to define the level of disease activity:  
• Remission: PASDAS ≤1.9  
• Low disease activity: PASDAS >1.9 to <3.2 
• Moderate disease activity: PASDAS 3.2 to <5.4 
• High disease activity: PASDAS ≥5.4 
The PASDAS categories and the change from Baseline in PASDAS score will be analyzed at 
Week 4, 12, and 16. 
8.3.1.7 
MDA response  
Method for derivation of the MDA response can be found in Section 8.2.1.4.  
MDA response will be analyzed at Week 4, 8, 12, and 16. 
8.3.1.8 
Very Low Disease Activity (VLDA) response 
Like MDA, VLDA is a state of disease activity deemed a useful target of treatment by both the 
subject and physician, given current treatment possibilities and limitations.  
A subject is considered as having VLDA if all 7 of the criteria used for MDA and listed in 
Section 8.2.1.4 are fulfilled. If any of the 7 criteria is not met, then the subject is considered as 
non-responder. 
VLDA response will be analyzed at Week 4, 8, 12 and 16.  
8.3.1.9 
Proportion of subjects with an IGA score of 0 (clear) or 1 (almost 
clear) AND at least a 2-grade reduction from Baseline in the subset of 
subjects with psoriatic skin lesions at Baseline 
Method for derivation of this variable can be found in Section 8.2.1.6. 
The proportion of subjects with an IGA score of 0 (clear) or 1 (almost clear) AND at least a 2-
grade reduction from Baseline in the subset of subjects with psoriatic skin lesions at Baseline 
will be analyzed at Week 4, 8, 12 and 16. 
For some subjects with BSA ≥ 3% at Baseline, IGA data have not been captured at some post-
Baseline visits when BSA<3% at those visits. To address that, an additional supportive analysis 
will be performed in which these subjects will be considered as IGA responders at the respective 
visit. 
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In this context of this analysis, observed data for % of BSA affected by PSO will also be 
analyzed by visit using descriptive statistics. 
8.3.1.10 
Disease Activity Index for Psoriatic Arthritis (DAPSA) score 
categories, state and change from Baseline in DAPSA score 
Disease Activity Index for Psoriatic Arthritis is a composite score of patient global and pain 
VAS, TJC, SJC and hs-CRP that incorporates a pattern of peripheral arthritis that often is 
encountered in PsA. DAPSA score will be calculated as follows:  
𝐷𝐴𝑃𝑆𝐴=  𝑆𝐽𝐶+ 𝑇𝐽𝐶+ 𝑃𝐺𝐴−𝐴𝑟𝑡ℎ𝑟𝑖𝑡𝑖𝑠 (𝑉𝐴𝑆) + 𝑃𝑡𝐴𝐴𝑃 (𝑉𝐴𝑆) + ℎ𝑠−𝐶𝑅𝑃 
where: 
• SJC ranges from 0 to 66 
• TJC ranges from 0 to 68 
• PGA-Arthritis represents the patient’s global assessment of arthritis ranging from 0 to 10; 
0=best, 10=worst (using the unrounded VAS that ranges from 0 to 100 mm and dividing this 
value by 10) (Refer to Section 8.3.1.24).  
• PtAAP VAS ranges from 0 to 10 0=best, 10=worst (unrounded, by dividing the original 
value by 10) 
• hs-CRP in mg/L (no upper limit applied).  
DAPSA values will be categorized in the following disease activity states: 
• Remission (REM) (DAPSA ≤4), 
• Low Disease Activity (LDA) (DAPSA from >4 to ≤14), 
• Medium Disease Activity (MDA) (DAPSA from >14 to ≤28),  
• High Disease Activity (HAD) (DAPSA >28). 
For analyses with imputation of missing data, the imputed value for DAPSA will be based on the 
imputed values for the individual components. 
For OC analyses, if any individual component score is missing, the DAPSA score will be set to 
missing. 
DAPSA state, DAPSA scores and changes in scores from Baseline will be analyzed at Week 4, 
8, 12, and 16. 
8.3.1.11 
Change from Baseline in the Disease Activity Score -28 based on C-
reactive protein (DAS28[CRP]) 
The components for DAS28[CRP] include: 
• the TJC and SJC based on 28 joints (Section 8.1.1.1): 
− Upper extremity (26) - bilateral shoulders, elbows, wrists (includes radiocarpal, and 
carpal and carpometacarpal bones considered as a single unit), metacarpophalangeal 
joints I, II, III, IV, and V, thumb interphalangeals, proximal interphalangeal II, III, IV, 
and V. 
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− Lower extremity (2) - knees. 
• the PGA-Arthritis (ranging from 0 to 10 by dividing the original value by 10)  
• the hs-CRP (in mg/L) 
DAS28[CRP] is calculated as follows: 
𝐷𝐴𝑆28[𝐶𝑅𝑃] = 0.56 × √𝑇𝐽𝐶+ 0.28 × √𝑆𝐽𝐶+ 0.014 × 𝑃𝐺𝐴−𝐴𝑟𝑡ℎ𝑟𝑖𝑡𝑖𝑠 
+ 0.36 × ln(ℎ𝑠−𝐶𝑅𝑃+ 1) + 0.96 
For analyses with imputation of missing data, the imputed value for DAS28[CRP] will be based 
on the imputed values for the individual components. 
For OC analyses, if any individual component score is missing, then the DAS28 [CRP] score 
will be set to missing. 
The changes from Baseline in DAS28[CRP] will be analyzed at Week 4, 8, 12, and 16. 
8.3.1.12 
Change from Baseline in all individual ACR core components  
Individual ACR components (as listed in Section 8.1.1) are:  
 
• SJC, 
• TJC, 
• HAQ-DI,  
• PtAAP, 
• PhGA-PsA,  
• PGA-PsA, 
• hs-CRP. 
The change from Baseline (ratio from Baseline for hs-CRP) for each of the ACR components 
will be summarized at Week 4, 8, 12, and 16. 
8.3.1.13 
Enthesitis-free state based on the LEI and change in LEI from 
Baseline in the subgroup of subjects with enthesitis at Baseline 
The Leeds Enthesitis Index (LEI) is an index composed of 6 items, 3 for the right part and 3 for 
the left part of the body that measures the severity of enthesitis. The body parts are lateral 
epicondyles of the humerus, medial femoral condyle, and Achilles tendons. Each item is scored 
for pain with either 1 (painful) or 0 (no pain). The total score ranges from 0 (no enthesitis) to 6 
(severe enthesitis).  
Note that LEI is collected for all subjects regardless of their Baseline score. 
In case 4 items are missing, the LEI will be set to missing. If at least 3 items are available, the 
available items will be assessed and scored and then weighted by the number of the assessed 
items (AI) as shown in the formula below: 
𝐿𝐸𝐼= 𝑛× ∑
𝑠𝑐𝑜𝑟𝑒
𝑛
𝑖=1
∑
𝐴𝐼
𝑛
𝑖=1
 
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Note that n refers to the number of total items. 
Enthesitis-free state is based on LEI of 0, for subjects with enthesitis at Baseline (LEI>0). 
Analyses on LEI will be restricted to the subset of subjects with enthesitis at Baseline (defined as 
LEI score>0). 
The percentage of subjects with enthesitis free-state and the change from Baseline in LEI, in the 
subgroup of subjects with enthesitis at Baseline, will be analyzed at Week 4, 8, 12, and 16.  
While not a secondary endpoint, to support the pooled endpoint in PA0010, enthesitis free-state 
at Week 16 will be analyzed using the same analysis method as the primary analysis. 
8.3.1.14 
Enthesitis-free state based on the SPARCC index and change in 
SPARCC index from Baseline in the subgroup of subjects with 
enthesitis at Baseline 
The SPARCC index measures the severity of enthesitis through the assessment of 16 sites, 8 for 
the right part and 8 for the left part of the body: the greater trochanter (right/left), quadriceps 
tendon insertion into the patella (right/left), patellar ligament insertion into the patella and tibial 
tuberosity (right/left), achilles tendon insertion (right/left), plantar fascia insertion (right/left), 
medial and lateral epicondyles (right/left), and the supraspinatus insertion (right/left). Tenderness 
on examination is recorded as either present (1) or absent (0) for each of the 16 sites, for an 
overall score range of 0 (no enthesitis) to 16 (severe enthesitis). 
In case 9 or more items are missing, the SPARCC index will be set to missing. If at least 8 items 
are available, the available items will be assessed and scored and then weighted by the number of 
the assessed items as shown in the formula below: 
𝑆𝑃𝐴𝑅𝐶𝐶 𝑖𝑛𝑑𝑒𝑥= 𝑛×
∑
𝑠𝑐𝑜𝑟𝑒
𝑛
𝑖=1
∑
𝐴𝐼
𝑛
𝑖=1
 
where n refers to the number of total items, and AI the number of assessed items. 
Analysis of the change of SPARCC index at Week 16 from Baseline will be restricted to the 
subset of subjects with enthesitis at Baseline (defined as SPARCC >0). 
Enthesitis-free state based on SPARCC index is a status defined as subjects having achieved a 
SPARCC index score of 0 at Week 16. This endpoint represents the proportion of subjects with 
enthesitis at Baseline who achieve a SPARCC index score of 0 at Week 16.   
The percentage of subjects with enthesitis free-state and the change from Baseline in the 
SPARCC index (on the subgroup of subjects with enthesitis at Baseline) will be analyzed at 
Week 4, 8, 12, and 16. 
8.3.1.15 
Dactylitis-free state based on the LDI and change in LDI from 
Baseline in the LDI in the subgroup of subjects with dactylitis at 
Baseline  
The LDI measures the percent difference between the circumference of the affected digit and the 
circumference of the digit on the opposite hand or foot (referred to as the contralateral digit), 
where circumference is measured in millimeters. A minimum difference of 10% and the 
assessment of the investigator that the digit was affected by dactylitis will be used to define a 
dactylitis digit.  
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The percent difference between circumferences will be multiplied by a tenderness score (0 for 
the score using the binary tenderness non-tender, 1 for tender). This score using the binary 
tenderness score is referred to as the LDI basic. The results from each digit with dactylitis will 
then be summed to produce a final LDI score.  
Table 8‒4 provides the comparison, if matching digits are thought to be involved. 
Table 8‒4: 
Normative values for LDI 
 
Digit 
Men 
Women 
Hand 
Thumb 
70 
58 
Index 
63 
54 
Middle 
63 
54 
Ring 
59 
50 
Little 
52 
44 
Foot 
Great toe 
82 
72 
Second 
52 
46 
Middle 
50 
44 
Fourth 
50 
44 
Little 
52 
45 
The following rules will be applied for the LDI calculation in case of unclear data.  
• Circumferences of 0 will be considered as missing. Circumferences <15 will be assumed to 
be in cm instead of mm and will be multiplied by 10 before being used in 
summaries/analyses. 
• If both digits of a given pair are recorded as affected, then each digit will be compared to the 
normative value (shown in the above table). Note that if both comparisons result in a 
difference ≥10%, then both digits will contribute to the final LDI score. 
• If the circumference of the affected digit is smaller than the unaffected digit, then the LDI 
will be calculated by comparing the smaller digit to the normative value.  
• If a digit is recorded as affected and the circumference of the contralateral digit is missing, 
the normative value will be used for comparison with the affected digit. 
• If a digit is selected but recorded as ‘not affected’ but has circumference and contralateral 
circumferences collected, a missing tenderness score will be considered as 1. 
• If the investigator did not complete the LDI questionnaire at Baseline, it will be assumed that 
no digits were affected (ie, a LDI score of 0 will be assigned).  
Dactylitis-free state is based on a Leeds Dactylitis Index (LDI) of 0, for subjects with dactylitis 
at Baseline (LDI>0). Analyses will be restricted to the subset of subjects with dactylitis at 
Baseline (defined as LDI score>0). 
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Note: A tender dactylitis count will be calculated as the sum of the tenderness scores for all 
digits and will be used for the PASDAS score calculation (Section 8.3.1.6 ). 
The percentage of subjects with dactylitis free-state and the change from Baseline in LDI (on the 
subgroup of subjects with dactylitis at Baseline) will be analyzed at Week 4, 8, 12, and 16. 
While not a secondary endpoint, to support the pooled endpoint in PA0010, dactylitis free-state 
at Week 16 will be analyzed using the same analysis method as the primary analysis. 
8.3.1.16 
Change from Baseline in the Bath Ankylosing Spondylitis Disease 
Activity Index (BASDAI) in the subgroup of subjects with axial 
involvement defined by a score of ≥4 at Baseline 
The BASDAI measures the disease activity of ankylosing spondylitis. The BASDAI is a 
validated self-reported instrument which consists of 6 horizontal NRSs, each with 10 units to 
measure the severity of the following 5 major symptoms over the last week: fatigue, spinal pain, 
peripheral joint pain and swelling, enthesitis, and morning stiffness (both severity and duration) 
over the last week.  
To give each symptom equal weighting, the average of the 2 scores relating to morning stiffness 
is taken. The resulting 0 to 50 sum score is divided by 5 to give a final BASDAI score between 0 
and 10, with lower scores indicating lower disease activity.  
The BASDAI is calculated as follows: 
𝐵𝐴𝑆𝐷𝐴𝐼=
𝑄1 + 𝑄2 + 𝑄3 + 𝑄4 + (𝑄5 + 𝑄6
2
)
5
 
where Q1 – Q6 are the six questions from the BASDAI questionnaire. 
If 1 of the 2 morning stiffness measurements (ie, questions: “How would you describe the overall 
level of morning stiffness you have had from the time you wake up?” and “How long does your 
morning stiffness last from the time you wake up?”) is missing, the other one will be used for the 
morning stiffness calculation.  
If one major symptom of the BASDAI is missing, the total score of the remaining symptoms will 
be divided by the number of symptoms assessed. If more than one major symptom is missing, the 
total BASDAI score will be set to missing. 
Analyses will be restricted to the subset of subjects with axial involvement at Baseline (defined 
as BASDAI score of ≥4). 
Change from Baseline in BASDAI will be analyzed for subjects with axial involvement at 
Baseline (BASDAI≥4) at Week 4, 8, 12, and 16. 
8.3.1.17 
Change from Baseline in the modified Nail Psoriasis Severity Index 
(mNAPSI) score at Week 4, 8, 12 and 16 in the subgroup of subjects 
with psoriatic nail disease at Baseline 
Subjects with psoriatic nail disease will have a target nail selected at the Baseline Visit for 
evaluation using the mNAPSI. The nail selected should be the most affected nail observed at 
Baseline and should be the only one assessed throughout the study. The target nail will be scored 
(from 0 to 3) for onycholysis/oil drop dyschromia, nail plate crumbling, and pitting and will be 
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scored (0 for “no” or 1 for “yes”) for leukonychia, nail bed hyperkeratosis, splinter hemorrhages, 
and red spots in the lunula. The total score (also called the mNAPSI score) will then range from 
0 to 13 with higher scores indicative of more severe nail disease. 
If any of the 7 response items that contribute to mNAPSI is present, while other items are 
missing (ie, partial mNAPSI data), then the missing items are assumed to be 0 for the mNAPSI 
calculation. In some cases, the data may be captured in such a way that only non-zero component 
scores are present in the database. Again, those components that are not present are simply 
assumed to be 0 for the mNAPSI calculation 
Analyses will be restricted to the subset of subjects with psoriatic nail disease at Baseline 
(defined as mNAPSI score>0). 
Change from Baseline in mNAPSI and mNAPSI resolution (mNAPSI=0 at post-Baseline 
assessments) will be analyzed for subjects with psoriatic nail disease at Baseline (mNAPSI 
score>0) at Week 4, 8, 12, and 16. 
8.3.1.18 
Change from Baseline in PsAID-12 total score 
The PsAID questionnaires measure the impact of disease on the subject. The impact of PsA is 
measured by weighting 12 different domains of health to derive a weighted summary score. The 
domains are pain, fatigue, skin problems, work and/or leisure activities, functional capacity, 
discomfort, sleep disturbance, coping, anxiety/fear/uncertainty, embarrassment and/or shame, 
social participation and depression. The PsAID score is based on the relative importance of each 
of the domains. Each domain is answered based on a numeric rating scale ranging from 0 to 10. 
The equation for the PsAID-12 score is as follows: 
𝑃𝑠𝐴𝐼𝐷−12 = 1
20 (3 × 𝑃𝑎𝑖𝑛+ 2 × 𝐹𝑎𝑡𝑖𝑔𝑢𝑒+ 2 × 𝑆𝑘𝑖𝑛 𝑃𝑟𝑜𝑏𝑙𝑒𝑚𝑠+ 2 × 𝑊𝑜𝑟𝑘𝐿𝑒𝑖𝑠𝑢𝑟𝑒
⁄
+ 2 × 𝐹𝑢𝑛𝑐𝑡𝑖𝑜𝑛𝑎𝑙 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦+ 2 × 𝐷𝑖𝑠𝑐𝑜𝑚𝑓𝑜𝑟𝑡+ 2 × 𝑆𝑙𝑒𝑒𝑝 𝐷𝑖𝑠𝑡𝑢𝑟𝑏𝑎𝑛𝑐𝑒+ 𝐶𝑜𝑝𝑖𝑛𝑔
+ 𝐴𝑛𝑥𝑖𝑒𝑡𝑦/𝐹𝑒𝑎𝑟+ 𝐸𝑚𝑏𝑎𝑟𝑟𝑎𝑠𝑠𝑚𝑒𝑛𝑡/𝑆ℎ𝑎𝑚𝑒+ 𝑆𝑜𝑐𝑖𝑎𝑙 𝑃𝑎𝑟𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑖𝑜𝑛+ 𝐷𝑒𝑝𝑟𝑒𝑠𝑠𝑖𝑜𝑛) 
 
The total score also ranges from 0 to 10 with higher scores indicating a worse impact of the 
disease. A score below 4 out of 10 is considered a subject-acceptable status. A change of 3 or 
more points is considered relevant absolute change. 
If 1 value (from the 12 domains) is missing, the missing value will be imputed in taking the 
mean value of the remaining (non-missing) domains, and the imputed value will be used to 
calculate the PsAID with the formula above. If 2 or more of the domains are missing, the PsAID 
score will be set to missing 
The proportion of subjects achieving a total score of PsAID-12 ≤ 4 - Patient Acceptable 
Symptom State (PASS), the proportion of subjects achieving a decrease of 3 or more points from 
Baseline on the total score (for subjects with minimal score of 3 at Baseline), the change from 
Baseline in the total score and in the individual scores for each PsAID-12 domains, will be 
analyzed at Week 4, 12, and 16 (the proportion of subjects achieving PASS will also be analyzed 
at Baseline). 
8.3.1.19 
Change from Baseline in the Psoriatic Arthritis Quality of Life 
(PsAQoL) total score 
PsAQoL is a disease specific Health-Related Quality of Life questionnaire comprised of 20 
items. Each item is scored as 0 for “not true” or 1 for “true”, so that the score ranges from 0 to 20 
with higher scores indicating worse health-related quality of life.  
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If 6 or less item responses are missing, the missing responses will be imputed with the mean of 
available responses to calculate a total score. If more than 6 items responses are missing, the total 
score will be left missing. 
Change from Baseline in PsAQoL total score will be analyzed at Week 4, 12, and 16. 
8.3.1.20 
Change from Baseline in the SF-36 PCS and MCS scores, as well as 
the 8 domain scores (Physical Functioning, Role Physical, Bodily 
Pain, General Health, Vitality, Social Functioning, Role Emotional, 
and Mental Health) 
Scoring instructions of SF-36 norm-based T-scores for the 8 domains and the SF-36 PCS and 
MCS are described in Section 8.2.1.3. 
Change from Baseline in SF-36 individual domain scores, MCS and PCS scores will be analyzed 
at Week 4, 12, and 16. 
8.3.1.21 
Change from Baseline in Functional Assessment of Chronic Illness 
Therapy (FACIT) – Fatigue subscale score 
The FACIT-Fatigue is 40-item measure that assesses self-reported fatigue and its impact upon 
daily activities and function over the past 7 days. The scale consists of 5 subscales (physical 
well-being, social/family well-being, emotional well-being, functional well-being, and fatigue). 
The fatigue subscale is the only one used in this study. It is composed of 13 items, all scored 
from 0 (Not at all) to 4 (Very much). The FACIT-fatigue subscale score ranges from 0 to 52 with 
0 being the worst possible score and 52 being the best possible score. To obtain a score from 0 to 
52, all negatively worded questions have to be recoded, so that responses range from worst (0) to 
the best (4) outcome. 
Items 1 to 6, and 9 to 13 are negatively framed questions for which the coding needs to be 
reversed before deriving the score. 
The FACIT-Fatigue subscale score is obtained by summing up the responses of all reversed / non 
reversed items with equal weight. In cases where some answers are missing, a total score is re-
scaled from the score of the answered items, so long as more than 50% of the items (ie, at least 7 
of 13) were answered. 
The formula to derive the FACIT-Fatigue subscale score is then: 
𝐹𝐴𝐶𝐼𝑇−𝐹𝑎𝑡𝑖𝑔𝑢𝑒 𝑠𝑢𝑏𝑠𝑐𝑎𝑙𝑒= 13 𝑥 
∑𝑆𝑐𝑜𝑟𝑒 𝑜𝑓 𝑖𝑡𝑒𝑚𝑠
𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑖𝑡𝑒𝑚 𝑎𝑛𝑠𝑤𝑒𝑟𝑒𝑑  
The minimum clinically-important difference for FACIT-Fatigue subscale in patients with PsA 
was determined to be a 4-point positive change. 
Change from Baseline in FACIT-Fatigue subscale score as well as the proportion of FACIT-
Fatigue subscale responders (subjects with minimum clinically-important difference for FACIT-
Fatigue subscale score, defined as an increase of ≥4) in subjects with FACIT-Fatigue subscale 
score ≤48 at Baseline will be analyzed at Week 4, 12, and 16. 
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8.3.1.22 
Change from Baseline in Work Productivity and Activity Impairment 
Questionnaire–Specific Health Problem (WPAI-SHP) v2.0 adapted to 
PsA scores 
The WPAI-SHP is a subject-reported questionnaire that assesses subject’s employment status, 
work absenteeism, work impairment while working, overall work, and daily activity impairment 
attributable to a specific health problem.  
Five out of 6 items of the WPAI-SHP are regrouped into the 4 dimensions (absenteeism, 
presenteeism, work productivity and activity impairment) with scores expressed as percentage, 
where higher numbers indicate greater impairment and less productivity (ie, worse outcomes) as 
described in the WPAI-SHP scoring rules. 
The scoring rules for the WPAI-SHP are as follows: 
Scores:  
• Percent work time missed due to problem from the target disease:  
𝑄2 ℎ𝑜𝑢𝑟𝑠
𝑄2 ℎ𝑜𝑢𝑟𝑠+ 𝑄4 ℎ𝑜𝑢𝑟𝑠∗100  
• Percent impairment while working due to problem from the target disease:  
𝑄5 score 
10
∗100  
• Percent overall work impairment due to problem from the target disease:  
[
𝑄2 hours
𝑄2 ℎ𝑜𝑢𝑟𝑠+ 𝑄4 ℎ𝑜𝑢𝑟𝑠+ (1 −
𝑄2 hours
𝑄2 ℎ𝑜𝑢𝑟𝑠+ 𝑄4 ℎ𝑜𝑢𝑟𝑠) ∗𝑄5 score
10
] ∗100  
• Percent activity impairment due to problem from the target disease:  
𝑄6 score 
10
∗100  
In order to make data consistent and amenable to statistical analysis, the following counting rules 
will be applied to handle out of range and ambiguous answers of the WPAI-SHP. These rules 
will be applied prior to conducting any type of statistical analysis of the data. Due to the inter-
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relation between certain questions of the WPAI-SHP, the priority order for implementing these 
specific counting rules is as in the listed order below. 
• Employment status: 
− If (Q1=missing) and (Q2>0 or Q3>0 or Q4>0), then Q1=YES. 
• Hours missed due to psoriatic arthritis: 
− If Q1 = NO, then Q2 = missing. 
− If (Q2 =0 or missing) and Q1 = missing, then Q2=missing.  
• Hours missed due to other reasons: 
− If Q1 = NO, then Q3 = missing. 
− If (Q3 =0 or missing) and Q1 = missing, then Q3=missing.  
• Hours actually worked: 
− If Q1 = NO, then Q4 = missing. 
− If (Q4 =0 or missing) and Q1 = missing, then Q4=missing. 
• Work productivity: 
− If Q1 = NO, then Q5 = missing. 
− If (Q5 =0 or missing) and Q1 = missing, then Q5=missing. 
− If Q4=0, then Q5 = missing. 
In the listings, the original values will be kept and displayed. 
 
WPAI-SHP scores are based on 1-item (presenteeism, activity impairment), 2-items 
(absenteeism) and multiple items (overall work productivity). A score cannot be calculated if 
there is a missing response to the corresponding item.   
A negative number will indicate a reduction in the score/improvement for subjects. 
The change from Baseline score is derived as post Baseline score minus Baseline score.  A 
negative change score indicates a reduction in the score/improvement for the subject. 
The change from Baseline in scores will be analyzed at Week 12 and 16. 
The analysis of WPAI-SHP scores will be performed on OC only. 
8.3.1.23 
Responses to the EuroQol-5D-3-Level (EQ-5D-3L) dimensions, 
change from Baseline in VAS score 
The Euro-Quality of Life 5-Dimensions 3 Level (EQ-5D-3L) version health questionnaire 
provides a descriptive profile and a single index value for health status (using a VAS).  
The instrument is composed of a 5-item health status measure (mobility, self-care, usual 
activities, pain/discomfort, anxiety/depression) and a VAS. Each of the 5 health states is divided 
into 3 levels (no problem, some or moderate problems, and extreme problems) and is scored as 1, 
2, and 3, respectively. These scores are referred as “utility scores”. 
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The EQ-5D VAS records the respondent’s self-rated health status on a vertical 20 cm visual 
analogue scale, graduated from 0 to 100 (0=worst imaginable health status, 100=best imaginable 
health status).  
The response in each of the 5 items of the EQ-5D-3L and the values and the changes in VAS 
from Baseline will be presented at Week 4, 12, and 16.  
8.3.1.24 
Change from Baseline in Patient’s Global Assessment of Arthritis 
(PGA-arthritis) and Physician’s Global Assessment of Arthritis 
(PhGA-Arthritis) 
The physician’s global assessment of arthritis (PhGA-Arthritis) and the patient’s global 
assessment of arthritis (PGA-Arthritis) are clinical outcomes based on visual analog scales 
(VAS) ranged from 0 to100 (in mm).  
• PGA-Arthritis: Subjects will assess the impact of their arthritis pain in answering the following 
question “Considering all the ways your arthritis affects you, please mark a vertical line on the 
scale below to show how you are feeling today.” The subject should be asked to consider their 
arthritis symptoms and functional capacity in their response to this question. Subjects will score 
PGA-Arthritis in using a VAS where 0 is “very good, no symptoms” and 100 is “very poor, 
severe symptoms.” 
• PhGA-Arthritis: The investigator will assess how the subject’s overall arthritis appears at the 
time of the visit using a numerical rating scale where 0 is “very good” and 100 is “very poor”. 
This assessment will be based through the following question: “The Patient’s arthritis at this time 
is: “Please mark a vertical line on the scale below to assess the overall status of the subject's 
arthritis signs and symptoms and the functional capacity of the subject.” 
Values and changes from Baseline in PhGA-Arthritis and PGA-Arthritis will be analyzed at 
Week 4, 8, 12, and 16.  
8.3.1.25 
Proportion of subjects with a decrease of HAQ-DI from Baseline of at 
least 0.35 in the subgroup of subjects with Baseline HAQ-DI≥0.35  
The proportion of HAQ-DI responders (subjects with a decrease of HAQ-DI from Baseline of at 
least 0.35 for subjects with HAQ-DI≥0.35 at Baseline) will be analyzed at Week 4, 8, 12, and16. 
In addition, subgroup analyses will be performed on the HAQ-DI response at Week 16. Refer to 
Section 4.8 for the list of subgroups of interest. The same analysis method used for the subgroup 
analysis of the primary endpoint will be performed and the results will be presented similarly. 
8.3.2 
Analyses of other efficacy endpoints 
Unless specified above, all other efficacy variables will be analyzed for all subjects in the RS.  
8.3.2.1 
Time to ACR20/50/70 response  
Each time to ACR20/50/70 response will be estimated and presented using the Kaplan-Meier 
(KM) product-limit method for each treatment group. 1- KM estimates will be presented in 
tables.  
The KM plots of time to ACR20,50,70 response will be presented by treatment group. The line 
will start at 0 and will increase over time, representing time to achieving the response. 
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The median time to response, including the 2-sided 95% CI, will be calculated for each treatment 
group. Comparisons of BKZ versus placebo will be analyzed using a log-rank test stratified by 
region and prior TNFα inhibitor exposure (considering that the same stratification factors were 
retained for the primary efficacy analysis). This comparison will be performed using PROC 
LIFETEST on subjects from both treatment groups. The hazard ratio as well as the 
corresponding 95% CI and p-value will be displayed (using PROC PHREG stratified by region 
and prior TNFα inhibitor exposure at Baseline).  
 
The time to ACR20/50/70 endpoints will be analysed using the OC data. 
8.3.2.2 
Other endpoints (excluding time to ACR20/50/70 response)  
For the binary variables, the following estimand structure (composite estimand) will be defined: 
• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP 
• Subject-level outcome = The given variable and time point being summarized  
• Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment prior to the time point being summarized. A composite strategy will be 
implemented in which a positive clinical outcome is defined as achieving the given variable 
at the specified time point and not having an intercurrent event through that time point. 
• Population-level summary measure = Unadjusted proportion of responder. 
Subjects who have an IE which will be considered associated to a treatment failure and thus 
considered as non-responders. Any missing data will also be considered as nonresponders (NRI 
approach). For categorical variables, the worst category will be imputed similarly instead of non-
response. 
For the continuous variables, the following estimand structure (hypothetical estimand) will be 
defined: 
• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP 
• Subject-level outcome = The given variable and time point being summarized  
• Intercurrent event handling = An IE is defined as discontinuation of study treatment prior to 
the time point being summarized. A hypothetical strategy will be implemented in which 
outcomes for subjects without an IE are as observed at the given time point, and outcomes 
for subjects with an IE are treated as though they had completed the randomized study 
treatment through the time point being summarized. A MI strategy will be used to impute 
data following an IE. 
• Population-level summary measure = Unadjusted mean. 
The other efficacy variables will also be summarized based on OC and the modified composite 
estimand (for binary variables) and summarized by visit for the 2 treatment groups as detailed 
below: 
For binary endpoints using:  
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• The number and proportion of responders using the NRI approach 
• The mean proportion of responder in the multiple imputed data sets and the 95% CI 
(modified composite estimand) 
• The observed number and proportion of responder on subjects with observed data.  
For categorical endpoints (ie, EQ-5D-3L dimensions score, DAPSA state, PASDAS categories) 
using:  
• The number and percentage by endpoint category using the NRI approach (as performed for 
the primary analysis of the primary endpoint with the exception that the worst category for 
the imputation = Worst Category imputation) 
• The mean percentage and corresponding 95% CI by endpoint category in the multiple 
imputed data sets (modified composite estimand). Regardless of imputed values, value of the 
categorical endpoint after IE are by default set to the worst category (ie, High Disease 
Activity for DAPSA state) 
• The observed number and percentage by endpoint category on subjects with observed data. 
For continuous endpoints, on absolute values and changes from Baseline (or ratio from Baseline 
for hs-CRP) using: 
• The mean (with geometric mean for hs-CRP and it 95% CI), SE, median, minimum, and 
maximum in the multiple imputed data sets (hypothetical estimand) (except for WPAI-SHP 
scores) 
• The observed number of observations (n), the mean (with the geometric mean for hs-CRP), 
SD, Median, CV (geometric CV for hs-CRP), minimum and maximum. 
For ACR20, ACR50, ACR70, PASI75, PASI90, and PASI100 responders over time, a line plot 
by treatment group will be produced. 
8.3.2.3 
Additional statistical analysis for other efficacy endpoints  
Although statistical testing is not planned for other efficacy variables as per protocol, for selected 
other efficacy variables, it is of interest to perform statistical testing and calculate inferential 
statistics. The associated p-values will be considered nominal and not controlled for multiplicity. 
For continuous variables, the MI-MCMC/monotone regression approach will be applied for the 
imputation model on the change from Baseline (hypothetical estimand). The analysis model will 
be based on ANCOVA with fixed effect of treatment, region, and prior TNFα inhibitor exposure 
and Baseline value as covariates. 
For responder variables, the analysis will follow the NRI approach (composite estimand). The 
analysis model will be based on a logistic model with fixed effect for treatment and prior TNFα 
inhibitor exposure at Baseline and region as stratification variables.    
Below is a list of other secondary efficacy variables for which these nominal p-values (with the 
timepoints in parentheses) will be calculated.  
The results of these inferential tests (LSM differences for continuous variables, OR for binary 
variables, along with 95% CI and p-value) will be presented in a single table:  
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For the following endpoints, the p-value provided (based on the change from Baseline for 
continuous variables) will be based on the comparison of the 2 treatment groups using the same 
statistical methods for binary variables as used for the primary analysis of ACR50 (Section 8.1.2) 
and for continuous variables as used for the analysis of ACR components (Section 8.1.4.4): 
• ACR20/50/70 (Week 4, 8, 12, 16) 
• PASI75/90/100 (Week 4, 8, 12, 16) 
• ACR50/PASI90 composite (Week 4, 8, 12, 16) 
• ACR50/PASI100 composite (Week 4, 8, 12, 16) 
• TJC (Week 4, 8, 12, 16) 
• SJC (Week 4, 8, 12, 16) 
• MDA (Week 4, 8, 12, 16) 
• PtAAP (Week 4, 8, 12, 16) 
• PsAQoL (Week 4, 12, 16) 
• PsAID-12 (Week 4, 12, 16) 
• FACIT-Fatigue subscale (Week 4, 12, 16) 
• WPAI-SHP (Week 12, 16) (on observed data) 
• DAPSA (Low Disease Activity or better) “response” (Week 4, 8, 12, 16)  
• PsARC Response (Week 4, 8, 12, 16) 
9 
PHARMACOKINETICS AND IMMUNOLOGICAL 
(IMMUNOGENICITY) ANALYSES 
9.1 
Pharmacokinetics  
Pharmacokinetic variables will be analyzed for all subjects in the PK-PPS.  
Only subjects treated with BKZ will be included in the PK analyses. The Baseline observation 
for the Placebo group will be the Week 16 pre-dose observation. PK variables will be 
summarized at each scheduled visit under the “BKZ 160mg Q4W” column. BKZ concentrations 
will also be summarized similarly for the subgroup of Japan. 
No imputation will be used for missing samples. However, if plasma concentration 
measurements are below the level of quantification (BLQ), then for the calculation of the derived 
statistics, the result will be set to ½ of LLOQ (ie, 1/2*0.250 = 0.125ug/mL). Descriptive statistics 
including number of values, geometric mean, its 95% CI, geometric CV, mean, SD, median, 
minimum, and maximum. Geometric mean and its 95% CI, geometric CV, mean and SD will be 
calculated if applicable will be calculated if at least ⅔ of the values of interest is above the 
LLOQ and number of values>=3; otherwise, only number of values, median, minimum, and 
maximum will be presented. 
In addition, geometric mean of BKZ plasma concentration time curves (with its 95% CI) will be 
plotted on linear and semi-logarithmic scales for all subjects dosed with 160mg Q4W.  
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The table summaries and figures will be primarily repeated by anti-BKZ antibody status 
(positive, negative, or missing) for the total BKZ 160mg Q4W concentration data. The Missing 
group will not be displayed if ≥95% of subjects are categorized in the non-missing groups.  
The ADAb status (positive, negative, or missing) will be considered in a cumulative manner at 
each time point: 
−  a subject will be counted as positive from the first visit at which the subject achieved a 
positive ADAb sample result to the end of the treatment period (regardless of any 
missing/inconclusive or negative ADAb sample result).  
− If a subject has only negative ADAb samples or only one missing/inconclusive sample 
with negative ADAb samples up to that timepoint, the subject will be classified as 
negative. An exception remains for the Baseline Visit where only one sample could be 
available. If the sample is missing/inconclusive, then the sample will be classified as 
being negative for the cumulative ADAb status. 
− Otherwise, the subject will be classified in the missing ADAb category. 
In addition, the table summaries and figures will be repeated by neutralizing anti-bimekizumab 
antibodies (NAb) status (ADAb negative, NAb positive, ADAb positive / NAb negative, 
missing, Section 9.2.2). Tables and figures will be generated for concentration data up to weeks 
16. For these tables and figures: the NAb status will be determined on a subject-level basis (ie 
not on a visit level) according to the categories in Section 9.2.2. For BKZ160mg Q4W dose 
group: the NAb status will be determined based on data from the Baseline visit (pre-dose sample 
on study day 1) up to Week 16 NAb sample (eg if a subject has no positive NAb samples for 
IL17AA or IL17F from Baseline up to Week 16, that subject will be assigned a NAb negative 
status for all visits of the initial treatment period). 
The NAb status will be re-derived and updated with SFU data for the final study analysis, 
followed by an update to the relevant tables and figures. 
PK samples collected at scheduled visits (except the SFU visit) and meeting the following 
requirements will be included in summaries and corresponding figures. Samples not meeting the 
following requirements will be excluded: 
• For PK samples associated with the ET visit: include samples collected >14 days and <42 
days after the last/previous dose received 
• For PK samples associated with all other visits (Week 4, 8, 12, 16):  include samples 
collected >14 days after the preceding dose, <42 days after the preceding dose, and no later 
than 1 hour after the current visit dose including unscheduled assessments as described in 
Section 3.1.    
• For the SFU visit, all concentrations obtained at the SFU visit will be included in the 
summary tables but will not be included in the figures. 
When multiple samples meeting the criteria above are associated with the same visit (either 
because multiple samples were collected or due to remapping or unscheduled visits), only results 
from one valid sample will be included in summaries and figures using the following rules. All 
others will be excluded and only listed:  
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• For PK samples with different dates, the sample that is closest to the target visit date will be 
included.  For samples with different dates that are the same distance to the target visit date, 
the sample collected prior to IMP dosing will be included. 
• For PK samples with the same date, the first sample as provided in the raw data will be 
included. 
The BKZ concentrations will also be listed for all subjects in the SS. All concentrations will be 
listed as received, prior to substitution of any BLQ values. The listing will include flags for 
concentrations that were excluded from the summary statistics where the reason for exclusion 
will be one or more of the following: 
• Dosing performed out of window 
− Sample collected out of window relative to current dose: for PK samples associated with 
visits other than ET, or SFU: includes samples >1 hour after the current visit dose 
− Sample collected out of window relative to previous dose: For PK samples associated 
with all visits except SFU visit; include samples collected <14 days or >42 days after the 
previous dose received 
− More than 1 sample obtained at the same visit: includes all samples excluded due to 
multiple valid samples associated with a visit. 
 
All plasma concentration data will be reported in ug/mL in the tables, figures, and listings. 
If more than 10% of the PK concentration results have been excluded from the table summaries, 
the PK excluded results will be listed in a separate listing. 
9.2 
Immunological (immunogenicity) analyses 
9.2.1 
Anti-bimekizumab antibody 
ADAb will be assessed using a 3-tiered assay approach: screening, confirmatory and titration 
assay. Samples confirmed as positive within the confirmatory assay will be further evaluated for 
the presence of NAb specific to binding of bimekizumab to IL-17AA, IL-17FF or both. 
ADAb (including positivity) will be summarized by BKZ treatment at each scheduled visit at 
which samples are collected. 
Screening, confirmatory and titer cut points of the respective assays will be determined by the 
bioanalytical laboratory based either on commercially available drug-naïve samples or on the 
pre-dose samples of a given study. The relevant statistical reports will be provided as part of the 
bioanalytical reports. ADAb samples are analyzed on the SS, but are not analyzed when subjects 
are on a treatment other than BKZ. Subjects assigned to the placebo arm will have only their 
Baseline (study day 1) and Week 16 samples analyzed for ADAb.  
The Screening cut point will be used to determine the ADAb status in the test sample as 
“Positive Screen” (PS) or “Negative Screen” (NS). For samples presenting anti-BKZ antibody 
levels that are PS, further confirmatory assay will be performed, and the result of which will be 
reported as either “Positive Immunodepletion” (PI) or “Negative Immunodepletion” (NI). 
ADAb status for each visit will be derived as follows:  
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− Samples that are either NS or PS and NI will be defined as ADAb negative. 
− Sample values that are either NS or PS and NI and where the BKZ concentration exceeds 
the validated ADAb assay drug tolerance limit (200 μg/mL) will be defined as 
inconclusive.  
− Sample values that are PS and PI will be defined as ADAb positive (regardless of 
availability of a titer value) 
− Missing if it does not go into one of the above categories. 
PI samples will be titrated, and the ADAb titer (reciprocal dilution factor including MRD) 
reported. The PI samples will also be subject to a neutralizing assay to evaluate whether the anti-
BKZ antibody neutralizes the target binding of bimekizumab (IL17A or IL17F or both) in-vitro. 
The following rule will be implemented for by-visit ADAb summaries where applicable: 
− If the ADAb sample is collected within ±14 days (inclusive) relative to the visit date at 
which the drug was administered (or ±14 days from a scheduled visit at which dosing 
was not performed), the ADAb result for that sample will be associated with the 
scheduled visit and summarized accordingly. This will include unscheduled assessments 
(if a dose was administered at an unscheduled visit). Samples collected outside this 
window will be excluded from the by-visit ADAb summaries and will be listed only. 
The rule above will apply to by-visit summaries only; all other summaries of ADAb status will 
use all available data (scheduled and unscheduled). This rule will not apply for the ET or SFU 
visits. Thus, all ADAb data obtained at these visits will be included in the by-visit summaries. 
In addition, the anti-BKZ antibody status will be further classified as outlined below: 
• Category 1: Pre ADAb negative – treatment emergent ADAb negative: Includes subjects 
who are negative at Baseline and antibody negative at all sampling points post treatment 
(including SFU), one post-baseline missing/inconclusive sample is allowed for subjects with 
pre-ADAb negative sample. This group also includes subjects who have 
missing/inconclusive pre-treatment sample (eg, either missing/inconclusive or insufficient 
volume) at baseline with all post-Baseline samples as ADAb negative. 
• Category 2: Pre ADAb negative – treatment emergent ADAb positive: Includes subjects 
who are negative at Baseline and antibody positive at any sampling point post treatment 
(including SFU). This group also includes subjects who have a missing pre-treatment sample 
(either missing or insufficient volume) at Baseline with one or more ADAb positive post-
treatment samples. 
• Category 3: Pre ADAb positive – treatment emergent reduced ADAb: Includes subjects 
who are positive at Baseline, and antibody negative at all sampling points post treatment 
(including SFU).  
• Category 4: Pre ADAb positive – treatment unaffected ADAb positive: Includes subjects 
who are positive at Baseline and are positive at any sampling point post treatment (including 
SFU) with titer values of the same magnitude as Baseline (ie, less than a predefined fold 
difference from the Baseline value). For the purpose of this study, this is set at an increase of 
less than the validated Minimum Significant Ratio (MSR) of 2.07-fold from Baseline. 
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• Category 5: Pre ADAb positive – treatment boosted ADAb positive: Includes subjects 
who are positive at Baseline and are positive at any sampling point post treatment (including 
SFU) with increased titer values compared to Baseline (greater than or equal to a predefined 
fold difference increase from Baseline value which is defined within the validation of the 
assay). For the purposes of this study, this is set at an increase greater than or equal to the 
validated Minimum Significant Ratio (MSR) of 2.07-fold from Baseline. 
Note: For any subject who is positive at Baseline and positive at a post-Baseline time point, 
but for whom titers are not available to determine treatment unaffected or treatment boosted 
status, the subject will be considered as treatment boosted (ie, Category 5), assuming no 
other samples are available.  
• Category 6: Inconclusive: Includes subjects who have a positive pre-treatment sample and 
some post-treatment samples are missing, while other post-treatment samples are ADAb 
negative or missing. 
• Category 7: Total treatment-emergent: Category 2 and 5 combined: Includes subjects who 
are pre ADAb negative – treatment emergent ADAb positive (Category 2) and pre ADAb 
positive – treatment boosted ADAb positive (Category 5). 
• Category 8: Total prevalence of pre-ADAb positivity: (Categories 3, 4, 5 and 6 
combined): Subjects that are tested ADAb positive at Baseline. 
• Category 9: Missing: Includes subjects who have a negative or a missing/inconclusive pre-
treatment sample and some post-treatment samples are missing/inconclusive, while other 
post-treatment samples are ADAb negative or missing. 
All the following analyses will be prepared on the SS:  
• Summary tables displaying the number and percentage of subjects with ADAb status 
(positive, negative, or missing) at the time of each visit by treatment group (160mg Q4W) 
will be provided. For the placebo arm, the by-visit summary of ADAb positive status will 
include a summary of subjects with ADAb status (positive, negative, or missing) at Baseline 
and Week 16.  For the overall summary at any visit (only applicable to 160mg Q4W dose 
arm), two summaries will be presented: one that will exclude data obtained at the SFU visit 
and will include data obtained at Baseline and one that will include data obtained at both the 
SFU visit and at Baseline. Subjects who rolled over to the OLE study will not have a SFU 
visit per study protocol. For these subjects, the ‘overall ADAb status including SFU’ will 
then be considered as being identical to the ‘overall ADAb status up to Week 16’. 
For the overall ADAb status, a subject will be classified as: 
− Positive if the subject has at least one positive sample at any time in the treatment period 
(regardless of having missing /inconclusive data) 
− Negative if the subject has all the samples negative or only one missing/inconclusive 
sample with negative ADAb samples up to the timepoint of interest 
− Missing if the subject has missed more than one sample result for ADAb assessment (or 
have more than one inconclusive sample) and all other available ADAb samples are 
negative during the period of interest (If there are ≥95% of subjects included in the non-
missing groups, the missing group will not be displayed on the table). 
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The above summary table displaying the number and percentage of subjects in each of the ADAb 
status (positive, negative, total of positive and negative, missing) will be repeated for the 
subgroup of Japan. 
• A summary table displaying the number and percentage of subjects in each of the ADAb 
status (positive, negative, total of positive and negative, missing) by concomitant medications 
(use of cDMARDs at entry, use of methotrexate at entry, use of oral/systemic corticosteroids 
at entry) will be provided (overall summaries only). 
• A table displaying the number and percentage of subjects with the first occurrence of any 
ADAb positivity during the study (ie, including Baseline visit) will be summarized. This 
summary will include the following categories: 
− Any ADAb+: ADA positive sample regardless of category during the treatment period  
− ADAb category 2: Pre ADAb negative – treatment-emergent ADAb positive 
− ADAb category 5: Pre ADAb positive – treatment-boosted ADAb positive (if this 
category represents at least 10% of the subjects, otherwise results are to be merged with 
category 2). For this category, the first occurrence of a boosted result is considered. 
The table will include the number and percentage of subjects with first occurrence of any 
ADAb+ sample, and also subjects who are either treatment-emergent ADAb positive or 
treatment-boosted ADAb positive for the first time at the specified time point in the study 
and will include the cumulative number and percentage of subjects with treatment-emergent 
ADAb positive results at each time point. 
• A boxplot of the ADAb titer by time of occurrence of ADAb positivity will be created. The 
ADAb titer results will be presented on the log-scale. The time represents the visit week for 
the ADAb positive sample. Subjects who do not have any ADAb positivity will be excluded 
from the plot.  
• A summary table of the number and percentage of subjects in each of the 9 ADAb categories 
will be tabulated.  
• Figure summarizing the time to achieve ADAb positivity and treatment-emergent ADAb 
positivity on a cumulative basis (2 lines per plot) will be presented. Subjects will be 
considered to have an event at the time point at which an ADAb+ result or treatment 
emergent ADAb positive is first achieved. Treatment-emergent ADAb+ in this plot will be 
based on ADAb category 7 (total treatment-emergent ADAb).  
In the event that ≥10% of subjects are classified as ADAb category 5, the lines will be further 
split by the following categories (thus the plot will include 3 lines): 
– ADAb category 2: Pre ADAb negative – treatment-emergent ADAb positive 
– ADAb category 5: Pre ADAb positive – treatment-boosted ADAb positive  
• Individual plots (1 plot per subject) of BKZ concentrations/ADAb titer and the ACR50 
response (based on NRI) will be created. Each time, all 3 endpoints will be plotted on the Y-
axis by visit (X-axis) for the full treatment period, including SFU where a subject has not 
progressed into the OLE. Plots should be labeled and grouped into the 9 ADAb categories 
and display vertical lines on the X-axis corresponding to the dosing incidences/visits. 
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• Individual plot (1 plot per subject) of BKZ concentrations/ADAb titer and PASI90 response 
will also be created similarly as described above.  
• Spaghetti plots of ADAb titer (Y-axis) will be reported on the log-scale by visit (X-axis) for 
all ADAb positive subjects, including Baseline positive subjects. This plot will include the 
following ADAb categories: 
– ADAb category 2: Pre ADAb negative – treatment-emergent ADAb positive 
– ADAb category 5: Pre ADAb positive – treatment-boosted ADAb positive 
Plots will be presented using a semi-logarithmic scale for the ADAb titers (ADAb negative 
samples will therefore be excluded from the plot). Furthermore, all ADAb titer values <100 
will be represented as 1 in these plots. 
• Figures will summarize efficacy response (ACR50, ACR20 and PASI90 responders based on 
NRI) versus ADAb titer quartiles. The X-axis will display the ADAb titer quartiles at Week 
16 (categorized as negative, Q1, Q2, Q3 and Q4) and the y-axis will display percentage of 
ACR50 (ACR20 or PASI90) responders at Week 16. The plot will therefore display the 
percentage of ACR50 (ACR20 or PASI90) responders as a function of the number of 
subjects within each ADAb and titer categories. Subjects with negative ADAb results at 
Week 16 will be included in the ‘negative’ category on the X‑axis.  
• A figure summarizing time course of efficacy response (ACR50 responders based on NRI) 
for the BKZ 160mg Q4W group by the following ADAb groups (3 lines per plot) will be 
created: 
− ADAb positive - defined as subjects having at least 2 ADAb positive samples during the 
study (including baseline and SFU) regardless of other ADAb negative samples and/or 
missing or inconclusive samples 
− ADAb negative - defined as subjects for whom either (1) all samples (including baseline 
and SFU) are ADAb negative and there are no missing or inconclusive samples, (2) only 
1 sample is ADAb positive and all other samples (including baseline and SFU) are ADAb 
negative or missing/inconclusive or 3) only one sample is missing/inconclusive and the 
remaining ADAb samples are negative. 
− Missing - defined as subjects who do not fulfil the criteria for one of the 2 groups listed 
above. 
If ≥95% of subjects are included in the non-missing groups, the missing group will not be 
displayed in the figure.  
The data will also be presented in a tabular format. The figure and table will be repeated for 
ACR20 and PASI90. 
Note: for efficacy by ADAb status summary up to a particular timepoint (Weeks 16), only 
ADAb data up to the timepoint of interest will be utilized in deriving the overall ADAb status 
during that period. The percent of subjects in each of the ADAb categories considered for 
efficacy sub-group analyses will be summarized. 
• All individual subject-level ADAb results will be listed including the Screening assay, 
confirmatory assay, ADAb status, and titers if applicable. Note, that titer results will only be 
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available, if the confirmatory assay is positive. The listing will also include flags for ADAb 
measurements that were excluded from the by-visit summaries. The reason for exclusion will 
be one of the following: 
− Sample collected out of window relative to current dose (or visit), 
− More than one sample obtained at the same visit. 
• Finally, if more than 10% of the ADAb results have been excluded from the table summaries, 
the ADAb excluded results will be listed in the same listing as the one mentioned in Section 
9.1 for excluded PK results.  
 
9.2.2 
Neutralizing anti-bimekizumab antibodies 
NAb will be assessed using IL-17AA- and IL-17FF-specific assay method, respectively. NAb 
results will be positive or negative to each specific NAb assay or both. 
All NAb results derived from samples with drug concentrations > the drug tolerance limits of the 
NAb assays (100μg/mL) will be labeled 'inconclusive'. All inconclusive results will be regarded 
as missing. 
 
Subjects will be assigned an overall Neutralizing anti-BKZ antibodies (NAb) classification, 
inclusive of Baseline and post-Baseline results from NAb assay: 
• NAb negative: No NAb positive samples for IL-17AA and IL-17FF at Baseline or post-
Baseline. This group will also include subjects who have only 1 missing sample and all other 
available samples during the period of interest are negative. Subjects who are NAb negative 
will be classified as follows: 
− ADAb positive / NAb negative: ADAb positive subjects who are 1) NAb negative for all 
available ADAb positive samples or 2) with only 1 missing NAb sample and all other 
evaluated ADAb positive samples are NAb negative. 
− ADAb negative: if the subject has all the samples as ADAb negative or only 1 
missing/inconclusive sample with all other available samples as negative ADAb. Note 
that ADAb negative samples are not subject to the neutralizing assay. 
• NAb positive: One or more positive samples (IL-17AA positive, IL-17FF positive, or both) 
at Baseline or post-Baseline (regardless of missing samples). Subjects who are NAb positive 
will be further classified as follows: 
− Positive for IL-17AA only: 1 or more positive samples for IL-17AA at Baseline or post-
Baseline. No positive samples for IL-17FF 
− Positive for IL-17FF only: 1 or more positive samples for IL-17 FF at Baseline or post-
Baseline. No positive samples for IL-17AA 
− Positive for both IL-17AA and IL-17FF: 1 or more positive samples for both IL-17AA 
and IL-17FF at Baseline or post-Baseline 
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• NAb Missing: more than one relevant NAb samples are missing/inconclusive and other 
available NAb samples during the period of interest are negative, missing or insufficient 
sample left for NAb testing. 
Note: For PK and efficacy analyses up to a certain timepoint (Week 16) by NAb status, only data 
up to the timepoint of interest will be utilized in deriving the subject’s overall NAb status during 
that period (eg for the ACR50 by NAb up to Week 16, only NAb data from Baseline up to Week 
16 will be used to derive subject’s overall NAb status during the 16-week Double-Blind 
Treatment Period). 
A listing will be produced to summarize the NAb status overall in the study. The listing will be 
sorted by treatment group, subject identifier and visit and will summarize the following 
information for each subject assessed for NAbs: 
− Visit 
− Study week 
− Laboratory sampling date and time 
− Time since previous dose (weeks) 
− The corresponding BKZ plasma concentration level at each visit (ug/mL) 
− Anti-BKZ anti-body titer at each visit 
− IL-17AA NAb status and corresponding IL-17AA signal/negative control result 
− IL-17FF NAb status and corresponding IL-17FF signal/negative control result 
A summary table will provide the following overall summary statistics by treatment group 
(based on the total number of subjects in the SS): 
− The number and percentage of subjects confirmed as anti-BKZ antibody positive and 
anti-BKZ antibody negative to Week 16 (excluding SFU), 16 (including SFU). 
− The number and percentage of subjects who are NAb positive, NAb negative and missing 
to Week 16 (excluding SFU), 16 (including SFU).   
The NAb summary tables will be repeated with percentages calculated on a denominator based 
on the number of ADAb positive subjects during the above periods. 
In addition, the following analyses will be performed to assess the impact of NAb status on 
efficacy variables: 
• A figure summarizing efficacy response (ACR50 based on NRI) versus time for each 
treatment group by NAb status (ADAb negative, NAb positive, ADAb positive/ NAb 
negative, missing) will be created. If ≥95% of subjects are included in the non-missing 
groups, the missing group will not be displayed in the figure. Separate figures will be 
presented for data up to Week 16. The data will also be presented in a tabular format. The 
analyses will be repeated for ACR20 and PASI90. The data will be also presented in a 
tabular format. 
10 
SAFETY ANALYSES 
All safety summaries will be done on all subjects in the SS. 
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10.1.1 
Extent of exposure and time at risk 
The extent of exposure will be evaluated based on the duration of exposure to IMP and the time 
at risk. Two summary tables will be created to describe the extent of exposure.  
The first table consists of a descriptive summary of study medication duration (in days), total 
study medication duration (in subject-years), and total time at risk (in subject-years).  
The sum of all durations of exposure (in subject-years) will be calculated as: 
∑
𝐷𝑢𝑟𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑒𝑥𝑝𝑜𝑠𝑢𝑟𝑒 (𝑑𝑎𝑦𝑠)
𝑆𝑢𝑏𝑗𝑒𝑐𝑡𝑠
365.25
 
 
The sum of all times at risk (in subject-years) will be calculated as: 
∑
𝑇𝑖𝑚𝑒𝑠 𝑎𝑡 𝑟𝑖𝑠𝑘 (𝑑𝑎𝑦𝑠)
𝑆𝑢𝑏𝑗𝑒𝑐𝑡𝑠
365.25
 
 
A second summary will be created on the cumulative study medication duration for subjects 
exposed to the following durations of time: 
− > 0 week 
− ≥ 4 weeks 
− ≥ 8 weeks 
− ≥ 12 weeks 
− ≥16 weeks 
The study medication duration (in days) will be calculated as follows: 
𝐷𝑎𝑡𝑒 𝑜𝑓 𝑙𝑎𝑠𝑡 𝑑𝑜𝑠𝑒−𝐷𝑎𝑡𝑒 𝑜𝑓 𝑓𝑖𝑟𝑠𝑡 𝑑𝑜𝑠𝑒+ 28 
− If the date of last dose + 28 days extends to a date beyond the final visit date (not 
including SFU), then this calculation reverts to:  
𝐷𝑎𝑡𝑒 𝑜𝑓 𝑙𝑎𝑠𝑡 𝑣𝑖𝑠𝑖𝑡 (𝑛𝑜𝑡 𝑖𝑛𝑐𝑙𝑢𝑑𝑖𝑛𝑔 𝑆𝐹𝑈) − 𝐷𝑎𝑡𝑒 𝑜𝑓 𝑓𝑖𝑟𝑠𝑡 𝑑𝑜𝑠𝑒 + 1 
− For subjects who die, this calculation reverts to: 
𝐷𝑎𝑡𝑒 𝑜𝑓 𝑑𝑒𝑎𝑡ℎ−𝐷𝑎𝑡𝑒 𝑜𝑓 𝑓𝑖𝑟𝑠𝑡 𝑑𝑜𝑠𝑒+ 1 
The time at risk (in days) will be calculated as follows: 
− For subjects who complete the study as planned and continue into the OLE study (and, 
therefore do not have a SFU visit):  
𝐷𝑎𝑡𝑒 𝑜𝑓 𝑙𝑎𝑠𝑡 𝑣𝑖𝑠𝑖𝑡−𝐷𝑎𝑡𝑒 𝑜𝑓 𝑓𝑖𝑟𝑠𝑡 𝑑𝑜𝑠𝑒+ 1 
− For subjects who die prior to the final visit, this calculation reverts to: 
𝐷𝑎𝑡𝑒 𝑜𝑓 𝑑𝑒𝑎𝑡ℎ−𝐷𝑎𝑡𝑒 𝑜𝑓 𝑓𝑖𝑟𝑠𝑡 𝑑𝑜𝑠𝑒+ 1 
− For all other subjects, this calculation reverts to the minimum of the following: 
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𝐷𝑎𝑡𝑒 𝑜𝑓 𝑙𝑎𝑠𝑡 𝑑𝑜𝑠𝑒− 𝐷𝑎𝑡𝑒 𝑜𝑓 𝑓𝑖𝑟𝑠𝑡 𝑑𝑜𝑠𝑒+ 141 
𝐷𝑎𝑡𝑒 𝑜𝑓 𝑙𝑎𝑠𝑡 𝑐𝑙𝑖𝑛𝑖𝑐𝑎𝑙 𝑐𝑜𝑛𝑡𝑎𝑐𝑡− 𝐷𝑎𝑡𝑒 𝑜𝑓 𝑓𝑖𝑟𝑠𝑡 𝑑𝑜𝑠𝑒 + 1 
Note: 140 days refer to 5 times the half-life of BKZ. 
Date of last clinical contact for each subject is defined as the maximum of [last visit date 
including SFU visit, last AE start date (including imputed AE start dates), date of study 
termination or completion, last date of study drug administration]. 
This group of subjects could include subjects who discontinue early from the study, subjects who 
complete study as planned but chose not to continue into the OLE study, or subjects who are 
ongoing in the SFU Period at the time of the data snapshot. 
A by-subject listing of date of first and last dose and the duration of exposure will be performed. 
10.1.2 
Time at risk in subject-years by COVID-19 pandemic period 
The time at risk will be determined by COVID-19 pandemic period as defined in Section 3.11. 
10.1.2.1 
Time at Risk in the pre-COVID-19 pandemic period  
Only subjects starting study drug during the pre-COVID-19 pandemic period will have a time at 
risk calculated during that period.  
• For subjects with date of last dose of study drug on or after 11Mar2020: 
10Mar2020 – date of first dose + 1 
• For subjects who have died on or before 10Mar2020: 
Date of death – date of first dose + 1 (If the date of death is later than 140 days 
following the last dose of BKZ, this rule does not apply). 
• For subjects with date of last dose of study drug on or before 10Mar2020 but with the earliest 
date between (date of last dose + 141) and (date of last clinical contact) on or after 
11Mar2020:  
10Mar2020 – date of first dose + 1  
• For subjects with date of last dose of study drug on or before 10Mar2020 but with the earliest 
date between (date of last dose + 140) and (date of last clinical contact) on or before 
10Mar2020, minimum between:  
date of last dose + 141 – date of first dose 
date of last clinical contact – data of first dose +1 
10.1.2.2 
Time at Risk in the COVID-19 pandemic period  
Subjects with study drug period overlapping the COVID-19 pandemic periods will have a time at 
risk calculated during that period.  
• For subjects with date of last dose of study drug on or after 11Mar2020, minimum between: 
Minimum (date of last dose + 141, COVID-19 pandemic end date) – maximum of 
(11Mar2020, date of first dose) 
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Minimum (date of last clinical contact, COVID-19 pandemic end date) – maximum of 
(11Mar2020, date of first dose) +1 
• For subjects who have died on or after 11Mar2020: 
Minimum (Date of death, COVID-19 pandemic end date) – maximum of (11Mar2020, 
date of first dose) + 1 (If the date of death is later than 140 days following the last dose 
of BKZ, this rule does not apply). 
• For subjects with date of last dose of study drug on or before 10Mar2020 but with the earliest 
date between (date of last dose + 141) and (date of last clinical contact) on or after 
11Mar2020, minimum between:  
Minimum (date of last dose+ 141, COVID-19 pandemic end date) – 11Mar2020 
Minimum (date of last clinical contact, COVID-19 pandemic end date) – 11Mar2020+1 
10.1.2.3 
Time at Risk in the post COVID-19 pandemic period  
Subjects with study drug period continuing after the COVID-19 pandemic periods will have a 
time at risk calculated during that period.  
• For subjects with date of last dose of study drug on or after the end date of the COVID-19 
pandemic period, minimum between: 
date of last dose + 141 – maximum of (COVID-19 pandemic end date, date of first dose) 
date of last clinical contact – maximum of (COVID-19 pandemic end date, date of first 
dose) +1 
• For subjects who have died on or after COVID-19 pandemic end date: 
Date of death – maximum of (COVID-19 pandemic end date, date of first dose) + 1 (If 
the date of death is later than 140 days following the last dose of BKZ, this rule does not 
apply). 
• For subjects with date of last dose of study drug on or before COVID-19 pandemic end date 
but with the earliest date between (date of last dose + 140) and (date of last clinical contact) 
on or after COVID-19 pandemic end date, minimum between:  
date of last dose + 141 – COVID-19 pandemic end date 
     date of last clinical contact – COVID-19 pandemic end date+1 
10.2 
Adverse events 
An AE is any untoward medical occurrence in a patient or clinical investigation subject 
administered a pharmaceutical product that does not necessarily have a causal relationship with 
this treatment. An AE can therefore be any unfavorable and unintended sign (including an 
abnormal laboratory finding), symptom, or disease temporally associated with the use of a 
medicinal (investigational) product, whether related or not to the IMP. 
AEs (including SAEs) are characterized as either non-treatment or treatment emergent according 
to the following criteria: 
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• Non-treatment emergent are the events with onset date and time prior to the very first 
administration of study medication (BKZ or placebo) or after a 140-day period after the final 
drug administration. 
• Treatment-emergent AEs (TEAEs) are those with onset date at or after the very first 
administration of study medication. The events that emerge within 140 days after the final 
drug administration, will also be considered as treatment emergent (eg, in the case of 
premature discontinuation or during the 20-week SFU Period). 
The incidence of TEAEs will be summarized descriptively by treatment group, MedDRA 
primary system organ class (SOC), high-level term (HLT), and preferred term (PT).  
AEs will be presented as “number of subjects (percentage of subjects) [number of events]”. In 
this style of output, “[number of events]” will include all cases of an AE including repeat 
occurrences in individual subjects, while “number of subjects” will count each subject only once. 
Adverse event summaries by SOC, HLT and PT will be ordered alphabetically for SOC and HLT 
within SOC and in terms of decreasing frequency for PT within HLT in the BKZ treatment group 
and then similarly by decreasing frequency in the placebo group. 
AE summaries by PT will be ordered in terms of decreasing frequency for PT within the BKZ 
treatment group, and in the event of ties, PT will be sorted alphabetically.  
TEAEs will be classified according to their date of emergence. 
All summaries will be provided by treatment group on the SS. 
10.2.1 
Standard AE summaries  
Tables for incidence of the following categories of TEAES will be provided: 
• TEAEs (Overview) 
• TEAEs by SOC, HLT, and PT  
• TEAEs by decreasing frequency of PT  
• TEAEs above reporting threshold of 5% by PT, by SOC and PT  
• TEAEs by maximum intensity  
• TEAEs by relationship to IMP 
• Related TEAEs by SOC, HLT, and PT  
• Related TEAEs above reporting threshold of 5% by PT, by SOC and PT  
• TEAEs leading to study discontinuation, by SOC, HLT, and PT  
• TEAEs leading to study drug discontinuation, by SOC, HLT, and PT  
• Treatment-emergent SAEs (TESAEs) by SOC, HLT, and PT  
• TESAEs by relationship by SOC, HLT, and PT  
• TEAEs leading to death by SOC, HLT, and PT - deaths will be also be tabulated and listed 
• Non-Serious TEAEs above reporting threshold of 5% by relationship by PT  
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Some selected tables of incidence will include the exposure adjusted incidence rate (EAIR) with 
associated 95% confidence interval and the exposure adjusted event rate (EAER) (see 
Section 10.2.3). The categories of TEAEs concerned are listed below.  
• TEAEs by SOC, HLT, PT,  
• TEAEs leading to study discontinuation by SOC, HLT, PT, 
• TEAEs leading to study drug discontinuation, 
• TEAEs by timing of onset relative to ADAb status by SOC, HLT, PT (on subjects treated 
with BKZ). This will include columns for the following: 
− TEAEs starting before the first ADAb positive result (includes ADAb categories 2 and 5) 
where TEAEs have occurred before the following events: a) the first positive ADAb 
result for subjects in category 2 and b) the first post-Baseline boosted ADAb titer result 
for subjects with titer results and the first post-Baseline positive ADAb result for subjects 
with positive ADAb at Baseline with no other samples with titer available for subjects in 
category 5 
− TEAEs starting on the same date or after the first ADAb positive result (includes ADAb 
Categories 2, 3, 4, 5 and 6) where TEAEs have occurred on or after the following events: 
a) the first positive ADAb results for subjects in categories 2, 3, 4 and 6, and b) the first 
post-Baseline boosted ADAb titer result for subjects with titer results and the first post-
Baseline positive ADAb result for subjects with positive ADAb at Baseline with no other 
samples with titer available for subjects in category 5 
− TEAEs for subjects who are ADAb negative at all timepoints (includes ADAb Category 
1) 
• TEAEs by NAb status (ADAb negative, NAb positive, ADAb positive / NAb negative) on 
subjects treated with BKZ. TEAEs will be sorted by system organ class, high level term and 
preferred term. 
 
Note: for TEAE by onset relative to ADAb positivity status and by NAb status, all available 
ADAb and NAb data at the time of IA cut-off, respectively, will be utilized to derive the 
subject-level ADAb/NAb status categories. 
• TESAEs by SOC, HLT, PT.  
By-subject listings on all AEs and all deaths will be provided on the ES. AEs leading to study 
discontinuation will also be listed on the SS. AEs occurring at first study drug administration will 
also be listed. A glossary listing will also be created for all TEAEs.  
10.2.2 
Exposure duration of AEs 
The duration of each AE will be calculated as follows: 
𝐷𝑢𝑟𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝐴𝐸 (𝑑𝑎𝑦𝑠) =  𝐸𝑛𝑑 𝑑𝑎𝑡𝑒 𝑜𝑓 𝐴𝐸−𝑆𝑡𝑎𝑟𝑡 𝑑𝑎𝑡𝑒 𝑜𝑓 𝐴𝐸+ 1  
For the calculation of duration for AEs with missing start dates, the dates will be imputed as 
described in Section 4.2.3. 
The time since first dose of IMP for each AE will be calculated as follows for all TEAEs: 
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𝑇𝑖𝑚𝑒 𝑠𝑖𝑛𝑐𝑒 𝑓𝑖𝑟𝑠𝑡 𝑑𝑜𝑠𝑒 (𝑑𝑎𝑦𝑠) =  𝑆𝑡𝑎𝑟𝑡 𝑑𝑎𝑡𝑒 𝑜𝑓 𝐴𝐸−𝐷𝑎𝑡𝑒 𝑜𝑓 𝑓𝑖𝑟𝑠𝑡 𝑑𝑜𝑠𝑒+ 1  
The time since the most recent dose of IMP for each AE will be calculated as follows for all 
TEAEs: 
𝑇𝑖𝑚𝑒 𝑠𝑖𝑛𝑐𝑒 𝑡ℎ𝑒 𝑚𝑜𝑠𝑡 𝑟𝑒𝑐𝑒𝑛𝑡 𝑑𝑜𝑠𝑒 (𝑑𝑎𝑦𝑠)
=  𝑆𝑡𝑎𝑟𝑡 𝑑𝑎𝑡𝑒 𝑜𝑓 𝐴𝐸−𝐷𝑎𝑡𝑒 𝑜𝑓 𝑚𝑜𝑠𝑡 𝑟𝑒𝑐𝑒𝑛𝑡 𝑑𝑜𝑠𝑒+ 1  
Time to first dose and time to most recent dose will not be calculated for pretreatment AEs. 
For the calculation of time to first BKZ and time to most recent BKZ dose the same formulas as 
above will be used but the date of first BKZ dose will be used instead of the date of first dose of 
IMP. The time to first dose and time to first BKZ dose differs only for those subjects who 
receive placebo at Baseline after the time they switch to BKZ. 
10.2.3 
Exposure adjusted incidence rate (EAIR) and exposed adjusted event 
rate (EAER) 
The EAIR is defined as the number of subjects (k) with a specific AE adjusted for the exposure 
and will be scaled to 100 patient-years: 
  
𝐸𝐴𝐼𝑅= 100 × 
𝑘
∑
(𝑇𝐸𝑥𝑝(𝑖))
𝑛
𝑖=1
 
 
where n is the total number of subjects and TExp(i) is the time of exposure for each subject defined 
as:  
• For subjects with the AE: years since first dose of IMP to the first occurrence for the AE of 
interest at the level of coding evaluated,  
• For subjects without the AE: the time at risk in years.  
Exact Poisson 95% CIs for incidence rates are calculated using the relationship between the 
Poisson and the Chi-square distribution (Ulm, 1990; Fay and Feuer, 1997): 
 
𝐿𝐶𝐿=
𝜒2𝑘,𝛼/2
2
2
 
𝑈𝐶𝐿=
𝜒2(𝑘+1),1− 𝛼/2
2
2
 
where k is the number of subjects with a specific AE for the incidence rate of interest and is the 
basis for the number of the degrees of freedom for the chi-square quantile for the upper tail 
probability χ2. 
The EAER will be the number of AEs (NAE)including repeat occurrences in individual subjects 
divided by the total time at risk scaled to 100 patient-years and calculated using: 
𝐸𝐴𝐸𝑅= 100 × 
𝑁𝐴𝐸
∑
(𝑇𝑅𝑖𝑠𝑘(𝑖))
𝑛
𝑖=1
 
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where NAE is the number of AE occurrences, n is the total number of subjects and TRisk(i) is the 
time at risk in years for each subject.  
No CI will be computed for EAER. 
10.2.4 
Other safety topics of interest 
The other safety topics of interest for this study include: 
• Infections (serious, fungal, opportunistic and tuberculosis) 
• Malignancies  
• Major adverse cardiac events (MACE)  
• Neutropenia 
• Suicidal Ideation and Behavior (SIB)Inflammatory bowel disease 
• Hypersensitivity (including anaphylaxis) 
• Hepatic events and drug-induced liver injury (DILI)  
The analyses produced for the above TEAE are based on the specifications described in the BKZ 
safety topic of interest document version from Apr-2021. 
The incidence of other safety topics of interest will be summarized by MedDRA system organ 
class, high level term, and PT. EAIR with associated 95% CI and the EAER will be included in 
the summary tables. 
Separate tables will be created to summarize the incidence of each of the above AEs (unless 
otherwise specified) per 100 subject years, by SOC, HLT, and PT. A listing will also be created.  
10.2.4.1 
Infections (serious, opportunistic, fungal and TB)  
Serious infections will be identified based on MedDRA classification (SOC “Infections and 
infestations”) using the “Any SAE” table. A separate table does not need to be produced to 
summarize these events. 
• Fungal infections will be summarized in a stand-alone table. The table will include all 
TEAEs (serious and non-serious) which code into the High-Level Group Term (HLGT) 
“Fungal infectious disorders”. 
• Opportunistic infections (including tuberculosis) will be summarized in a stand-alone table 
and will include all opportunistic infection TEAEs identified as per the UCB-defined search 
criteria which were adjudicated as opportunistic infections (refer to Section 12.2 for further 
details on the process for identifying opportunistic infections).  
10.2.4.2 
Malignancies  
Two tables will be created on malignancies:  
• One table will be based on the criteria SMQ= “Malignant or unspecified tumors (SMQ)”.  
• One table will be based on the criteria SMQ=” Malignant tumors (SMQ)”.  
SMQ search will include all TEAEs which code to a PT included in the Scope=Narrow group 
within each SMQ. 
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Note that the events included in the “Malignancies” table will be a subset of the events included 
in the “Malignancies (including unspecified)” table. While the “Malignant tumors (SMQ)” is 
most relevant, “Malignant or unspecified tumors (SMQ)” must be reviewed for potential 
malignancies. 
The output tables will include 2 different overall incidence rows: 
• The first overall incidence row will summarize “Any Malignancy” and this row will 
summarize the incidence of all AEs flagged for inclusion in the table (using the appropriate 
SMQ depending on the table), regardless of the High Level Term (HLT) it codes to.  
• The second overall incidence row will summarize “Any Malignancy excluding non 
melanomic skin cancers HLT” and this row will summarize the incidence of AEs flagged for 
inclusion in the table (using the appropriate SMQ depending on the table), excluding those 
which code to an HLT of “skin neoplasms malignant and unspecified (excl melanoma)”. 
10.2.4.3 
Major adverse cardiac events (MACE) 
Major adverse cardiac events will be presented in a table. The classification of an event as 
MACE is determined by external cardiovascular event adjudication committee.  
Extended MACE events will be presented in a separate table and listing. All events which are 
classified by the adjudication committee as any of the following events types will be considered 
an extended MACE event.  
Table 10‒1: Type of Extended MACE events 
Event Type Code Event Type 
1 
Non-Fatal Myocardial Infarction (MI) 
2 
Non-Fatal Stroke: hemorrhagic 
3 
Non-Fatal Stroke: ischemic 
4 
Non-Fatal Stroke: embolic 
5 
Non-Fatal Stroke: undeterminable 
6 
Hospitalization or ER for Unstable Angina with urgent 
revascularization 
8 
Hospitalization for Heart Failure 
10 
Coronary Revascularization Procedures (eg, percutaneous coronary 
intervention, coronary artery bypass grafting) 
11 
Urgent Revascularization Procedures (ie, due to symptoms of brain 
ischemia or pending infarction) 
18 
Death due to Myocardial Infarction (MI) 
19 
Death due to Stroke 
20 
Sudden Cardiac Death 
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Event Type Code Event Type 
21 
Other CV Death (eg, heart failure, pulmonary embolism, 
cardiovascular procedure-related) 
22 
Cardiovascular: Undetermined Cause of Death (ie, cause of death 
unknown) 
A separate table and listing will present the adjudicated cardiovascular events by type. For each 
cardiovascular event type (24 in all, for full list refer to Bimekizumab-Event-Adjudication-
Committee-Analysis- Plan), the individual PTs which fall within each event type will be 
summarized.  
Additionally, a listing of all events identified for potential review by the cardiovascular event 
adjudication committee will be produced. This listing will indicate whether each event was 
escalated to the committee for formal review/adjudication.  
10.2.4.4 
Neutropenia 
The table on neutropenia will be based on the following PTs (regardless of seriousness): 
• Autoimmune neutropenia 
• Band neutrophil count decreased 
• Cyclic neutropenia 
• Febrile neutropenia 
• Idiopathic neutropenia 
• Neutropenia 
• Neutropenic infection 
• Neutropenic sepsis 
• Neutrophil count decreased 
10.2.4.5 
Suicidal Ideation and Behavior Neuropsychiatric events 
An external neuropsychiatric adjudication committee will evaluate potential neuropsychiatric 
events and determine whether any of those events were associated with suicidal ideation and 
behavior (SIB). If an event is adjudicated as SIB, further information will be provided. A table 
and a listing for SIB events as determined by the adjudication committee will be produced. 
A separate table will present the adjudicated neuropsychiatric events by type. For each 
neuropsychiatric event type (6 total), the individual PTs which fall within each event type will be 
summarized. It will include events adjudicated as SIB and events adjudicated as non-suicidal. 
Note that the event type Suicidal ideation can be classified as either SIB or non-suicidal. 
Additionally, a listing of all events identified for potential review by the neuropsychiatric 
adjudication committee will be produced. This listing will indicate whether each event was 
escalated to the committee for formal review/adjudication. A separate listing will also be 
produced to summarize the adjudicated results of all events escalated to the full committee.  
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10.2.4.6 
Inflammatory bowel disease 
An external inflammatory bowel disease (IBD) adjudication committee will evaluate potential 
IBD events and will classify each one as follows: 
• Event Type Code 1: Possible IBD – Crohn’s Disease 
• Event Type Code 2: Probable IBD – Crohn’s Disease 
• Event Type Code 3: Definite IBD – Crohn’s Disease 
• Event Type Code 4: Possible IBD – Ulcerative Colitis 
• Event Type Code 5: Probable IBD – Ulcerative Colitis 
• Event Type Code 6: Definite IBD – Ulcerative Colitis 
• Event Type Code 7: Possible IBD – Unclassified 
• Event Type Code 8: Probable IBD – Unclassified 
• Event Type Code 9: Definite IBD – Unclassified 
• Event Type Code 10: Symptoms not consistent with IBD 
• Event Type Code 11: Possible Inflammatory Bowel Disease – Microscopic Colitis 
• Event Type Code 12: Probable Inflammatory Bowel Disease – Microscopic Colitis 
• Event Type Code 13: Definite Inflammatory Bowel Disease – Microscopic Colitis 
• Event Type Code 14: Possible Inflammatory Bowel Disease – no further differentiation 
possible 
• Event Type Code 15: Probable Inflammatory Bowel Disease – no further differentiation 
possible 
• Event Type Code 16: Definite Inflammatory Bowel Disease – no further differentiation 
possible 
• Event Type Code 99: Not enough information to adjudicate 
A table for adjudicated IBD events (event type codes 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15 
and 16) as determined by the adjudication committee will be produced. It will summarize events 
determined by the adjudication committee as definite IBD (event type codes 3, 6, 9, 13, and 16), 
probable IBD (event type codes 2, 5, 8, 12, and 15) and possible IBD (event type codes 1, 4, 7, 
11, and 14). Definite and probable IBD will also be aggregated and summarized. This table will 
be stratified by subjects with or without a previous medical history of IBD. Previous medical 
history of IBD will be determined using the information recorded on the Extra-Articular 
Assessment at Screening CRF page ("Does subject have a history of IBD?”). 
A separate table will present the adjudicated gastrointestinal events by type. For each 
gastrointestinal event type (17 total), the individual PTs which fall within each event type will be 
summarized. It will include events determined by the adjudication committee as definite IBD 
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probable IBD and possible IBD. It will also include events determined as Symptoms not 
consistent with IBD (event type code 10) and Not enough information to adjudicated (event type 
code 99). 
A listing of all events identified for potential review by the IBD adjudication committee will be 
produced. This listing will indicate whether each event was escalated to the committee for formal 
review/adjudication.  
A listing will present the adjudicated IBD events by type. For each IBD event type (event type 
codes 1 through 16 and 99; 17 total), the individual PTs which fall within each event type will be 
listed.  
A third listing will present the individual diagnostic criteria met for each adjudicated IBD event. 
10.2.4.7 
Hypersensitivity (including Anaphylaxis) 
A separate table will be prepared based on the MedDRA anaphylaxis Algorithm (see Section 
12.1) for acute anaphylactic events (reported on the same day as when an injection was 
administered or 1 day after). An AE glossary table will also be produced to summarize the 
MedDRA coding for these events. The glossary table will include the following fields: reported 
term, PT, LLT, HLT, and SOC.  
A separate table will be prepared to summarize all hypersensitivity events and serious 
hypersensitivity events, identified using the SMQ “Hypersensitivity (SMQ)”. All TEAEs which 
code to a PT included in the Scope=Narrow search will be included in this table. In addition, a 
separate table will be prepared to summarize serious hypersensitivity events, identified using the 
SMQ “Hypersensitivity (SMQ)”. All serious TEAEs which code to a PT included in the 
Scope=Narrow search will be included in this table. An AE glossary table will also be produced 
to summarize the MedDRA coding for these events. The glossary table will include the 
following fields: reported term, PT, LLT, HLT, and SOC. 
Furthermore, a separate table will be prepared to summarize injection site reactions, identified by 
looking under the HLTs “Administration site reactions NEC” and “Injection site reactions”. 
10.2.4.8 
Hepatic events and DILI 
The table for hepatic events will be created based on the SMQ of “Drug related hepatic disorders 
- comprehensive search (SMQ)” excluding the 2 sub-SMQs “Liver neoplasms, benign (incl cysts 
and polyps) (SMQ)” and “Liver neoplasms, malignant and unspecified (SMQ)”. For each of the 
above SMQs, include all TEAEs which code to a PT included in the Scope=Broad and/or 
Scope=Narrow.  
Note that all AEs meeting the above criteria are to be included. It should be limited to events that 
the investigator determined to be related to study drug. 
Also, potential Hy’s Law cases will be reported separately in a liver function test table (see 
Section 10.3) 
10.2.5 
COVID-19 impact 
To assess the impact of COVID-19 pandemic on safety, additional summaries and listings will 
be presented.  
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For reporting purposes, AEs will be assigned to either Pre-COVID-19, COVID-19, or post-
COVID-19 pandemic period by comparing the AE start date (based on imputed date) to the 
COVID-19 pandemic period dates (AE allocated to a period if it starts during the period): 
The following categories of TEAEs will be summarized by MedDRA SOC, HLT and PT, 
including EAIR and EAER. 
• All TEAEs by time of onset relative to COVID-19 pandemic period (pre – during – post) 
by region and overall, 
• All TEAEs leading to study discontinuation and/or permanent withdrawal of study 
medication by time of onset relative to COVID-19 pandemic period (pre – during – post) 
by region and overall, 
• All Serious TEAEs by time of onset relative to COVID-19 pandemic period (pre – during 
– post) by region and overall, 
• All COVID-19 related TEAEs by treatment group, by region and overall - COVID-19 
related TEAEs will be identified by the two preferred terms “Corona virus infection” and 
“coronavirus test positive” and will include confirmed or suspected COVID-19 
infections. 
A listing of COVID-19 related AEs will be presented where these AEs are identified as 
described above. Additionally, the listing of AEs will include a column for COVID-19 
relatedness and the time of onset of each AE relative to the COVID-19 pandemic will be 
included in all AE listings. 
For the purpose of calculating EAIR and EAER by COVID-19 pandemic period, the calculation 
of exposure time at risk presented in Section 10.1.2 will be used. An individual subject may 
therefore be counted in the denominator for several COVID-19 pandemic periods dependent on 
whether the subject is still considered at risk on the COVID-19 pandemic start and stop dates. In 
this case time at risk will be calculated separately for each period. 
10.3 
Clinical laboratory evaluations 
The list of the laboratory measurements/variables that will be evaluated in the study is specified 
in Table 10‒2 per laboratory category.  
Table 10‒2: Laboratory measurements 
Hematology 
Biochemistry 
Urinalysis 
Basophils 
Calcium 
pH 
Eosinophils 
Chloride 
Albumin (protein) 
Lymphocytes 
Magnesium 
Glucose 
Monocytes 
Potassium 
Blood 
Neutrophils 
Sodium 
Leukocyte esterase 
Hematocrit 
Glucose 
Nitrite 
Hemoglobin 
BUN 
Urine dipstick for pregnancy testingb 
MCH 
Creatinine 
Urine drug screenc 
MCHC 
hs-CRP 
 
MCV 
AST 
 
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Hematology 
Biochemistry 
Urinalysis 
Platelet count 
ALT 
 
RBC count 
GGT 
 
WBC count 
ALP 
 
 
Total bilirubin 
 
 
Triglyceridesa 
 
 
Cholesterola 
 
 
HDL cholesterola 
 
 
LDL cholesterola 
 
 
LDH 
 
 
Serum pregnancy 
testingb 
 
ALP=alkaline phosphatase; ALT=alanine aminotransferase; AST=aspartate aminotransferase; BUN=blood urea nitrogen; 
CRP=C-reactive protein; ET=early termination; GGT=gamma-glutamyltransferase; HDL=high density lipoprotein, 
IMP=investigational medicinal product; LDH=lactate dehydrogenase; MCH=mean corpuscular hemoglobin; MCHC=mean 
corpuscular hemoglobin concentration; MCV=mean corpuscular volume; RBC=red blood cell; SFU=Safety Follow-Up; 
WBC=white blood cell. 
a Biochemistry will include triglycerides, cholesterol, HDL cholesterol, and LDL cholesterol at Baseline, Weeks 12 
and 24, and at the ET Visit. 
b Pregnancy testing will consist of serum testing at the Screening Visit for all women of childbearing potential. The 
pregnancy test will be urine at all other visits.  
c Urine drug screen will be performed at Screening Visit. 
 
Biochemistry and hematology values will be flagged based on their reference range:  
• Values that are below the lower limit of the reference range will be flagged as ‘L’ (low)  
• Values that are above the upper limit of the reference range will be flagged as ‘H’ (high) 
• All other values will be referenced as normal. 
Markedly abnormal values for blood chemistry and hematology will be defined as laboratory 
values graded 3 or 4 according to the Rheumatology Common Toxicity Criteria (RCTC). 
Definitions of the markedly abnormal values are given in Table 10‒3 and Table 10‒4 and are 
based on the RCTC units. All units in the tables below will be converted to the standard units 
based on Clinical Data Interchange Standards Consortium (CDISC) standards. 
Table 10‒3: Definitions of markedly abnormal biochemistry values 
Parameter name 
Unit 
Criteria 
Abnormal designation 
Creatinine 
mmol/L 
>3.0 x ULN or 
>3.0 x Baseline 
AH 
Glucose 
mmol/L 
<2.2 
>13.9 
AL 
AH 
Calcium 
mmol/L 
>3.1 
<1.75 
AH 
AL 
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Parameter name 
Unit 
Criteria 
Abnormal designation 
Magnesium 
mmol/L 
>1.23 
<0.4 
AH 
AL 
Potassium 
mmol/L 
>6.0 
<3.0 
AH 
AL 
Sodium 
mmol/L 
>155 
<130 
AH 
AL 
Triglyceride 
mmol/L >5.7 
AH 
Cholesterol 
mmol/L >10.34 
AH 
AH=abnormal high; AL=abnormal low; dL = deciliter; L = liter;  
mg = milligram; mmol = millimoles; ULN = upper limit of normal. 
Table 10‒4: Definitions of markedly abnormal hematology values 
Parameter name 
Unit 
Criteria 
Abnormal Designation 
Hemoglobin 
g/L 
<80 
>40 above ULN 
or >40 above 
Baseline if Baseline 
is above ULN 
AL 
AH 
Lymphocytes Absolute 
109/L 
<0.5 
>20.0 
AL 
AH 
Neutrophils Absolute 
109/L 
<1.0 
AL 
Platelets 
109/L 
<50 
AL 
WBC/ 
Leukocytes 
109/L 
<2.0 
>100 
AL 
AH 
 
Definitions of the markedly abnormal values for liver enzyme elevation are given in Table 10‒5.  
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Table 10‒5: Definitions of markedly abnormal liver enzyme elevation values 
Parameter name 
Unit 
Criteria 
Abnormal Designation 
Alkaline Phosphatase 
 
>5.0 x ULN 
AH 
ALT 
U/L 
>5.0 x ULN 
AH 
AST 
U/L 
>5.0 x ULN 
AH 
Total Bilirubin 
umol/L 
>3.0 x ULN 
AH 
GGT 
U/L 
>5.0 x ULN 
AH 
ALT= alanine aminotransferase; AST = aspartate aminotransferase; GGT=gamma-glutamyltransferase. 
All laboratory summaries will be presented in standard international (SI) units and will be based 
on observed case values. In the case where laboratory values are below the lower limit of 
quantification, then these will be set to the midpoint between 0 and the lower limit of 
quantification for the purpose of summarizing the data. 
In the case where laboratory data are expressed as above a fixed value (ie,: “>xx.xx”), then the 
numeric portion of the value will be used (ie, : xx.xx) to present and calculate statistics. 
To define the minimum/maximum post-Baseline values, all post-Baseline assessments including 
those at unscheduled visits (but excluding any that occur more than 140 days after the last 
administration of study medication) will be used. 
Different summary tables for hematology, biochemistry variables (except hs-CRP which will be 
analyzed in the efficacy section) and urinalysis (pH, Albumin (protein), glucose, blood, 
leukocyte esterase and nitrite) will be provided in the SS. For shift tables, results for the 
treatment period will be presented together for the overall study period.  
As indicated in Section 3.1, for tables where data are summarized by visit only values occurring 
at scheduled visits will be included. 
For each laboratory parameter, the below results will be presented for the overall study period, 
by treatment group: 
• Observed values at Baseline and observed values and changes from Baseline at each 
scheduled post-Baseline visit.  
• Number and percentage of subjects by CTCAE grade (version 4.03) (when applicable) based 
on the minimum/maximum post-Baseline value (for blood chemistry and hematology).  
• Shift in CTCAE grade from Baseline to minimum/maximum post-Baseline (for blood 
chemistry and hematology). Subjects who meet the decreased potassium criterion of 3.0-
<LLN, which is specified as the decreased potassium lab criterion for both CTCAE Grade 1 
and Grade 2, will be counted as Grade 2. 
• Number and percentage of subjects meeting the below criteria at any time during the study: 
– AST: >2xULN, >3xULN, >5xULN, >10xULN, >20xULN 
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– ALT: >2xULN, >3xULN, >5xULN, >10xULN, >20xULN 
– AST or ALT: >2xULN, >3xULN, >5xULN, >10xULN, >20xULN 
– Bilirubin: >1xULN, >1.5xULN 
– ALP: >2xULN 
• Number and percentage of subjects with potential Hy’s Law cases based on the two 
following definitions: 
– [AST ≥3xULN or ALT ≥3xULN] and Total Bilirubin ≥2xULN 
– [AST ≥3xULN or ALT ≥3xULN] and Total Bilirubin ≥2xULN in the absence of ALP 
≥2xULN  
In order to meet either of the above criteria, a subject must experience the elevation in bilirubin 
and ALT or AST (and the absence of ALP elevation, if applicable) at the same visit.  
The below results will be presented on the SS. All values observed at any time while on 
treatment (ie, occurring at scheduled and unscheduled visits) will be included in the below tables. 
Baseline values and values observed more than 140 days after the last administration of study 
medication are not considered:  
• Number and percentage of subjects with treatment emergent markedly abnormal laboratory 
data overall (for blood chemistry and hematology), All values observed at any time while on 
treatment (ie, occurring at scheduled and unscheduled visits) will be included in this table 
summarizing markedly abnormal values. For this summary, Baseline values and values 
observed more than 140 days after the last administration of study medication are not 
considered.  
• Number and percentage of subjects with markedly abnormal liver enzyme elevation tests 
(data beyond the CTCAE Grade 3 thresholds as outlined in Table 10‒5) 
All laboratory data will be listed by treatment, subject and visit including changes from Baseline 
for numeric variables, flags for measurements outside the normal ranges, the relative study day, a 
flag for whether the test was not done and a flag for whether the subject was fasting. 
The markedly abnormal laboratory data will also be listed separately.   
Listings will include Hepatitis B and C, human immunodeficiency virus (HIV), genomic 
proteomic/metabolomics, and genetic/epigenetic tests. 
In addition, the laboratory results classified as Grade 3 or Grade 4 will be listed separately. 
Urinalysis laboratory results and hepatic events will be listed separately.  
10.4 
Vital signs, physical findings, and other observations related to 
safety 
10.4.1 
Vital signs, weight and physical findings 
The following results will be tabulated for all vital sign variables (systolic blood pressure 
(mmHg), diastolic blood pressure (mmHg), and pulse rate (beats/min), by treatment group and 
visit: 
• A summary of the absolute and change from Baseline value  
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• A summary of the number and percentage of subjects experiencing at least one markedly 
abnormal value for a vital sign variable as defined in Table 10‒6. 
Table 10‒6: Definitions of markedly abnormal blood pressure values 
Parameter (unit) 
Markedly abnormal low 
Markedly abnormal high 
Systolic blood pressure (mmHg) 
<90 and a decrease from 
Baseline of ≥20 
>180 and an increase from 
Baseline of ≥20 
Diastolic blood pressure 
(mmHg) 
<50 and a decrease from 
Baseline of ≥15 
>105 and an increase from 
Baseline of ≥15 
 
For the Baseline visit where several BP assessments are taken, the individual observed data 
assessments as well as the mean of these assessments will be summarized and listed (pre-dose, 
30 min post-dose and 1-hour post-dose). 
Treatment-emergent markedly abnormal values will be analyzed on the SS.  
Vital signs measurements will also be listed by visit and timing relative to dosing including 
changes from Baseline. The listing will also include details of abnormal value based on flags as 
defined in Table 10‒6 (“L” for markedly abnormal low and “H” for markedly abnormal high). 
Similarly, physical examination findings together with the details of abnormalities (when 
applicable) will be listed by treatment group, subject and visit. 
Body weight will also be listed. 
10.4.2 
Electrocardiograms  
Since it is only planned to assess electrocardiogram (ECG) at the Screening Visit, the Baseline 
value will be derived based on the Screening assessment.  
A summary of the absolute and change from Baseline values at Week 16 and at SFU in each 
ECG variable will also be created by treatment group. The following ECG variables will be 
assessed: 
• Heart Rate (bpm) 
• PR interval (ms) 
• RR interval (ms) 
• QRS duration (ms) 
• QT interval (ms) 
• QTcF interval (ms) 
• QTcB interval (ms) 
The date and time of the ECG will be recorded in the eCRF together with the Investigator 
interpretation. A summary of the number and percentage of subjects with normal, abnormal not 
clinically significant, and abnormal clinically significant ECG results will be presented for 
Baseline, Week 16 and SFU timepoints.  
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QTc outliers are defined as QTcF (or QTcB) values following dosing that are greater than 450 
ms or are increases from Baseline greater than 30 ms. QTcF and QtcB outliers will be 
summarized in a dedicated table using the following categories: 
• Values >450 ms, >480 ms, >500 ms 
• Increase from Baseline of >30 ms, >60 ms, >90 ms 
• Values >450 ms and increase of >30 ms. Values >500 ms and increase from Baseline >60 
ms. 
Number and percentage of subjects who meet the ECG outlier criteria at any assessment post 
first dose will be summarized. 
All ECG tables will be provided on the SS by randomized treatment. 
All 12-lead ECG data where QTcF and QTcB outliers are highlighted will also be listed.  
10.5 
Other safety variables 
10.5.1 
Electronic Columbia Suicide Severity Rating Scale (eC-SSRS) 
The eC-SSRS is an assessment tool that evaluates suicidal ideation and behavior.  
 
The eC-SSRS contains 9 categories with binary responses (yes/no): 
• Category 1 - Wish to be dead  
• Category 2 - Non-specific active suicidal thoughts  
• Category 3 - Active suicidal ideation with any methods (not plan), without intent to act  
• Category 4 - Active suicidal ideation with some intent to act, without specific plan  
• Category 5 - Active suicidal ideation with specific plan and intent  
• Category 6 - Preparatory acts or behavior 
• Category 7 - Aborted attempt 
• Category 8 - Interrupted attempt 
• Category 9 - Actual attempt 
Following composite endpoints based on the above categories are defined as: 
• Suicidal ideation: A “yes” answer at any time during treatment to any one of the five suicidal 
ideation questions (Categories 1-5). 
• Suicidal behavior: A “yes” answer at any time during treatment to any one of the four 
suicidal behavior questions (Categories 6-9). 
• Suicidal ideation or behavior: A “yes” answer at any time during treatment to any one of the 
nine suicidal ideation and behavior questions (Categories 1-9). 
Self-injurious behavior without suicidal intent is defined as event in the category non-suicidal 
self-injurious behavior (in category 9). 
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The visit identification for each assessment of eC-SSRS will not be part of the data collected and 
the visit date in eCRF will then be used to assign a visit identification to the eC-SSRS data. 
For each subject, eC-SSRS assessment dates will be compared to eCRF visit dates.  
In the Study Data Tabulation Model (SDTM):  
If an eC-SSRS assessment date is matching an eCRF scheduled visit date, then the eC-SSRS visit 
identification will be the one corresponding to eCRF visit date. Otherwise, the eC-SSRS visit 
identification will be considered as “unscheduled”.   
In the analysis data sets (ADaM):  
If an eC-SSRS assessment date is matching an eCRF scheduled visit date within a window of +/- 
3 days, then the eC-SSRS visit identification will be the one corresponding to the eCRF visit 
date. Otherwise, the eC-SSRS visit identification will stay as “unscheduled”.   
The incidence of subjects with suicidal ideation, suicidal behavior, suicidal behavior or ideation, 
and self-injurious behavior without suicidal intent will be summarized by treatment and by visit 
for the SS. A by-subject listing of the eC-SSRS questionnaire data will be provided. 
10.5.2 
Assessment of tuberculosis 
The laboratory test results (negative, positive or indeterminate) from the TB assessment 
performed by interferon gamma release assay will be summarized by treatment group for 
Baseline (Screening) and Week 12 timepoints, as well as be listed.  
The results from the ‘Evaluation of signs and symptoms of tuberculosis’ questionnaire data will 
be also be listed.  
10.5.3 
Change from Baseline in the Patient Health Questionnaire-9 (PHQ-9) 
The PHQ-9 is a multipurpose instrument for Screening, diagnosing, monitoring, and measuring 
the severity of subject’s depression. The PHQ-9 score is based on nine questions assessing the 
depression over the last two weeks. Each criterion is scored from 0 (not at all) to 3 (nearly every 
day). The total score for the nine questions is added up and provide the PHQ-9 score and can 
range from 0 to 27 with higher scores indicating worse state. If one of the nine criteria is missing, 
the PHQ-9 score will be set to missing. 
The following depression states are defined based on the PHQ-9 score: 
• A score of 0-4 is considered to be none or minimal depression severity 
• A score of 5-9 is considered to be mild depression severity  
• A score of 10 to 14 is considered to indicate moderate depression severity  
• A score of 15 to 19 is considered to indicate moderately severe major depression 
• A score ≥20 is considered to be severe major depression  
The percentage of subjects with PHQ-9 scores below 5, between 5 and 9, between 10 and 14, 
between 15 and 19, and 20 or greater will be summarized by visit and treatment group, as well as 
the change from Baseline over time.  
Only observed data will be presented for PHQ-9 results. 
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11 
REFERENCES 
Fleiss JL, Tytun A, Ury SHK. A simple approximation for calculating sample sizes for 
comparing independent proportions. Biometrics. 1980;36:343-6. 
Moser, BK; Stevens, GR; Watts, CL. The Two-Sample T Test Versus Satterthwaite's 
Approximate F Test. Communication in Statistics- Theory and Methods 18(11):3963-3975 · 
Mallinckrodt CH. Preventing and Treating Missing Data in Longitudinal Clinical Trials: A 
Practical Guide. New York, NY: Cambridge University Press; 2013. 
O'Kelly, Michael, and Bohdana Ratitch. Clinical trials with missing data: A guide for 
practitioners. John Wiley & Sons, 2014. 
Rubin, Donald B. "The calculation of posterior distributions by data augmentation: Comment: A 
noniterative sampling/importance resampling alternative to the data augmentation algorithm for 
creating a few imputations when fractions of missing information are modest: The SIR 
algorithm." Journal of the American Statistical Association 82, no. 398 (1987): 543-546. 
Eberl G, Studnicka-Benke A, Hitzelhammer H, et al. Development of a disease activity index for 
the assessment of reactive arthritis (DAREA). Rheumatology (Oxford) 2000;39:148–55. 
Ulm K. A simple method to calculate the confidence interval of a standardized mortality ratio. 
American Journal of Epidemiology 1990;131(2):373-375.  
Hosmer, D. W., Jr., and Lemeshow, S. (2000). Applied Logistic Regression. 2nd ed. New York: 
John Wiley & Sons. 
Maruish M, Kosinki M, Bjorner J, Gandek B, Turner-Bowker D, Ware J. User’s mamual for the 
SF36v2 Health Survey. 
 
 
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12 
APPENDICES 
12.1 
Appendix1: MedDRA algorithmic approach to anaphylaxis 
The SMQ Anaphylactic reaction consists of 3 parts:  
• A narrow search containing PTs that represent core anaphylactic reaction terms (Cat A) 
 
• A broad search that contains additional terms that are added to those included in the narrow 
search. These additional terms are signs and symptoms possibly indicative of anaphylactic 
reaction and categorized in B, C, or D  
Cat B 
 
Cat C 
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Cat D 
          
 
• An algorithmic approach which combines a number of anaphylactic reaction symptoms in 
order to increase specificity. A case must include either (on the same day):  
– A narrow term or a term from Category A;  
– A term from Category B - (Upper Airway/Respiratory) AND a term from Category C - 
(Angioedema/Urticaria/Pruritus/Flush);  
– A term from Category D - (Cardiovascular/Hypotension) AND [a term from Category B - 
(Upper Airway/Respiratory) OR a term from Category C - (Angioedema/Urticaria/ 
Pruritus/Flush)]  
• Hypersensitivity events will be identified using the “Hypersensitivity (SMQ)”. All TEAEs 
which code to a PT included in the Scope=Narrow search will be included.   
 
12.2 
Appendix2: UCB-defined search criteria for identifying 
Opportunistic infections 
Opportunistic infections are identified in two steps:  
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Step 1: Refer to column B of the UCB Opportunistic infections document (Opportunistic 
infections MedDRA v 19.xlsx) which identifies the Preferred Terms (PTs) to be classified as 
opportunistic infections using either a single ‘x’ or a double ‘xx’. 
TEAEs which code to a PT flagged with a single ‘x’ need to also be serious to be considered an 
opportunistic infection. 
All TEAEs which code to a PT flagged with a double ‘xx’ are considered to be an opportunistic 
infection, regardless of seriousness.  
Step 2: Refer to column C of the spreadsheet which identifies the PTs that need to be evaluated 
on a case-by-case basis by the study physician to determine whether or not it is an opportunistic 
infection. If Column C has a single ‘x’, then the corresponding preferred term should be flagged 
for case-by-case review by the study physician.  
 
 
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13 
AMENDMENT(S) TO THE STATISTICAL ANALYSIS PLAN 
(SAP) 
13.1 
Amendment 1 
Rationale for the amendment 
The primary purpose of this amendment was to implement changes in response to protocol 
amendments and discussions and feedback provided at meetings between UCB and Parexel 
technical teams for procedural clarifications and due to COVID-19 global pandemic impact. The 
main changes are changing the statistical hierarchy, rules for handling missing data and 
guidelines on the implementation of multiple imputation, modifying the secondary variables, and 
incorporate latest guidelines from the BKZ AE of special monitoring convention document.  
Modifications and changes 
Global changes 
• Study participants was changed to subjects 
• Re-classification of Change from Baseline in Patient Health Questionnaire-9 (PHQ-9) 
variable from other efficacy variable to other safety variable 
• New rules for handling of missing data for the primary and key secondary efficacy variables 
• Use of latest guidelines from the BKZ AE of special monitoring convention document 
• Clarification on use and multiple imputation approaches in supportive analyses 
− Observed cases 
− NRI 
− Reference Based imputation 
• Imputation of partial start dates 
• FACIT-F has been corrected to FACIT-Fatigue subscale, as it is the fatigue subscale that is 
being assessed in this study 
• Deleted Asia/Australia to represent only Asia now which includes Australia 
 
 
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Specific changes 
Change #1 
Section 1 Introduction 
The SAP is based on the final Protocol (26 NOV 2018) 
Has been changed to: 
The SAP is based on the Protocol Amendment 2 (1 APR 2021).  
Change #2  
Section 2.2.2.1 Secondary efficacy variables 
The following has been changed: 
Was section 2.2.1.2 
• PASI90 response at Week 4 and Week 16 in the subgroup of subjects with PSO involving at 
least 3% BSA at Baseline 
• Change from Baseline in Health Assessment Questionnaire—Disability Index (HAQ-DI) at 
Week 16 
• Change from Baseline in the Short-Form 36-item Health Survey (SF-36) Physical 
Component Summary (PCS) at Week 16 
Etc 
Changed ordering to: 
Section 2.2.2.1 
• Change from Baseline in Health Assessment Questionnaire—Disability Index (HAQ-DI) at 
Week 16 
• PASI90 response at Week 4 and Week 16 in the subgroup of subjects with PSO involving at 
least 3% BSA at Baseline 
• Change from Baseline in the Short-Form 36-item Health Survey (SF-36) Physical 
Component Summary (PCS) score at Week 16 
• Change from Baseline in Psoriatic Arthritis Impact of Disease-12 (PsAID-12) total score at 
Week 16 
 
Change #3 
Section 2.2.2.2 Secondary Safety variables 
The section was moved from section 2.2.5.1 to 2.2.2.2 and the following was updated: 
Treatment-emergent adverse events leading to withdrawal from IMP 
 Change #4 
Section 2.2.3.1 Other efficacy variables 
The section was moved from section 2.2.1.3 to 2.2.3.1 and the following was added: 
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• Composite endpoint composed of ACR50 and PASI100 response in subjects with PSO 
involving at least 3% BSA at Baseline 
• Proportion of Psoriatic Arthritis Response Criteria (PsARC) responders 
• Psoriatic Arthritis Disease Activity Score (PASDAS) categories 
• Change from Baseline in the PASDAS  
• Disease Activity Index for Psoriatic Arthritis (DAPSA) score categories 
• Proportion of subjects with a decrease of HAQ-DI from Baseline of at least 0.35 in the 
subgroup of subjects with Baseline HAQ-DI≥0.35 
• Proportion of FACIT-Fatigue subscale responders (subjects with a minimum clinically 
important difference for FACIT-Fatigue subscale score, defined as an increase of ≥4) in 
subjects with FACIT-Fatigue subscale score ≤48 at Baseline 
Change #5 
Section 2.2.3.1 Other efficacy variables 
• Disease Activity Index for Psoriatic Arthritis (DAPSA) score 
• Change from Baseline PsAID-12 
• Change from Baseline in the Psoriatic Arthritis Quality of Life (PsAQoL) 
• Change from Baseline in Functional Assessment of Chronic Illness Therapy—Fatigue 
(FACIT-F) 
Changed to:  
• Disease Activity Index for Psoriatic Arthritis (DAPSA) score categories 
• Change from Baseline in PsAID-12 total score 
• Change from Baseline in the individual domain scores of PsAID-12 
• Proportion of subjects achieving PsAID-12 total score ≤4 
• Proportion of PsAID-12 responders (decrease Change from Baseline in PsAID-12 total score 
≥3) (PsAID-12 responders) in subjects with PsAID-12 total score >3 at Baseline 
• Change from Baseline in the Psoriatic Arthritis Quality of Life (PsAQoL) total score 
• Change from Baseline in Functional Assessment of Chronic Illness Therapy (FACIT)—
Fatigue (FACIT-F) subscale score 
Change #6 
Section 2.2.5.2 Other safety variables 
Has been moved to  
Section 2.2.3.2 Other safety variables 
Change #7 
Moved PHQ-9 variable  
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Section 2.2.1.3 Other efficacy variables  
Moved to section 2.2.3.2 Other safety variables 
Change #8 
Moved and updated the following: 
Section 2.2.2 Pharmacokinetic variable 
Section 2.2.3 Pharmacogenomic variables 
Section 2.2.4 Immunological variables 
Moved to: 
Section 2.2.3.3 Pharmacokinetic variable 
Section 2.2.3.4 Pharmacogenomic variables 
Where local regulations permit, additional blood samples will be collected at specific time points 
from study participants consenting to participate in a pharmacogenomic substudy. These samples 
will be stored at -80°C for up to 20 years to allow for potential, exploratory analyses of genomic, 
genetic, epigenetic, proteins, and metabolite biomarkers to evaluate the relationship with 
response to treatment with bimekizumab, psoriatic arthritis disease biology, and inflammatory 
and immune response processes.  
The pharmacogenomic variables are the blood or blood derivative (eg, serum) concentrations of 
cytokines and chemokines of relevance to IL-17A/F signaling pathway and psoriatic arthritis 
biology and will be assessed at Baseline and at Week 16.  
These variables will be described in a separate statistical analysis plan. The nature and format of 
these substudy analyses will be determined at a later date. 
Updated to the following: 
Additional blood samples will be collected from subjects who consent to participate in the sub 
study at specific time points and stored at -80°C for up to 20 years. 
Genomic, genetic, epigenetic, proteins, and metabolite biomarkers may be measured to evaluate 
the relationship with response to treatment with BKZ, PsA disease biology, and inflammatory 
and immune response processes. The nature and format of these tentative sub study analyses will 
be determined when the results of the main study are made available. 
The candidate exploratory variables are the blood or blood derivative (eg, serum) concentrations 
of cytokines and chemokines of relevance to IL-17A/F signaling pathway and PsA biology. 
Additional variables may include but will not be limited to serum complement concentrations 
Section 2.2.3.5 Other Immunological variables 
Added the following: 
• The neutralizing anti-drug antibody (NAb) status 
These 3 variables will be assessed at all visits except Screening 
Change #9  
Moved section 3.2.2 to section 2.3.2 Study Periods 
The following study periods are defined for the classification by study period: 
Screening Period (≥14 days to ≤35 days) 
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Starts at time of the informed consent date (Screening Visit -Visit 1) and ends the day before the 
first dose administration of study drug (Baseline Visit – Visit 2) (ie, generally the day before 
Visit 2 date). This period should last between 14 to 35 days and will involve obtaining laboratory 
data and verifying that the doses of nonsteroidal anti-inflammatory drugs (NSAIDs) or permitted 
DMARDs, if used to treat PsA, are stable. The Screening Period will also enable washout of any 
medications not permitted for use during the study. 
 
Double-Blind Treatment Period (16 weeks) 
Starts on the day of first dose administration of study drug (Visit 2) and ends as described in 
Section 3.2.1.2. This period should last 16 weeks maximum. During the Double-Blind Treatment 
Period, subjects will be randomized 2:1 (stratified by region and prior TNFα inhibitor exposure 
[inadequate response to 1 or 2 prior TNFα inhibitors, or intolerance to TNFα inhibitors]) to 
receive 1 of 2 blinded treatment regimens: 
• Bimekizumab 160mg sc Q4W,  
• Placebo 
Visit windows of ±3 days are allowed from the first dose at all visits through Week 16. The visit 
window is relative to the Day 1 (Baseline) Visit.  
BKZ and placebo will be administered sc by unblinded study personnel at the clinical site. 
The time between IMP doses should be ≥21 days and ≤35 days during the Double-Blind 
Treatment Period.  
Subjects discontinuing IMP during the Double-Blind Treatment Period will return for all 
scheduled visits through Week 16 and the SFU Visit (20 weeks after the final dose of IMP) as 
applicable. Subjects withdrawing from the study will have an Early Termination (ET) Visit and a 
SFU Visit 20 weeks after the final dose of IMP, as applicable. 
 
The end of the 16-week Double-Blind Treatment Period will be either the date of Week 16 visit 
(Visit 6) for subjects completing the treatment period, or the date of the early termination (ET) 
visit for subjects who discontinued during the Treatment Period. 
If a subject does not have a Visit 6 or ET visit, then either the date of the last scheduled or 
unscheduled visit during the Treatment Period or the date of last known dose of study drug 
during the Treatment Period, whichever is later, will define the end date of the Treatment Period. 
 
Safety Follow-Up 
The SFU Period will be defined for all subjects who complete the study and do not enter the 
OLE study, or for subjects who discontinue early including those withdrawn from IMP. This 
period should last 20 weeks. 
• For subjects who complete the study and do not enter the OLE study, the SFU Period starts 
the day after Visit 6 date and ends on the day of the SFU Visit.  
• For subjects who discontinue early, the SFU Period starts the day after the ET date and ends 
on the day of the SFU Visit 
A subject will be considered to have completed a study period if they complete the last scheduled 
study visit for that period. Note that subject participants who previously discontinued IMP and 
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are continuing for all scheduled visits through Week 16 will also be considered as completed the 
Double-Blind Treatment Period. 
Change #10 
Section 2.4 Determination of sample size 
Was moved to section 2.6 Determination of sample size and following text was added: 
Approximately 390 subjects will be randomly assigned in a 2:1 ratio to the following treatment 
groups: BKZ 160mg sc Q4W (260 subjects) and placebo (130 subjects).  
The primary efficacy analysis is based on the primary comparison of BKZ versus placebo for 
ACR50 response at Week 16.  
All sample size and power calculations were done at a significance level of 0.05. 
All sample size and power calculations were performed using the software nQuery Advisor® 
7.0. 
Change #11 
Section 3.1 General presentation of summaries and analyses 
The following text was updated: 
• Percentages will be summarized based on all subjects in the analysis set and a “Missing” 
category (corresponding to subjects with missing data for the variable being summarized) 
will be included as the last row in the list of categories being summarized (this approach 
will be used when reporting demographics and Baseline characteristics, some NAb 
tables and some shift tables from Baseline for laboratory data). 
For hs-CRP variable, the summary statistics should contain arithmetic mean, geometric mean, 
geometric coefficient of variation (CV), median, first and third quartile (Q1 and Q3), minimum 
and maximum (for the value and ratio to Baseline).  
Decimal places for descriptive statistics will always apply the following rules: 
• “n” will be an integer.  
• Mean, SD, SE, and median (Q1 and Q3 where applicable) will use 1 additional decimal place 
compared to the original data (for a derived score, number of decimals of the original 
data considered is the one obtained where deriving the score in the absence of missing 
data).  
• Coefficient of variance (CV [%]) will be presented with 1 decimal place.  
• Minimum and maximum will have the same number of decimal places as the original raw 
value. 
If the number of decimal places reported in the raw data is varied then either the maximum raw 
number of reported decimal places or 3 will be used, whichever is the lowest, as a guide for the 
descriptive statistics. 
Table 3.1: List of decimals for continuous efficacy endpoints 
Continuous efficacy endpoint  
Decimal places used for 
Minimum and 
maximum  
Decimal places used 
for Mean, SD (or SE) 
and median  
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BASDAI  
1 
2  
DAPSA  
1 
2  
DAS28[CRP]  
2 
3  
EQ-5D-3L dimension scores  
0 
1  
EQ-5D-3L (VAS)  
0 
1  
FACIT-Fatigue subscale score  
1 
2  
HAQ-DI  
3 
4  
hs-CRP  
2 
3 
IGA  
1 
2  
LDI  
1 
2  
LEI  
0 
1  
mNAPSI  
1 
2  
PASDAS  
1 
2  
PASI  
0 
1  
PGA-Arthritis /PhGA-Arthritis  
0 
1  
PGA-PsA / PhGA-PsA  
1 
2  
PsAID-12  
1 
2  
PsAQoL  
1 
2 
PsARC  
0 
1  
PtAAP  
2 
3  
SF-36  
1 
2  
SPARCC  
1 
2  
TJC / SJC  
1 
2 
WPAI-SHP  
1 
2  
BASDAI=Bath Ankylosing Spondylitis Disease Activity Index; DAPSA=disease activity index for psoriatic 
arthritis; DAS28[CRP]=disease activity score-28 based on C-reactive protein; EQ-5D-3L=Euro-Quality of Life 5-
Dimensions 3 Level version; FACIT=Functional Assessment of Chronic Illness Therapy; HAQ-DI=Health 
Assessment Questionnaire – Disability Index; hs-CRP=High sensitivity C-reactive protein; IGA=Investigator 
Global assessment; LDI=Leeds Dactylitis Index; LEI=Leeds Enthesitis Index; mNAPSI=Modified Nail Psoriasis 
Severity Index; PASDAS= Psoriatic Arthritis Disease Activity Score; PASI=Psoriasis Area and Severity 
Index;  PGA-Arthritis=Patient’s Global Assessment of Arthritis; PGA-PsA=Patient’s Global Assessment of 
Psoriatic Arthritis; PhGA-Arthritis=Physician’s Global Assessment of Arthritis; PhGA-PsA=Physician’s Global 
Assessment of Psoriatic Arthritis;   PHQ-9=Patient Health Questionnaire-9; PSAID-12=Psoriatic Arthritis impact of 
disease-12; PsAQoL=Psoriatic Arthritis Quality of Life; PsARC= Psoriatic Arthritis Response Criteria; 
PtAAP=Patient’s assessment of Arthritis Pain;  SF-36=Short-Form 36-item Health Survey; SJC= Swollen Joint 
Count; SPARCC= Spondyloarthritis Research Consortium of Canada ; TJC=Tender Joint Count; WPAI-SHP=Work 
Productivity and Activity Impairment questionnaire – Specific Health Problem  
Unless stated otherwise, statistical tests of efficacy variables will be performed 2-sided and p-
values will be rounded to 3 decimal places. P-values less than 0.001 will be presented as 
“<0.001” and p-values greater than 0.999 will be presented as “>0.999.” Statistical comparison 
will be performed at the 0.05 level of significance. Least square means (LSM), odds-ratios (OR) 
and corresponding confidence intervals (CI) will be presented using 3 decimalsUCB uses SAS in 
a 64-bit Windows environment, and it is well-documented that in this environment the maximum 
accuracy of any numeric value is 15 significant digits. However, SAS by default does not limit 
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the accuracy of numeric values to 15 significant digits which, in certain instances, may result in 
inaccurate representation of the data and cause errors when used in subsequent calculations, 
particularly when comparing a value to a chosen threshold. This, in turn, could potentially result 
in a change in classification of a subject from a responder to a nonresponder (and vice versa) if 
these values occur on a threshold used in the evaluation of response (or a critical laboratory value 
for example). 
Therefore, in order to avoid issues caused by inaccurate floating point representation of numeric 
values, temporary variables are created (i.e., for absolute values, change and percentage change 
from Baseline) during programming which are rounded to 12 decimal places prior to comparison 
to a specific threshold in the derivation of a response parameter. This does not imply inherent 
rounding on the analysis variables for absolute value, change or percentage of change which are 
retained unrounded in the final analysis dataset. Thus, rounding is applied exclusively during the 
derivation of new response parameters or critical value variables, and the rounded values are 
created on a temporary basis only. 
The SAS® outputs supportive of any inferential statistics that are part of the hierarchical testing 
procedure (ie, all inferential statistics associated with the endpoints in Table 7‒4), will be 
provided as a separate PDF document in addition to TFLs. These outputs will be included in the 
‘Documentation of Statistical Methods’ section of the clinical study report. 
The order of treatment groups to be presented in tables from left to right will be: 
• Placebo 
• Bimekizumab 160mg Q4W 
Selected tables may also include columns for all subjects (regardless of study treatment). 
The abbreviation for bimekizumab is BKZ and will be used in tables and listings headers. In the 
TLFs subjects randomized to bimekizumab 160mg will be labeled as “BKZ 160mg Q4W”.  
Change #12 
Section 3.2.3 Mapping of assessments performed at Early Termination Visit 
The following text was added: 
If there is an existing scheduled site visit in the window, then the assessments at the ET visit will 
be mapped to the next scheduled site visit. 
The anti-bimekizumab antibody (ADAb) assessments and PK are exceptions to this rule:  
• ADAb levels, PK from an ET visit will be mapped to the next visit where antibody levels / 
PK are measured. 
Change #13 
Section 3. 3 Definition of Baseline values 
The following text was added: 
By default, for randomized subjects for which no start date of treatment is available, the Baseline 
value will be considered as the last available value prior to the randomization date 
Baseline values for component scores should be computed using components from the same 
visit where the relevant measurements were recorded prior to dosing. For example, if the 
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Screening Visit has all of the components, and the Baseline visit is missing one or more 
components, the Baseline value for the component score should be calculated using the 
Screening Visit values. 
Chest x-ray performed within 3 months before the Screening Visit is considered as Baseline 
measurement. 
Change #14 
Added the following: 
Section 3.4 Study Treatment Discontinuation and Intercurrent Event 
The concept of intercurrent event is one of the estimand attributes. 
 
Unless otherwise noted, treatment discontinuation due to any reason will be considered as 
intercurrent event (IE). The IE date will be defined similarly as the treatment discontinuation 
date below. Since there is no treatment discontinuation date collected, the treatment 
discontinuation date is defined as: 
• 
Treatment end date + 31 days. 
Change #15 
Updated the following: 
Section 3.4 Protocol deviations 
A specific category of PD, as a consequence of the Coronavirus Disease 2019 (COVID-19) 
pandemic, called COVID-19 related PD will be assessed based especially on the information 
collected on a dedicated eCRF page (and other available sources).  
Change #16 
Modified the following: 
Section 3.6 Analysis sets 
Deleted the following text: 
The primary efficacy variable will be analyzed for all study participants in the Randomized Set 
(RS), and the primary efficacy analysis will be repeated on the Full Analysis Set (FAS) and the 
PPS. All other efficacy variables will be based on the RS.  
Demographics tables will be performed on the RS as well as on the Safety Set (SS), if SS is 
different from RS. Safety variables will be summarized on the SS. PK variables will be analyzed 
for all study participants in the PK-PPS. 
Updated Section 3.6.2 Randomized Set 
The Randomized Set (RS) consists of all enrolled subjects who have been randomized.  
Demographic tables, primary, secondary and other efficacy variables will be presented on 
the RS. 
Updated Section 3.6.3 Safety Set 
The Safety Set (SS) consists of all subjects who received at least one dose of the IMP. 
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Demographic tables, study treatment compliance and exposure and safety variables will be 
presented on the SS. The anti-BKZ antibody will also be analyzed on the SS for subjects 
receiving BKZ. 
Updated Section 3.6.4 Full-Analysis Set 
Supportive analysis of the primary efficacy variable will be performed on the FAS.  
Updated Section 3.6.5 Per-Protocol Set 
Exclusion from the FAS will be considered as important protocol deviations that also result in 
exclusion from the PPS. 
Supportive analysis of the primary efficacy variable will be performed on the PPS. 
Updated Section 3.6.6 Pharmacokinetic Per-Protocol Set 
PK variables will be analyzed for all subjects in the PK-PPS. 
Added Section 3.6.7 COVID-19-free Set 
The COVID-19 free set will consist of all subjects in the RS who had no COVID-19 impact up to 
the primary efficacy endpoint. This will be defined as subjects: 
• not having a COVID-19 related IPD 
• not having an impact based on the COVID-19 eCRF. 
• not having an AE related COVID-19 (Section 10.2.5) 
• not discontinuing due to COVID-19 
The disposition data, the primary efficacy endpoint and the secondary efficacy endpoints 
included in the testing hierarchy will be analyzed on the COVID-19-free Set. 
Change #17 
Updated the following: 
Section 3.10 Changes to protocol-defined analyses 
The following changes from the protocol will be considered:  
• The subgroup analysis on BASDAI will be performed on the categories: <4 vs. ≥4 rather than 
≤4 vs. >4 
• Proportion of subjects with a decrease of HAQ-DI from Baseline of at least 0.35 (HAQ-DI 
responders) in those subjects with HAQ-DI ≥0.35 instead of >0.35 
• Proportion of PsAID-12 responders (decrease from Baseline in PsAID-12 total score ≥3) in 
subjects with PsAID-12 total score ≥3 at Baseline instead of >3 at Baseline. 
• An additional supportive analysis for primary endpoint based on the analysis of the 
individual components of ACR will be performed using the Reference-Based imputation 
method. 
• The main analyses of the secondary continuous variables included in the testing hierarchy 
will be performed using the Reference-Based imputation method. 
• Additional subgroup analyses will be performed for HAQ-DI responders at Week 16. 
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• Additional variable added for subgroups: Concomitantly receiving MTX vs. cDMARDs at 
Baseline (concomitant MTX, no concomitant MTX and cDMARDs at Baseline, no 
concomitant MTX and no cDMARDs at Baseline 
Change #18 
Added the following section: 
Section 3.11 Changes related to COVID-19 
The impact of the COVID-19 pandemic on study procedures/conduct as well as the efficacy and 
safety endpoints will be investigated, and additional analysis outputs will be provided as 
appropriate. These additional analyses were not planned as part of the original protocol as the 
pandemic was not ongoing at the time of protocol finalization. These additional analyses will 
include analyses by period of the COVID-19 pandemic (pre/during/post) as defined below: 
• Pre COVID-19 pandemic period: Period prior to COVID-19 pandemic start date defined as 
11-Mar-2020. 
• COVID-19 pandemic period: Period from 11-Mar-2020 though the COVID-19 pandemic end 
date which is currently not defined at the time of approval of the SAP. 
• Post COVID-19 pandemic period: Period after the declaration of the end of the pandemic 
The additional analyses are described in the following sections: 
• Subject disposition (Section 5.1) 
• Details of impacted visits and effects on collection and reporting of efficacy data 
(Section 5.2) 
• Protocol deviations (Section 5.3) 
• Efficacy analyses related to the hierarchy endpoints (Section 8.1.4.8  and Section 8.2.3 ) 
• Adverse events (Section 10.2.5) 
Change #19 
Modified the following section: 
Section 4.1 Adjustments for covariates 
The primary efficacy analysis that will investigate the treatment effect will be adjusted for: 
• Prior TNFα inhibitor exposure (inadequate response to 1 prior TNFα inhibitor, inadequate 
response to 2 prior TNFα inhibitors, intolerance to TNFα inhibitors), and  
• Region (Asia/Australia, Eastern Europe, North America, Western Europe) 
However, prior TNFα inhibitor exposure may be dropped from the model in order to achieve 
model convergence (ie, in case the likelihood maximization algorithm failed to converge). If 
convergence is still not obtained, then region may also be dropped from the model.  
Prior TNFα inhibitor exposure and region are the stratification factors of the randomization. In 
the event that a study participant is stratified in the incorrect stratum (i.e. the stratum recorded in 
the Interactive voice or web Response System (IXRS) differs from the actual stratum the study 
participant belongs to), the actual stratum will be used for the analysis.  
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The secondary analyses will be adjusted on the same categorical factors as the primary analysis. 
For continuous variables, Baseline value (of the variable of interest) will also be included as 
covariates where appropriate. 
Modified to the following: 
The primary efficacy analysis will investigate the treatment effect, adjusting on the two 
randomization stratification variables: 
• Region  
− North America, Western Europe, Eastern Europe, Asia  
or 
− North America, Eastern Europe, Western Europe + Asia if the percentage of randomized 
subjects is less than 10% in either of the Asia or Western Europe regions  
• Prior TNFα inhibitor exposure (inadequate response to 1 prior TNFα inhibitor, inadequate 
response to 2 prior TNFα inhibitors, intolerance to TNFα inhibitors). 
When adjusting on these 2 variables, a statistical model might not converge (ie, in case the 
likelihood maximization algorithm failed to converge). In that case, the statistical model will be 
run after dropping stratification variables in their order of appearance, successively region (one 
first and the other after) and prior TNFα inhibitor exposure.  
In the event that a subject is stratified in the incorrect stratum (ie, the stratum recorded in the 
Interactive voice or web Response System (IXRS) differs from the actual stratum the subject 
belongs to), the actual stratum will be used for the analysis.  
The secondary analyses will be adjusted on the same categorical factors as the primary analysis. 
For continuous variables, Baseline value (of the variable of interest) will also be included as 
covariate where appropriate.  
Change #20 
Section 4.2.1 Handling missing data for efficacy analyses 
Added the following table as follows: 
Section 4.2.1 Strategy for handling missing data for efficacy analyses 
Different approaches will be used to handle missing data including how the intercurrent events 
will be considered (Section 3.4).  
In this section, 3 terms will be defined for binary endpoints:  
• Non-composite binary endpoint: Binary endpoints derived based on 1 continuous 
measurement (eg, PASI90).  
• Composite binary endpoint: Binary endpoints derived based on several continuous 
measurements (eg, ACR50).  
• Composite continuous endpoint: Continuous endpoint derived based on several continuous 
measurements (eg, PASDAS).  
The table below summarizes all continuous endpoints (excluding composite continuous 
endpoints) along with their observed ranges and indicate whether they are represented by an 
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integer value. These endpoints will be analyzed and / or used in the derivation of composite or 
non-composite endpoints: 
Table 4.1: List of non-composite continuous endpoints 
Efficacy endpoint 
Minimum 
Maximum 
Integer 
Value 
BASDAI 
0 
10 
 
EQ-5D-3L dimension scores 
1 
3 
Yes 
EQ-5D-3L (VAS) 
0 
100 
Yes 
FACIT-Fatigue subscale score 
0 
52 
 
HAQ-DI 
0 
3 
 
hs-CRP 
LLOQ/2 where 
LLOQ=0.10mg/L 
No maximum 
 
IGA 
0 
4 
Yes 
LDI 
0 
No maximum 
 
LEI 
0 
6 
 
mNAPSI 
0 
13 
Yes  
PASI 
0 
72 
 
PGA-Arthritis /PhGA-Arthritis 
0 
100 
Yes 
PGA-PsA / PhGA-PsA 
0 
100 
Yes 
PsAID-12 
0 
10 
 
PsAQoL 
0 
20 
 
PtAAP 
0 
100 
Yes 
SF-36a  
Physical Functioning (PF) 
Role Physical (RP) 
Bodily Pain (BP) 
General Health (GH) 
Vitaly (VT) 
Social Functioning (SF) 
Role Emotional (RE) 
Mental Health (MH) 
Physical component summary (PCS) 
Mental component summary (MCS) 
 
19.26 
21.23 
21.68 
18.95 
22.89 
17.23 
14.39 
11.63 
5.02 
-3.33 
 
57.54 
57.16 
62.00 
66.50 
70.42 
57.34 
56.17 
63.95 
79.78 
80.09 
 
SPARCC 
0 
16 
 
TJC / SJC 
0 
68/66 
 
WPAI-SHP 
0 
100 
 
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BASDAI=Bath Ankylosing Spondylitis Disease Activity Index; EQ-5D-3L=Euro-Quality of Life 5-Dimensions 3 Level version; 
FACIT=Functional Assessment of Chronic Illness Therapy; HAQ-DI=Health Assessment Questionnaire – Disability Index; hs-
CRP=High sensitivity C-reactive protein; IGA=Investigator Global assessment; LDI=Leeds Dactylitis Index; LEI=Leeds 
Enthesitis Index; LLOQ=lower limit of quantification; mNAPSI=Modified Nail Psoriasis Severity Index; PASI=Psoriasis Area 
and Severity Index;  PGA-Arthritis=Patient’s global assessment of Arthritis; PGA-PsA=Patient’s Global assessment of 
Psoriatic Arthritis; PhGA-Arthritis=Physician’s Global Assessment of Arthritis;  PhGA-PsA=Physician’s Global 
Assessment of Psoriatic Arthritis;  PHQ-9=Patient Health Questionnaire-9; PSAID-12=Psoriatic Arthritis Impact of Disease-
12; PsAQoL=Psoriatic Arthritis Quality of Life; PtAAP=Patient’s Assessment of Arthritis Pain;  SF-36=Short-Form 36-item 
Health Survey; SJC= Swollen Joint Count; SPARCC= Spondyloarthritis Research Consortium of Canada ; TJC=Tender Joint 
Count; WPAI-SHP=Work Productivity and Activity Impairment questionnaire – Specific Health Problem 
a minimum and maximum of the norm-based scores – Normal range for SF-36 scores is 0-100  
Change #21 
Section 4.2.1 Handling of missing data for efficacy analyses 
Main analysis method 
 “Main analysis” refers in this section to the primary method of analysis used for a given 
endpoint, regardless of whether it be a primary, secondary, or other efficacy endpoint.Binary 
endpoints 
For binary efficacy endpoints, the main analysis method is as follows:  
• If study participants have missing data that is not preceded by an intercurrent event, then: 
− For non-composite binary endpoints, the standard MI (MI) methods (See Section 4.2.1.1) 
will be implemented on the raw score (eg, PASI for the PASI90 endpoint) before 
deriving the binary endpoint based on the imputed score.  
− For composite binary endpoints, where the composite binary endpoint cannot be 
constructed (i.e. either TJC/SJC are missing or >2 out of 5 PRO measures are missing), 
the MI will be implemented on each component variable that has missing data (e.g. TJC, 
SJC, PhGA-PsA, PGA-PsA, HAQ-DI, PtAAP, hs-CRP for the ACR50 endpoint), before 
deriving the binary endpoint based on the imputed components. 
• If study participants have an intercurrent event, then the endpoint at all subsequent visits 
(whether or not the data were observed) will be set to ‘nonresponse’ as the study participant 
has not met the criteria for response based on the composite estimand definition (See 
Section8.1.2). 
Note that in the case of a binary endpoint that is based on the combination of a non-composite 
binary endpoint with a composite binary endpoint (as with the ACR50 and PASI90 combined 
endpoint), each binary endpoint is derived independently, as described above. Then, the 
combined binary endpoint is derived based on the imputed data from each of the component 
binary endpoints.  
Continuous endpoints 
For continuous efficacy endpoints, the main analysis method is as follows:  
• Missing data will be imputed based on the standard MCMC/Monotone Regression MI 
approach described in Section4.2.1.1, regardless whether missing data is preceded by an 
intercurrent event. 
Supportive analysis methods 
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For the primary endpoint, which is a composite binary endpoint, several supportive analyses 
assuming different missing data mechanisms will be conducted: 
• The MCMC/Logistic Regression approach described in Section 4.2.1.2. 
• The reference-based MI approach described in Section 4.2.1.3.  
• The tipping point approach implemented within the MI framework, but only if the primary 
endpoint analysis result is statistically significant at alpha=0.05. The method is specified in 
Section 4.2.1.4 below.  
• The treatment policy strategy described in Section 4.2.1.5. 
• The observed case (OC) analysis that will only include the observed data for study 
participants who did not discontinue study treatment. Data collected after study treatment 
discontinuation for any reason and all other missing data will be excluded from this analysis. 
• Non-responder imputation (NRI) analysis will consider that study participants with missing 
data at the time point of interest did not respond to the treatment (ie, non-responder). This 
also include time points following study medication discontinuation for study participants 
who have stopped treatment but remain in the study. In the case of ACR50, nonresponse is 
imputed if any of the following are true (otherwise, ACR50 is evaluated based on the 
available data): 
− All ACR component variables are missing, or 
− TJC or SJC components are missing, or  
− TJC or SJC data are present, but more than 2 of the other 5 components are missing 
For all secondary endpoints, the OC analysis will be done as a supportive analysis. For binary 
secondary endpoints, NRI will in addition be performed as a supportive analysis.  
The OC analysis will be performed as a supportive analysis for other efficacy variables whose 
value at Week 16 are part of the hierarchical procedure. 
See Section 8.1.4, 8.2.3 and 8.3.2 for further details on these analyses. 
Table 7‒1 summarizes which missing data handling approaches will be used for each type of 
efficacy endpoint.  
Table 4.1: Missing data handling approaches for efficacy endpoints 
Variable 
Priority 
Variable 
Type 
Missing data handling approach 
MI 
(MCMC/ 
Monotone 
Regression) 
MI 
(MCMC/ 
Logistic 
Regression) 
NRI 
MI 
(MCMC/ 
Reference-
based) 
OC 
Treatment 
Policy 
Tipping 
Point 
Analysis 
Primary 
Composite 
Binary 
Pa 
S 
S 
Sa 
S 
Sa 
Sa 
Secondary 
Binary  
Pa 
 
S 
 
S 
 
 
Secondary 
Continuous 
P 
 
 
 
S 
 
 
Other 
Binary  
Pab 
 
 
 
Sc 
 
 
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Variable 
Priority 
Variable 
Type 
Missing data handling approach 
MI 
(MCMC/ 
Monotone 
Regression) 
MI 
(MCMC/ 
Logistic 
Regression) 
NRI 
MI 
(MCMC/ 
Reference-
based) 
OC 
Treatment 
Policy 
Tipping 
Point 
Analysis 
Other 
Continuous 
Pb 
 
 
 
Sc 
 
 
a Imputation method is applied on continuous data, and binary variable is derived from the continuous variable 
based on complete data set. 
b MI will be used to provide point estimates at each timepoint only, i.e. mean ACR50 proportion 
c Required only for by-visit summaries of variables whose value at Week 16 is part of the hierarchical testing 
procedure. 
P=Primary method, S=Supportive method. 
Was modified to: 
Section 4.2.1.1 Primary analysis of binary endpoints that are part of the testing hierarchy 
(primary and secondary endpoints) 
All binary endpoints (composite & non-composite) are based on continuous component 
variables. 
The primary analysis of binary efficacy endpoints that are part of the testing hierarchy is 
considered under a framework estimand in which missing data (due to study treatment 
discontinuation) is considered indicative of failed treatment and imputed to nonresponse. Further 
data missing while on treatment, or data observed while not on treatment, will also be imputed to 
nonresponse. 
This composite estimand approach to handling missing data which is the primary analysis 
method for binary efficacy endpoints is similar to the non-responder imputation (NRI) method. 
Section 4.2.1.2 Primary analysis of continuous endpoints that are part of the testing 
hierarchy (secondary endpoints) 
For continuous efficacy endpoints that are part of the testing hierarchy, the main analysis method 
is based on the hypothetical estimand approach as follows:  
• If subjects have missing data regardless whether the missing data is preceded by an IE, then 
missing data will be imputed based on the MI-MCMC/Reference-Based imputation method 
(Section 4.2.2.3). 
• If subjects have non-missing data after IE, then such data will be set to missing prior to 
running MI. 
Section 4.2.1.3 Supportive analyses of primary efficacy endpoints 
For the primary endpoint, which is a composite binary endpoint, several supportive analyses 
assuming different missing data mechanisms will be conducted: 
• The modified composite estimand approach: the IE is changed from all treatment 
discontinuation to discontinuation of treatment due to AE or lack of efficacy. The same as the 
primary method will be used with the difference that only data after discontinuation due to 
AE or lack of efficacy is set to nonresponse. All other imputed data will be used.  
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• For the analysis of individual components of ACR, under the hypothetical estimand approach 
using the Reference-Based imputation method (Section 4.2.2.3). 
• The tipping point approach implemented within the MI framework, but only if the primary 
endpoint analysis result is statistically significant at alpha=0.05. (Section 4.2.2.4).  
• The treatment policy strategy (Section 4.2.2.5). 
• The observed case (OC) analysis that will only include the observed data.  For subjects who 
had treatment discontinuation, only observed data prior to treatment discontinuation date will 
be analyzed.  For visits with missing data without treatment discontinuation, the data will 
remain missing.  For observed data after treatment discontinuation, the corresponding visit 
data and subsequent visit data will be treated as missing. 
Section 4.2.1.4 Supportive analyses of endpoints that are part of the testing hierarchy 
(secondary endpoints) 
The following supportive analysis methods will be performed for the secondary and the other 
efficacy variables that are part of the testing hierarchy: 
For binary endpoints:  
• The modified composite estimand approach: the IE is changed from all treatment 
discontinuation to discontinuation of treatment due to AE or lack of efficacy. For composite 
or non-composite binary endpoints, the standard MI approach) will be implemented 
(similarly as in Section 4.2.1.3) on the raw continuous score(s) (eg, PASI for the PASI90 
endpoint) before deriving the binary endpoint based on the imputed score(s).  
• The OC analysis.  
For continuous endpoints: 
• The hypothetical estimand approach:  
− If subjects have missing data regardless whether the missing data is preceded by an IE, 
then missing data will be imputed based on the MI-MCMC/Monotone regression method 
(Section 4.2.2.2). 
− If subjects have non-missing data after IE, then such data will be set to missing prior to 
running MI. 
• The OC analysis.  
Section 4.2.1.5 Analyses of secondary endpoints that not part of the testing hierarchy and 
other efficacy endpoints 
The other efficacy endpoints including the secondary efficacy endpoints that are not part of the 
testing hierarchy will be analyzed as the secondary efficacy endpoints (with the exclusion of the 
MI-MCMC/referenced based imputation method for continuous variables) but with no 
designated priority, with the exclusion of the MI-MCMC/reference-based imputation method for 
continuous variables. 
For a combined binary endpoint based on the combination of a non-composite and a composite 
binary endpoint (as with the ACR50 and PASI90 combined endpoint), each binary endpoint will 
be derived independently, as described above, before deriving the combined endpoint. 
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Section 4.2.1.6 Summary table of missing data handling approaches for efficacy analyses 
Table 4.2 summarizes which missing data handling approaches will be used for each type of 
efficacy endpoint.  
Table 4.2: Missing data handling approaches for efficacy endpoints 
Efficacy Endpoint 
Priority 
Variable Type 
Missing data handling approach 
Composite 
estimand 
(NRI) 
Modified 
Composite 
estimand 
(MI) 
Hypothetical 
estimand 
(MI) 
Hypothetical 
estimand 
Reference-
Based 
(MI) 
OC 
Tipping 
Point 
analysis 
(MI) 
Treatment 
Policy (MI) 
Primary endpoints 
Composite 
Binary 
P 
 Sa 
 
S 
Sa 
Sa 
Secondary 
endpoints included 
in the testing 
hierarchy 
Binary  
P 
Sa 
 
 
S 
 
 
Continuous 
 
 
S 
P 
S 
 
 
Other Secondary 
endpoints (not 
included in the 
testing hierarchy 
Binary 
X 
Xa 
 
 
X 
 
 
Continuous 
 
 
X 
 
X 
 
 
Other endpoints 
Binary  
X 
Xa,b 
 
 
X 
 
 
Continuous 
 
 
X b 
X d 
X 
 
 
Categorical 
X c 
X c 
 
 
X 
 
 
P=Primary method, S=Supportive method, X=Method to be used (no priority designated) MI=multiple imputation, NRI=non-
responder imputation, OC=observed cases. 
Note: Composite estimand (NRI) refers to the approach in which data preceded by the intercurrent event of study treatment 
discontinuation are imputed as nonresponse, and other missing data are also imputed as nonresponse. 
Note: Modified Composite Estimand (MI) refers to the approach in which data preceded by the intercurrent event of study 
treatment discontinuation due to AE or lack of efficacy are imputed as nonresponse (or worst category for categorical variable), 
and other missing data are imputed via a MI model.  
Note: Hypothetical Estimand (MI) refers to the approach where outcomes for subjects without an intercurrent event of study 
treatment discontinuation are as observed, and outcomes for subjects with the intercurrent event are imputed via a MI model. 
Note: Referenced Based imputation refers to the approach in which it is assumedthat the statistical behavior of the bimekizumab 
and placebo-treated subjects after discontinuing study medication becomes that of the placebo-treated subjects that remain in the 
study.a  Imputation method is applied on continuous data, and binary variable is derived from the continuous variable based on 
complete imputed data set. 
b MI will be used to provide point estimates at each timepoint only.  
c Missing data to be imputed to the worst category. 
d For ACR components analysis at Week 16. 
Change #22 
Added section 4.2.2 Methods for handling missing data for efficacy analyses 
The sections below describe the method to be used for missing efficacy data handling. 
Note: For a specific endpoint, if analyzed subjects in a one or several treatment groups have no 
missing data, then analysis of observed cases will be performed in the concerned treatment 
group(s). 
 
Change #23 
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Added section 4.2.2.1 Non-responder imputation  
For binary endpoints, the nonresponder imputation (NRI) analysis, also described above as the 
primary composite estimand, will consider the following subjects as “non-responders” for the 
timepoint of interest: 
• Subjects with missing data at the timepoint of interest. In the case of ACR50, nonresponse is 
imputed if ACR50 cannot be derived (i.e. derived as “missing”) based on available ACR 
components. (Section 8.1.1). 
• Subjects remaining in the study at the timepoint of interest but discontinuing study treatment 
before the timepoint of interest (data after IE). 
• Subjects with missing Baseline value (for composite or non-composite binary variables based 
on change(s) from Baseline of continuous endpoint(s)). 
Change #24 
Section 4.2.1.1 MI-MCMC/Monotone Regression 
This section describes the algorithms to be implemented for the MI – MCMC/Monotone 
Regression procedures for non-composite binary endpoints, composite binary endpoints, and 
continuous endpoints. These descriptions focus on the multiple imputation procedure itself and 
do not specifically account for dealing with intercurrent events, though it is assumed that those 
will be addressed as previously described. 
Non-composite binary endpoints 
For non-composite binary endpoints, the MI method will be applied as follows based on raw 
values: 
• Step 1: Create a dataset, one for each treatment group, of study participants with observed 
values and those needing estimation by multiple imputation. For the imputation step, missing 
values will be separated into non-monotone missing values (ie, intermittent missing values 
between completed assessments) and monotone missing values (ie, where all study 
participant data is missing after a given time point).  
− For the intermittent missing values, the missing value in each dataset will be filled in 
using the Markov-Chain Monte Carlo (MCMC) method with multiple chains, monotone 
missing data imputing pattern, and non-informative priors for all parameters. Unless 
specified differently, the first 200 iterations will not be used (the ‘burn-in’ option). A 
total of 100 sets of imputations will be performed. The seed used for these imputations 
will be 2017 and all other multiple imputation procedures described in this SAP will use 
this same seed as well.   
The resulting 100 imputed data sets will have a monotone missing pattern and will be imputed 
using a method for monotone missingness: 
− For monotone missing data, monotone regression will be used to impute missing data. 
A separate regression model is estimated for each variable with missing values (i.e., 
measurement at each time point). Based on the resulting model, a new regression model 
is then drawn and is used to impute the missing values for the variable. Since the data set 
has a monotone missing data pattern, the process is repeated sequentially for variables 
with missing values. The procedure will be based on the 100 imputed datasets generated 
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from the MCMC procedure and will be performed by Imputation. This will be based on 
100 sets of imputations.  
The SAS® PROC MI procedure will be used for the imputation.  
In both cases, the imputation model will include prior TNFα inhibitor exposure, region, the value 
at Baseline and at each post-Baseline visit (prior to week of interest). The stratification factors 
(prior TNFα inhibitor exposure and region) may be dropped from the imputation model to 
facilitate model convergence if required (and this holds true for all imputation models). The post-
Baseline values will need to be specified in chronological order in the imputation model so that 
the SAS® PROC MI imputes variables from left to right (i.e. the Week 4 value will be first 
imputed using regression based on Baseline value, and then the Week 5 value will be imputed 
using regression based on Baseline and Week 4 values, etc). In case a Baseline raw value is 
missing, the study participant will be excluded. The resulting datasets for each treatment arm will 
be combined into one complete dataset based on each of the 100 imputations (containing 100 
times the number of study participants analyzed).  
The imputation model based on the MCMC method will only allow multivariate normal 
variables. Therefore, prior TNFα inhibitor exposure and region will be re-coded as indicator 
variables: 
− For prior TNFα inhibitor exposure, this will be 0 for intolerance to TNF, and 1 for 
inadequate response to 1 or 2 prior TNFs.  
− For region, which has 4 levels, one indicator variable will be defined as 0 for regions 
other than North America and 1 for North America. Three more indicator variables will 
be defined similarly replacing North America with Eastern Europe, Western Europe, and 
Asia/Australia respectively.  
• Step 2: Standard rounding rules will be applied to the imputed values. If the MI procedure 
yields a value outside of the pre-defined range for the given variable, the value will be 
updated to be within the predefined range of values for the endpoint of interest. For example, 
the imputed value for PASI will be updated to 0 or 72 in the case of an imputed value less 
than 0 or greater than 72, respectively.  
• Step 3: For each of the 100 complete imputed data set obtained from Step 2, the binary 
responder variable will be derived. In practice, the value at the week of interest (eg, Week 
16) in the imputed data sets will be used to categorize the study participant as a responder or 
not.  
• Step 4: For each of the datasets obtained in Step 3, the responder rate will be analyzed using 
a logistic regression model with factors of treatment group, region, and prior TNFα inhibitor 
exposure as fixed effects. For the Other efficacy binary endpoints, at each timepoint the MI 
main method will calculate the mean of the calculated responder rates from the imputed 
datasets. 
• Step 5: The results obtained from the 100 logistic regression analyses in step 4 (ie, the 
adjusted responder rates for each treatment group and the corresponding 95% CI, the odds 
ratio of the treatment comparison and corresponding 95% CI) will be combined for overall 
inference using Rubin’s rules, which account for the uncertainty associated with the imputed 
values (Rubin, 1987). This will be done using SAS® PROC MIANALYZE. The method for 
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determining the degrees of freedom when combining results will be the freedom default 
Rubin’s method. 
Composite binary endpoints 
For composite binary endpoints, the MCMC/monotone regression method described above in 
Step 1 and 2 for handling intermittent and monotone missing data will be performed separately 
for each individual component variable. Then, based on the multiply imputed data sets obtained 
for each component, the binary response will be derived as follows: 
− The 100 data sets obtained for each component will be merged by imputation number and 
study participant number. 
− For each of the 100 complete imputed data sets, the binary endpoint will be derived for 
each study participant/visit based on the component values.  
Procedures described for Step 4 and Step 5 will then follow.  
For the primary endpoint, the ‘burn-in’ option in PROC MI may be set higher than the default 
value. The convergence of the MCMC will be assessed graphically, and the results will be 
provided in a SAS® output.  
Calculation of adjusted responder rates, odds ratio and CIs for binary endpoints. 
Estimates of the adjusted responder rates for each treatment group and the associated standard 
errors are obtained from the logistic regression in Step 4 on the logit scale and as such are 
assumed to follow a normal distribution. These estimates will be combined using Rubin’s rules 
and the combined estimates and associated SEs will be used to construct 95% CIs on the logit 
scale. The combined estimates and 95% CIs on the logit scale will be back-transformed using the 
inverse logit link function to obtain the adjusted responder rates (%) and associated 95% CIs. 
Some key points to consider relative to the calculation of the odds ratios and corresponding 
confidence intervals .As the estimates of the odds ratios from the logistic regression model in 
step 3 follow a lognormal distribution, a log transformation is needed to normalize these 100 odd 
ratio estimates since the procedures for combining results from multiple imputed datasets are 
based on the assumption that the statistics estimated from each imputed dataset are normally 
distributed. Therefore, the log of the odds ratio estimates from the logistic regression model are 
used when combining into a single inference (step 3). Additionally, the standard errors (SE) for 
the odds ratios are transformed as follows: 
𝑆𝐸= log(𝑈𝐶𝐿) −log(𝐿𝐶𝐿)
2𝑍𝛼/2
 
where UCL and LCL are the upper and lower confidence limit, respectively, for the CI of the 
odds ratio from the logistic regression model, and 𝑍𝛼/2 is the relevant critical value from the 
standard normal distribution (1.96 for a 95% CI). The estimates of the log odds ratio for 
bimekizumab relative to placebo and the corresponding upper and lower confidence limits will 
be provided. The odds ratio will be then estimated by exponentiating the estimate of the log odds 
ratio. The odds ratio and the confidence limits of the odds ratio will be estimated as follows: 
𝑂𝑅= exp(𝐿𝑜𝑔 𝑜𝑑𝑑𝑠 𝑟𝑎𝑡𝑖𝑜 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒 ) 
𝐿𝐶𝐿= 𝑂𝑅∗exp(−𝑆𝐸∗𝑍𝛼/2 ) 
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𝑈𝐶𝐿= 𝑂𝑅∗exp(𝑆𝐸∗𝑍𝛼/2 ) 
where OR is the back-transformed estimate of the odds ratio just described, SE is the standard 
error of the log odds ratio and 𝑍𝛼/2 is the relevant critical value from the standard normal 
distribution (1.96 for a 95% CI). These calculations will be done such that odds ratios and 
corresponding CIs are calculated for the odds ratio of bimekizumab versus placebo. 
Continuous efficacy endpoints 
For secondary continuous efficacy endpoints, the same methods as the ones described above for 
the non-composite binary endpoints will apply based on the values at the timepoint of interest, 
with the following differences:  
− In Step 3, for each of the 100 complete imputed dataset obtained, the change from 
Baseline will be calculated 
− In Step 4, the analysis will be done on the change from Baseline, and the model will be 
an ANCOVA model with treatment group, region, and prior TNFα inhibitor exposure as 
fixed effects and the Baseline value as covariate.  
− In Step 5, the results obtained from the 100 ANCOVA analyses in Step 4 (i.e. the Least 
Square Means for the treatment difference and the 95% CI for the contrasts) will be 
combined with Rubin’s rules.  
For other continuous efficacy endpoints, the following steps will apply: 
– Step 1 and Step 2 as described for secondary continuous efficacy endpoints will be 
implemented. 
– The 100 imputed datasets will be combined and simple means and standard errors will be 
calculated using Rubin’s rules (via SAS® PROC MIANALYZE). For calculation of 
other descriptive statistics such as the median, min and max, Rubin's rules do not apply. 
Multiple imputation estimates will be computed by calculating arithmetic means of the 
estimates from the multiple repetitions of the imputation algorithm. 
Was modified to: 
Section 4.2.2.2 MI-MCMC/Monotone Regression 
In instances where MI is used, the missing value is replaced by a set of plausible values, where 
each value is a Bayesian draw from the conditional distribution of the missing data given the 
observed data. Intermittent missing data will be imputed using the MCMC method, followed by 
regression for monotone missing data (called “MI-MCMC/Monotone regression” method in this 
SAP). The multiple imputation procedures planned for efficacy analyses are based on an 
assumption of data missing at random (MAR). 
 
This section describes the algorithms to be implemented for the MI – MCMC/Monotone 
Regression procedures for non-composite binary endpoints, composite binary endpoints, and 
continuous endpoints. These descriptions focus on the multiple imputation procedure itself and 
do not specifically account for dealing with intercurrent events which is addressed in Section 
4.2.1 .  
Added section 4.2.2.2.1 Non-composite binary endpoints 
For non-composite binary endpoints, the MI method will be applied as follows based on raw 
values: 
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• Step 1: Imputation of missing data using MI: 
Create datasets, one for each treatment group, of subjects with observed values and missing 
values (needing estimation by MI). For the imputation step, missing values will be separated into 
2 categories: intermittent missing values (ie, missing values for a given subject that has available 
data before and after the missing timepoint, including missing value at Baseline)  and monotone 
missing values (ie, where all subject data is missing after a given time point). Datasets should be 
designed in a horizontal structure meaning that each subject should be present in a single 
observation, with a set of values, one for each scheduled visit where the endpoint is supposed to 
be collected according to the protocol (this excludes the unscheduled visits).  
Datasets should also be sorted by subject number before proceeding with the MI process.  
a. For the intermittent missing values, the missing value in each dataset will be filled in using 
the Markov-Chain Monte Carlo (MCMC) method with multiple chains, monotone missing 
data imputing pattern, and non-informative priors for all parameters. Unless specified 
differently, the first 200 iterations will not be used (the ‘burn-in’ option). A total of 100 sets 
of imputations will be performed. The seed used for these imputations will be 2017 and all 
other MI procedures described in this SAP will use this same seed as well.  The procedure 
will be performed for each treatment group separately. 
The resulting 100 imputed data sets will have a monotone missing pattern and will be imputed 
using a method for monotone missingness: 
b. For monotone missing data, one monotone regression will be used to impute missing data. 
A separate regression model is estimated for each variable with missing values (ie, 
measurement at each time point). Based on the resulting model, a new regression model is 
then drawn and is used to impute the missing values for the variable. Since the data set has a 
monotone missing data pattern, the process is repeated sequentially for variables with 
missing values. The procedure will be based on the 100 imputed datasets generated from the 
MCMC procedure and will be performed for each treatment group separately byimputation.  
The SAS® PROC MI procedure will be used for the imputation.  
In both cases, the imputation model will include the randomization strata as stratification 
variables (region and prior TNFα inhibitor exposure), the value at Baseline and at each post-
Baseline visit (up to the week of interest). The imputation model based on the MCMC method 
will only allow joint multivariate normal variables. For the MCMC method (when imputing 
intermittent missing values), randomization strata will be re-coded as indicator variables, and 
will be always specified in the following order if they are retained in the model: 
− North America region  (1 for North America, 0 otherwise) 
− Western Europe region (1 for Western Europe, 0 otherwise) 
− Eastern Europe region (1 for Eastern Europe, 0 otherwise)  
− Prior TNFα 1 (1 for inadequate response to 1 prior TNFα inhibitor) 
− Prior TNFα 2 (1 for inadequate response to 2 prior or more TNFα inhibitors) 
No variable needs to be created for the 3rd category of prior TNFα inhibitors (intolerance  
to TNFα inhibitors) or the 4th region (Asia) which is covered when all above variables are 
“0”.    
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The randomization strata (region and prior TNFα inhibitor exposure) may be dropped from the 
imputation model to facilitate model convergence if required (this will be the case for all 
imputation models) as described below: 
− If the MI fails to converge when adjusting on the stratification variables specified above, 
or if the percentage of randomized subjects is less than 10% in either of the Asia or 
Western Europe regions, then the Western Europe and Asia region will be combined  and 
the binary variables for region that will be left in the MI will then be for North America 
and Eastern Europe regions.  
− If after doing that, the MI still fails to converge then all region factors will be removed 
from the MI.  
− If the MI still does not converge after dropping the regions, the remaining stratification 
variables (Prior TNFα 2,1) will also be removed. 
− If a variable is dropped in order to allow convergence for one model in the study, that 
variable does not have to be dropped from other models in the study of the model 
converges without dropping the variable. That is, model convergence should be evaluated 
for each efficacy table independently. Furthermore, this means that a table based on a 
single timepoint may have different variables in the imputation model than a separate by-
visit table for the same variable. 
The post-Baseline values will need to be specified in chronological order after the Baseline value 
in the imputation model so that the SAS® PROC MI imputes variables from left to right (ie, the 
Week 4 value will be first imputed using regression based on Baseline value, and then the Week 
8 value will be imputed using regression based on Baseline and Week 4 values, etc.). The 
resulting datasets for each treatment arm will be combined into 1 complete dataset containing 
100 times the number of subjects analyzed.  
Note: When imputing missing hs-CRP values, missing values due to values below LLOQ (0.10 
mg/L) will be replaced by the midpoint value between 0 and LLOQ prior to running MI. 
• Step 2: Standard rounding rules will be applied to the imputed values after each SAS® 
PROC MI. If an imputed value falls outside of the range for the given variable (as listed in 
Table 4.1), the value will be updated to be within the predefined range. For example, the 
imputed value for PASI will be updated to 0 or 72 in the case of an imputed value less than 0 
or greater than 72, respectively. For endpoints that can take only integer values (eg,: IGA as 
listed in Table 4.1), the imputed values will be rounded to the closest integer after each 
SAS® PROC MI. 
Note: For hs-CRP, the lower limit used the midpoint value between 0 and LLOQ. For some 
parameters, there is not necessarily an upper limit to the imputed value (ie, LDI) 
• Step 3: On the dataset obtained from Step 2, the binary responder variable will be derived. In 
practice, the value at the week of interest (eg, Week 16) in the imputed data sets will be used 
to categorize the subject as a responder or not.  If subjects have an IE, then the endpoint at all 
subsequent visits will be set to “nonresponse” and the following will be performed: 
− When date of visit is available: by comparing IE date vs. date of visit 
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− When the date of visit is missing in case of fully imputed data at a visit: by comparing the 
next visit number after the visit where the last study medication occurs vs. the visit 
number where data are imputed.  
• Step 4: At each timepoint the (unadjusted) proportion of responders will be calculated by 
treatment group from the imputed datasets using SAS® PROC FREQ. 
Step 5: (For primary and secondary efficacy endpoints only): For each value of the imputation 
number from 1 to 100, the adjusted proportion of responders will be analyzed using a logistic 
regression model with a fixed effect for treatment. The suitability of including region and prior 
TNFα inhibitor exposure as fixed effects will be assessed using goodness-of-fit tests (Deviance 
and Pearson’s and Hosmer-Lemeshow) and added, if appropriate, if it allows model 
convergence. Covariates kept in the modelling should also be the same as the ones previously 
used for the MI. Comparisons will be made using 2-sided Wald test level of significance of 5%. 
The results obtained from the 100 logistic regression analyses (ie, the adjusted proportion of 
responders for each treatment group, the OR and the difference of proportions for the BKZ-
placebo comparison and corresponding 95% CI) will be combined for overall inference using 
Rubin’s rules, which account for the uncertainty associated with the imputed values (Rubin, 
1987). This will be done using SAS® PROC MIANALYZE.  
Added section 4.2.2.2.2 Composite binary endpoints 
For composite binary endpoints, the MI method will be applied as follows: 
• Step1: The MCMC/monotone regression approach described above in Step 1 for non-
composite binary endpoints will be performed separately for each individual component 
variable.  
• Step 2: The same rounding rules described in Step 2 above for non-composite binary 
endpoints will be performed for each component. 
• Step 3: Based on the multiply imputed data sets obtained for each component, the binary 
response will be derived as follows: 
− The dataset obtained for each component will be merged by imputation number and 
subject number 
− On the dataset obtained, the binary endpoint will be derived for each subject/visit based 
on the component values. 
− If subjects have an intercurrent event, then the endpoint at all subsequent visits (from the 
day after the intercurrent event date, whether the data were observed or not) will be set to 
“nonresponse”. 
• Steps 4 and 5: Same as Steps 4 and 5 above for non-composite binary endpoints (4.2.2.2.1).   
For the primary endpoint, the ‘burn-in’ option in SAS® PROC MI may be set higher than the 
default value. The goodness-of-fit tests to assess convergence of the MCMC will be provided in 
a SAS® output.  
Added section 4.2.2.2.3 Calculation of adjusted responder rates, odds ratio and CIs for 
binary endpoints 
Estimates of the adjusted responder rates for each treatment group and the associated standard 
errors are obtained from the logistic regression in Step 5 on the logit scale and as such are 
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assumed to follow a normal distribution. These estimates will be combined using Rubin’s rules 
and the combined estimates and associated SEs will be used to construct 95% CIs on the logit 
scale. The combined estimates and 95% CIs on the logit scale will be back transformed using the 
inverse logit link function to obtain the adjusted responder rates (%) and associated 95% CIs. 
Some key points to consider relative to the calculation of the odds ratios and corresponding 
confidence intervals. As the estimates of the odds ratios from the logistic regression model in 
step 5 follow a lognormal distribution, a log transformation is needed to normalize these 100 odd 
ratio estimates since the procedures for combining results from multiple imputed datasets are 
based on the assumption that the statistics estimated from each imputed dataset are normally 
distributed. Therefore, the log of the odds ratio estimates from the logistic regression model are 
used when combining into a single inference (step 3). Additionally, the standard errors (SE) for 
the odds ratios are transformed as follows: 
𝑆𝐸= log(𝑈𝐶𝐿) −log(𝐿𝐶𝐿)
2𝑍𝛼/2
 
where UCL and LCL are the upper and lower confidence limit, respectively, for the CI of the 
odds ratio from the logistic regression model, and 𝑍𝛼/2 is the relevant critical value from the 
standard normal distribution (1.96 for a 95% CI). The estimates of the log odds ratio for BKZ 
relative to placebo and the corresponding upper and lower confidence limits will be provided. 
The odds ratio will be then estimated by exponentiating the estimate of the log odds ratio. The 
odds ratio and the confidence limits of the odds ratio will be estimated as follows: 
𝑂𝑅= exp(𝐿𝑜𝑔 𝑜𝑑𝑑𝑠 𝑟𝑎𝑡𝑖𝑜 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒 ) 
𝐿𝐶𝐿= 𝑂𝑅∗exp(−𝑆𝐸∗𝑍𝛼/2 ) 
𝑈𝐶𝐿= 𝑂𝑅∗exp(𝑆𝐸∗𝑍𝛼/2 ) 
where OR is the back-transformed estimate of the odds ratio just described, SE is the standard 
error of the log odds ratio and 𝑍𝛼/2 is the relevant critical value from the standard normal 
distribution (1.96 for a 95% CI). These calculations will be done such that odds ratios and 
corresponding CIs are calculated for the odds ratio of BKZ versus placebo. 
In addition to calculating the odds ratio, associated CIs, and p-values for the comparisons of 
BKZ vs. placebo, the estimated proportion of responders (ie, estimated responder rate) and the 
difference in the proportion of responders between BKZ and placebo will be estimated, along 
with 2-sided 95% CIs. The creation of the estimates of this difference will be completed using 
the process detailed below: 
1. Use the logistic regression model to calculate: 
Least squares mean (LSM) estimates of the log odds of BKZ (GB) and placebo (GP), as well 
as their corresponding standard errors (SB and SP, respectively). 
Standard error of the LSM estimate of the log odds ratio (SR) 
2. Compute estimates for predicted proportions using the following transformations: 
PB = exp(GB)/(1 + exp(GB)) 
PP = exp(GP)/(1 + exp(GP)) 
The difference in proportions is then given by: 
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D = PB – PP 
3. Estimate the standard error of D by: 
SD = sqrt[PB2(1-PB)2SB2 + PP2(1-PP)2SP2 + PB(1-PB)PP(1-PP)SR2 – PB(1-PB)PP(1-PP)(SB2 + 
SP2]) 
The MI/MCMC monotone regression method, as previously outlined, will be used to account for 
missing values. The calculation steps described above will be based on the results provided from 
the logistic regression model of the multiple imputed datasets. An estimate for the difference in 
proportions, D, and corresponding standard error, SD, will be computed for each of these 
datasets. The results from these analyses will be combined into a single estimate of the difference 
in predicted proportion of response and a 2-sided 95% CI interval using SAS PROC 
MIANALYZE. 
Added section 4.2.2.2.4 Continuous efficacy endpoints 
For secondary and other continuous efficacy endpoints, the same methods as the ones described 
above for the non-composite binary endpoints will apply based on the values at the timepoint(s) 
of interest, with the following differences:  
• Step 1: The same imputation procedure as the described in step 1 for the non-composite 
binary endpoints will be used.  
• Step 2: The same rounding rules described in step 2 above for non-composite binary 
endpoints will be performed.   
• Step 3: On the dataset obtained with the imputation number from 1 to 100; change from 
Baseline will be derived. Simple means and standard errors will be calculated using Rubin’s 
rules (via SAS® PROC MIANALYZE) for each timepoint(s) of interest. For calculation of 
other descriptive statistics such as the median, min and max, Rubin's rules do not apply. MI 
estimates will be computed by simply averaging the estimates from the multiple repetitions 
of the imputation algorithm. For CRP data (that will be presented using the geometric mean 
and corresponding 95% CI, arithmetic mean, median, Q1, Q3, minimum and maximum). The 
change from Baseline will be expressed as the ratio to Baseline (value at the visit divided by 
value at Baseline) in the by-visit summaries. The following approach will be applied: 
− Following the MI procedure, the ratio to Baseline will be calculated for any of the 
imputed values  
− The natural logarithm of the absolute values and of the ratios to Baseline will be 
calculated 
− The logged values will be summarized by treatment, visit and imputation  
− The datasets will be combined using PROC MIANALYZE in order to get the mean from 
the absolute values and ratios to Baseline across imputations 
− The estimates of the mean will be back transformed to obtain the geometric mean on the 
original scale 
− For the median, Q1, Q3, minimum and maximum the procedure outlined above for the 
other endpoints will be followed 
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• Step 4: (for primary and secondary efficacy variables): For each value of the imputation 
number from 1 to 100, the change from Baseline will be analyzed using an ANCOVA model 
with treatment group, region, and prior TNFα inhibitor exposure as fixed effects and the 
Baseline value as covariate. The results obtained from the 100 ANCOVA analyses (ie, the 
LSM for the treatment difference and the 95% CI for the contrasts) will be combined using 
Rubin’s rules (via SAS® PROC MIANALYZE). 
For composite continuous endpoints, the MI will be applied on each component the same way as 
for composite binary endpoint. The datasets obtained for each component will be merged by 
imputation number and subject number. On the dataset obtained, the endpoint will be derived for 
each subject/visit based on the component values. The endpoint obtained will be analyzed as 
above. 
Added section 4.2.2.2.5 Ordinal efficacy endpoints 
For ordinal efficacy endpoints, the MI method will be applied as for the continuous efficacy 
endpoints with the following exceptions:  
• After the imputation of the intermittent and monotone missing data , the rounding rules will 
be performed to align the data with the possible responses for the respective endpoint (eg, If 
the variable can take the value 1, 2 or 3, the imputed values will be rounded to the closest 
possible value).   
• If the ordinal efficacy endpoint is used to derive a binary endpoint, the same analysis strategy 
as described above for the binary endpoints will be used.    
• If the ordinal efficacy endpoint is not used to derive a binary endpoint, the unadjusted 
proportions of subject by categories will be presented. 
• If subjects have an IE, then the ordinal endpoint at all subsequent visits (from the day after 
the IE date, whether the data were observed or not) will be set to the value used for the worst 
category. 
Change #25 
Deleted section 4.2.1.2 MI-MCMC/Logistic Regression 
Change #26 
Updated section 4.2.1.3 MI-MCMC/Reference-Based Regression 
Updated to the following: Section 4.2.2.3 MI-MCMC/Reference-Based Regression 
For the primary analysis of the secondary continuous efficacy variable included in the testing 
hierarchy and the individual components of the ACR response, the Reference-Based multiple 
imputation method will be used. In this imputation method, the missing data will be imputed 
based on data from the placebo group only (Mallinckrodt, 2013). 
Reference-Based MI assumes that the statistical behavior of the BKZ and placebo-treated 
subjects after discontinuing study medication becomes that of the placebo-treated subjects. All 
time points after study treatment discontinuation for BKZ and placebo groups will be considered 
missing. MIs are used to replace missing outcomes for BKZ- and placebo-treated subjects who 
discontinued using multiple draws from the posterior predictive distribution estimated from the 
placebo arm.  
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Note: SAS 9.4 may be used for this analysis where equivalent steps to those outlined below will 
be used to perform the imputation: 
In the case of continuous endpoints, the procedure will be implemented as follows on the raw 
values: 
4. Data will be processed sequentially, one timepoint (visit) at a time, by repeatedly calling 
SAS® PROC MI to impute missing outcome data at visits t=1,…, Week 16 (Week 16 being 
the time point of interest) using data from the placebo-treated subjects arm only. 
c. Initialization. Set t=1 (Baseline visit) 
d. Iteration. Set t=t+1. Create a dataset combining records from BKZ- and placebo-treated 
subjects with columns for covariates (prior TNFα exposure and region) and outcomes at 
visits 1 to t. Outcomes for all BKZ-treated subjects are set to missing at visit t and set to 
observed or previously imputed values at visits 1 to t-1. Outcomes for placebo-treated 
subjects are set to observed at visit t or observed or previously imputed values at visits 1 to t-
1. The outcomes should be sorted in chronological order in the model.  
e. Imputation. Impute missing values for visit t using previous outcomes for visits 1 to t-1, prior 
use of TNFα inhibitor, and region. Note that only placebo data will be used to estimate the 
imputation model since no outcome is available for BKZ- treated subjects at visit t. As a 
consequence, the input dataset should include all subjects from placebo but only subjects 
from the BKZ arm that have values at timepoint t missing.  
f. Repeat steps 2a-2c for all timepoints, 100 times with different seed values (seeds ranging 
from 201 to 300) to create 100 imputed complete datasets. Subjects whose missing values 
were imputed in the last PROC MI call will be included in the input dataset for the next 
PROC MI call. Standard rounding rules will be applied to the imputed values. If the MI 
procedure yields a value outside of the pre-defined range for the given variable, the value 
will be updated to be within the predefined range of values for the endpoint of interest. For 
example, the imputed value for TJC will be updated to 0 or 68 in the case of an imputed 
value less than 0 or greater than 68, respectively.  
5. The analysis will be done on the change from Baseline, and the model will be an ANCOVA 
model with treatment group, region, and prior TNFα inhibitor exposure classification as fixed 
effects and the Baseline value as covariate.  
For generation of summary statistics, the 100 imputed datasets will be combined, and simple 
means and standard errors will be calculated using Rubin’s rules (via SAS® PROC 
MIANALYZE). For calculation of other descriptive statistics (median, Q1, Q3, minimum 
and maximum), Rubin’s rules do not apply. Multiple imputation estimates will be computed 
by calculating arithmetic means of the estimates from the multiple repetitions of the 
imputation algorithm. Thus, for median, Q1, Q3, minimum and maximum the following 
approach will apply: 
• The data will be summarized by treatment, visit and imputation and the summary 
statistics will be computed.  
• Results will be summarized by taking the mean value of each summary statistic at 
each visit across all imputations.  
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• The number of decimal places will remain the same as the original for display 
purposes (ie, if the mean was presented to 1 decimal place, the mean of the means 
will also be presented to 1 decimal place). 
The results obtained from the 100 ANCOVA analyses in Step 4 (i.e. the Least Square Means for 
the treatment difference and the 95% CI for the contrasts) will be combined with Rubin’s rules. 
Change #27 
Section 4.2.1.4 Tipping Point analysis 
Tipping point analyses will also be implemented as a supportive analysis for the primary efficacy 
endpoint. 
The objective of the tipping point analyses is to identify assumptions about the missing data 
under which the conclusions from the main analysis change, ie, under which there is no longer 
evidence of a treatment effect. These tipping point analyses will only be performed if the primary 
efficacy analysis results in a statistically significant treatment effect (p<0.05). 
As a first step, the worst-case scenario will be evaluated for the primary endpoint (ACR50 at 
Week 16). Specifically, all bimekizumab-randomized study participants with a missing ACR50 
at Week 16 will be imputed as non-responders, while all placebo-randomized study participants 
with a missing ACR50 at Week 16 will be imputed as responders. While there is little 
justification for such an approach, it makes the most putative assumption possible against a 
bimekizumab treatment effect. After applying this imputation approach, a logistic regression 
model consistent with the one described for the primary analysis will be applied. If the p-value 
for the odds ratio of bimekizumab versus placebo is less than 0.05, then no further tipping point 
analyses are needed. 
If this analysis based on the worst-case scenario results in a p-value greater than 0.05, then 
additional tipping point analyses will be performed. Various assumptions will be made about 
average outcomes among the subsets of study participants who prematurely discontinued study 
treatment and hence have a monotone missing data pattern (O’Kelly, 2014). In practice, it 
implies different delta adjustments will be made to the assumed responses on the monotone 
missing data in each treatment group independently with various degrees of plausibility with the 
goal to find for each treatment group the “tipping point” that will significantly reverse the 
primary result which yielded a p-value less than 0.05. These delta adjustments will be done on 
the components of ACR50 and will be implemented for each component as follows: 
1. The same MCMC method described in Section 4.2.1.1 will be implemented for non-
monotone (intermittent) missing pattern values, using the same imputation model. This 
will be done only once for each study participant in order to provide a dataset with 
monotone missing data.  
2. Based on the dataset obtained in Step 1, a monotone regression model will be applied 
(using the same imputation model as in Step 1) while adjusting the imputed values by 
various delta adjustments. This will be based on 100 sets of imputations.  
These delta adjustments will be made independently in each treatment group, and the 
delta parameters should be defined within the pre-defined range of values of the endpoint 
of interest.  
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Several scenarios will be considered to define these shift parameters. Once defined, the 
same shift parameter value will be applied on the imputed endpoint value for all visits.  
Scenario 1 will be based on the assumption that study participants randomized to bimekizumab 
and who have missing data have a lower probability of response compared to study participants 
randomized to placebo with missing data.  
− For endpoints for which high scores are associated with a more favorable outcome, it will 
mean that:  
• A negative shift is applied to the imputed value for study participants randomized to 
bimekizumab in order to decrease the imputed value. 
• A positive shift is applied to the imputed value for study participants randomized to placebo 
in order to increase the imputed value. 
− For endpoints for which high scores are associated with a less favorable outcome, it will 
mean that:  
• A positive shift is applied to the imputed value for study participants randomized to 
bimekizumab in order to decrease the imputed value. 
• A negative shift is applied to the imputed value for study participants randomized to placebo 
in order to increase the imputed value. 
For each continuous endpoint, a set of possible values will be first pre-defined for the shift 
parameter (example: 0, 1, 2, 3)  
Following the delta adjustments for the individual components, the composite binary endpoint 
(ACR50) will then be derived based on the multiply delta-adjusted imputed data sets obtained for 
each component. 
3. Each of the 100 imputed datasets will then be analyzed using a logistic regression model 
with factors of treatment group, region, and prior TNFα inhibitor exposure as fixed 
effects. 
4. The results obtained from the 100 logistic regression analyses in Step 3 will be combined 
for overall inference using Rubin’s rules, and the results obtained for each shift parameter 
will be presented in a single table.  
5. Step 2 to Step 4 will be repeated so that, at each iteration, missing values are adjusted 
with a larger delta than at the previous iteration. Depending on the results obtained, shift 
parameters with more granularity (eg, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9) may also be 
investigated. The process will go on until the p-value for the odds ratio between 
bimekizumab and placebo is no longer statistically significant (i.e. ≥ 0.05). The odds 
ratio, 95% CI, and p-values obtained for each value of delta will be combined in one 
single table.  
Was modified to: 
Section 4.2.2.4 Tipping Point analysis 
Tipping point analyses will also be implemented as a supportive analysis for the primary efficacy 
endpoint. 
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The objective of the tipping point analyses is to identify assumptions about the missing data 
under which the conclusions from the main analysis change, ie, under which there is no longer 
evidence of a treatment effect. These tipping point analyses will only be performed if the primary 
efficacy analysis results in a statistically significant treatment effect (p<0.05). 
As a first step, the worst-case scenario will be evaluated. Specifically, all BKZ-randomized 
subjects with a missing ACR50 at Week 16 (or non-missing ACR50 after study treatment 
discontinuation) will be imputed as non-responders, while all placebo-randomized subjects with 
a missing ACR50 at Week 16 will be imputed as responders. While there is little justification for 
such an approach, it makes the most putative assumption possible against a BKZ treatment 
effect. After applying this imputation approach, a logistic regression model consistent with the 
one described for the primary analysis will be applied. If the p-value for the odds ratio of BKZ 
versus placebo is less than 0.05, then no further tipping point analyses are needed. 
If this analysis based on the worst-case scenario results in a p-value greater than 0.05, then 
additional tipping point analyses will be performed. In practice, it implies different delta 
adjustments will be made to the assumed responses on the missing data (where missing values 
include observations after the intercurrent event date and any other missing values) in each 
treatment group independently with various degrees of plausibility with the goal to find for each 
treatment group the “tipping point” that will significantly reverse the primary result which 
yielded a p-value less than 0.05. These delta adjustments will be done on the components of 
ACR50 and will be implemented for each component as follows: 
• Step 1: The same MCMC method described in Section 4.2.2.2 will be implemented for non-
monotone (intermittent) missing pattern values, using the same imputation model. This will 
be based on 100 imputations. 
• Step 2: Based on the dataset obtained in Step 1, a monotone regression model will be applied 
(using the same imputation model as in Step 1) and as described in Section 4.2.2.2. This will 
be based on 1 imputation.  
• Step 3: Imputed values will be shifted using a delta adjustment independently in each 
treatment group.   
Once defined, the same delta adjustment value will be applied on the imputed values for the 
Week 16 visit only. The selected scenario will assume that subjects randomized to BKZ and who 
have missing data have a lower probability of response compared to subjects randomized to 
placebo with missing data. 
- For ACR components for which high scores are associated with a less favorable outcome, it 
will mean that:  
▪ A positive shift is applied to the imputed value for subjects randomized to BKZ in order 
to increase the imputed value. 
▪ A negative shift is applied to the imputed value for subjects randomized to placebo in 
order to decrease the imputed value. 
A set of possible values will be first pre-defined for the delta parameter as follows: 
-  For all ACR components, the value of the initial delta parameter will be equivalent to a 
specific percentage of the possible range of the component (eg, 5%). For hs-CRP, the range 
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will be based on the log-transformed values at Week 16. The delta parameters for each 
endpoint are listed in the Table 7‒3.  
Table 4.3: Tipping Point analysis: Delta parameters for each ACR component 
ACR component1 
Range 
Delta 
SJC 
0-66 
3.3 
TJC 
0-68 
3.4 
HAQ-DI 
0-3 
0.15 
PtAAP, PhGA-PsA, PGA-PsA 
0-100 
5 
hs-CRP2 
Observed range  
of the loge transformed values for overall 
subjects at Week 16 
5% of the observed 
range 
1The shifted imputed value should not exceed the range for the ACR component. 
2The delta adjustment will be applied on the loge transformed imputed values which will then be exponentiated prior to deriving 
endpoint.   
• Step 4: Standard rounding rules will be applied to the imputed values. If the SAS® PROC 
MI yields a value outside of the range for the given component, the value will be updated 
after the imputation has been performed to be within the predefined range.  
• Step 5: Repeat steps 1 to 4 for each ACR component. The composite binary endpoint 
(ACR50) will then be derived based on the multiple shifted imputed data sets obtained for 
each component. 
• Step 6:Additionally, as the primary endpoint is derived using NRI, subjects randomized to 
BKZ with missing data (where missing values include observations after the IE date and any 
other missing values) should be set to non-response, after applying the delta adjustment 
outlined in Step 3 above. This ensures subjects randomized to BKZ do not have a higher 
probability of response in the tipping point analyses compared to the primary analysis (ie, a 
subject randomized to BKZ who is non-responder in the primary analysis cannot become a 
responder in the tipping point analyses). 
• Step 7: In the data obtained, for each value of the imputation number, ACR50 will be 
analyzed using a logistic regression model with factors of treatment group, region, and prior 
TNFα inhibitor exposure at Baseline as fixed effects. 
• Step 8: The results obtained from the 100 logistic regression analyses in Step 6 will be 
combined for overall inference using Rubin’s rules, and the results obtained for each shift 
parameter will be presented in a single table.  
• Step 9: Step 3 to Step 8 will be repeated so that, at each iteration, missing values are adjusted 
with a larger shift than at the previous iteration. Depending on the results obtained, delta 
parameters with more granularity (eg, 2 times, 3 times the initial delta) will be investigated. 
The process will go on until the p-value for the odds ratio between BKZ and placebo is no 
longer statistically significant (ie, ≥ 0.05). The odds ratio, 95% CI, and p-values obtained for 
each value of delta will be combined in one single table.  
Change #28 
Section 4.2.2 Handling of missing data for AE 
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Imputation of Partial Start Dates 
• If only the month and year are specified and the month and year of first dose is not the same 
as the month and year of AE onset, then use the 1st of the month 
• If only the month and year are specified and the month and year of first dose is the same as 
the month and year of AE onset, then use the date/time of first dose 
• If only the year is specified, and the year of first dose is not the same as the year of onset, 
then use January 1 of the year of AE onset 
• If only the year is specified, and the year of first dose is the same as the year of AE onset, 
then use the date/time of first dose 
• If the AE onset date is completely unknown, then use the date of first dose 
Was updated to section 4.2.3 Handling of missing data for AE 
Imputation of Partial AE Start Dates 
• If only the month and year are specified: 
− if the month and year of first dose of IMP is not the same as the month and year of the 
start date, then use the 1st of the month, 
− if the month and year of first dose of IMP is the same as the month and year of the start 
date, then use the date of first dose of IMP, 
• If only the year is specified: 
− if the year of first dose is not the same as the year of the start date, then use January 1 of 
the year of the start date. 
− if the year of first dose is the same as the year of the start date, then use the date of first 
dose. 
• If the date is completely unknown: 
− use the date of first dose of IMP if the stop date is unknown or not prior to the onset date.  
For seriousness, no imputation rule will be applied for the interim analysis, but the worst-case 
approach will be applied for the final analysis.  
The following was added: 
If the imputed stop date is prior to the imputed start date:  
• For missing start day and start month:  
− if the year of start date is the same as the year of first dose and the imputed stop date is on 
or after the date of first dose then set the start date to the date of first dose 
− otherwise set to the 1st January of the year of the start date 
• For missing start day only 
− if the month and year of the start date is the same as the month and year of first dose and 
the imputed stop date is on or after the date of first dose, then set the start date to the date 
of first dose 
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− if the month and year of the start date is the same as the month and year of first dose and 
the imputed stop date is before the date of first dose, then set the start date to the 1st of 
that month 
In the event of ambiguity or incomplete data which makes it impossible to determine whether an 
AE is treatment emergent, the AE will be considered as treatment emergent. 
For missing seriousness, no imputation rule will be applied for both the interim and the final 
analysis. 
Change #29 
Section 4.2.3 Handling of missing data for prior and concomitant medications 
Imputation of Partial Start Dates 
• If only the month and year are specified and the month and year of first dose is not the same 
as the month and year of the start date, then use the 1st of the month. 
• If only the month and year are specified and the month and year of first dose is the same as 
the month and year of the start, then use the date of first dose. 
• If only the year is specified, and the year of first dose is not the same as the year of the start 
date, then use January 1 of the year of the start date. 
• If only the year is specified, and the year of first dose is the same as the year of the start date, 
then use the date of first dose. 
• If the start date is completely unknown, and the stop date is unknown or not prior to the date 
of first dose, then use the date of first dose. 
Was modified to the following: 
Section 4.2.4 Handling of missing data for prior and concomitant medications 
Imputation of Partial Start Dates 
• If only the month and year are specified: 
− if the month and year of first dose of IMP is not the same as the month and year of the 
start date, then use the 1st of the month. 
− if the month and year of first dose of IMP is the same as the month and year of the start, 
then use the date of first dose of IMP. 
• If only the year is specified: 
− if the year of first dose of IMP is not the same as the year of the start date, then use the 
1st of January of the year of the start date. 
− if the year of first dose of IMP is the same as the year of the start date, then use the date 
of first dose of IMP. 
• If the start date is completely unknown: 
−  if the stop date is unknown or not prior to the date of first dose of IMP, then use the date 
of first dose of IMP. 
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− if the stop date is prior to the date of first dose of IMP, then set the start date to the 1st of 
January of the year of the end date. 
Added the following: 
If the imputed stop date is prior to the imputed start date:  
• For missing start day and start month:  
− if the year of start date is the same as the year of first dose and the imputed stop date is on 
or after the date of first dose, then set the start date to the date of first dose 
− otherwise set to the 1st January of the year of the start date 
• For missing start day only 
− if the month and year of the start date is the same as the month and year of first dose and 
the imputed stop date is on or after the date of first dose, then set the start date to the date 
of first dose 
− if the month and year of the start date is the same as the month and year of first dose and 
the imputed stop date is before the date of first dose, then set the start date to the 1st of 
that month 
In the event of ambiguity or incomplete data which makes it impossible to determine whether a 
medication was concomitant, the medication will be considered as concomitant. 
Change #30 
Section 4.4 Multicenter studies 
Centers will be grouped in the geographic regions North America, Western Europe, 
Central/Eastern Europe, and Asia/Australia. 
Was modified to: 
However, the effect of center (using a pooling of centers by region) on results will be evaluated 
as mentioned in Section 3.8.  
Change #31 
Section 4.5 Multiple comparisons/multiplicity 
Figure 10.1: Sequential testing procedure of primary and key secondary efficacy endpoints 
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Was modified to the following: 
Table 4.4: Sequential testing procedure of primary/ secondary efficacy endpoints (fixed 
sequence testing procedure) (All efficacy endpoints at Week 16) 
BKZ 160mg Q4W 
H1 
ACR50 Response superior to Placebo 
H2 
Change from Baseline HAQ-DI superior to Placebo  
H3 
PASI90 Response superior to Placebo in subjects with PSO BSA ≥3% at Baseline 
H4 
Change from Baseline SF-36 PCS superior to Placebo 
H5 
MDA superior to Placebo 
ACR50=American College of Rheumatology 50% response crtiteria; BKZ=bimekizumab; H=hypothesis; HAQ-DI=Health 
Assessment Questionnaire - Disability Index; MDA=Minimal Disease Activity; PASI90=Psoriasis Area and Severity Index 90; 
PCS=Physical Component Summary; Q4W=every 4 weeks; SF-36=Short-Form 36-item Health Survey; W=week. 
Change #32 
Section 4.8 Examination of subgroups 
Table 4.2: Categories of variable for subgroup analyses 
Subgroup 
Categories 
Age (years) 
<45,  
≥45  
Gender 
Male, 
Female 
Race  
Black, 
White, 
Other  
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Subgroup 
Categories 
Region 
Asia/Australia,  
Eastern Europe,  
North America,  
Western Europe 
Disease duration (years) 
<1, 
≥1  
Body weight (kg) 
≤100, 
>100 
hs-CRP level 
< 6 mg/L, 
≥ 6mg/L 
Prior TNFα exposure 
Intolerance to TNFα inhibitor,  
Inadequate response to 1 TNFα inhibitor,  
Inadequate response to 2 TNFα inhibitors 
Prior cDMARDsa 
0, 
1,  
≥2 
Concomitant cDMARDsa 
Yes, 
No 
BSA affected by PSO (%) 
<3, 
 ≥3 to ≤10, 
 >10 
BASDAI  
≤4, 
 >4 
ADAb statusb 
Positive,  
Negative 
HLA-B27 statusc 
Positive,  
Negative 
a cDMARD= conventional disease-modifying antirheumatic drugs 
b Refer to Section 9.2 for further details on the definition categories.  
c  HLA-B27= human leukocyte antigen B27 
Was modified to the following: 
Subgroup analyses will be performed on the variables below. They are all assessed at Baseline,  
except concomitant cDMARDs, concomitant Methotrexate (MTX) and ADAb status which will 
be assessed during the 16-week period. Subgroup analyses will be performed on the ACR50 
response, the PASI90 response and the HAQ-DI response (subjects with a decrease of HAQ-DI 
from Baseline of at least 0.35) at Week 16. The ADAb status will also be used for subgroup 
analysis for the PK endpoints.  
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The variables for subgroup analyses will be  
• Age (<45 years of age, ≥45 years of age), 
• Gender (male, female), 
• Disease duration (<1 year, ≥1 year), 
• Region (eg, North America, Western Europe, Eastern Europe, Asia), 
• Race (White, Black and Other), 
• Body weight at Baseline (≤100kg, >100kg), 
• Prior TNFα exposure (intolerance to TNFα inhibitor, inadequate response to at least 1 TNFα 
inhibitor, inadequate response to 2 prior or more TNFα inhibitors), 
• hs-CRP at Baseline (<6mg/L, ≥6mg/L),  
• Prior conventional disease-modifying antirheumatic drugs (cDMARDs) (0, 1, ≥2) (taken 
prior to Baseline). Such medications will be classified using an adjudicated spreadsheet. 
• Concomitantly receiving cDMARDs versus no concomitant cDMARDs,  
• Concomitantly receiving MTX versus no concomitant MTX, 
• Concomitantly receiving MTX vs. cDMARDs at Baseline (concomitant MTX, no 
concomitant MTX and cDMARDs at Baseline, no concomitant MTX and no cDMARDs at 
Baseline),  
• PSO affected BSA at Baseline (<3%, ≥3% to 10%, >10%), 
• BASDAI Baseline (<4, ≥4), 
• ADAb status (positive, negative) (See 9.2) for the BKZ 160mg Q4W group only, 
• Human leukocyte antigen B27 (HLA-B27) (positive, negative). 
Note: In the context of submission for Japanese health authorities, a subset of tables, listings and 
figures will be provided for the subgroup of subjects randomized in Japan. 
Change #32 
Section 5.1 Subject disposition 
Included COVID-19-free set and modified to the following: 
The disposition of subjects into treatments groups and analysis sets will also be summarized on 
the RS. 
The number and percentage of randomized subjects who completed the study, completed the 
study not on randomized treatment, who discontinued IMP, overall and by reason, and 
who discontinued the study, with the primary reason for study discontinuation (as collected on 
the Study Termination CRF page), will be tabulated overall and by treatment group. The 
numbers and percentage of randomized subjects entering the SFU Period will additionally be 
presented.  
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A subject will be said to have completed the study if she/he had completed the last 
scheduled study visit, not including SFU visits. (The SFU visit is typically 140 days post last 
dose of IMP, which is roughly equivalent to 5 half-lives of BKZ).For subjects who 
previously discontinued IMP, the primary reason for discontinuation as collected on the 
Study Medication termination CRF page will be summarized in a separate table. 
Finally, the number of randomized subjects who discontinued the study due to AEs by type of 
AEs (serious fatal, non-fatal, other) will be summarized. 
Study disposition and termination details will be listed for all subject screened. Additional 
listings will be created on study discontinuation, subject analysis sets and visit dates (both 
actual visit and visit remapped for analysis). A listing will also be provided for subjects who 
did not meet the study eligibility criteria. 
To assess subject disposition (entry and periods in the study) during the COVID-19 
pandemic, subject disposition will be assessed by period of the COVID-19 pandemic (pre – 
during – post) (Section 3.6.7 ), by comparing the dates of visits (or events) to the dates of 
the COVID-19 pandemic period. 
 
Change #33 
Added the following section 5.2 Impact of COVID-19 
A listing of visits affected by COVID-19 will be presented based on the Enrolled Set including 
the visit, date of visit, relationship to COVID-19, impact category, and a narrative (short 
description) of the event. These data will be summarized for non-randomized subjects and by 
treatment group and overall, for enrolled subjects. 
A summary of study visits by COVID-19 pandemic period (pre – during – post) will be 
presented for subjects enrolled prior, during and after the pandemic.  
In addition, in order to assess the potential impact of COVID-19 on the collection and reporting 
of efficacy data, a separate summary on the RS will be presented to display missing data as well 
as data collected via an alternative modality (e.g.: phone, video call) for efficacy endpoints 
included in the hierarchy (Table 7‒4). For the purpose of these displays, missing data will be 
presented only for visits affected by COVID-19, as reported on the dedicated eCRF page. 
Missing data at other visits and for other reasons will not be included. 
For visits conducted remotely, it was not possible to assess some endpoints (e.g., TJC, SJC, LDI, 
LEI, PASI, etc.) and therefore these assessments will be missing for those visits. In addition, for 
any missed visit or visit conducted remotely, the CRP assessment will also be missing. Such 
assessments will be considered missing as a result of the COVID-19 pandemic. For these visits, 
it will therefore not be possible to assess composite endpoints like ACR response. For this 
summary table, reported on the RS, only visits at which efficacy assessments are scheduled will 
be included. 
 
Change #34 
Added COVID-19 IPD to section 5.3 Protocol deviations 
Change #35 
Added the following to section 6.1 Demographics 
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To understand the study population during the different periods of the COVID-19 pandemic, the 
reporting of Baseline demographics will be repeated by COVID-19 period (pre - during - post) as 
determined by the Baseline visit date) on the SS. 
 
Change #36 
Section 6.2.1 Baseline efficacy variables 
The different ACR components at Baseline (TJC, SJC, PGA-PsA, PhGA-PsA, PtAAP, HAQ-DI 
and hs-CRP (mg/dL)) will be summarized descriptively overall and by treatment group  
In addition, hs-CRP will be presented in category (< 6 mg/L, ≥ 6mg/L).  
Was modified to the following: 
Baseline values for the 7 components for primary efficacy variable will be summarized by 
treatment group and overall. The following variables will be summarized: 
• TJC,  
• SJC,  
• PGA-PsA, 
• PhGA-PsA, 
• PtAAP, 
• HAQ-DI, 
• hs-CRP (mg/L).  
For hs-CRP, SJC, and TJC the following rule will be applied: If Baseline value is missing, then 
take the most recent value (taken at previous unscheduled visit or at Screening); If value is still 
missing, the Baseline value will be considered missing. hs-CRP will be summarized using 
descriptive statistics   and in classes (≥6mg/L, <6mg/L). 
To understand the study population during the different periods of the COVID-19 pandemic, the 
reporting of Baseline demographics will be repeated by COVID-19 period (pre - during – post as 
determined by the Baseline visit date) on the SS. 
Change #37 
Section 6.2.2 Other baseline characteristics 
The following categorical variables will be summarized:  
• BASDAI (≤4,>4) 
• CASPAR criteria fulfilled (score ≥3), 
• BSA affected by PSO (<3%, ≥3% to ≤10%, >10%), 
• Rheumatoid factor (positive, negative), 
• Anti-cyclic citrullinated peptide (CCP) antibodies (Positive, Negative) 
• Nail psoriasis (yes, no), 
• Dactylitis (yes, no), 
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• Enthesitis (yes, no), 
• Past nonsteroidal anti-inflammatory drug (NSAID) therapy (yes, no) 
• Current NSAID therapy (yes, no) 
• Prior cDMARD (0, 1, ≥2) 
• Current DMARD (yes, no) 
• HLA-B27 status (positive, negative) 
 
Was modified to the following: 
The following variables will be summarized by treatment group and overall:  
• Prior TNFα exposure (Intolerance to TNFα inhibitor, Inadequate response to 1 TNFα 
inhibitor, Inadequate response to 2 TNFα inhibitors) – IXRS randomization strata 
• Prior TNFα exposure (Intolerance to TNFα inhibitor, Inadequate response to at least 1 TNFα 
inhibitor, Inadequate response to 2 prior or more TNFα inhibitors) – actual randomization 
strata 
• % of BSA affected by PSO (<3%, ≥3% to ≤10%, >10%) 
• PASI score at Baseline (for subjects with PSO involving at least 3% of BSA at Baseline). 
This variable will be summarized as a continuous variable and in classes (<10, 10 to 20,>20)  
• BASDAI (<4, ≥4) 
• Rheumatoid factor (positive, negative). A rheumatoid factor value < 30 IU/mL is defined as 
negative and a value ≥ 30 IU/mL is defined as positive. (Chemistry results / Proteins / 
Test=RF). 
• Anti-cyclic citrullinated peptide (CCP) antibodies (Positive, Negative).  Anti-CCP antibodies 
negative is a value < 20 U/mL and a value ≥ 20 U/mL is defined as positive. 
• Nail psoriasis (yes, no) 
• Dactylitis (“yes” if LDI score>0, “no” if LDI score=0 or missing) 
• Enthesitis based on LEI (“yes” if LEI score>0, “no” if LEI score=0 or missing) 
• Enthesitis based on SPARCC (“yes” if SPARCC>0, “no” if SPARCC=0 or missing) 
• Prior NSAID (yes, no)  
• NSAID at Baseline (yes, no)  
• Prior cDMARDs (0, 1, ≥2) (see Section 4.8 ) 
• cDMARDs at Baseline (yes, no) 
• HLA-B27 status (positive, negative) 
• Methotrexate at Baseline (yes, no)  
• Prior oral corticosteroids (yes, no)  
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• Oral corticosteroids at Baseline (yes, no) 
The above data including intra-auricular assessments will also be listed.  
Efficacy variables not listed above will not be presented in the Baseline characteristics section. 
They will be presented in by-visit tables in the context of the analysis of secondary and other 
efficacy variables. 
To understand the study population during the different periods of the COVID-19 pandemic, the 
reporting of Baseline demographics will be repeated by COVID-19 period (pre - during – post as 
determined by the Baseline visit date) on the SS. 
 
Change #38 
Section 6.2.3 History of psoriatic arthritis and psoriasis 
For both PsA and PSO, time since first diagnosis (years) will be calculated as follows: 
𝐷𝑎𝑡𝑒 𝑜𝑓 𝑖𝑛𝑓𝑜𝑟𝑚𝑒𝑑 𝑐𝑜𝑛𝑠𝑒𝑛𝑡−𝐷𝑎𝑡𝑒 𝑜𝑓 𝑑𝑖𝑎𝑔𝑛𝑜𝑠𝑖𝑠+ 1
365.25
 
Was updated to the following: 
Time since first diagnosis of PsA/PSO (years) will be calculated as follows: 
𝐷𝑎𝑡𝑒 𝑜𝑓 𝑖𝑛𝑓𝑜𝑟𝑚𝑒𝑑 𝑐𝑜𝑛𝑠𝑒𝑛𝑡−𝐷𝑎𝑡𝑒 𝑜𝑓 𝑑𝑖𝑎𝑔𝑛𝑜𝑠𝑖𝑠
365.25
 
If the date of diagnosis is partial, it should be imputed to the most recent feasible date (ie, last 
day of the month if only day is missing, or the last day of the year if day and month are missing). 
Partial dates should not be imputed later than the subject’s screening date. For subjects enrolled 
at German sites, only the year of birth may be entered into the eCRF for this study. For these 
subjects age will be calculated after imputing their date of birth to be on January 1st. 
The data on history of psoriasis and psoriatic arthritis will be listed for all screened subjects. 
Change #39 
Section 6.4 Prior and concomitant medications 
The following was added and updated: 
Prior medications include any medications that started prior to the date of the first IMP 
administration. 
The IMP dosing period corresponding to the combined Double-Blind Treatment Period will be 
calculated as follows: 
The study medication dosing period start date is defined as the date of first dose. 
The study medication dosing period stop date is defined as follows: 
• For subjects who are ongoing at the time of the clinical data cut (not including subjects who 
are in SFU) use date of last clinical contact 
• For subjects who died prior to last visit (not including those who died during SFU), use the 
minimum of the following: 
− Date of death 
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− Date of last dose of any study medication + 28 days 
• For subjects who complete the study as planned, the dosing period ends at the later of the 
following two dates: 
− Date of last administration of IMP + 28 days 
− The last scheduled visit date not including SFU 
• For all other subjects, use the maximum of the following: 
− Date of last dose of any study medication + 28 days 
Date of last visit (not including SFU) 
The number and percentage of subjects taking prior medications and prior Anti-TNFs 
(excluding past psoriasis medications) will be summarized on the RS by treatment group, 
overall and by ATC class, presenting Anatomical Main Group (ATC Level 1), 
Therapeutical/Pharmacological Subgroup (ATC level 3), and preferred term (PT).  
The table summary will be ordered alphabetically for the ATC class and in terms of decreasing 
frequency for PT within ATC class in the BKZ treatment group. In the event of ties, PT will be 
ordered alphabetically. 
A by-subject listing of all prior medications and prior Anti-TNFs, and concomitant 
medications (on the SS) as well as glossary of all medical medications will be provided. 
Change #40 
Section 6.5 Prohibited concomitant medications 
Refer to the study protocol for the list of prohibited or restricted medications. 
The number and percentage of study participants who used prohibited concomitant medication 
will be summarized by ATC class, presenting ATC Level 1, ATC level 3, and PT similarly as 
done for the summary on concomitant medications.  
The prohibited medications will be listed on RS. 
Was modified to the following: 
Prohibited or restricted medications are defined in the protocol (section 7.8.2). 
Prohibited medications will be listed on SS. 
Change #41 
Section 7 Treatment compliance 
The following was added: 
Treatment compliance summaries will be performed based on the SS, by randomized treatment 
and for all subjects. 
If a subject discontinues early, then the number of expected injections is based on the time of 
early discontinuation relative to the dosing visits. This number will be calculated by 
determining the number of expected dosing visits prior to the date of early discontinuation. 
If the early discontinuation coincides with an expected dosing visit, this visit will used to 
determine the number of expected injections. 
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Change #42 
Section 8.1.1 Derivation of ACR50 response 
The following was added: 
As the ACR response is based on 7 different component scores, it is necessary to consider 
various data scenarios that could impact the calculation of ACR response. The rules described 
here are applicable in the context of the calculation of ACR response and may differ from the 
rules applied for calculating and summarizing the components, individually (some values may 
need to be imputed for component for component analysis but are not required here to evaluate 
the ACR response). 
 
The following rules will be applied prior to invoking any imputation analysis at the variable 
level: 
• If a subject has a component value that is equal to 0 or is missing at Baseline and the post-
Baseline value is greater than or equal to 0, then the percentage of improvement for that 
component will be treated as 0 for purposes of ACR response calculations. 
• If a subject has a component value that is missing at Baseline, then the percentage of 
improvement for that component will be treated as missing for purposes of ACR response 
calculation.   
Observed data will be used to calculate ACR response where possible. In case of partial missing 
data where an observed response may be calculated, imputed data will not change the result.  
To address possible missing data in ACR components, ACR50 will be derived as below:  
• Positive response on ACR50 
o Improvement at Week 16 of at least 50% from baseline on SJC and TJC and at least 3 
out of the 5 remaining ACR components (regardless of whether the two remaining 
components are missing or not) 
• Negative response on ACR50 
o No improvement at Week 16 of at least 50% from baseline on SJC (regardless of 
whether the remaining components are missing or not) 
o No improvement at Week 16 of at least 50% from baseline on TJC (regardless of 
whether the remaining components are missing or not) 
o No improvement for at least 3 out of the 5 ACR components (PGA-PsA, PhGA-PsA, 
PtAAP, HAQ-DI, hs-CRP) regardless of whether the remaining components are 
missing or not 
• Missing ACR50 response 
o For all other situations that are not specified above. 
For the OC analysis: if a given visit falls after the treatment discontinuation date, the endpoint at 
all subsequent visits (whether the data were observed or not) will be derived but reported as 
missing in corresponding table under “OC” (Section 8.1.4.6). 
For the MI analysis: if a given visit falls after the treatment discontinuation date, the endpoint at 
this visit and all subsequent visits (whether the data were observed or not) will be imputed. 
Responses falling after an IE (defined as treatment discontinuation due to AE or lack of efficacy) 
will be set to nonresponse (Section 8.1.4.3).  
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Change #43 
Section 8.1.1.1 Derivation of tender joint count (TJC) and swollen joint count (SJC) 
Table 8.1 Swelling and tenderness grading 
Grade 
Tenderness response (68) 
Swelling response (66) 
0 
Not tender 
None 
1 
Tenderness present 
Detectable synovial thickening 
Was modified to the following: 
Table 8.1 Swelling and tenderness grading 
Present 
Tenderness response (68) 
Swelling response (66) 
No (0) 
Not tender 
None 
Yes (1) 
Positive response to questioning (tender), 
spontaneous response elicited (tender and winced) 
or withdrawal by subject on examination (tender, 
winced, and withdrew) 
Detectable synovial thickening 
with or without loss of bony 
contours, or bulging synovial 
proliferation with or without 
cystic characteristics 
 
Change #44 
Section 8.1.1.4 High-sensitivity C-Reactive Protein (hs-CRP) 
Hs-CRP values which are below the lower limit of quantification (LLOQ) should be set to the 
midpoint between 0 and the LLOQ. Listing will show values below the LLOQ. The limit of 
quantification for hs-CRP is 0.16 mg/dL. 
Was updated to the following: 
hs-CRP values which are below the lower limit of quantification (LLOQ) should be set to the 
midpoint between 0 and the LLOQ prior to the analysis. Listing will show values below the 
LLOQ. The LLOQ for hs-CRP is 0.10 mg/L. 
 
Change #45 
Section 8.1.2 Primary analysis of the primary efficacy variable 
The following 4 attributes describe the estimand that will be used to define the treatment effect 
of interest for the primary efficacy analysis: 
• Population = Study participants screened according to the protocol-specified 
inclusion/exclusion criteria and randomized to IMP 
• Study participant-level outcome = ACR50 at Week 16 
• Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment due to an AE or lack of efficacy prior to Week 16. A composite strategy will be 
implemented in which a positive clinical outcome is defined as achieving ACR50 at Week 16 
and not discontinuing study treatment due to an AE or lack of efficacy through Week 16. 
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• Population-level summary measure = Conditional odds ratio comparing bimekizumab to 
placebo. 
Intercurrent event will then be acknowledged as an unfavorable outcome for the composite 
estimand in considering study participants with intercurrent as ‘non-responders’ to the study 
treatment. 
Any missing data at Week 16 that is not preceded by an intercurrent event (ie discontinuation of 
study medication due to an AE or lack of efficacy) will be imputed by standard MI techniques 
(see Section 4.2.1.1 for details). In MI, the missing value is replaced by a set of plausible values, 
where each value is a Bayesian draw from the conditional distribution of the missing data given 
the observed data.  
As outlined in Section 4.5, the statistical null hypothesis for the ACR50 response at Week 16 is 
that there is no difference in the proportion of study participants with ACR50 response between 
the bimekizumab treatment and placebo (i.e. the conditional odds ratio for ACR50 response in 
the bimekizumab treatment compared with placebo is equal to 1). The alternative hypothesis is 
that there is a difference between bimekizumab treatment and placebo.  
The summary table results will present the adjusted responder rates and the associated 95% CI 
for bimekizumab and placebo, the adjusted odds ratio and 95% CI for the comparison of 
bimekizumab versus placebo, and the p-value that the OR=1. The treatment comparison will be 
made using the 2-sided Wald test at a significance level of α=0.05. 
Was updated to the following: 
The following 4 attributes describe the estimand that will be used to define the treatment effect 
of interest for the primary efficacy analysis: 
• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP 
• Subject-level outcome = ACR50 at Week 16  
• Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment prior to Week 16. A composite strategy will be implemented in which a positive 
clinical outcome is defined as achieving ACR50 at Week 16 and not discontinuing study 
treatment through Week 16. 
• Population-level summary measure = Conditional odds ratio comparing BKZ to placebo and 
difference of response rate between BKZ and placebo. 
Missing data at Week 16 that are not preceded by an IE and any data after an IE will be imputed 
as non-responders. This results in a more traditional NRI approach and will be labeled as such 
throughout the SAP. 
The statistical hypothesis for the ACR50 response at Week 16 is that the conditional OR for 
ACR50 response in the BKZ treatment compared to placebo treatment is equal to 1.   
A logistic regression model will be used to assess the treatment effect on ACR50 response at 
Week 16. The model will include fixed effects for treatment, and prior TNFα inhibitor exposure 
and region as stratification factors. The suitability of including these variables in the model will 
be assessed using goodness-of-fit tests (Deviance and Pearson and Hosmer-Lemeshow).  
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P-values below 0.05 would lead to a reconsideration of the model to be used and if the logistic 
regression model is unable to converge the stratification variables will be dropped (Section 4.1). 
In that case, all supportive analyses as well as imputation models conducted for the primary 
endpoint will disregard these exploratory factors from their models.  
The country-specific analyses performed on subjects randomized in Japan will not consider the 
region factor as a covariate for the modelling. 
The SAS® PROC LOGISTIC will be used to run the logistic regression.  
The summary table results will present the adjusted responder rates and the associated 95% CI 
for BKZ and placebo, the adjusted odds ratio and 95% CI for the comparison of BKZ versus 
placebo, and the p-value that the OR=1 and the difference of response rate between BKZ and 
placebo and associated 95% CI. The treatment comparison will be made using the 2-sided Wald 
test at a significance level of α=0.05 (ie, H1 Table 7‒4).  
Change #46 
Section 8.1.3 Secondary analyses of the primary efficacy variable 
Unless otherwise notified, for each subgroup analysis, a logistic regression will be fitted 
involving all model terms from the primary analysis model and additional terms for subgroup 
and subgroup by treatment interaction. For the analysis by stratification variables (ie, prior TNFα 
exposure and region), the analysis model will contain terms from the primary analysis model and 
the subgroup by treatment interaction. The same imputation method as the one used for the 
primary analysis will be used to handle missing data. In case of model convergence issue, 
missing data will be imputed using NRI instead of MI. For each subgroup category and each 
treatment group, the mean proportion of responders, the adjusted responder rates with associated 
95% CI will be provided. The adjusted OR (for the comparison bimekizumab and placebo) and 
95% CI will also be provided. The results obtained for each subgroup will be presented in one 
single table. The ORs and associated 95% CIs for each subgroup category will also be displayed 
on a single forest-plot.  
Was modified to the following: 
Section 8.1.3 Subgroup analyses of the primary efficacy variable 
For each subgroup analysis (except for the analysis by prior TNFα exposure , by region, and by 
ADAb status), a logistic regression will be fitted involving the same terms that were retained 
when running the primary analysis model, plus a term for the subgroup and the subgroup by 
treatment interaction as detailed below:  
• Fixed effect for treatment  
• Prior TNFα 1 (1 for inadequate response to at least 1 prior TNFα inhibitor) 
• Prior TNFα 2 (1 for inadequate response to 2 prior or more TNFα inhibitors) 
• Region  
• Term for subgroup  
• Terms for subgroup by treatment interaction(s).  
For subgroup analyses by Prior TNFα exposure, the terms that will be retained will be:  
• Fixed effect for treatment  
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• Prior TNFα 1 (1 for inadequate response to 1 prior TNFα inhibitor) 
• Prior TNFα 2 (1 for inadequate response to 2 prior TNFα inhibitors) 
• Region  
• Terms for Prior TNFα inhibitor exposure by treatment interaction  
For subgroup analyses by region, the terms that will be retained will be:  
• Fixed effect for treatment  
• Prior TNFα 1 (1 for inadequate response to 1 prior TNFα inhibitor) 
• Prior TNFα 2 (1 for inadequate response to 2 prior TNFα inhibitors) 
• Region  
• Terms for region by treatment interaction  
For subgroup analyses by ADAb status, the terms that will be retained will be:  
• prior TNFα exposure at Baseline   
• Region  
• ADAb Status (Positive, Negative) 
For all subgroup analyses, the terms for the subgroups will coded as below: 
• For Yes/No or positive /negative variables, the category “yes” or “positive” will be coded 
“1”. 
• For continuous variables in 2 classes, the highest category will be coded “1”. 
• For continuous variables in 3 classes (or more), 2 (or more) binary variables will be created 
and coded “1” for the 2 (or more) top categories. 
• For gender, “male” will be the category coded “1”. 
The same estimand approach as the one used for the primary analysis will be used to handle 
missing data (NRI).  
For each subgroup category and each treatment group (subgroup analysis on the ADAb status for 
only BKZ group), the mean proportion of responders on imputed datasets, the adjusted responder 
rates with associated 95% CI will be provided. The adjusted OR (for the comparison BKZ and 
placebo) and the corresponding 95% CI will also be provided. In addition, the difference in 
response rates between BKZ and placebo and the corresponding 95% CI will also be presented 
(except for the subgroup analysis on the ADAb status). The results obtained for each subgroup 
will be presented in one single table. The ORs and associated 95% CIs for each subgroup 
category will also be displayed on a single forest-plot.  
The observed rates of responses by subgroup categories will be also provided along with the 
results obtained on imputed data. 
Change #47 
Section 8.1.4 Supportive analyses of the primary efficacy variable 
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• and the same statistic results as the ones produced for the primary efficacy analysis will be 
calculated 
Was updated to: 
• the same statistics will be provided: the mean proportion of responders (on imputed datasets 
when applicable) the adjusted responder rates for each treatment group, the adjusted ORs for 
the comparison BKZ versus placebo and its 95% CI, the p-value for the comparison between 
BKZ and placebo and the difference of response rates between BKZ and placebo and its 
corresponding 95% CI. 
Change #48 
Added Section 8.1.4.3 Analysis using modified composite estimand where intercurrent 
events are defined as discontinuation due to AE or Lack of efficacy 
The modified composite estimand for this analysis is detailed below  
• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP. 
• Subject-level outcome = ACR50 at Week 16. 
• Intercurrent event handling = An intercurrent event is defined as discontinuation due to AE 
or lack of efficacy. A composite strategy will be implemented in which a positive clinical 
outcome is defined as achieving ACR50 at Week 16 and not discontinuing study treatment 
due to an AE or lack of efficacy through Week 16. Subjects discontinuing study treatment 
due to AE or lack of efficacy will be imputed based on completer subjects.  
• Population-level summary measure = Conditional OR comparing BKZ to placebo  
Any missing data at Week 16 that is not preceded by an intercurrent event will be imputed based 
on a predefined MI model (MI/MCMC - Monotone Regression) (Section 4.2.2.2).  
The following categories of subjects will enter the MI/MCMC – Monotone regression process 
for each ACR component:  
• Subjects with all post-baseline values missing.  
• Subjects withdrawn from the study treatment (data collected prior to the treatment 
withdrawal will be retained) - Those subjects will have values imputed for missing 
assessments and non missing assessment falling after study treatment discontinuation (falling 
after or before the study withdrawal). 
• Subjects with IE - Data collected after the intercurrent event will be set to missing.  
• Subjects with missing value at Baseline. MI will be applied for each of the components 
separately before deriving the response.  
In the case of partial missing data, ACR will be derived as in Section 8.1.1. 
If an IE occurred prior to or at week 16 (or for any other intermittent missing data at Week16), 
the subjects will be considered as “nonresponders”. 
In MI, the missing value is replaced by a set of plausible values, where each value is a Bayesian 
draw from the conditional distribution of the missing data given the observed data. 
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Change #49 
Section 8.1.4.3 Analysis on individual components of the ACR 
The change from Baseline in each individual component variable of the ACR50 response (TJC, 
SJC, PGA-PsA and PhGA-PsA) or ratio to Baseline for hs-CRP, will be analyzed at Week 16 
using an analysis of covariance (ANCOVA) model. The analyses for the component variables 
PtAAP and HAQ-DI will be described in Section 8.2.2  where analyses for secondary endpoints 
are described. For all five variables, the model will include treatment, prior TNFα inhibitor 
exposure and region as fixed effects and the respective Baseline value as covariate. For hs-CRP, 
the model will be run on ln-transformed data and the results will be presented back-transformed 
towards their original scale. These analyses will be done on the RS and will explore the effect of 
the signs and symptoms of the individual components on the composite endpoint. 
The following 4 attributes describe the estimand that will be used to define the treatment effect 
of interest for this analysis: 
• Population = Study participants screened according to the protocol-specified 
inclusion/exclusion criteria and randomized to IMP 
• Study participant level outcome = The change from Baseline in the ACR component variable 
at Week 16 
• Intercurrent event handling = A hypothetical strategy will be implemented in which the 
estimand targets the treatment difference in a scenario where intercurrent does not occur, 
such that outcomes for study participants without an intercurrent event are as observed, and 
outcomes for study participants with an intercurrent event are treated as though they had 
completed the randomized study treatment through Week 16.  
• Population-level summary measure = the difference in the adjusted means between 
bimekizumab and placebo. 
As detailed in Section 4.2.1  any missing data at Week 16 will be imputed by the standard MI 
techniques described in Section 4.2.1.1.  
The SAS® PROC MIXED will be used to run the ANCOVA model.  
For each ANCOVA model specified in this analysis (except the one for hs-CRP), the following 
statistics will be presented: 
− For placebo and bimekizumab: the adjusted least-square means (LSM) and standard error 
(SE) 
− For the comparison between placebo and bimekizumab: the difference between the LSM, 
the associated 95% CI for the contrasts, and the corresponding p-value. 
For the ANCOVA analysis on the hs-CRP endpoint, the following statistics will be presented: 
− For placebo and bimekizumab: the adjusted geometric mean and geometric CV (%) 
− For the comparison between placebo and bimekizumab: the geometric LSM ratio, the 
associated 95% confidence intervals for the contrasts, and the corresponding p-value. 
An additional table will present the descriptive statistics for the two treatment groups for each 
ACR component variable at Week16. Those statistics will be the mean and SD (geometric mean 
and CV (%) for hs-CRP), median, minimum and maximum after MI imputation. 
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The following supportive analyses described in Section 8.1.4.4 to 8.1.4.8  are planned in order to 
check the robustness of the primary analysis results to missing data handling. 
Was modified to the following: 
Section 8.1.4.4 Analysis on individual components of the ACR 
The primary comparison (BKZ vs. placebo) will also be repeated for all individual components 
of the ACR50 response to explore the effect of the signs and symptoms of the individual 
components on the composite endpoint. Since all ACR components are continuous variables (eg, 
change from Baseline in TJC), an analysis of covariance (ANCOVA) with treatment, region, and 
Prior TNFα inhibitor exposure as fixed effects and the Baseline value as covariate will be used 
for the analysis. Missing data imputation described in Section 4.2.2 will be successively applied 
for each component. 
The following 4 attributes describe the hypothetical estimand that will be used to define the 
treatment effect of interest for each of the 7 ACR components: 
• Population = Subjects who meet the protocol-specified inclusion/exclusion criteria and 
randomized to IMP 
• Subject level outcome = Change from Baseline in the ACR components at Week 16 
• Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment prior to Week 16. This estimand targets the treatment difference in a scenario 
where withdrawal from study treatment does not occur, such that outcomes for subjects 
without an intercurrent event are as observed, and outcomes for subjects with an intercurrent 
event are treated successively according to the two following hypothetical strategies: 
− (a) as they had completed treatment through Week 16. In that strategy, missing data or 
non missing data after IE (reset as missing) will be imputed using MI as though they had 
completed the randomized study treatment through Week 16.  
− (b) as they had completed the randomized study treatment through Week 16 but on 
Placebo. In that strategy, missing data or non missing data after IE (reset as missing) will 
be imputed using Reference-Based MI, in which the MI model is based on data from the 
Placebo group. 
• Population-level summary measure = The difference in the adjusted means between BKZ and 
placebo. 
For the results obtained using the two MI methods, the SAS® PROC MIXED will be used to run 
the ANCOVA model. The inferential statistics obtained from each model will be displayed in a 
single table. 
For all variables, the following statistics will be presented: 
− the adjusted least-square means (LSM) and standard error (SE) by treatment group, 
− for the comparison between placebo and BKZ: the difference between the LSM, the 
associated 95% CI for the contrasts, and the corresponding p-value. 
An additional table will present the descriptive statistics for the 2 treatment groups for each ACR 
component variable at Week16. Those statistics will be the mean and SE, median, minimum and 
maximum after MI. 
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Change #50 
Section 8.1.4.5 Analyses using treatment policy strategy imputation for missing data 
Added the following: 
In the context of this analysis, in addition to the statistics provided in the context of MI, the 
number of observed ACR50 responses regardless of the existence of intercurrent events will be 
also reported. 
The following 4 attributes describe the treatment policy strategy analysis is detailed below: 
Population = Subjects enrolled according to the protocol-specified inclusion/exclusion criteria 
and randomized to IMP. 
Change #51 
Section 8.1.4.6 Analyses on Observed Cases 
Modified the following:  
The following 4 attributes describe the estimand that will be used to define the treatment effect 
of interest for the OC analysis: 
• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP 
Change #52 
Added the following:  
Section 8.1.4.8 Analyses including COVID-19 impact 
To assess the impact of the COVID-19 pandemic on the primary efficacy endpoint, 2 sensitivity 
analyses will be conducted using the same analysis method as the primary analysis (Section 
8.1.2): 
• on the COVID-19-free Set 
• by COVID-19 period (pre- during -post as determined by the Week 16 date). 
Change #53 
Added the following:  
Section 8.2.1. Derivation of secondary efficacy variables 
The primary and supportive analysis methods of secondary efficacy variables for which the 
derivation method is provided below are described in Section 8.2.2 and Section 8.2.3. 
For the other secondary variables which are not part of the testing hierarchy, there is no priority 
designated between methods described as primary and supportive analysis methods. 
Change #54 
Added the following: 
Section 8.2.1.1 HAQ-DI: Change from Baseline at Week 16 
The derivation for HAQ-DI is described in Section 8.1.1.3 (The analysis of this variable is 
already covered in Section 8.1.4.4).   
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Change from Baseline at Week 16 in HAQ-DI is the 2nd endpoint in the sequential testing 
hierarchy (Table 7‒4). 
 
Change #55 
Section 8.2.1.1. Psoriasis Area and Severity Index (PASI), PASI90 has been changed to: 
Section 8.2.1.2 Psoriasis Area and Severity Index 90 (PASI90) at Week 16 (in subjects with 
PSO involving at least 3% of BSA at Baseline) 
 
Change #56 
Section 8.2.1.2. Short Form-36 (SF-36) Physical Component Summary (PCS)  
The SF-36 (Version 2, standard recall) is a 36-items generic health-related quality of life 
instrument that uses a recall period of 4 weeks.  Items are grouped into 8 domains as follows:  
• Physical Functioning (10 items) 
• Role Physical (4 items) 
• Bodily Pain (2 items) 
• General Health (5 items) 
• Vitality (4 items) 
• Social Functioning (2 items) 
• Role Emotional (3 items) 
• Mental Health (5 items) 
One additional item (Question 2) asks respondents about perceived stability or change in health 
(Health Transition) over the past year. The concepts represented by these domains contribute to 
physical, mental, and social aspects of health-related quality of life. 
 In addition to domain scores, the PCS and MCS scores are calculated from the 8 domains 
(excluding the Health Transition item). Component scores reflect the impact of each domain on 
physical and mental health status. 
The norm-based T-scores for the 2 SF-36 component summary (PCS and MCS) and the 8 
domains are standardized with a mean of 50 and a standard deviation (SD) of 10 in the general 
US population (Maruish, 2011). An individual respondent’s score that falls outside the T-score 
range of 45 to 55 should be considered outside the average range for the US general population. 
When considering group-level data, a score below 47 should be considered indicative of 
impaired functioning within that health domain or dimension. Similar to individual respondent 
data, group mean scores of 47 or greater should be considered average or above average as 
compared to the general US population. Higher scores indicate a better health status. 
For the calculation of the SF-36 norm-based T-scores for the 8 domains and the PCS and MCS, 
the scoring software Optum’s PRO CoRE (version 1.4) will be used. The software uses updated 
2009 U.S. population norms and applies a Full Missing Score Estimation method as follows: 
• A health domain score (except the Physical Functioning domain) will be estimated provided 
that at least one 1 non-missing response is available within that domain.  
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• For the Physical Functioning domain, item response theory will be used to develop a model 
for estimates of the missing score. 
• Regression methods will then be applied to estimate the PCS and MCS on the basis of the 
available domains. 
Change from Baseline at Week 16 in SF-36 PCS score is the 4th endpoint in the sequential testing 
hierarchy (Table 7‒4).  
Change #57 
Section 8.2.1.3. MDA at Week 16 has been updated to Section 8.2.1.4 
And the following has been deleted: 
MDA response will be equal to 0 if the condition about achieving at least 5 of the 7 above 
criteria is not met. 
The following was added: 
A subject has achieved MDA if 5 or more of the 7 above criteria are fulfilled.  
The following rule will be applied for subjects with BSA <3 at Baseline: Subjects with BSA <3 
at Baseline will always meet the criteria PASI ≤1 or BSA ≤3 except in the cases where a BSA 
score ≥3 is observed. 
Change #58 
Section 8.2.1.5. Investigator’s Global Assessment (IGA)  
Has been updated to: 
Section 8.2.1.6 Proportion of subjects with an Investigator’s Global Assessment (IGA) score 
of 0 (clear) or 1 (almost clear) AND at least a 2-grade reduction from Baseline at Week 4 
and Week 16 in the subset of subjects with psoriatic skin lesions at Baseline 
 
The following has been added: 
For some subjects with BSA ≥ 3% at Baseline, IGA data have not been captured at Week 4 and 
Week 16 visits when BSA<3% at those visits. To address that, an additional supportive analysis 
will be performed in which these subjects will be considered as IGA responders at the respective 
visit. 
Change #59 
Section 8.2.1.5. Investigator’s Global Assessment (IGA) has been updated to section 8.2.1.6 
Proportion of subjects with an Investigator’s Global Assessment (IGA) score of 0 (clear) or 
1 (almost clear) AND at least a 2-grade reduction from Baseline at Week 4 and Week 16 in 
the subset of subjects with psoriatic skin lesions at Baseline 
 
The following has been added: 
For some subjects with BSA ≥ 3% at Baseline, IGA data have not been captured at Week 4 and 
Week 16 visits when BSA<3% at those visits. To address that, an additional supportive analysis 
will be performed in which these subjects will be considered as IGA responders at the respective 
visit. 
Change #60 
Added the following Section 8.2.1.7. Change from Baseline in the Patient’s Assessment of 
Arthritis Pain (PtAAP) 
 
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Change #61 
Section 8.2.1.6. Psoriatic Arthritis Impact of Disease, PsAID-12 has been updated to section 
8.2.1.8 Change from Baseline in PsAID-12 total score at Week 16 
 
Change #62  
Added the following sections: 
Section 8.2.1.9 Psoraiais Area Severity Index (PASI90) at Week 4 (in subjects with PSO 
involving at least 3% of BSA at Baseline) 
 
Change #63  
Updated the following section: 
Section 8.2.2 Primary analysis of secondary efficacy variables 
The secondary efficacy variables will be analyzed for all subjects in the RS. 
As indicated in Table 7‒4, there are 4 secondary endpoints included in the testing hierarchy that 
will be tested in a chronological order until one is failed to be statistically significant.  
For the other secondary endpoints (which are not part of the testing hierarchy), the p-values 
produced by the statistical models will be considered nominal since these endpoints are not 
controlled for multiplicity. 
For the secondary composite and non-composite binary endpoints, the same estimand structure 
(composite estimand) as the one defined for the primary efficacy analysis of the primary efficacy 
endpoint (Section 8.1.2) will be used. The NRI approach for handling missing data and the same 
analysis model will be considered, and the analysis results will be presented similarly.  
The statistical hypothesis for the binary variables at Week 16 is that the conditional odds ratio in 
the BKZ group compared with placebo treatment group is equal to 1. For the secondary 
continuous endpoints, the analysis will evaluate the hypothetical estimand as defined below: 
• Population = Subjects enrolled according to the protocol-specified inclusion/exclusion 
criteria and randomized to IMP.  
• Subject level outcome = variable as stated in Section 2.2.2     
• Intercurrent event handling = An intercurrent event is defined as discontinuation of study 
treatment prior to Week 16. A hypothetical strategy for addressing intercurrent events will be 
implemented. This estimand targets the treatment difference in a scenario where withdrawal 
from study treatment does not occur, such that outcomes for subjects without an IE are as 
observed, and outcomes for subjects with an IE are treated as though they had completed 
treatment through Week 16 but on Placebo. A MI strategy will be used to impute any missing 
data and observed data after IE which will be set to missing prior to running MI. Such data 
will be imputed using Reference-Based MI, in which the MI model is based on data from the 
placebo group.  
• Population-level summary measure = the difference in the adjusted means between BKZ 
160mg Q4W and placebo. 
The same analysis model and imputation strategy for handling missing data as in Section 8.1.4.4 
will also be considered. The analysis results will be presented similarly as for this analysis on the 
individual components. 
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In the case of MDA as the response is based on 7 different component scores, it is necessary to 
consider various data scenarios that could impact the calculation of response. The rules described 
here are applicable in the context of the calculation of MDA response and may differ from the 
rules applied for calculating and summarizing the components individually (some values may 
need to be imputed for component analysis but are not required here to evaluate MDA response).  
The following rules will be applied to complete the derivation of MDA response based on the 
composite estimand definition: 
• If a given visit has been preceded by an IE (treatment discontinuation): 
o The endpoint at all subsequent visits (whether the data were observed or not) will be set 
to “nonresponse” as the subject has not met the criteria for response. 
• If a given visit has not been preceded by an intercurrent event: 
o If a subject satisfies at least 5 of the 7 MDA criteria, the subject is considered as MDA 
responder 
o If a subject does not satisfy at least 3 MDA criteria, the subject is considered as non-
MDA responder 
o In all other cases, the NRI approach will be applied.  
An overview table will combine the results of the primary analysis for the primary and secondary 
efficacy endpoints included in the testing hierarchy.  
For the country specific analyses performed on subjects randomized in Japan, the region factor 
will net be considered as a covariate for the modelling. 
 
Change #64  
Updated the following section: 
Section 8.2.3 Supportive analyses of the secondary efficacy variables 
As mentioned in Table 7‒2, the supportive analyses for all secondary variables will be performed 
using the modified composite estimand for binary variables (using MI-MCMC/monotone 
regression as in Section 8.1.4.3) and on OC.  
For PASI90, the MI will be run on the PASI score on subjects involving at least 3% of BSA at 
Baseline. 
Additionally, subgroup analyses will be performed on the PASI90 response at Week 16 (in 
subjects with PSO involving at least 3% of BSA at Baseline) endpoint. Refer to Section 4.8 for 
the list of subgroups of interest. The same analysis method than the one used for the subgroup 
analysis of the primary endpoint will be performed. The results will be presented similarly.  
To assess the impact of the COVID-19 pandemic, the analysis of secondary efficacy endpoints 
with be repeated on the COVID-19-free Set using the primary analysis method. 
Change #65  
Updated the following sections: 
Section 8.3.1.1 Time to ACR20/50/70 response from Baseline 
Time to a given response will be defined as the length in days from Baseline until the first date 
when the response is achieved.  
Time from Baseline to censoring will be considered for the following subjects:  
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• Subjects who discontinue study treatment prior to achieving a response will be censored at 
the date of study treatment discontinuation.  
• Subjects who reach the end of treatment period visit without achieving the given response 
will be censored at the date of the end of treatment period visit (for the interim analysis, 
subjects who reached Week 16 without achieving the given response will be censored at that 
visit). 
Change #66 
Added section 8.3.1.2 ACR20, ACR50 and ACR70 response 
 
Change #67 
Added sections 8.3.1.3 PASI90 response and 8.3.1.4 PASI75 and PASI100 response 
 
Change #68 
Updated section 8.3.1.2 to section 8.3.1.5 to include composite endpoint of ACR50/PASI100 
 
Change #69 
Added section 8.3.16 Proportion of Psoriatic Arthritis Response Criteria (PsARC) 
responders 
 
Change #70  
Added section 8.3.1.7 Psoriatic Arthritis Disease Activity Score (PASDAS) categories 
 
Change #71 
Section 8.3.2.3 Additional statistical analysis of other efficacy endpoints 
Many details have been added to this section. See SAP section in main text. 
 
Change #72 
Sections 9 has been updated. See SAP main text 
 
Change #73 
Added section 10.1.2 Time at risk in subject-years by COVID-19 pandemic period 
 
Change #74 
Updated section 10.2.1 Standard AE summaries 
TEAEs by timing of onset relative to ADAb status by SOC, HLT, PT (on subjects treated with 
BKZ). This will include columns for the following: 
− TEAEs starting before the first ADAb positive result (includes ADAb categories 2, 4 and 
5) where TEAEs have occurred before the following events: a) the first positive ADAb 
result for subjects in category 2 and b) the first post-baseline boosted ADAb titer result 
for subjects with titer results and the first post-Baseline positive ADAb result for subjects 
with positive ADAb at Baseline with no other samples with titer available for subjects in 
category 5 
− TEAEs starting on the same date or after the first ADAb positive result, including 
Baseline (includes ADAb Categories 2, 3, 4, 5 and 6) where TEAEs have occurred on or 
after the following events: a) the first positive ADAb results for subjects in categories 2, 
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3, 4 and 6, and b) the first post-baseline boosted ADAb titer result for subjects with titer 
results and the first post-Baseline positive ADAb result for subjects with positive ADAb 
at Baseline with no other samples with titer available for subjects in category 5 
− TEAEs for subjects who are ADAb negative at all timepoints (includes ADAb Category 
1) 
TEAEs by NAb status (ADAb negative, NAb positive, ADAb positive / NAb, negative) on 
subjects treated with BKZ. TEAEs will be sorted by system organ class, high level term and 
preferred term. 
Note: for TEAE by onset relative to ADAb positivity status and by NAb status, all available 
ADAb and NAb data at the time of IA cut-off, respectively, will be utilized to derive the subject-
level ADAb/NAb status categories. 
 
Change #75  
Section 10.2.4 Other safety topics of interest  
The following has been updated 
The analyses produced for the above TEAE are based on the specifications described in the BKZ 
safety topic of interest document version from 8-Apr-2019. 
Has been updated to: 
The analyses produced for the above TEAE are based on the specifications described in the BKZ 
safety topic of interest document version from Apr-2021 
 
Subsections were created for all safety topics of interest separately and details have been updated 
in the sub sections. 
 
Change #76  
Added section 10.2.5 COVID-19 impact 
See SAP for main text 
 
Change #77 
Updated Tables 10.3, 10.4, and 10.5 
 
Change #78 
Updated section 11 References 
 
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13.2 
Amendment 2 
Rationale for the amendment 
The primary purpose of this amendment was to address discrepancies of the SAP amendment 1 
and additional updates as requested by UCB.  
Modifications and changes 
Change #1 
Added the following text to Section 3.5: Protocol deviations 
In addition to IPDs resulting in the exclusion from the PPS, subjects who reduce the dose or 
dosing frequency of certain medications due to intolerance, AE, side-effects or receive new 
prohibited medication for AE will be removed from the PPS. While this is not an IPD, as it is 
allowed per protocol for safety reasons, these subjects will be removed from the PPS as this non-
PD could have an affect the primary efficacy outcome in the same way as flagged IPDs resulting 
in exclusion from the PPS. 
 
Change #2 
Section 3.6.5: Per Protocol Set 
The Per-Protocol Set (PPS) will consist of all subjects in the RS who had no IPD affecting the 
primary efficacy. The IPDs will be predefined and subjects with IPDs will be evaluated during 
ongoing data cleaning and data evaluation meetings prior to unblinding of the data (Section 3.5). 
Exclusion from the FAS will be considered as IPDs that also result in exclusion from the PPS. 
Supportive analysis of the primary efficacy variable will be performed on the PPS. 
Has been changed to: 
The Per-Protocol Set (PPS) will consist of all subjects in the RS who had no IPD or non-PD 
related to prohibited medications affecting the primary efficacy. The IPDs deviations will be 
predefined and subjects with IPDs deviations will be evaluated during ongoing data cleaning 
and data evaluation meetings prior to unblinding of the data (Section 3.5). Exclusion from the 
FAS will be considered as an IPDs that also results in exclusion from the PPS. 
Supportive analysis of the primary efficacy variable will be performed on the PPS. 
 
Change #3 
Section 4.2.1: Strategy for handling missing data for efficacy analyses  
Added line to Table 4-1  
Efficacy endpoint 
Minimum  
Maximum 
Integer value 
Tender dactylitis 
count 
0 
20 
Yes 
 
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Change #4  
Section 4.2.2.3: MI-MCMC / Reference-based imputation (steps of the procedure) 
In the case of continuous endpoints, the procedure will be implemented as follows on the raw 
values:  
1. Data will be processed sequentially, one timepoint (visit) at a time, by repeatedly calling 
SAS® PROC MI to impute missing outcome data at visits t=1,…, Week 16 (Week 16 being 
the time point of interest) using data from the placebo-treated subjects only.  
a. Initialization. Set t=1 (Baseline visit).  
b. Iteration. Set t=t+1. Create a dataset combining records from BKZ and placebo subjects with 
columns for covariates (bone erosion and region) and outcomes at visits 1 to t. Outcomes for all 
BKZ randomized subjects are set to missing at visit t and set to observed or previously imputed 
values at visits 1 to t-1. Outcomes for placebo-treated subjects are set to observed at visit t or 
observed or previously imputed values at visits 1 to t-1. The outcomes should be sorted in 
chronological order in the model.  
c. Imputation. Impute missing values for visit t using previous outcomes for visits 1 to t-1, bone 
erosion at Baseline, and region. Note that only placebo data will be used to estimate the 
imputation model since no outcome is available for BKZ-treated subjects at visit t. As a 
consequence, the input dataset should include all subjects from Placebo but only subjects from 
the BKZ arm that have values at timepoint t missing.  
d. Repeat steps 2a-2d for all timepoints, (…) 
Has been changed to: 
In the case of continuous endpoints, the procedure will be implemented as follows on the raw 
values:  
1. Data will be processed sequentially, one timepoint (visit) at a time, by repeatedly calling 
SAS® PROC MI to impute missing outcome data at visits t=1 (Baseline),…, Week 16 
(Week 16 being the time point of interest) using data from the placebo-treated subjects only.  
a. Initialization. Set t=1 (Baseline visit). Create a dataset combining all records from all 
subjects with columns for covariates (bone erosion and region) and outcome at Baseline. 
Impute missing values at Baseline using bone erosion at Baseline, and region.  
b. Iteration. Set t=t+1. Create a dataset combining records from BKZ subjects with missing 
data at visit t and all placebo subjects with columns for covariates (bone erosion and region) 
and outcomes at visits 1 to t. In this dataset, outcomes for all BKZ randomized subjects are set 
to missing at visit t and set to observed or previously imputed values at visits 1 to t-1. Outcomes 
for placebo-treated subjects are set to observed or missing at visit t or and observed or 
previously imputed values at visits 1 to t-1. The outcomes should be sorted in chronological 
order in the model.  
c. Imputation. Impute missing values for visit t using previous outcomes for visits 1 to t-1, bone 
erosion at Baseline, and region. Note that only placebo data will be used to estimate the 
imputation model since no outcome is available for BKZ-treated subjects at visit t. As a 
consequence, the input dataset should include all subjects from Placebo but only subjects from 
the BKZ arm that have values at timepoint t missing.  
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d. Repeat steps 1b-1c for all timepoints after Baseline up to Week 16, (…) 
 
Change #5 
Section 4.8 Examination of subgroups (5th bullet from the end) 
• Concomitantly receiving MTX vs. cDMARDs at Baseline (concomitant MTX, no 
concomitant MTX and cDMARDs at Baseline, no concomitant MTX and no cDMARDs at 
Baseline)  
Has been changed to: 
• Concomitantly receiving MTX at Baseline vs. other cDMARDs at Baseline (concomitant 
MTX at Baseline, no concomitant MTX at Baseline and cDMARDs at Baseline, no 
concomitant MTX at Baseline and no cDMARDs at Baseline)  
 
Change #6 
Added new text to Section 5.1 Subject Disposition  
The numbers and percentages of these subjects who either complete the SFU visit or not will 
additionally be presented. The numbers and percentages of randomized subjects entering the 
Open Label Extension (OLE) study and those not entering the OLE study will also be presented.  
Change #7 
Section 6.2.2 Other baseline characteristics  
Added: 
Past cDMARDs Therapy (Yes, No) 
Change #8 
Following text was added to Section 5.3 Protocol deviations. 
number and percentage of subjects excluded from the PPS due to reason other than PD. 
A by-subject listing of subjects excluded from the PPS for reasons other than IPD will be 
provided. 
 
Change #9 
Section 7 Measure of treatment compliance  
A summary of percent treatment compliance categorized as ≤75% and >75% will be provided by 
treatment group, as well as a by-subject listing of treatment compliance. 
Has been changed to: 
A summary of percent treatment compliance categorized as <75% and >=75% will be provided 
by treatment group, as well as a by-subject listing of treatment compliance. 
 
Change #10 
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Added following text in Section 8.1.2 Primary analysis of the primary efficacy variable  
Considering that the number of subjects randomized in Japan is low (less than 10% of the RS), 
statistical models might not converge. If a model (logistic model or mixed model) is not 
converging, all related adjusted statistics and p-value will not be presented: “NE” for “Not 
Evaluable” will be displayed instead.  
Change #11 
Section 8.2.1.4 MDA at Week 16 (last but one paragraph) 
The following rule will be applied for subjects with BSA <3 at Baseline: Subjects with BSA <3 
at Baseline will always meet the criteria PASI ≤1 or BSA ≤3 except in the cases where a BSA 
score ≥3 is observed.  
Has been changed to: 
The following rule will be applied for subjects with BSA <3 at Baseline: Subjects with BSA <3 
at Baseline will always meet the criteria PASI ≤1 or BSA ≤3 except in the cases where a post-
Baseline BSA score >3 is observed 
Change #12 
Following text has been added in Section 8.2.3 Supportive analyses of the secondary efficacy 
variables  
For the MDA (and VLDA) MI analysis, subjects with BSA <3 at Baseline will always meet the 
criteria PASI ≤1 or BSA ≤3 except in the cases where a BSA score >3 is observed.  Subjects 
involving at least 3% of BSA at Baseline will have their BSA values imputed using MI when 
deriving MDA (VLDA). 
Change #13 
Section 8.3.1.6: Psoriatic Arthritis Disease Activity Score (PASDAS) categories and change 
from Baseline in PASDAS  
The following categories are used to define the level of disease activity:  
• Low disease activity: PASDAS 1.9 to <3.2 
The PASDAS categories and the change from Baseline in PASDAS score will be analyzed at 
Week 4, 8, 12, 16. 
Has been changed to: 
If Tender Dactylitis count is missing because LDI=0 at Baseline, Tender Dactylitis count will be 
replaced by 0 in the formula. 
If for any other reason a any of the  PASDAS component is missing, PASDAS will be set to 
missing.  
The following categories are used to define the level of disease activity:  
• Low disease activity: PASDAS >1.9 to <3.2 
The PASDAS categories and the change from Baseline in PASDAS score will be analyzed at 
Week 4, 12, 16. 
Change #14 
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Section 8.3.2.2 Other endpoints (excluding time to ACR20/50/70 response) (paragraph about 
analysis of categorical endpoints) 
For categorical endpoints (ie, EQ-5D-3L dimensions score, DAPSA state) using:  
• The number and percentage by endpoint category using the NRI approach (as performed for 
the primary analysis of the primary endpoint with the exception that the NRI is replaced by 
the worst category imputation) 
• The mean percentage by endpoint category in the multiple imputed datasets (modified 
composite estimand). Regardless of imputed values, the value of the categorical endpoint 
after IE are by default set to the worst category (ie:  High Disease Activity for DAPSA state)   
Has been changed to: 
For categorical endpoints (ie, EQ-5D-3L dimensions score, DAPSA state, PASDAS categories) 
using:  
• The number and percentage by endpoint category using the NRI approach (as performed for 
the primary analysis of the primary endpoint with the exception that the NRI is replaced by 
the worst category imputation) 
• The mean percentage and corresponding 95% CI by endpoint category in the multiple 
imputed datasets (modified composite estimand). Regardless of imputed values, the value of 
the categorical endpoint after IE are by default set to the worst category (ie:  High Disease 
Activity for DAPSA state)   
Change #15 
Section 9.1: Pharmacokinetics (paragraph 3) 
No imputation will be used for missing samples. However, if plasma concentration 
measurements are below the limit of quantification (BLQ), then for the calculation of the derived 
statistics, the result will be set to ½ of LLOQ (ie, 1/2*0.250 = 0.125 ug/mL). Descriptive 
statistics including number of values, geometric mean, its 95% CI, geometric coefficient of 
variation, mean, SD, median, minimum, and maximum. Geometric mean and its 95% CI, 
geometric CV, mean and SD will be calculated if at least ⅔ of the values of interest is above the 
LLOQ; otherwise, only number of values, median, minimum, and maximum will be presented. 
Has been changed to: 
No imputation will be used for missing samples. However, if plasma concentration 
measurements are below the limit of quantification (BLQ), then for the calculation of the derived 
statistics, the result will be set to ½ of LLOQ (ie, 1/2*0.250 = 0.125 ug/mL). Descriptive 
statistics including number of values, geometric mean, its 95% CI, geometric coefficient of 
variation, mean, SD, median, minimum, and maximum. Geometric mean and its 95% CI, 
geometric CV, mean and SD will be calculated if at least ⅔ of the values of interest is above the 
LLOQ and number of values>=3; otherwise, only number of values, median, minimum, and 
maximum will be presented. 
 
Change #16 
Section 9.1: Pharmacokinetics (Third bullet) 
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• The table summary and figures will be primarily repeated by anti-BKZ antibody status 
(positive, negative, missing) by treatment group (3 lines per graph, one graph per treatment 
group). The missing group will not be displayed if ≥95% of subjects are categorized in the 
non-missing groups.  
The ADAb status (positive, negative, or missing) will be considered in a cumulative manner 
at each time point:  
− a subject will be counted as positive from the first visit at which the subject achieved a 
positive ADAb sample result to the end of the treatment period (regardless of any 
missing/inconclusive or negative ADAb sample result).  
− If a subject has only negative ADAb samples or only one missing/inconclusive sample 
with negative ADAb samples up to that timepoint, the subject will be classified as 
negative.  
Has been changed to: 
• The table summary and figures will be primarily repeated by anti-BKZ antibody status 
(positive, negative, missing) by treatment group (3 lines per graph, one graph per treatment 
group). The missing group will not be displayed if ≥95% of subjects are categorized in the 
non-missing groups.  
The ADAb status (positive, negative, or missing) will be considered in a cumulative manner 
at each time point:  
− a subject will be counted as positive from the first visit at which the subject achieved a 
positive ADAb sample result to the end of the treatment period (regardless of any 
missing/inconclusive or negative ADAb sample result).  
− If a subject has only negative ADAb samples or only one missing/inconclusive sample 
with negative ADAb samples up to that timepoint, the subject will be classified as 
negative. An exception remains for the Baseline Visit where only one sample would 
be available. If the sample is missing/inconclusive, then the sample will be classified 
as being negative for the cumulative ADAb status. 
 
 
Change #17 
Section 9.1: Pharmacokinetics (last sentence) 
All plasma concentration data will be reported in ug/mL in the tables, figures, and listings. 
Has been changed to: 
All plasma concentration data will be reported in ug/mL in the tables, figures, and listings. 
If more than 10% of the PK concentration results have been excluded from the table 
summaries, the PK excluded results will be listed in a separate listing. 
 
Change #18 
Section 9.2.1: Anti-bimekizumab antibody (line before the description of the ADAb categories) 
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Summaries of cumulative ADAb status and time to treatment-emergent positivity will use all 
available data.  
Has been changed to: 
All other summaries of ADAb status will use all available data (scheduled and unscheduled).  
 
Change #19 
Section 9.2.1: Anti-bimekizumab antibody (ADAb categories) 
− Category 1: Pre ADAb negative – treatment-emergent ADAb negative: Includes 
subjects who are negative at Baseline and antibody negative at all sampling points post 
treatment (including SFU). This group also includes subjects who have 
missing/inconclusive pre-treatment sample (eg either missing/inconclusive or insufficient 
volume) at baseline with all post-baseline samples as ADAb negative.  
(…) 
− Category 6: Inconclusive: Includes subjects who have a positive pre-treatment sample 
and some post-treatment samples are missing, while other post-treatment samples are 
ADAb negative or missing. 
(…) 
− Category 9: Missing: Includes subjects who have a negative or a missing/inconclusive 
pre-treatment sample and some post-treatment samples are missing/inconclusive, while 
other post-treatment samples are ADAb negative. 
 
Has been changed to: 
− Category 1: Pre ADAb negative – treatment-emergent ADAb negative: Includes 
subjects who are negative at Baseline and antibody negative at all sampling points post 
treatment (including SFU), one post-baseline missing/inconclusive sample is allowed 
for subjects with pre-ADAb negative sample. This group also includes subjects who 
have missing/inconclusive pre-treatment sample (eg either missing/inconclusive or 
insufficient volume) at baseline with all post-baseline samples as ADAb negative.  
(…) 
− Category 6: Inconclusive: Includes subjects who have a positive pre-treatment sample 
and some post-treatment samples are missing, while other post-treatment samples are 
ADAb negative or missing. 
(…) 
− Category 9: Missing: Includes subjects who have a negative or a missing/inconclusive 
pre-treatment sample and some post-treatment samples are missing/inconclusive, while 
other post-treatment samples are ADAb negative or missing. 
 
Change #20 
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Added text in Section 9.2.1: Anti-bimekizumab antibody (First Bullet) 
Has been changed to: 
Subjects who rolled over to the OLE study will not have a SFU visit per study protocol. For 
these subjects, the ‘overall ADAb status including SFU’ will then be considered as being 
identical to the ‘overall ADAb status up to Week 16’. 
 
Change #21 
Section 9.2.1: Anti-bimekizumab antibody (Second, third and fourth bullet) 
The above summary table displaying the number and percentage of subjects in each of the ADAb 
status (positive, negative, missing) will be repeated by region. 
• A summary table displaying the number and percentage of subjects in each of the ADAb 
status (positive, negative, missing) by concomitant medications (use of cDMARDs at entry, 
use of methotrexate at entry, use of oral/systemic corticosteroids at entry) will be provided 
(overall summaries only). 
A table displaying the number and percentage of subjects with the first occurrence of ADAb 
positivity during the study (ie, including Baseline visit) will be summarized.  
Has been changed to: 
The above summary table displaying the number and percentage of subjects in each of the ADAb 
status (positive, negative, total of positive and negative, missing) will be repeated by region. 
• A summary table displaying the number and percentage of subjects in each of the ADAb 
status (positive, negative, total of positive and negative, missing) by concomitant 
medications (use of cDMARDs at entry, use of methotrexate at entry, use of oral/systemic 
corticosteroids at entry) will be provided (overall summaries only). 
− A table displaying the number and percentage of subjects with the first occurrence of any 
ADAb positivity during the study (ie, including Baseline visit) will be summarized. 
 
Change #22 
Added text in Section 9.2.1:  Anti-bimekizumab antibody  
Furthermore, all ADAb titer values<100 will be represented as 1 in these plots. 
 
Change #23 
Added following text in Section 9.2.1: Anti-bimekizumab antibody (last paragraph) 
Finally, if more than 10% of the ADAb results have been excluded from the table summaries, the 
ADAb excluded results will be listed in the same listing as the one mentioned in Section 9.1 for 
excluded PK results.  
 
Change #24 
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Section 9.2.2: Neutralizing anti-bimekizumab antibodies (first bullet) 
− ADAb negative: if the subject has all the samples as ADAb negative or only one 
missing/inconclusive sample with all other available samples as negative ADAb. 
Has been changed to: 
− ADAb negative: if the subject has all the samples as ADAb negative or only one 
missing/inconclusive sample with all other available samples as negative ADAb. Note 
that ADAb negative samples are not subject to the neutralizing assay. 
 
Change #25 
Section 9.2.2: Neutralizing anti-bimekizumab antibodies (Third bullet) 
• NAb Missing:  
− >1 relevant NAb samples are missing and other available NAb samples during the period 
of interest are negative, eg, missing or insufficient sample left for NAb testing. 
Has been changed to: 
• NAb Missing:  
− >1 relevant NAb samples are missing/inconclusive and other available NAb samples 
during the period of interest are negative, eg, missing or insufficient sample left for NAb 
testing. 
 
Change #26 
Section 10.2.1: Standard AE summaries (18th bullet) 
• TEAEs by timing of onset relative to ADAb status by SOC, HLT, PT (on subjects treated 
with BKZ). This will include columns for the following: 
− TEAEs starting before the first ADAb positive result (includes ADAb categories 2, 4 and 
5) where TEAEs have occurred before the following events: a) the first positive ADAb 
result for subjects in category 2 and b) the first post-baseline boosted ADAb titer result 
for subjects with titer results and the first post-Baseline positive ADAb result for subjects 
with positive ADAb at Baseline with no other samples with titer available for subjects in 
category 5. 
Has been changed to: 
• TEAEs by timing of onset relative to ADAb status by SOC, HLT, PT (on subjects treated 
with BKZ). This will include columns for the following: 
− TEAEs starting before the first ADAb positive result (includes ADAb categories 2,and 5) 
where TEAEs have occurred before the following events: a) the first positive ADAb 
result for subjects in category 2 and b) the first post-baseline boosted ADAb titer result 
for subjects with titer results and the first post-Baseline positive ADAb result for subjects 
with positive ADAb at Baseline with no other samples with titer available for subjects in 
category 5. 
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Change #27 
Section 10.3: Clinical laboratory evaluations (2nd bullet after Table 10-5) 
• Number and percentage of subjects by CTCAE grade (version 4.03) (when applicable) based 
on minimum/maximum post Baseline value (for blood chemistry and hematology).  
Has been changed to: 
Number and percentage of subjects by CTCAE grade (version 4.03) (when applicable) based on 
minimum/maximum post Baseline value (for blood chemistry and hematology).  Subjects who 
meet the decreased potassium criterion of 3.0-<LLN, which is specified as the decreased 
potassium lab criterion for both CTCAE Grade 1 and Grade 2, will be counted as Grade 2 
 
 
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14 
STATISTICAL ANALYSIS PLAN SIGNATURE PAGE 
This document has been reviewed and approved per the Review and Approval of Clinical 
Documents Standard Operating Procedures. Signatures indicate that the final version of the 
Statistical Analysis Plan (SAP) or amended SAP is released for execution. 
 
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Approval Signatures
Name:
PA0011 SAP AMENDMENT 2.0
Version:
1. 0
Document Number:
CLIN-000180308
Title:
PA0011 Statistical Analysis Plan Amendment 2.0
Approved Date:
09 Nov 2021
Document Approvals
Approval
Verdict: Approved
Name: 
Capacity: Document Author
Date of Signature: 09-Nov-2021 02:19:54 GMT+0000
Approval
Verdict: Approved
Name: 
Capacity: Clinical
Date of Signature: 09-Nov-2021 07:40:46 GMT+0000
Approval
Verdict: Approved
Name: 
Capacity: Clinical
Date of Signature: 09-Nov-2021 14:18:11 GMT+0000
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