Real-World Analysis of Belantamab Mafodotin Care Patterns in Patients With Relapsed and/or Refractory Multiple Myeloma
Conditions: Multiple Myeloma
Sponsor: Duke University

 
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Observational Study Protocol  
Duke IRB#:  Pro00110976 
 
NCT - 05986682 
 
REAL-WORLD ANALYSIS OF BELANTAMAB MAFODOTIN - BLMF CARE PATTERNS IN 
PATIENTS WITH RELAPSED AND/OR REFRACTORY MULTIPLE MYELOMA  
 
September 6, 2023 
 
 
 

 
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REAL-WORLD ANALYSIS OF BELANTAMAB MAFODOTIN - BLMF CARE PATTERNS IN PATIENTS WITH 
RELAPSED AND/OR REFRACTORY MULTIPLE MYELOMA 
 
TABLE OF CONTENTS 
 
BACKGROUND AND RATIONALE ........................................................................... 4 
 
OBJECTIVES ............................................................................................................ 4 
 
Primary Objectives .............................................................................................. 4 
 
Secondary Objectives ......................................................................................... 4 
 
RESEARCH METHODOLOGY ................................................................................. 5 
 
Study Design ...................................................................................................... 5 
 
Data Source / Data Collection ............................................................................ 5 
3.2.1. DCI’s EHR ...................................................................................................... 6 
3.2.2. Sources of Data ............................................................................................. 6 
3.2.3. Data Collection (Structured and Unstructured Data) ..................................... 6 
 
Study Population ................................................................................................. 6 
3.3.1. Inclusion Criteria ............................................................................................ 6 
3.3.2. Exclusion Criteria ........................................................................................... 7 
 
Variables ............................................................................................................. 7 
3.4.1. Patient Characteristics ................................................................................... 7 
 
Feasibility Counts/Sample Size/Power Calculation ............................................ 9 
 
Data Analysis Considerations ............................................................................. 9 
 
Quality Control and Quality Assurance ............................................................. 10 
 
LIMITATIONS .......................................................................................................... 10 
 
STUDY CONDUCT, MANAGEMENT, AND ETHICS .............................................. 11 
 
Legal Basis for Processing Individual Human Data .......................................... 11 
 
PLANS FOR DISSEMINATING AND COMMUNICATING STUDY 
RESULTS ................................................................................................................ 11 
 
REFERENCES ........................................................................................................ 12 
 
 

 
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ABBREVIATIONS 
ADC 
antibody–drug conjugate 
AE 
adverse events 
BCMA 
B-cell maturation antigen 
BLENREP 
Belantamab mafodotin - blmf 
CI 
confidence interval 
DCI 
Duke Cancer Institute 
EMR 
electronic medical record 
HCRU 
Healthcare resource utilization 
ICD 
International Classification of Diseases 
IHD 
Individual Human Data 
IMiD 
immunomodulatory drugs 
IQR 
interquartile range 
IRB 
Institutional review board 
NCCN DT 
National Comprehensive Cancer Network Distress Thermometer 
NLP 
natural language processing 
PI 
proteasome inhibitors 
REDCap 
Research Electronic Data Capture 
RRMM 
refractory multiple myeloma 
SAP 
statistical analysis plan 
SAS 
Statistical Analytical Software 
SD 
standard deviation 
SME 
subject matter expert 

 
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 BACKGROUND AND RATIONALE 
Belantamab mafodotin - blmf (BLENREP) is a first-in-class anti-B-cell maturation antigen (BCMA) 
antibody–drug conjugate (ADC) that recently gained regulatory approval for the treatment of 
relapsed and/or refractory multiple myeloma (RRMM).  As the first BCMA-targeted therapy to 
receive approval for multiple myeloma with an “off-the-shelf” outpatient administration, BLENREP 
addresses a significant unmet need in RRMM that is refractory to immunomodulatory drugs 
(IMiD), proteasome inhibitors (PI), and anti-CD38 mAb therapy, otherwise known as triple-class 
refractory myeloma. However, BLENREP is associated with frequent corneal ocular adverse 
events, which represents a unique toxicity in multiple myeloma therapeutics. Due to the potential 
of ocular adverse events, the administration of BLENREP requires a multidisciplinary approach 
with oncologists and eye care specialists to safely and effectively manage patients on the therapy. 
 
 OBJECTIVES 
This study aims to describe the real-world use of BLENREP and associated patterns of care, 
including dosing and dose modification, and eye care specialist visits, and associated healthcare 
utilization and clinical outcomes in patients with relapsed and/or refractory multiple myeloma 
(RRMM) seen in the Duke Cancer Institute (DCI) clinics.   
 
Primary Objectives 
• 
Describe the demographic and clinical characteristics of RRMM patients who receive 
BLENREP treatment at the DCI clinics. 
 
• 
Describe the treatment characteristics of BLENREP therapy (e.g. dose, length of 
treatment, delays and dose reductions, reasons for discontinuation) in these patients. 
 
• 
Describe the clinical outcomes of RRMM patients who receive BLENREP treatment at the 
DCI clinics, as available. 
 
 
Secondary Objectives 
• 
Describe Ophthalmology visit patterns before and during treatment, investigating the 
specific adverse event of interest (keratopathy) as available. 
 
• 
Explore the magnitude and sources of distress for these patients via the National 
Comprehensive Cancer Network Distress Thermometer (NCCN DT) instrument, as 
already collected in the DCI clinics per routine care. 
 
• 
Describe the health care resource utilization (HCRU) at Duke Health for patients receiving 
BLENREP. 
 
 
 
 
 

 
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 RESEARCH METHODOLOGY  
 
Study Design 
This is a single center retrospective observational study using electronic health record (EHR) data 
from routine cancer care practices at the DCI clinics. The study incorporates both cross-sectional 
and longitudinal components to yield novel insights regarding real-world use of BLENREP to treat 
RRMM and to describe the patient experience thereof.  The study will analyze clinical data from 
adult patients with RRMM who were seen in the DCI outpatient oncology clinics on or after August 
5, 2020. Demographic data, disease and treatment characteristics, data on comorbid conditions, 
and NCCN Distress Thermometer results will be manually abstracted from the medical record for 
each eligible patient using a standardized research electronic data capture (REDCap) case report 
form, to ensure data quality. Study feasibility was assessed in November 2021 via a preliminary 
medical record search. This search identified approximately 6000 patients with a corresponding 
ICD-9 or ICD-10 diagnosis code consistent with multiple myeloma who were seen in some 
capacity at Duke since January 2014.  Approximately 30 of those patients also had a record of 
treatment with BLENREP between August 5, 2020, and Nov. 11, 2021. Note that BLENREP / 
Belantamab mafodotin – blmf received accelerated approval on August 5, 2020, by the Food and 
Drug Administration (FDA) for RRMM, and GSK (Glaxo SmithKline) requested withdrawal from 
the market on November 22, 2022.   
Figure 1. Study Design Schema 
 
 
Data Source / Data Collection 
DCI’s clinical EHR system will be used as the data source for chart abstractions into the REDCap 
case report forms.  
 

 
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3.2.1. DCI’s EHR 
The DCI EHR system, called Maestro Care, utilizes Epic (i.e., Epic Systems Corporation) 
healthcare software.  Epic is a proprietary clinical database containing EHR data including 
medical diagnosis and procedures, prescriptions, laboratory results, provider notes, and practice-
management data with longitudinal electronic patient data.  
A particularly unique aspect of the data available within DCI standard care records is the inclusion 
of patient-reported outcomes (PRO) data. All patients seen in DCI clinics are asked to complete 
the NCCN Distress Thermometer instrument. This validated tool describes patients’ experiences 
of illness, and contributors to their overall wellbeing (or lack thereof)1. The NCCN DT also collects 
information regarding patients’ physical symptoms, emotional or social difficulties, functional 
issues, and spiritual well-being. Our team has successfully used these data in other studies2,3,4, 
which have yielded unexpected and important findings about the relationship between patient-
reported distress and clinical outcomes. 
3.2.2. Sources of Data 
Maestro Care captures a comprehensive collection of clinical and operational information that 
providers reference at the time of an encounter. This includes all details of a patient’s office visit, 
including but not limited to laboratory results, procedures, and diagnoses, as well as provider, 
pathology, radiology notes, detailed records of all biologics administrations and the results from 
the NCCN Distress Thermometer.  Data pertaining to prescription medications includes Generic 
Product Identifier, generic and brand names, date of prescription start, strength, administration 
instructions, and reasons for discontinuation. Maestro Care also contains data pertaining to 
patient demographics (e.g., age, gender, ethnicity, insurance type and state).  
3.2.3. Data Collection (Structured and Unstructured Data) 
The study will utilize carefully developed methods to input manually abstracted chart data into 
explicitly structured data elements within a set of standardized case report forms that we design 
for each unique research project. The structured data elements are then actively managed within 
the REDCap data environment, ensuring data provenance, security, and completeness. 
 
Maestro Care leverages structured data as well as extensive unstructured data to diagnose and 
develop patient care plans. The structured data, such as those described in section 3.2.2 are 
combined with unstructured data that are included in clinicians’ notes and clinical reports. These 
notes may provide additional details relevant to the patient profile and symptoms that may lead 
to treatment differences and patterns. The notes can be used to provide pre-categorized 
information that may be codified into structured variables (such as severity of disease and 
rationale behind treatment changes, etc.). Text fields often include valuable information, regarding 
signs and symptoms, family history, disease-severity scores, medication changes, and physician 
rationale behind prescribing decision. Abstracted physicians’ notes are key to identify patients in 
the RRMM cohort as well as their disease burden.  
 
 
Study Population 
3.3.1. Inclusion Criteria 

 
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To be included in the final study sample, patients must meet the following inclusion criteria 
provided below: 
• 
Age > 18 years of age as of start of treatment with Belantamab mafodotin - blmf 
• 
Patients with a corresponding ICD-9 or ICD-10 diagnosis code consistent with multiple 
myeloma seen at Duke. 
• 
Patients with a record of starting treatment with Belantamab mafodotin - blmf for RRMM 
between August 5, 2020 and November 22, 2022. 
• 
Patients having healthcare encounters at DCI > 1-month post index 
3.3.2. Exclusion Criteria 
• 
Patients who were included in any clinical trial for BLENREP including expanded access 
clinical trials 
• 
Age > 89 years of age as of start of index therapy    
 
 
Variables 
General descriptions of the study variables are provided below. Additional operational details will 
be included in the statistical analysis plan (SAP). 
3.4.1. Patient Characteristics 
The following patient characteristics will be measured as listed in the table below. Demographics 
will be summarized for the most recent measures on or prior to the index date, and all the other 
characteristics (i.e., clinical characteristics) will be abstracted at each clinic visit thereafter, until 
the end of follow-up. The end of follow-up will be defined as the date of the last clinical encounter 
available in the database prior to the IRB cut-off date.  
Category 
Variable 
At Baseline 
At Subsequent 
Clinical 
Encounters 
Demographics 
Age: Defined as of the index year. 
x 
 
Age groups: Patients will be 
assigned to one of the following age 
groups: 18-34, 35-44, 45-54, 55-64, 
65-74, 75+. 
x 
 
Sex: Male, Female, Unknown 
x 
 
Weight 
x 
 
Height 
x 
 
Body mass index 
x 
 

 
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Current Payer type: Whether the 
patient is covered by commercial, 
Medicaid, Medicare, self-insured, or 
was missing insurance payer type. 
x 
 
Race 
x 
 
RRMM diagnosed by DCI (yes/no) 
x 
 
Comorbid 
Conditions 
NCI Comorbidity Index 
x 
 
Clinical 
Characteristics 
of RRMM 
• 
Subtype (e.g., IgA, IgG, light 
chain only, etc.) 
• 
Cytogenetics 
• 
Immunologic Studies 
• 
Molecular testing results 
x 
 
Administered 
systemic 
treatments for 
MM prior to 
index 
• 
Medication Name 
• 
Start/end dates of treatment 
• 
Reason for discontinuation 
or change of treatment 
• 
Line of therapy 
• 
Prior HCST 
x 
x 
Treatment with 
BLENREP 
• 
Start/Re-start and end dates 
of treatment (as applicable) 
• 
Dosing 
• 
Line of therapy 
• 
Reasons for discontinuation 
or delays of therapy 
x 
x 
NCCN Distress 
Thermometer 
• 
DT Score 
• 
Problem List items 
x 
x 
Clinical 
Outcomes 
assessments  
• 
Myeloma markers (differs 
per patient and MM subtype; 
includes M-spike, UPEP, 
serum free light chains, etc.)  
• 
Physician Reported Notes 
• 
Disease response if 
available (using IMWG 
response criteria) 
• 
Lab tests/assessments 
• 
Death, if documented 
 
x 
Ophthalmologic 
Status 
• 
Date of eye exam and 
results, as available. 
• 
Documentation of ocular-
toxicity 
 
x 
HCRU 
• 
Disease-related 
hospitalizations 
• 
Disease-related ED visits 
• 
Disease-related outpatient 
visits 
 
x 

 
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Feasibility Counts/Sample Size/Power Calculation 
In order to determine the feasibility of conducting the study, a query of structured EMR data was 
conducted in November 2021.  Since January 2014, approximately 6000 patients with a 
corresponding ICD-9 or ICD-10 diagnosis code consistent with multiple myeloma were seen in 
some capacity at Duke.  Approximately 30 of those patients also had a record of treatment with 
Belantamab mafodotin - blmf for RRMM between August 5, 2020 and Nov. 11, 2021.  For this 
study, we would exclude patients who were included in any clinical trial, including expanded 
access clinical trials (approximately 2 patients).  Thus, our cohort would include up to 
approximately 30 patients (accounting for additional patients starting on BLENREP between the 
proposal date and the final IRB approval date). 
As the intention of this study is to be descriptive in nature to provide insight into patient 
characteristics, treatment patterns, and dosing, no formal hypothesis/power calculations/sample 
size estimates are required. 
 
Data Analysis Considerations 
Analyses will be undertaken by Duke University statisticians with expertise in patient-centered 
outcomes research. Details of the analyses will be furthered described in the statistical analysis 
plan (SAP) to be created at a later date.  
Primary Objectives:  Describe patient characteristics and treatment patterns for patients treated 
with BLENREP   
Patient demographics and clinical characteristics (including diagnosis, laboratory measurements, 
general symptoms, and other comorbidities) will be summarized using descriptive statistics, 
consisting of the mean (± standard deviation [SD]) and median (with interquartile range [IQR]) 
values for continuous variables and frequency distributions and proportions for categorical 
variables.  
Demographics will be described for the most recent measures on or prior to the index date. 
Clinical outcomes will be described until the end of follow-up. The end of follow-up will be defined 
as the date of the last clinical encounter available in the database prior to the IRB cut-off date. 
Summary statistics such as mean (± SD) and median (with IQR) values for continuous variables 
and frequency distributions and proportions for categorical variables will be calculated.  
Time to clinical outcomes (i.e., time to response, duration of response, OS) will be analyzed using 
Kaplan-Meier analysis and median times to event will be reported (if the medians are achieved). 
95% CIs will be reported in addition to the medians. 
Treatment use and treatment patterns will be summarized using proportions (i.e., proportion of 
patients with select treatment for the control of symptoms). Sequences of treatment will also be 
described.  
Secondary Objective: Describe Ophthalmology visit patterns and events 
To the extent that they are available, events related to Ophthalmology outcomes (i.e., eye exams, 
outpatient visits, treatments for ocular toxicity, and other related HCRU events) will be 
summarized by the mean (± SD) and median (with IQR) number of events per patient per year 
and by the proportion and frequency distribution of patients with any occurrence of the respective 

 
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outcome.  Treatment use and treatment patterns associated with ocular toxicity will be 
summarized using proportions (i.e., proportion of patients with select treatment for the control of 
symptoms). 
Secondary Objective: Explore magnitude and sources of distress for these patients 
The main outcome variable is the occurrence of actionable distress, defined as a NCCN DT score 
of 4 or higher. This outcome is clinically relevant because it is aligned with the medical practice 
guidelines for management of distress in cancer patients. The analysis will describe the proportion 
of clinic visits where actionable distress is reported during treatment with BLENREP, and the 
frequency of actionable distress over time. 
Sources of distress will be assessed using the NCCN DT Problem List by examining the 
proportion of visits where types of problems are reported (e.g., physical or emotional problems). 
The frequency of individual types of problems, and the most commonly-reported problems will be 
examined descriptively.  
Secondary Objective: Describe healthcare resource utilization (HCRU) 
To the extent that they are available, HCRU (i.e., inpatient admissions, treatment-related 
outpatient visits, and emergency department visits) will be summarized by the mean (± SD) and 
median (with IQR) number of events per patient per year and by the proportion and frequency 
distribution of patients with any occurrence of the respective outcome. Likewise, mean (± SD) and 
median (with IQR) length of stay per year will be summarized for inpatient visits.   
 
Quality Control and Quality Assurance 
Duke ensures quality control of the data collection and analysis in several ways.  First, the case 
report form is developed in a rigorous, iterative approach, and reviewed for clear and accurate 
data abstraction.  The case report form (CRF) is then piloted with a few patients in an iterative 
trial and error approach, to ensure it functions as intended, and is able to capture even 
unanticipated scenarios, thus facilitating high-quality data abstraction.  In addition, the study relies 
on initial cohort selection based upon data from the Duke Enterprise Data Unified Content 
Explorer (DEDUCE), a query platform for Duke’s enterprise data warehouse, which ensures high-
quality data cohorts based upon disease and treatment characteristics.  Furthermore, our data 
abstraction tool, REDCap, is designed with data checks throughout to eliminate implausible 
entries (i.e. date ranges, branching logic, integers vs. decimals, etc.).  REDCap also features 
access control logs, which ensure audit trails exist, tracking who and what was entered or 
changed in the participant records, and is thus superior to spreadsheets and other such 
databases.  Finally, data analyses are reviewed by the team to ensure meaningful reports without 
unexplained anomalies potentially created by erroneous data.  
 LIMITATIONS 
The limitations of the study are primarily a function of the descriptive nature of the study objective; 
thus, lacking a control group by which to put the study results in context. However, given the 
nature of disease and treatments under consideration, the study may provide key insights into 
RRMM and belamaf use from a real-world, clinical practice setting.  
The retrospective nature of this study also calls for caution in the interpretation of the study 
findings: 

 
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• 
This study may be affected by potential biases including reporting bias, selection bias, 
measurement error, and non-random missing data.  
• 
Data are from locations/facilities within the DCI network only, so resources used outside 
of the network may be underestimated. 
• 
Assessment of symptoms and treatment characteristics in real-world settings may be 
based on heterogeneous criteria and frequency, and the level of recording may vary 
across healthcare sites and providers.  
• 
Comorbidities may be underestimated as they will be captured using ICD 9/10 diagnosis 
codes and diagnoses recorded in oncology clinical practices. Physicians may not include 
comorbidities that do not require active interventions or workups, and diagnoses made in 
primary care settings may not necessarily be captured. 
• 
The study population includes RRMM patients which is heterogeneous in terms of disease 
severity, symptoms and treatments. 
• 
Assessment of lab and clinical measures will be based on patients with data on the 
relevant tests or records. The results may not be representative of the full RRMM study 
population. 
• 
The study population identified through this data set may not be generalizable to other 
populations in the US. 
• 
The analyses are exploratory and descriptive in nature; no formal hypothesis-testing will 
be performed. 
 STUDY CONDUCT, MANAGEMENT, AND ETHICS 
This study will comply with all applicable laws regarding subject privacy. No direct subject contact 
or primary collection of individual human subject data will occur. Study results will be in tabular 
form and aggregate analyses that omit subject identification. Institutional Review Board (IRB) 
approval will be obtained prior to any data collection. Any publications and reports will not include 
subject identifiers. 
 
Legal Basis for Processing Individual Human Data 
The authors confirm that study data is Individual Human Data (IHD) not owned by GSK, but that 
the proposed use of the IHD aligns with the ‘purpose of use’ outlined in the source contract and/or 
the terms and conditions of use of the data source and will comply with any specified prohibitions 
of use. 
 PLANS FOR DISSEMINATING AND COMMUNICATING STUDY 
RESULTS 
All abstracts, posters or manuscripts for publication must be submitted to GSK for review and 
approval 30 days in advance.  

 
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A final study report will be prepared describing methods, results, and interpretation of results upon 
completion of the study. In addition, the results are intended to be presented at appropriate 
scientific meetings and published in a peer-reviewed journal.  
 
 REFERENCES 
1. Baken DM, Woolley C. Validation of the Distress Thermometer, Impact Thermometer 
and combinations of these in screening for distress. Psycho-oncology. Jun 
2011;20(6):609-614.  
 
2. Troy JD, deCastro C, Pupa MR, Samsa GP, Abernethy AP, LeBlanc TW. Patient-
reported distress in adults with myelodysplastic syndromes (MDS). Poster presentation, 
ASCO PallOnc Meeting, September 2016, San Francisco, CA. 
 
3. Troy JD, deCastro C, Pupa MR, Samsa GP, Abernethy AP, LeBlanc TW. Patient-
reported distress in myelodysplastic syndromes and its association with clinical 
outcomes: A retrospective cohort study. Journal of the National Comprehensive Cancer 
Network: JNCCN. March 2018. 
 
4. Troy JD, Locke SC, Samsa GP, Feliciano J, Richhariya A, LeBlanc TW. Patient-reported 
distress in Hodgkin lymphoma across the survivorship continuum. Supportive Care in 
Cancer.  July 2019. 27(7): 2453-62.