【ダラキューロ配合皮下注】
未治療の全身性 AL アミロイドーシスに関する費用対効果評価[第 1.0 版]【ヤンセンファーマ株式会社】【提出日】2022 年 5 月 20 日

1

Table of Contents
Table of Contents ....................................................................................2
Table of abbreviations ..............................................................................50

Abstract.......................................................................................... 10

1

Nature of drugs and medical devices subject to the study ...................... 14
1.1

Name ....................................................................................... 14

1.2

Insurance Reimbursement Price ................................................... 14

1.3

Mechanism of Therapeutic Effect .................................................. 14

1.4

Target Disease ........................................................................... 15

1.5

Method of Use ........................................................................... 16

1.5.1

Drug Dosing, Administration Route, and Frequency ofAdministration ................................................................................. 16
1.5.2

Co-medications .................................................................... 18

1.5.3

Disease Monitoring Tests ....................................................... 18

1.6

Positioning of the Drug in the Treatment of the Target Disease.......... 19

1.6.1

Position of DCyBorD in treatment flow ..................................... 19

1.7

Major Adverse Events ................................................................. 20

1.8

Results of Evaluation by Health Technology Assessment Bodies in

Other Countries .................................................................................. 21
2

3
2

Setting of analytical conditions for cost-effectiveness analysis ................ 34
2.1

Analysis Populations ................................................................... 34

2.2

Analytical Position and Cost Range ............................................... 35

2.3

Effectiveness Indices .................................................................. 35

2.4

Analysis Period .......................................................................... 35

2.5

Discount rate............................................................................. 36

2.6

Summary of Determination of Analytic Framework .......................... 36

Additional Benefits ........................................................................... 37

3.1

Clinical Questions ....................................................................... 37

3.2

Systematic Review ..................................................................... 38

3.2.1

Literature Searches .............................................................. 38

3.2.2

Study Selection .................................................................... 48

3.2.3

Quality Assessment .............................................................. 50

3.2.4

Search Results ..................................................................... 50

3.2.5

Clinical studies identified in the systematic literature review ....... 52

3.2.6

Summary of Additional Benefit ............................................... 53

3.2.6.1 ANDOMEDA clinical trial ........................................................ 53
3.2.7

ANDROMEDA Study Details .................................................... 58

3.3

Clinical Questions (Different controlled or single-arm studies)........... 74

3.4

Systematic Review (Different controlled or single-arm studies) ......... 74

3.5

Reanalysis of Existing Data .......................................................... 75

3.6

Details of Meta-Analysis .............................................................. 78

3.7

Results of Indirect Comparison and Network Meta-Analysis .............. 78

3.8

Evaluation of Additional Benefit .................................................... 78

3.8.1

Additional Benefit Assessment for DCyBorD vs CyBorD Based on

ANDROMEDA Trial ............................................................................ 78
4

Details of Analytical Methods ............................................................. 83
4.1

4.1.1

Calculation of cost-effectiveness ............................................. 83

4.1.2

Model assumptions ............................................................... 91

4.2

3

Analytical Procedures.................................................................. 83

Parameters Used in the Analysis................................................... 99

4.2.1

Efficacy Parameters ............................................................ 121

4.2.2

Safety Parameters .............................................................. 154

4.2.3

Details of QOL values .......................................................... 155

4.2.4

Details of cost parameters ................................................... 170

5Analytical Results ........................................................................... 205
5.1

Results of Basic Analysis (Analysis using an analytical framework

determined by the specialized organization for cost-effectivenessassessments) ................................................................................... 205
5.1.1

Incremental Cost, Incremental Effectiveness, and Incremental Cost

Effectiveness Ratio for Main Analysis ................................................. 205
5.1.2

Sensitivity analysis ............................................................. 207

5.1.3

Validity of the analysis ........................................................ 257

5.1.4

Interpretation of Analysis Results ......................................... 260

5.1.5

Weight of price adjustment ratio ........................................... 260

5.1.6

Higher prices ..................................................................... 261

5.2

Analysis Including Public Care Costs and Productivity Losses .......... 261

5.3

Other Analyses ........................................................................ 261

6

Data for reanalysis ......................................................................... 261

7Implementation system .................................................................. 262

8References .................................................................................... 263

4

ECOG

Eastern Cooperative Oncology GroupeGFR

Estimated glomerular filtration rate

EQ-5D

EuroQol-5 Dimension questionnaire

EQ-5D-5L

EuroQol-5 Dimension-5 Level questionnaire

EORTC QLQ-

European Organization for Research and Treatment of

C30

Cancer Quality of Life Questionnaire Core 30-item

ER

Emergency room

FDT

Fixed daratumumab treatment

FLC

Free light-chain

FLCr

Free light-chain ratio

G

Grams

GHS

Global health status

HAS

French National Authority for Health

HBV

Hepatitis B Virus

HCRU

Healthcare resource use

Hr

Hour

HRQoL

Health-related quality of life

ICER

Incremental cost-effectiveness ratio

iFLC

Involved free light-chains

Ig

Immunoglobulin

IHC

Immunohistochemistry

IMiD

Immunomodulatory drug

IPD

Individual patient data

IQR

Interquartile range

IQWiG

Institute for Quality and Efficiency in Health Care

IRR

Infusion related reaction

6

ITT

Intent-to-treat

IV

Intravenous

Kg

Kilogram

KM

Kaplan-Meier

L

liter

LY

Life-year

M

Meter

Md

Melphalan and dexamethasone

MDV

Medical Data Vision

Mg

Milligrams

MHLW

Ministry of Health, Labor and Welfaremin

MinutemL

Milliliters

MM

Multiple myeloma

MOD

Major organ deterioration

Mp

Melphalan, prednisone

N

NumberN/A

Not applicable

NCCN

National Comprehensive Cancer Network

Ng

Nanograms

NHS

National Health Service

NICE

National Institute for Health and Care ExcellenceNR

Not reported or no response

NT-proBNP

N-terminal prohormone B-type natriuretic peptide

NYHA

New York Heart Association

7

OS

Overall survival

PBAC

Pharmaceutical Benefits Advisory Committee

PFS

Progression-free survival

PI

Package insert

PO

Oral

PR

Partial response

PSA

Probabilistic sensitivity analysis

Py

Person year

QALY

Quality-adjusted life year

RBd

REVLIMID® (lenalidomide), bortezomib, dexamethasone

RCT

Randomized controlled trial

Rd

REVLIMID® (lenalidomide), dexamethasone

RDI

Relative dose intensity

REML

Restricted maximum likelihood

rHuPH20

Vorhyaluronidase Alfa (Genetical Recombination)

SC

SubcutaneousSD

Standard deviation

SE

Standard error

SF-12

Short-form 12

SF-36

Short-form 36

SGStandard gamble

SLR

Systematic literature review

SMC

Scottish Medicines Consortium

SMR

Service Médical Rendu

Tab

Tablet8

TCd

Thalidomide, cyclophosphamide, dexamethasone

TEAE

Treatment-emergent adverse event

TNT

Time to next treatment

TSD

Technical Support Document

Tx

Treatment

UK

United Kingdom

USA

United States of America

VAS

Visual analog scale

VAT

Value-added tax

VGPR

Very good partial response90Abstract

The summary of analytical results for the target drug is summarized anddescribed in Table 0.1 below.

Table 0.1. Summary of analytical results
Name of technology
subject to analysis[Section 1.1]

DARZQURO® SC (daratumumab andvorhyaluronidase alfa [genetical recombination][rHuPH20]) in combination with bortezomib,
cyclophosphamide, and dexamethasone (DCyBorD)
CADTH (Canada): Recommended with conditions
HAS (France): Recommended

Evaluation results at health

IQWiG (Germany): Minor additional benefit

technology evaluation

NICE (UK): Not recommended (draft

institutions in otherrecommendation)

countries [Section 1.8]

SMC (Scotland): Under evaluation
PBAC (Australia): Not recommended; two options of
re-submission pathway are provided by PBAC

Target disease/population

Newly diagnosed Amyloid light-chain (AL)

[Section 2.1]amyloidosis

Comparative technicalCyclophosphamide, bortezomib, andnamedexamethasone (CyBorD)

Analysis position and scopeof costs [Section 2.2]

Public healthcare payer

Effectiveness indicators toLife years (LYs) and quality-adjusted life years

be used [Section 2.3]

(QALYs)Analysis period [Section
2.4]
Discount rate [Section
2.5]
10

35 years (i.e., lifetime)

2% (costs), 2% (effects)

P: Newly diagnosed AL amyloidosis patients
Systematic Review Clinical
Questions [Section 3]

I: DCyBorD
C: CyBorD
O: Efficacy (hematologic response, MOD-PFS, OS),safety and HRQoL
One RCT, the ANDROMEDA trial, was identified

Summary of Results of
Systematic Review[Section 3]

where eighteen records, all pertaining to
ANDROMEDA, were identified by systematic review
via database and registry searches in addition tohand-searching of pre-specified conference abstract
lists

Results of Indirect
Comparison [Section 3]

Not applicable■ Presence of additional benefit □ "No additional
usefulness" or "Cannot be determined"
Evidence from the ANDROMEDA study
demonstrates the presence of additional benefit for
DCyBorD compared to CyBorD with respect tohematologic response, MOD-PFS, organ response,and HRQoL.

Presence or absence ofThe rate of hematologic CR was significantly
higher in the DCyBorD arm vs the CyBorD

additional usefulnessarm (53.3% vs. 18.1%; OR: 5.1 (95% CI:[Section 3]

3.2 to 8.2); p<0.001) in the primary analysis(median follow-up 11.4 months). At themedian follow-up of 25.8 months, the CR
rate continued to be higher (59.5% vs
19.2%; OR [95% CI], 6.03 [3.80–9.58];
p<0.0001).


MOD-PFS was significantly longer in the
DCyBorD group than the CyBorD group (HR0.58, 95% CI 0.36 to 0.93, p=0.02) in the11primary analysis.
At 6 months, cardiac response and renal
response favored DCyBorD compared with
CyBorD among evaluable subjects. 41.5% of
DCyBorD (95% CI 32.5 to 51.0) and 22.2%
of CyBorD (95% CI 15.1 to 30.8) subjects
achieve cardiac response; 53.0% (95% CI
43.5 to 62.3) of DCyBorD and 23.9% (95%
CI 16.4 to 32.8) of CyBorD subjects had arenal response. Greater cardiac responses(53% vs. 24%) and renal response rate
(58% vs. 26%) were achieved at 18 months.

Median time to improvement was shorter andmedian time to worsening was longer in the
DCyBorD group than in the CyBorD group for
EORTC QLQ-C30 GHS and fatigue scales andEQ-5D-5L VAS. The median time toimprovement for global health status asmeasured by the EORTC QLQ-C30 was 7.83
months in the DCyBorD arm and 16.79
months in the CyBorD arm (hazard ratio =1.53, 95% CI, 1.10 to 2.13). EORTC QLQ-30
global health status showed continued
improvement in the DCyBorD arm after 6
months.

Overview of Cost-

A CUA model was developed consisting of a decision

Effectiveness Analysis

tree paired with a Markov model where patients

Methods [Sections 4.1.1,

transition through independent health states and

4.2, etc.]

OS is stratified by hematologic response.
Compared with CyBorD, DCyBorD was more

Summary of Results[Section 5]

effective (incremental 1.85 QALYs) and was
associated with higher costs (￥ 10,414,642) over a
35-year horizon, resulting in an ICER of￥ 5,626,171 per QALY gained.

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ICER threshold: □ 通常の品目 X 配慮が必要な品目(designated intractable disease)□

Cost reduction or dominantX≤ 7.5 million yen

Interval considered to have □More than 7.5 million yen and ≤ 11.25

the highest probability of

million yen

belonging to ICER□

More than 11.25 million yen and ≤ 15

million yen□

Over 15 million yen□

Equivalent (or inferior) efficacy and highcost
Abbreviations: AL = amyloid light chain; CUA = cost-utility analysis; CyBorD =cyclophosphamide, bortezomib, dexamethasone; DCyBorD = daratumumab,
cyclophosphamide, bortezomib, dexamethasone; ICER = incremental cost-effectivenessratio; Lys = life years; OS = overall survival; QALY = quality adjusted life year; RCT =randomized controlled trial; SC = subcutaneous; SLR = systematic literature review.

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1

Nature of drugs and medical devices subject to the study

1.1 Name•

製品名
ダラキューロ配合皮下注•

一般名
ダラツムマブ（遺伝子組換え）1800mg、ボルヒアルロニダーゼ アルファ（遺伝子組換え）
30000 単位（1 バイアル 15mL 中）

Regimen for the evaluation: DARZQURO® (daratumumab and vorhyaluronidasealfa [rHuPH20]) in combination with cyclophosphamide, bortezomib, anddexamethasone. (DCyBorD)

1.2 Insurance Reimbursement Price
保険償還価格： 15mL 1 バイアル 445,064 円 (2022 年 5 月 20 日時点)
算定方式： 類似薬効比較方式(I)
算定上の最類似技術: ダラザレックス点滴静注 400mg
有用性系加算: 有用性加算 II（A=5%）
2022 年 4 月薬価改定時の加算: 希少疾病の効能追加等に係る加算（A=5%）

1.3 Mechanism of Therapeutic Effect
Daratumumab is a CD38-targeted human IgG1ĸ monoclonal antibody thatfunctions as an immunotherapy directed toward CD38, an antigen that is highly
and uniformly expressed on the surface of multiple myeloma (MM) cells andalso on plasma cell clones responsible for amyloid light-chain (AL) amyloidosis(1). The specific mechanisms of action of daratumumab include both immunemediated effects (ie, complement-dependent cytotoxicity, antibody-dependentcell-mediated cytotoxicity, antibody dependent cell-mediated toxicity, antibody
dependent cellular phagocytosis, and direct cellular apoptosis) andimmunomodulatory effects (1-3). Vorhyaluronidase alfa (rHuPH20) reduces the14viscosity of the extracellular matrix by depolymerizing hyaluronian, acomponent of the extracellular matrix in the subcutaneous space. Thisfacilitates the diffusion and absorption of therapeutic drugs.

1.4 Target Disease
Indications covered by public insuranceMultiple myeloma

Systemic AL Amyloidosis (Target disease of this analysis)

Systemic AL amyloidosis is a subtype of “systemic amyloidosis (Notification No.
28)” which has been designated as a designated intractable disease in Japan(4). AL amyloidosis is a rare, underdiagnosed disease characterized by the
extracellular accumulation of insoluble amyloid fibril deposits on various organs
and tissues (5, 6). Over time, these deposits disrupt tissue structure and cause
organ dysfunction. AL amyloidosis is the most common and severe form ofamyloidosis (7) and is a distinctly different plasma cell disorder from multiple
myeloma (MM) (8). In MM, abnormal plasma cells proliferate and inhibit the
production of normal blood cells. In AL amyloidosis, clonal plasma cells produce
immunoglobulin (Ig) light chains that misfold and deposit systemically as
amyloid in any organ outside the central nervous system (9). The deposition ofthese fibrils can affect multiple organs, most commonly the heart (50%-75%)
and kidneys (70%), resulting in a variety of associated complications including
malabsorption, nephrotic syndrome, and heart failure (7). Presenting symptomsof this disease, such as asthenia and dyspnea, generally overlap with those ofother diseases; as a result, diagnosis is often delayed by several months oreven years in some cases (10-13). Patients typically require at least threephysician visits before their diagnosis and this delay is often challenging forpatients, especially for those experiencing unpredictable symptoms (10, 13).
Because of these delays, many patients are diagnosed after their disease has
progressed to more advanced stages and organ damage has already occurred(14).
Studies pertaining to the incidence of systemic AL amyloidosis are sparse; assuch, the incidence of AL amyloidosis both globally and in Japan remains
unclear. United States (US)-based estimates range from 10 to 12 cases per
15

million per year, while studies based out of Argentina and Sweden reportincidences of 6.1 and 3.0 cases per million person-years, respectively (15-17).
In Japan, a 2019 study reported the estimated incidence of AL amyloidosis as
4.2 per million person-years (18). According to a recent Japanese study of 741
patients with AL amyloidosis, the median age at diagnosis was 65 years (range:
31-93) and men were more afflicted by the disease than women (59% male;
41% female) (19).
Number of people expected to use the drug for the disease to beanalyzed
Based on the annual incidence of systemic AL amyloidosis (4.2 per 1 million) inJapan (18), it is estimated to have 500 adults with newly diagnosed AL
Amyloidosis per year (20). Treatment for these patients is selected on the basisof individual patient risk status. It is estimated thatof newly diagnosed AL

Amyloisis paitents may receive DCyBord based on a market research conductedby Janssen in 2021 (21). As the result, it is estimated that

adult patients

will receive DCyBorD per year. Note that the market research result is alignedwith patient risk profile in the ANDROMEDA trial (eligible portion of patient
ranges from 60-80% of total based on an epidemiology study) (18, 22, 23).

1.5 Method of Use

1.5.1 Drug Dosing, Administration Route, and Frequency ofAdministration
DCyBorD consists of four individual drugs: daratumumab, cyclophosphamide,bortezomib, and dexamethasone. The route and frequency of administration,dose, and duration of treatment for DCyBorD are presented in Table 1.1.

16

* The daratumumab SC formulation uses a higher concentration of daratumumab comparedto the IV formulation and reduces the infusion volume to 15 mL, which reduces the risk thatpatients with cardiac or renal comorbidities will experience signs or symptoms of volume
overload (24). Daratumumab SC formulation is approved to treat AL Amyloidosis patients inJapan.
Abbreviations: DCyBorD = daratumumab, cyclophosphamide, bortezomib, anddexamethasone; m = meter; mg = milligrams; PO = oral; rHuPH20 = vorhyaluronidase alfa;
SC = subcutaneous.
Source: DARZQURO® package insert (25).

1.5.2 Co-medications
According to the DARZQURO® package insert (PI), co-medications should be
used to reduce the infusion reaction caused by administration of this drug (25).
Corticosteroids, antipyretic analgesics and antihistamines should be given one
to three hours before the start of administration of this drug. In addition, inorder to reduce the delayed infusion reaction, corticosteroids, etc. should be
administered after administration of this drug as necessary (25).
1.5.3

Disease Monitoring Tests

According to the DARZQURO® PI (25), important basic precautions must be
taken. Since myelosuppression may occur, blood and other tests should be
performed regularly before and during administration of this drug. Additionally,
hepatitis due to reactivation of hepatitis B virus (HBV) may occur due toadministration of this drug. Therefore, hepatitis virus infection should be tested
for prior to drug administration and appropriate measures should be taken
before administration of this drug. Other precautions may be required forpatients with specific complications or a history of disease, such as tumor lysis
syndrome, pulmonary disease, bronchial asthma, or patients who are HBVcarriers (25). If abnormalities related to tumor lysis syndrome are observed,
patients should be treated (administration of physiological saline, therapeutic
agents for hyperurinary acidemia, dialysis, etc.) until symptoms are resolved. If
abnormalities related to interstitial lung disease are observed, administration ofthis drug should be discontinued, and chest CT, serum markers, etc. should be
examined as necessary.
18

1.6 Positioning of the Drug in the Treatment of the Target Disease
Treatment for systemic AL amyloidosis focuses on destruction of the underlying
plasma cell clone, thereby suppressing amyloidogenic Ig light-chain formationand preserving organ function (5, 26). Before DARZQURO®, no therapies wereapproved in Japan.
Due to lack of approved pharmacologic treatment regimens, CyBorD and othertreatments have been used but result in suboptimal patient outcome; mostpatients fail to achieve hematologic complete response (CR) during first-line
treatment (27, 28) and low rates of cardiac and renal response are observed(27, 29-33). As most treatments for systemic AL amyloidosis are associatedwith poor efficacy and/or unacceptably high safety risks, a strong need exists
for an effective and approved first-line therapy that can rapidly induce highrates of CR and organ response, prolong survival, and improve health-related
quality of life (HRQoL).
1.6.1 Position of DCyBorD in treatment flow
Recently updated local and clinical guidelines, including National Comprehensive
Cancer Network (NCCN) guidelines and guidelines from the Japanese Society of
Myeloma (JSM), now recommend that daratumumab combination therapy beused as a first-line treatment for this disease (Table 1.2) (34-36). In NCCN
guidelines version 1.2022, DCyBorD is the only preferred regimen (Category 1)
for newly diagnosed AL Amyloidosis as the primary therapy for hematopoietic
cell transplant eligible candidates and non-eligible candidates. Other
recommended regimens including CyBorD and other off label regimens are also
included in Table 1.2. According to JSM guidelines, DCyBorD therapy forpatients with newly diagnosed AL amyloidosis is recommended regardless ofwhether ASCT is indicated or not (level A recommendation / evidence level Ib)(36).

Table 1.2. NCCN Guideline for Systemic Light Chain Amyloidosis:
Therapy for newly diagnosed disease19

Primary therapy for hematopoietic cell transplant eligible candidates
and non-eligible candidates
Preferred Regimen

Daratumumab/cyclophosphamide/bortezomib/dexamethasone(category 1)

Other Recommended Regimens

Bortezomib± dexamethasoneBortezomib/cyclophosphamide/dexamethasoneBortezomib/lenalidomide/dexamethasoneBortezomib/melphalan/dexamethasone

Melphalan/dexamethasone

Abbreviations: NCCN = National Comprehensive Cancer Network.
Note: If not a candidate for hematopoietic cell transplant at initial diagnosis,
reassess after two cycles of systemic therapy; All recommendations are
category 2A unless otherwise indicated. Note: the order of regimens in eachcategory is alphabetical and does not indicate preference.
Source: Adapted from NCCN Guidelines Version 1.2022 (Systemic Light Chain
Amyloidosis) (35)

1.7 Major Adverse Events
The following major adverse events may occur as described in the DARZQURO®
PI (25):
Infusion Reactions
Infusion reactions (24.9%) such as anaphylaxis, nasal congestion, cough, chills,
bronchospasm, hypoxia, and dyspnea may occur. If any abnormalities areobserved, administration of this drug should be interrupted or discontinued,
appropriate measures should be taken, and the patient's condition should be
carefully monitored until the symptoms resolve. If a severe infusion reaction isobserved, appropriate measures, including discontinuation of administration ofthis drug should be taken.
20

Assessment Status: Draft
The draft outcome is “notrecommended” due to theuncertainty of costeffectiveness. However, theclinical experts considered
DCyBorD to be a stepchange in managing newly
diagnosed AL amyloidosis
as the treatment extends
life for at least an
additional 3 months,
compared to current NHS
treatment. The second
committee meeting isplanned.

SMC



Recommendation: Other(in review, result notavailable)

Assessment Status: Other(In review) (38)FranceHASRecommendation:
recommended

Actual benefit (SMR):

per1800 mgvial.

ImportantImprovement in actual
benefit (ASMR): IV (minor)
vs CyBorD

Germany

IQWiG

Minor additional benefit vs
CyBorDper 1,800
mg vial*222Setting of analytical conditions for cost-effectiveness analysis

2.1 Analysis Populations
The analysis population includes newly diagnosed AL Amyloidosis patients
based on the analytic framework agreed upon by an expert committee meetingon 24th December, 2021).
The model uses a cohort-based approach to model patients as they transition
through health states. The model assumed a hypothetical cohort of 1,000
patients, with baseline characteristics that aligned with newly diagnosed AL
amyloidosis adult patient characteristics in Japan.
The starting age and proportion of male subjects were set based on the
ANDROMEDA global ITT population which are closely aligned with values for theJapanese population as reported by Shimazaki et al., (2018) (19). For patientbody weight and body surface area (BSA), model values were based on the
Asian subjects included in the ANDROMEDA study (n=60) to more accuratelyreflect Japanese patient characteristics. In addition, a subgroup analysis was
conducted using efficacy outcome of the Asian subjects from the ANDROMEDA
trial (N=60; DCyBorD n=29; CyBorD n=31). Details pertaining to this subgroup
analysis can be found in Section 5.1.2.2.1.
The ANDROMEDA trial included adult (≥18 years) patients newly diagnosed
with AL amyloidosis who had ≥1 organ involved (24). Patients were excluded ifthey had received prior therapy for AL amyloidosis, if they had a previous orcurrent diagnosis of symptomatic MM, or if they presented with evidence ofsignificant cardiovascular conditions (New York Heart Association [NYHA] stage
IIIB and IV). Furthermore, patients were excluded if they were planning toreceive ASCT during the first six cycles of treatment (24). Base case patient
demographics used in the model are presented in Table 4.3.

Comparative Controls
As agreed upon by the expert committee (24th December, 2021), CyBorD wasselected as the most appropriate comparator based on the rationale that34

CyBorD is widely used for systemic AL amyloidosis in Japan and isrecommended by international clinical guidelines (35).

2.2 Analytical Position and Cost Range
The analysis was conducted from the perspective of the Japanese publichealthcare system and included direct medical costs.
Cost parameters included in the model were first-line drug therapy costs, firstline drug administration costs, first-line co-medication costs, disease monitoring
costs, AE management costs, second-line drug therapy costs, end-stage organ
failure management costs, other health state-specific healthcare resource use
costs, and end of life costs.
Drug costs were sourced from the Ministry of Health, Labor, and Welfare(MHLW) and were relevant as of May 2022. Medical fees were sourced from thecurrent Japan medical fee points schedule as of May 2022 and were notinflated. Costs sourced from published literature were inflated to 2022 values
using the Japanese Consumer Price Index for medical care (42). Where
uncertainty existed, both sensitivity and scenario analyses were included toassess the impact of parameter uncertainty and using alternative parameters(see Section 5.1.2).

2.3

Effectiveness Indices

Effectiveness outcomes in the analysis are life-years (LYs) and quality-adjusted
life years (QALYs).

2.4

Analysis Period

A lifetime horizon was selected for the model analysis period (per C2H
guidelines) (43) since AL amyloidosis treatments have an impact on costs andoutcomes over a patient’s lifetime. Given the mean starting cohort age of ~63
years in the population of interest, the model predicted that >99% of patientsin both treatment arms would die and the cohort population would be ~100
years old by 35 years. Thus, a 35-year time horizon would represent a lifetime
35



Inception to 7th February, 2022

Clinicaltrials.gov


Inception to 24th January, 2022

Conference abstract repositories

1st January, 2020 to 31st December, 2021

Abbreviations: CyBorD = cyclophosphamide, bortezomib, dexamethasone; DCyBorD =daratumumab, cyclophosphamide, bortezomib, dexamethasone; HRQoL = health-related
quality of life; MOD-PFS: major organ deterioration progression-free survival; OS = overall
survival.

3.2

Systematic Review

3.2.1

Literature Searches

The following databases and registries were searched:oOvid MedlineoOvid Medline Epub ahead of print, in-process, and other nonindexed citations and dailyoOvid EmbaseoOvid EBM Reviews – Cochrane Central Register of Controlled Trials– CENTRALo

EBM Reviews – Cochrane Database of Systematic ReviewsoIchushi Weboclinicaltrials.gov

Hand-searching of conference abstracts for pre-specified conference
proceedings was also performed. Please refer to Section 3.2.1.4 for a listof conferences for which hand-searching of abstracts was performed.

38

3.2.1.1 Search Strategy for Ovid and Cochrane Databases
The search strategy for Ovid and Cochrane databases was developed by anexperienced information specialist and was peer-reviewed by anotherinformation specialist using the PRESS Checklist (44) prior to execution. Using
the Ovid platform, databases searched included Embase, Medline (Epub Aheadof Print, In-Process & Other Non-Indexed Citations, Ovid Medline® Daily andOvid Medline®), and Cochrane Controlled Register of Trials (CENTRAL). The
search strategies included a combination of controlled vocabulary (eg,“Amyloidosis”) and keywords (eg, “light chain, amyloid”). Vocabulary andsyntax were adjusted across databases. In the search strategy, language wasrestricted to English and Japanese. Studies published earlier than 2005 were
excluded based on the publication date (August 2005) of the consensus opinion
for organ involvement and response by the 10th International Symposium in
Amyloid and Amyloidosis, which was when uniform criteria to define organ
involvement and response were developed (45). The search strategy for theOvid and Cochrane searches is presented below in Table 3.2.
Table 3.2. Search strategy for Ovid and Cochrane databases
Search strategy for: (1) Ovid Medline and Epub ahead of print, inprocess, in-data-review and other non-indexed citations and daily,(2) Ovid Embase, (3) EBM Reviews – Cochrane Central Register ofControlled Trials, (4) EBM Reviews – Cochrane Database of
Systematic Reviews.
Date of search: January 19, 2022
Resulting number of publications: 117#

Searches

Results1

exp Amyloidosis/ or Plaque, Amyloid/ or (amyloido$ or beta-

189360amyloido$ or betaamyloido$ or paraamyloido$ or "paraamyloido$" or beta fibrillos$ or betafibrillos$ or(amyloid$ adj3 (AL or light-chain or primary or systemic or
senile or abeta or fibril? or tumo?r Or deposit? or plaque?))or (amyloid$ adj2 (neuropathy or neuropathi$ or39polyneuropathy or polyneuropathi$ or polyneuritic$ or polyneuropathy or poly-neuropathi$ or poly-neuritic$)) or
cerebral amyloid? angiopath$ or (abeta adj4 amyloido$) or
famil$ mediterranean fever? or ((HCHWA or FMF or MWS or
UDA) and amyloido$) or ((muckle wells or Wohlwill Andrade)adj2 (syndrome$ or disease?)) or (neuritic plaque? or senile
plaque?)).ti,ab,kw,kf. [Amyloidosis Terms]
2(daratumumab$ or darzalex$ or dalinvi$ or jnj54767414 or6811

jnj-54767414 or 945721-28-8 or 4Z63YK6E0E or ((CD38 or
CD-38) adj2 (monoclonal antibod$ or mab or moab orhumax)) or D-VCd).ti,ab,kw,kf,rn. [Daratumumab Terms]
3

1 and 2539

4

(randomized controlled trial or controlled clinical trial).pt. or

14314646(randomized or placebo or randomly or trial or groups).ab.
or drug therapy.fs. [RCTs – MEDLINE sensitive Filter –Cochrane HSSS, 2019]5

exp Randomized Controlled Trials as Topic/ or Clinical Trial,

2280495

Phase II/ or Clinical Trial, Phase III/ or (equivalence trial or
pragmatic clinical trial).pt. or (randomised or
randomi#ation? or RCT or placebo$ or ((singl$ or doubl$ ortrebl$ or tripl$) adj (mask$ or blind$ or dumm$)) or ((study
or trial or CT) adj3 (phase 2 or phase 2a or phase 2b orphase 2c or phase Ii or phase IIa or phase IIb or phase IIcor phase 3 or phase 3a or phase 3b or phase 3c or phase IIIor phase IIIa or phase IIIb or phase IIIc or "phase? 2/3" or"phase? II/III")) or open label$).tw,kf. [PHASE 2-3, OPENLABEL - ADDITIONAL TERMS TO SUPPLEMENT RCTs FILTER]
6

4 or 5 [RCTs only]

14636281

7

3 and 6387

8

exp Animals/ not Humans/

17080928

9

7 not 8 [ANIMAL-ONLY REMOVED]

315

40

10

(address or autobiography or bibliography or biography or

4595454

comment or dictionary or directory or editorial or"expression of concern" or festschrift or historical article orinteractive tutorial or lecture or legal case or legislation ornews or newspaper article or patient education handout or
personal narrative or portrait or video-audio media or
webcast or (letter not (letter and randomized controlled
trial))).pt.
11

9 not 10 [OPINION PIECES REMOVED]

280

12

exp Child/ not (exp Adult/ and exp Child/)

340308613

exp Infant/ not (exp Adult/ and exp Infant/)

1729334

14

11 not (12 or 13) [CHILD AND INFANT - ONLY REMOVED]

280

15

14 use ppez [MEDLINE records]

55

16

exp amyloidosis/ or plaque, amyloid/ or (amyloido$ or beta-

189360amyloido$ or betaamyloido$ or paraamyloido$ or "paraamyloido$" or beta fibrillos$ or betafibrillos$ or(amyloid$ adj3 (AL or light-chain or primary or systemic or
senile or abeta or fibril? or tumo?r Or deposit? or plaque?))or (amyloid$ adj2 (neuropathy or neuropathi$ orpolyneuropathy or polyneuropathi$ or polyneuritic$ or polyneuropathy or poly-neuropathi$ or poly-neuritic$)) or
cerebral amyloid? angiopath$ or (abeta adj4 amyloido$) or
famil$ mediterranean fever? or ((HCHWA or FMF or MWS or
UDA) and amyloido$) or ((muckle wells or Wohlwill Andrade)adj2 (syndrome$ or disease?)) or (neuritic plaque? or senile
plaque?)).ti,ab,kw,kf. [Amyloidosis Terms]
17

daratumumab/ or (daratumumab$ or darzalex$ ordalinvi$ or jnj54767414 or jnj-54767414 or 945721-28-8 or
4Z63YK6E0E or ((CD38 or CD-38) adj2 (monoclonal
antibod$ or mab or moab or humax)) or D-VCd).ti,ab,kw,rn.
[Daratumumab Terms]

41

6807

18

16 and 17539

19

Randomized controlled trial/ or Controlled clinical study/ or10645734

randomization/ or intermethod comparison/ or double blind
procedure/ or human experiment/ or (compare or comparedor comparison or trial).ti. or ((evaluated or evaluate or
evaluating or assessed or assess) and (compare orcompared or comparing or comparison)).ab. or (random$ orplacebo or (open adj label) or ((double or single or doubly or
singly) adj (blind or blinded or blindly)) or parallel group$1or (crossover or cross over) or ((assign$ or match or
matched or allocation) adj5 (alternate or group$1 orintervention$1 or patient$1 or subject$1 or participant$1))or (assigned or allocated) or (controlled adj7 (study or
design or trial)) or (volunteer or volunteers)).ti,ab.
20(Cross-sectional study/ not (randomized controlled trial/ or

5432169

controlled clinical study/ or controlled study/ or randomi?edcontrolled.ti,ab. or control group$1.ti,ab.)) or ((((case adj
control$) and random$) not randomi?ed controlled) or(nonrandom$ not random$) or "Random field$" or (random
cluster adj3 sampl$)).ti,ab. or (Systematic review not (trial
or study)).ti. or ((review.ab. and review.pt.) not trial.ti.) or("we searched".ab. and (review.ti. or review.pt.)) or("update review" or (databases adj4 searched)).ab. or ((rator rats or mouse or mice or swine or porcine or murine or
sheep or lambs or pigs or piglets or rabbit or rabbits or cat
or cats or dog or dogs or cattle or bovine or monkey ormonkeys or trout or marmoset$1).ti. and animal
experiment/) or (Animal experiment/ not (humanexperiment/ or human/))21

19 not 20 [RCTs – Embase sensitive Filter – Cochrane HSSS,

97278762019]
22

phase 2 clinical trial/ or phase 3 clinical trial/ or (equivalencetrial or pragmatic clinical trial).pt. or (randomised or

422058379

randomi#ation? or RCT or placebo* or ((singl* or doubl* or
trebl* or tripl*) adj (mask* or blind* or dumm*)) or ((study
or trial or CT) adj3 (phase 2 or phase 2a or phase 2b orphase 2c or phase Ii or phase IIa or phase IIb or phase IIcor phase 3 or phase 3a or phase 3b or phase 3c or phase IIIor phase IIIa or phase IIIb or phase IIIc or "phase? 2/3" or"phase? II/III")) or open label*).tw,kw. [PHASE 2-3, OPENLABEL - ADDITIONAL TERMS TO SUPPLEMENT RCTs FILTER]
23

21 or 22996491324

18 and 23

158

25(exp animal/ or exp animal experimentation/ or exp animal

11774963

model/ or exp animal experiment/ or nonhuman/ or exp
vertebrate/) not (exp human/ or exp humanexperimentation/ or exp human experiment/) [ANIMALONLY REMOVED]
26

24 not 25 [ANIMAL-ONLY REMOVED]

156

27

(comment or editorial or news or newspaper article or (letter

4159298

not (letter and randomized controlled trial))).pt. [OPINIONPIECES REMOVED]
28

26 not 27 [OPINION PIECES REMOVED]

156

29

exp adolescent/ not (exp adult/ and exp adolescent/)

128867630

exp child/ not (exp adult/ and exp child/)

3403086

31

fetus/ not (fetus/ and exp adult/)

23325232

28 not (29 or 30 or 31) [UNDER 18 REMOVED]

156

33

conference abstract.pt.

4313905

34

32 not 33 [CONFERENCE ABSTRACTS REMOVED]

69

35

32 and 33

8736

24 not 25 [ANIMAL-ONLY REMOVED]

156

37

34 or 36 [MOST RECENT 2 YEARS CONF ABSTRACTS

116

43

RETAINED]
38

37 use oemezd [EMBASE RECORDS, MOST RECENT 2 YEARS

68

CONF ABSTRACTS RETAINED]39

exp Amyloidosis/ or Plaque, Amyloid/ or (amyloido$ or beta-

188319amyloido$ or betaamyloido$ or paraamyloido$ or "paraamyloido$" or beta fibrillos$ or betafibrillos$ or(amyloid$ adj3 (AL or light-chain or primary or systemic or
senile or abeta or fibril? or tumo?r Or deposit? or plaque?))or (amyloid$ adj2 (neuropathy or neuropathi$ orpolyneuropathy or polyneuropathi$ or polyneuritic$ or polyneuropathy or poly-neuropathi$ or poly-neuritic$)) or
cerebral amyloid? angiopath$ or (abeta adj4 amyloido$) or
famil$ mediterranean fever? or ((HCHWA or FMF or MWS or
UDA) and amyloido$) or ((muckle wells or Wohlwill Andrade)adj2 (syndrome$ or disease?)) or (neuritic plaque? or senile
plaque?)).ti,ab,kw. [Amyloidosis Terms]
40(daratumumab$ or darzalex$ or dalinvi$ or jnj54767414 or

5358

jnj-54767414 or 945721-28-8 or 4Z63YK6E0E or ((CD38 or
CD-38) adj2 (monoclonal antibod$ or mab or moab orhumax)) or D-VCd).ti,ab,kw. [Daratumumab Terms]
41

39 and 40

401

42

exp Child/ not (exp Adult/ and exp Child/)

3403086

43

exp Infant/ not (exp Adult/ and exp Infant/)

172933444

41 not (42 or 43) [CHILD AND INFANT - ONLY REMOVED]

401

45

44 use cctr [CENTRAL records]

3546(amyloido$ or beta-amyloido$ or betaamyloido$ or

172177

paraamyloido$ or "para-amyloido$" or beta fibrillos$ orbetafibrillos$ or (amyloid$ adj3 (AL or light-chain or primaryor systemic or senile or abeta or fibril? or tumo?r Or
deposit? or plaque?)) or (amyloid$ adj2 (neuropathy orneuropathi$ or polyneuropathy or polyneuropathi$ or44polyneuritic$ or poly-neuropathy or poly-neuropathi$ or
poly-neuritic$)) or cerebral amyloid? angiopath$ or (abeta
adj4 amyloido$) or famil$ mediterranean fever? or ((HCHWA
or FMF or MWS or UDA) and amyloido$) or ((muckle wells or
Wohlwill Andrade) adj2 (syndrome$ or disease?)) or(neuritic plaque? or senile plaque?)).ti,ab,kw. [Amyloidosis
Terms]
47(daratumumab$ or darzalex$ or dalinvi$ or jnj54767414 or

5358

jnj-54767414 or 945721-28-8 or 4Z63YK6E0E or ((CD38 or
CD-38) adj2 (monoclonal antibod$ or mab or moab orhumax)) or D-VCd).ti,ab,kw. [Daratumumab Terms]
48

46 and 47

390

49

48 use coch

050

15 or 38 or 45 or 49

158

51

limit 50 to yr="2005 -Current"

158

52

limit 51 to english language [Limit not valid in CDSR;

153

records were retained]
53

limit 51 to japanese [Limit not valid in CDSR; records were1

retained]54

52 or 53

154

55

remove duplicates from 54

117

3.2.1.2 Search Strategy for Ichushi Web
Five searches were performed using Ichushi Web which combined the terms“daratumumab” (in English) and the English and Japanese translations of“amyloidosis” (ie, “アミロイドーシス”). Ultimately, 402 records (ie, 382 fromsearch 4 and 20 from search 5) from Ichushi Web underwent screening forinclusion. The search strategy and results for the Ichushi Web search arepresented below in Table 3.3.
45

“amyloidosis” were searched in English. For JSM and JSH, the program of abstracts fromeach conference were screened manually (ie, without the use of keywords or search terms).
Abbreviations: ASCO = American Society of Clinical Oncology; ASH = American Society of
Hematology; EHA = European Hematology Association; JSH = Japanese Society of
Hematology; JSM = Japanese Society of Myeloma.

3.2.2

Study Selection

Study screening was performed by two independent reviewers using thesystematic review software DistillerSR (Evidence Partners, Ontario, Canada).
After the removal of duplicate citations, titles and abstracts were reviewed forstudy eligibility according to pre-specified inclusion and exclusion criteria
established using the population, intervention, comparators, outcomes, andstudy design (PICOS) framework (see Table 3.6 below). Non-English and nonJapanese publications were excluded during title and abstract screening
provided that the publication language was known. Studies that met theinclusion criteria and those that could not be excluded due to insufficient
information were further reviewed at the full-text screening phase. The study
selection criteria excluded conference abstracts or posters older than two years
from the dates of the search. It was expected that full-text publications
associated with conference abstracts and posters dated prior to 2020 would be
published by the time the search was conducted. During both screening phases,
any discrepancies between the two reviewers were resolved by consensus or bya third reviewer.
Data extraction was performed for all records that met all inclusion criteria.
Information from the full-text articles was extracted by one reviewer andvalidated by a second reviewer. A third reviewer was consulted to resolve
discrepancies, as necessary.

48

were identified for inclusion in the SLR, all of which pertained to the
ANDROMEDA trial.
Three additional relevant records were identified by performing hand-searchingof EHA, ASCO, ASH, JSM, and JSH conference websites (61-63). Notably, allrelevant records identified in the conference hand-searches pertained to the
ANDROMEDA trial. The Preferred Reporting Items for Systematic Reviews andMeta-Analyses (PRISMA) (64, 65) flow diagram for the selection of thesestudies is presented in Figure 3.1.

Figure 3.1. PRISMA flow diagram

Abbreviations: ASCO = American Society of Clinical Oncology; ASH = American Society of
Hematology; EHA = European Hematology Association; JSH = Japanese Society of
Hematology; JSM = Japanese Society of Myeloma; n = number; PRISMA = Preferred
Reporting Items for Systematic Reviews and Meta-Analyses.

51

Abbreviations: CI = confidence interval; CR = hematologic complete response; CyBorD =cyclophosphamide, bortezomib, dexamethasone; DCyBorD = daratumumab,
cyclophosphamide, bortezomib, dexamethasone.

3.2.6

Summary of Additional Benefit

3.2.6.1 ANDOMEDA clinical trial
The SLR search strategy and screening process were robust and aimed to
identify RCTs reporting efficacy, safety, and HRQoL when comparing DCyBorD
and CyBorD in patients newly diagnosed with AL amyloidosis. All relevant
articles identified in this SLR (resulting from both database and grey literaturesearches) pertained to the ANDROMEDA trial. Database searches identified 2
relevant full-text articles (50, 57), 12 relevant conference abstracts (46-49, 5156, 58, 59), and one record retrieved via a search of clinicaltrials.gov (60).
Targeted searching of key conference websites (see Section 3.2.1.4) identified
three additional records (61-63) related to the ANDROMEDA study. All relevant
records identified are summarized in Table 3.8.

53Key exclusionPrevious therapy for AL amyloidosis.

criteria (50)Symptomatic multiple myeloma according toInternational Myeloma Working Group
criteria.

Eastern Cooperative Oncology Group
performance-status score of more than 2 (ona 5-point scale in which higher numbers
indicate greater disability).

Estimated glomerular filtration rate of lessthan 20 ml per minute per 1.73 m2 of bodysurface area.



Evidence of a severe cardiovascular condition
including an N-terminal pro– B-typenatriuretic peptide level of more than 8500
ng per liter, a systolic blood pressure of lessthan 90 mm Hg, or a New York Heart
Association classification of stage IIIB or IV
at screening.

Details of

DCyBorD group (n=195)

interventional

Daratumumab component

method (50)oDosing: 1800 mg of daratumumab coformulated with rHuPH20 2000 U/mL.

oPatients received daratumumab via
SC injection once weekly (cycles 1
and 2), every 2 weeks (cycles 3–6),
and then every 4 weeks until diseaseprogression, the start of subsequent
therapy, or for a maximum of 24
cycles from the start of the trial,
whichever occurred first.
Each cycle consisted of 28
days.



Cyclophosphamide componento59

Dosing: 300 mg/m2 ofcyclophosphamide.
oPatients received cyclophosphamide
as an oral or IV weekly dose for a
maximum of 6 cycles.

Bortezomib componentoDosing: 1.3 mg/m2 of bortezomib.

oPatients received bortezomib via SC
injection weekly for a maximum of 6
cycles.



Dexamethasone component*oDosing: 40 mg of dexamethasone
weekly.

oPatients received dexamethasone as
an oral or IV weekly dose for a
maximum of 6 cycles.

Details ofcomparator method

CyBorD group (n=193)
(50)

Cyclophosphamide componentoDosing: 300 mg/m2 of
cyclophosphamide.

oPatients received cyclophosphamide
as an oral or IV weekly dose for a
maximum of 6 cycles.

Bortezomib componentoDosing: 1.3 mg/m2 of bortezomib.

oPatients received bortezomib via SC
injection weekly for a maximum of 6
cycles.



Dexamethasone component*oDosing: 40 mg of dexamethasone
weekly.

oPatients received dexamethasone as
an oral or IV weekly dose for a
maximum of 6 cycles.

Study design (50)60

Phase 3 randomized controlled trial.

Randomization was stratified according to cardiac
stage (I, II, or IIIA on the basis of the European
modification of the Mayo Clinic Cardiac Staging
System (33)), availability of transplantation in thelocal country, and renal function.
Blinding method

Open label(50)
Primary endpoint



(50)

Hematologic CR rate (or Complete
Hematologic Response, CHR)

Key secondary

MOD-PFS

endpoints (50)Organ response



OS



Hematologic complete response at 6-months



Hematologic VGPR or betterTime to/duration of hematologic complete
response

Statistical methodsTime to next treatment

Reduction in fatigue



The Kaplan-Meier method was used toestimate time-to-event distributions.

(50)Hazard ratios and 95% CIs were estimatedusing a stratified Cox proportional hazards
regression model.



The infusion-related reaction rate and rates
of very good partial response or better werecompared between groups using a stratified
Cochran-Mantel-Hansel test.

Sample size (50)
Follow-up period

DCyBorD group: n=195



CyBorD group: n=193

Primary analysis: Median 11.4 months(range 0.03 to 21.3 months) (50)Interim analysis: Median 15.7 months (range
0.0 to 24.1 months) (61)61

12-month landmark analysis: NR (49, 58)18-month landmark analysis: Median 25.8
months (47)

Patient

DCyBorD group vs CyBorD group: the demographic

demographics (50)and clinical characteristics of the patients atbaseline were balanced between the groups.
Male, n (%):108 (55.4) vs 117 (60.6)

Median age (range), years: 62 (34-87) vs 64(35-86)

Median time since initial diagnosis (range),days: 48 (8-1,611) vs 43 (5-1,102)Median dFLC (range), mg/liter: 200 (24,749) vs 186 (1-9,983)

Median number of involved organs (range):
2 (1-5) vs 2 (1-6)

Median NT-proBNP level (range), ng/liter:
1388.6 (51-10182) vs 1746.0 (51-12950)

Median eGFR (range), ml/min/1.73 m2: 77.8
(21-126) vs 76.2 (20-121)



Cardiac (Mayo) stageoStage I, n (%): 47 (24.1) vs 43(22.3)oStage II, n (%): 76 (39.0) vs 80(41.5)oStage IIIA, n (%): 70 (35.9) vs 64(33.2)oSage IIIB, n (%): 2 (1.0) vs 6 (3.1)

Renal stageoStage I, n/total n (%): 107/193(55.4) vs 101/193 (52.3)

oStage II, n/total n (%): 67/193 (34.7)
vs 74/193 (38.3)

oStage III, n/total n (%): 19/193 (9.8)
vs 18/193 (9.3)

62

Efficacy results (47,

Safety Run-in Results in 28 patients (DCyBorD

49, 50, 57, 58, 60-

arm only; July 2019; median follow-up 17.6

62)

months) (57)Overall hematologic response rate was 96%,
with a complete hematologic response in 15(54%) patients.



23 (82%) patients achieved VGPR or better.

PR or better was achieved by 20 (71%)
patients at 1 month, 22 (79%) patients at 3
months, and 17 (61%) patients at 6 months.

Renal response occurred in 6 of 16 (38%), 7
of 15 (47%), and 10 of 15 (67%) patients.

Cardiac response occurred in 6 of 16 (38%),
6 of 13 (46%), and 8 of 13 (62%) patients
at 3, 6, and 12 months, respectivelyHepatic response occurred in 2 of 3 (67%)
patients at 12 months.



5 patients died.

Primary Analysis (February 2020; medianfollow-up 11.4 months) (50, 60)CR was achieved in 104 patients (53.3%) in
the DCyBorD group and 35 patients (18.1%)
in the CyBorD group (RR ratio: 2.9 (95% CI:
2.1 to 4.1), p<0.001; OR: 5.1 (95% CI: 3.2
to 8.2), p<0.001).
oAt 6-months, 49.7% of DCyBorD
subjects and 14.0% of CyBorD
subjects achieved CR (RR ratio: 3.5[95% CI 2.4 to 5.2]; OR 6.1 [95% CI
3.7 to 10.0]; p<0.001 for bothcomparisons).

oAt 6-months, VGPR or better wasachieved by 78.5% of DCyBorD

63

subjects and 49.2% of CyBorD
subjects (RR ratio 1.6 [95% CI 1.4 to1.9]; OR 3.8 [95% CI 2.4 to 5.9]).
oMedian time to CR was 60 days for
DCyBorD subjects and 85 days for
CyBorD subjects.



MOD-PFS was significantly longer in the
DCyBorD group than the CyBorD group (HR0.58, 95% CI 0.36 to 0.93, p=0.02; see
Figure 3.2).

Among subjects who were evaluable for
cardiac response (ie, 118 in DCyBorD and
117 in CyBorD groups), 41.5% of DCyBorD(95% CI 32.5 to 51.0) and 22.2% of CyBorD(95% CI 15.1 to 30.8) subjects had a cardiac
response at 6-months.

Among subjects who were evaluable forrenal response (ie, 117 in DCyBorD and 113
in CyBorD groups), 53.0% (95% CI 43.5 to62.3) of DCyBorD and 23.9% (95% CI 16.4
to 32.8) of CyBorD subjects had a renal
response at 6-months.

Overall survival data were immature at thetime of the primary analysis and did not
differ substantially between the two groups.

Updated/Interim Results (Median follow-up
15.7 months) (61)The overall CR rate continued to be higher
with DCyBorD than CyBorD (56.9% vs18.7%; OR 5.68; 95% CI 3.58-9.00;
p<0.0001).

64

12-month Landmark Analysis (November
2020; median follow-up not reported) (49, 58)
The overall CR rate continued to be higher
with DCyBorD than CyBorD (59% vs 19%;
OR 5.9; 95% CI 3.7–9.4; p<0.0001).
oMore patients achieved a VGPR or
better (≥VGPR) with DCyBorD than
CyBorD (79% vs 50%; OR 3.7; 95%
CI 2.4–5.9; p<0.0001).

oAmong responders, median time fromrandomization to ≥VGPR was shorter
for DCyBorD than CyBorD (0.56 vs
0.82 months).



Cardiac response rates were higher with
DCyBorD than CyBorD at 6 months (42% vs22%) and at 12 months (57% vs 28%)

Renal response rates for DCyBorD vs CyBorD
were 54% vs 27% at 6 months and 57% vs
27% at 12 months.

A total of 71 deaths** occurred (DCyBorD, n= 31; CyBorD, n = 40).

18-month Landmark Analysis (May 2021;
median follow-up 25.8 months) (47)

The rate of hematologic CR was significantly
higher in the DCyBorD arm vs the CyBorD
arm (59.5% vs 19.2%; OR [95% CI], 6.03
[3.80–9.58]; p<0.0001).
oMore patients achieved a VGPR or
better (≥VGPR) (DCyBorD vs CyBorD,
79.0% vs 50.3%; OR [95% CI], 3.74
[2.39–5.86]; p<0.0001)

oAmong patients who responded, themedian time from randomization to65

≥VGPR was shorter in the DCyBorD
arm (0.56 months) vs the CyBorD
arm (0.82 months).


Comparable to the cardiac response analysis
at 6 months (DCyBorD vs CyBorD, 42% vs22%), greater cardiac response rates wereachieved with DCyBorD compared with
CyBorD at 18 months (53% vs 24%).

Renal response rates remained superior with
DCyBorD vs CyBorD alone at 18 months(58% vs 26% compared with 6 months[54% vs 27%]).



A total of 79 deaths** occurred (DCyBorD,
N=34; CyBorD, N=45). OS will be analyzed
and major organ deterioration PFS will be
updated after approximately 200 events
have occurred.

Safety results (47,

Safety Run-in Results (July 2019; median49, 50, 57, 58)

follow-up 17.6 months; pertains to DCyBorD
arm only) (57, 60)


26 (93%) patients experienced TEAEs
considered related to study treatment;
TEAEs in 21 (75%) patients were consideredrelated to daratumumab.

Serious TEAEs occurred in 12 (43%) patientsand included fall and acute kidney injury(11% each) and pneumonia and cellulitis(7% each; cellulitis not related to injectionsite).

An IRR occurred in 1 (4%) patient,comprising chest discomfort, cough,hypotension, oropharyngeal pain, andsneezing, all of which were grade 1.

66

A total of 6 injection-site reactions occurredin 3 (11%) patients.
o

All injection-site reactions were grade
1 and included erythema, bruising,and skin discoloration; none led tochanges in treatment.

No new safety concerns were identified with
DCyBorD compared with daratumumab
monotherapy (IV or SC) or CyBorD alone.



Daratumumab SC is associated with low
rates of IRRs, few injection-site reactions,and reduced administration times comparedwith Daratumumab IV.

Primary Analysis (February 2020; medianfollow-up 11.4 months) (50, 60)
The most common AEs of grades 3 or 4 werelymphopenia (13.0% in the daratumumabgroup and 10.1% in the control group),
pneumonia (7.8% and 4.3%, respectively),
cardiac failure (6.2% and 4.8%), diarrhea(5.7% and 3.7%), syncope (5.2% and6.4%), neutropenia (5.2% and 2.7%),
peripheral edema (3.1% and 5.9%), andhypokalemia (1.6% and 5.3%).

The incidence of grade 3 or 4 infections was
16.6% in the daratumumab group and10.1% in the control group.



SAEs occurred in 43.0% of patients in the
DCyBorD arm and 36.2% of patients in the
CyBorD arm.



The most common SAE reported waspneumonia, which occurred in 7.3% and4.8% of subjects in the DCyBorD and
CyBorD arms, respectively.

67The percentage of patients who had AEs that
led to discontinuation of trial treatment was
4.1% in the DCyBorD group and 4.3% in the
CyBorD group.



Local injection-site reactions to any agent
occurred in 54 patients (28.0%) in the
DCyBorD group and 45 patients (23.9%) in
the CyBorD group.



A total of 21 patients (10.9%) in the
DCyBorD group had local injection-site
reactions related to daratumumab, all ofwhich were grade 1 or 2.

12-month Landmark Analysis (November
2020; median follow-up not reported) (49, 58)
From cycle 7 onward in the DCyBorD group,no grade 3/4 TEAE occurred in ≥5% of pts.



There were no systemic administrationrelated reactions with DCyBorD after cycle 6.

18-month Landmark Analysis (May 2021;
median follow-up 25.8 months) (47)In the DCyBorD arm, only 1 additional grade
3/4 TEAE occurred over 18 months
compared with 12 months (119 [61.7%] vs
118 [61.1%] patients) and no additional
IRRs were reported.

Patient-reported

outcomes (53)Median time to improvement was shorterand median time to worsening was longer inthe DCyBorD group than in the CyBorD
group for EORTC QLQ-C30 GHS and fatigue
scales and EQ-5D-5L VAS.



Least squares mean scores for EORTC QLQC30 GHS and fatigue, EQ-5D-5L VAS, and68SF-36 MCS remained stable in the DCyBorD
group but worsened compared with baselinein the CyBorD group.
The greatest between-group differences in
PRO score changes from baseline wereobserved at Week 16 (Cycle 4).

After Cycle 6, patients in the DCyBorD groupreported improvements in mean GHS andfatigue scores that continued while ontreatment.

Efficacy results –tested for cytogenic abnormalities.

impact of cytogenic
abnormalities on

Among ANDROMEDA subjects, 321 were

In the DCyBorD and CyBorD arms,

treatment outcomes

respectively, 42.9% vs 40.0% had t(11;14),(51)

25.4% vs 20.3% had amp1q21, 16.2% vs22.0% had del13q14, and 6.7% vs 6.1% had
del17p13.


At a median follow-up of 20.3 months, thehematologic CR rate was higher with
DCyBorD vs CyBorD across all four cytogenic
subgroups, ranging from 56-72% vs 0-14%(p<0.05).

Organ response rates were numericallyhigher with DCyBorD in all subgroups except
for cardiac response rate in the del17p13
subgroup.

Rates of deep hematologic response were
not impacted by t(11;14) and amp1q21 inpatients treated with DCyBorD but weregenerally lower in CyBorD-treated patientswith t(11;14) and amp1q21.

Efficacy results –Rates of deep hematological responses by all

reduction in absolute

criteria strongly favored the DCyBorD

involved free lighttreatment arm.

69

chain and differenceoOverall hematologic CR rate forbetween involved

DCyBorD vs CyBorD was 53% vsand uninvolved free

18%, respectively.

light chains (46)oHematologic response rate forsubjects with iFLC≤20 mg/L
(regardless of FLCr) receiving
DCyBorD vs CyBorD was 71% and20%, respectively.

o

Hematologic response rate forsubjects with dFLC<10 mg/L
(regardless of FLCr) receiving
DCyBorD vs CyBorD was 64% and31%, respectively.



MOD-PFS was longer in patients achieving
deep hematological responses regardless ofwhich criteria for deep hematologic response
was utilized.

Efficacy results –MOD-PFS was longer in patients with

rapid and deep

CR/VGPR at 1- and 3-months compared tohematologic

patients with lower levels of response.

responses and MOD-PFS (55)

CR/VGPR at 1 and 3 months was associatedwith reduced risk of death or major organ
deterioration in a multivariate analysis
adjusting for baseline difference between
involved and uninvolved free light chains andcardiac stage, (HR: 0.399, p=0.0006 and
HR: 0.262, p=0.0003, respectively).



At 1 and 3 months, cardiac and renal
response rates were higher in those whoachieved early and deep hematologic
responses (CR and VGPR).

Efficacy and safety
results – Asian

Overall CR rate was 59% for DCyBorD and
10% for CyBorD (OR 13.2; 95% CI 3.3-53.7;
p<0.0001).

70

subgroup analysiso(54, 63)

DCyBorD vs CyBorD achieved higher
rates of VGPR or better (≥VGPR; 93%
vs 61%).



MOD-PFS favored DCyBorD-treated patients(HR 0.21; 95% CI, 0.06-0.75, P=0.0079).



A total of 12 deaths occurred (DCyBorD,
n=3; CyBorD, n=9).

The most common (≥10%) grade 3/4 TEAEs
were lymphopenia (DCyBorD 35%/CyBorD32%), neutropenia (10%/3%), diarrhea(10%/7%), pneumonia (7%/10%), cardiac
failure (7%/10%), hypokalemia (7%/10%),anemia (3%/10%), thrombocytopenia(3%/10%), hypoalbuminemia (3%/10%),and syncope (3%/10%).



TEAEs leading to treatment discontinuation
occurred in 1 patient in each treatment arm.



Please refer to Appendix A for a moredetailed description of the ANDROMEDAAsian subgroup analysis.

Efficacy and safety

Hematologic CR rates were higher in the

results – outcomes

DCyBorD group than in the CyBorD group in

by cardiac stage

patients with cardiac stages I, II, and III at(52)baseline.
HRs for MOD-PFS were 0.33, 0.55 and 0.66
for cardiac stages I, II and III, respectively,favoring DCyBorD.



Cardiac and renal response rates at 6
months were also higher in the DCyBorD
group regardless of cardiac stage atbaseline.



Rates of any grade AEs were similar inpatients with and without cardiac
involvement at baseline.

71

Across both treatment arms, rates of serious
TEAEs were higher in patients with cardiac
involvement at baseline than in those
without.

Efficacy and HRQoL

140 and 137 patients in the DCyBorD andresults – outcomes

CyBorD groups had cardiac involvement,for patients withrespectively.

cardiac involvement



(48)

At 6-months, 41.5% of DCyBorD and 22.2%
of CyBorD patients with cardiac involvement
had a cardiac response (p=0.0029).



GHS and fatigue scores remained stable with
DCyBorD but worsened with CyBorD.



The greatest between-group differences wereat cycles 4 and 5 (GHS LS mean difference:
6.2 [95% CI 1.1 to 11.3, p=0.0174]; fatigue
LS mean difference: -11.4 [95% CI -17.6 to-5.3, p=0.0003]).

Over six cycles, higher percentages of
DCyBorD vs CyBorD subjects had meaningfulimprovements (≥1 point) in shortness ofbreath (33.3% vs 26.6%) and feeling weak
(31.1% vs 12.5%) and tired (24.4% vs
10.9%).

Overall, DCyBorD resulted in higher rates ofcardiac response with the PRO results
suggesting improvement in fatigue-relatedparameters in AL amyloidosis patients withcardiac involvement.

Efficacy and HRQoL

115 and 114 patients in the DCyBorD andresults – outcomes

CyBorD groups had renal involvement,for patients withrespectively.

renal involvement(56, 59)



At 6-months, 53.8% of DCyBorD and 27.4%
of CyBorD patients had a renal response(p<0.0001).

72



GHS and fatigue scores remained stable with
DCyBorD but worsened with CyBorD by cycle
3 with the greatest between-groupdifferences were observed at cycle 5.

More DCyBorD than CyBorD patients
experienced ≥1-point improvement inshortness of breath or feeling weak/tired by‘a little or more’.

Overall, DCyBorD increased renal responsewith indications of improvement in fatiguerelated HRQoL parameters.

Limitations

Open label design. Patients and physicians
were not blinded to treatment.

* For patients who were older than 70 years of age, were underweight (body-mass index[the weight in kilograms divided by the square of the height in meters], <18.5), or had
hypervolemia, poorly controlled diabetes mellitus, or previous unacceptable side effects
associated with glucocorticoid therapy, dexamethasone could be administered at a dose of 20
mg weekly at the discretion of their physician.
**OS will be analyzed and MOD-PFS will be updated after approximately 200 events haveoccurred.
Abbreviations: AE = adverse event; AL = amyloid light-chain; CI = confidence interval; dFLC
= difference in free light chains; CR = hematologic complete response; CyBorD =cyclophosphamide, bortezomib, dexamethasone; DCyBorD = daratumumab,
cyclophosphamide, bortezomib, dexamethasone; eGFR = estimated glomerular filtration
rate; EORTC QLQ-C30 = European Organization for Research and Treatment of Cancer
Quality of Life Questionnaire Core 30-item; EQ-5D-5L = EuroQol 5-dimensional descriptive
system; GHS = global health status; Hg = mercury; IRR = infusion-related reaction; ITT =intent-to-treat; IV = intravenous; HR = hazard ratio; HRQoL = health-related quality of life;
MCS = mental component summary; mg = milligrams; min = minute; mL = milliliters; MODPFS = major organ deterioration progression-free survival; ng = nanograms; NT-proBNP =N-terminal pro-hormone B-type natriuretic peptide; OR = odds ratio; OS = overall survival;
PR = partial response; rHuPH20 = recombinant human hyaluronidase PH20 enzyme; PRO =patient-reported outcome; RR = relative risk; SAE = serious adverse event; SC =subcutaneous; SF-36 = Short Form-36; TEAE = treatment-emergent adverse event; VAS =visual analog scale; VGPR = very good partial response.

73

Figure 3.2. Kaplan-Meier estimates of MOD-PFS from ANDROMEDA

Abbreviations: CI = confidence interval; CyBorD = cyclophosphamide, bortezomib, dexamethasone;
DCyBorD = daratumumab, cyclophosphamide, bortezomib, dexamethasone.
Source: Adapted from Kastritis et al., 2021 (50).

3.3

Clinical Questions (Different controlled or single-arm studies)

Not applicable.

3.4

Systematic Review (Different controlled or single-arm studies)

Not applicable.

74Data to support□ Meta-analysis of RCTs

judgment■ Single clinical trial (18 associated unique records)□ Prospective, controlled, observational study□ Indirect comparison of RCTs
□ Comparison of single-arm studies□ No relevant clinical study data
□ Other

Reason for judging
the presence or

Hematologic responsePrimary results from the ANDROMEDA study (50,absence of62) indicated that the proportion of subjects

additional

achieving CR was significantly greater in theusefulness

DCyBorD arm compared to the CyBorD arm(53.3% vs 18.1%; OR: 5.1 (95% CI: 3.2 to 8.2);
p<0.001)).


As reported in the ANDROMEDA primary analysis(50, 62), at 6-months, more DCyBorD subjects
than CyBorD subjects had achieved CR (49.7% vs
14.0%, respectively [RR ratio: 3.5 with 95% CI:
2.4 to 5.2; OR 6.1 with 95% CI 3.7 to 10.0;
p<0.001 for both comparisons]) and ≥VGPR(78.5% vs 49.2%, respectively [RR ratio: 1.6
with 95% CI 1.4 to 1.9; OR 3.8 with 95% CI 2.4
to 5.9]) and the median time to CR was shorterfor subjects receiving DCyBorD (60 days)
compared to CyBorD (85 days).

An ANDROMEDA interim analysis (median followup 15.7 months) indicated that, similar to theprimary results, subjects in the DCyBorD arm hada higher overall CR rate compared to those in the
CyBorD arm (p<0.0001) (61).

Similar hematologic response data were reported
for both the ANDROMEDA 12-month landmark(49, 58) and 18-month landmark (47) analyses
with higher rates of CR, higher rates of ≥VGPR,

79

and shorter time to response for subjects
receiving DCyBorD compared to CyBorD. Notably,at the 18-month landmark data cut (medianfollow-up of 25.8 months), the CR rate continued
to be higher for subjects receiving DCyBorD
compared to CyBorD (59.5% vs 19.2%; OR [95%CI], 6.03 [3.80–9.58]; p<0.0001).


Similar results were observed in an ANDROMEDAAsian subgroup analysis (54) with higher overall
CR rates for DCyBorD compared to CyBorD (59%vs 10%, respectively) and higher rates of ≥VGPR
for DCyBorD compared to CyBorD (93% vs 61%,
respectively).

Regardless of baseline cardiac stage, hematologic
CR rates were higher in the DCyBorD groupcompared to the CyBorD group (52).



Rates of deep hematologic response were notimpacted for patients with t(11;14) and amp1q21
cytogenic abnormalities; however, rates of deep
hematologic response were generally lower forpatients with these abnormalities that weretreated with VCd (51).

Regardless of which criteria was used to define“deep hematologic response”, rates ofhematologic response strongly favored the
DCyBorD arm compared to the CyBorD arm (46).

MOD-PFS

Data from the ANDROMEDA primary analysis (50,62) indicated that survival free from major organ
deterioration or hematologic progression (ie,MOD-PFS) was longer for subjects in the
DCyBorD arm compared to those in the CyBorD
arm (HR 0.58, 95% CI 0.36 to 0.93, p=0.02).

80

o

The Kaplan-Meier curve for MOD-PFS
based on the primary analysis is presented
in Figure 3.2.



Similar results were reported in the Asian
subgroup analysis (54) where MOD-PFS favoredsubjects treated with DCyBorD compared to thosetreated with CyBorD (HR 0.21; 95% CI, 0.060.75, p=0.0079).

Compared to subjects receiving CyBorD, subjects
receiving DCyBorD had improved MOD-PFS
regardless of cardiac stage (HRs for cardiac stage
I, II, and III were 0.33, 0.55, and 0.66,
respectively) (52).

Organ response

At 6 months, cardiac response and renal response
favored DCyBorD compared with CyBorD among
evaluable subjects: 41.5% of DCyBorD (95% CI
32.5 to 51.0) and 22.2% of CyBorD (95% CI 15.1
to 30.8) subjects achieve cardiac response;
53.0% (95% CI 43.5 to 62.3) of DCyBorD and
23.9% (95% CI 16.4 to 32.8) of CyBorD subjects
had a renal response (50). Greater cardiac
responses (53% vs. 24%) and renal response
rate (58% vs. 26%) were achieved at 18 months
(47).



Regardless of baseline cardiac stage, 6-month
cardiac and renal response rates were higher inthe DCyBorD arm compared to the CyBorD arm(52).

SafetyThe safety profiles of daratumumab andbortezomib, cyclophosphamide, and81

dexamethasone in this trial were consistent with
their known profiles and the underlying disease(50).
No new safety concerns were identified with
DCyBorD compared with daratumumab
monotherapy (IV or SC) or CyBorD alone (57).

HRQoL


Median time to improvement was shorter andmedian time to worsening was longer in the
DCyBorD group than in the CyBorD group for
EORTC QLQ-C30 GHS and fatigue scales and EQ5D-5L VAS (53).The median time to improvement
for GHS as measured by the EORTC QLQ-C30 was
7.82 months in the DCyBorD arm and 16.79
months in the CyBorD arm (hazard ratio = 1.53,
95% CI, 1.10 to 2.13). EORTC QLQ-30 global
health status showed continued improvement in
the DCyBorD arm after 6 months (53).

Compared to the CyBorD group, the DCyBorD
group had higher percentages of patients (withrenal and/or cardiac involvement) withmeaningful improvements in shortness of breathand feeling weak/tired over six cycles (48, 56).



HRQoL measures (EORTC QLQ-C30 GHS andfatigue, EQ-5D-5L VAS, and SF-36 MCS)
remained stable in the DCyBorD group but
worsened compared with baseline in the CyBorD
group (48, 53, 56).

Abbreviations: AEs = adverse events; CI = confidence interval; CR = hematologic complete
response; CyBorD = cyclophosphamide, bortezomib, dexamethasone; DCyBorD =daratumumab, cyclophosphamide, bortezomib, dexamethasone; EORTC QLQ-C30 =European Organization for Research and Treatment of Cancer Quality of Life QuestionnaireCore 30-item; EQ-5D-5L = EuroQol 5-dimensional descriptive system; GHS = global healthstatus; HR = hazard ratio; HRQoL = health-related quality of life; IV = intravenous; MCS =82

mental component summary; MOD-PFS = major organ deterioration progression-freesurvival; OR = odd ratio; QoL = quality of life; RCT = randomized controlled trial; RR =relative risk; SC = subcutaneous; SF-36 = Short Form-36; VAS = visual analog scale; QoL =quality of life; VGPR = very good partial response.

4

Details of Analytical Methods

4.1 Analytical Procedures

4.1.1 Calculation of cost-effectivenessAn economic model was developed de novo to conduct a CUA for DCyBorD
compared to CyBorD for patients newly diagnosed with AL amyloidosis.
Achieving a swift and deep hematologic response is the goal of first-line therapy
as it prevents further organ damage and improves survival in patients with AL
amyloidosis (66). The level of hematological response (better response) iscorrelated with lower risk of progression and longer OS (additional details
provided in Appendix C) (27, 33, 67-76). The model was, therefore, developed
based on the importance of hematologic response in AL amyloidosis. In clinicalpractice, hematologic response is assessed at each cycle of the treatment
course. Based on expert opinion and current clinical practice (35), thehematologic response at 3 months allows clinicians to consider changing
therapies if the current treatment is not effective.
The CUA model consists of a decision tree paired with a Markov model where
patients transition through independent health states and OS is stratified byhematologic response. The cycle length selected for the model was 28 days toalign with the duration of treatment cycles and observation timepoints in the
ANDROMEDA trial (24). In general, costs that are applied on a per-cycle basis
were calculated based on a 28-day cycle. In some instances where
ANDROMEDA individual patient data (IPD) were used to inform inputs (eg,
distribution of patients in the decision tree) and were only reported/calculated
on a monthly basis, a simplifying assumption was made where one month was
equivalent to one model cycle.

834.1.1.1 Model Structure
The CUA model was developed in Microsoft® Excel and consisted of a hybrid
cohort model that included a decision tree treatment component. The decision
tree allowed for patient stratification by hematologic response to identify
responders or non-responders after three cycles of treatment. Patients were
distributed into 1 of 3 hematologic response categories: “complete response[CR]”, “very good partial response [VGPR]” or combined “partial or no response[PR & NR]” or death.
The decision tree was followed by a Markov model to capture the patient
disease course after being assessed for their initial response to treatment. The
Markov model includes 11 Markov health states, as shown in Figure 4.1.
Remain on first-line treatment (‘1L Tx’)

Off first-line treatment (if previously on CyBorD) or on fixed
daratumumab (monotherapy) treatment (if previously on DCyBorD) (‘OffTx/FDT’)

Second-line treatment (‘2L Tx’)End-stage organ failure



Death

For patients in the response category of “CR” or “VGPR”, after they complete
their first-line treatment regimen or transition to receive daratumumab
monotherapy (ie, patients in the off treatment or fixed daratumumab
treatment [‘Off Tx/FDT’] health state), patients are monitored and may
eventually experience disease relapse necessitating second-line treatment.
Patients in the response category “PR & NR” move immediately to secondline treatment.
In this model, it is assumed that patients with relapsed/refractory diseasereceived one line of subsequent therapy based on clinical feedback that laterline therapies provide risk/toxicity that outweighs their potential benefits.
This was also observed in the ANDROMEDA trial where the majority ofpatients (84) received only one line of subsequent therapy (77).

Ultimately patients experience disease progression or death, which is
captured in the ‘End-stage Organ Failure’ health state and “death” healthstates.
Patients can die and move to “death”, the absorbing health state, at any
time.

Figure 4.1. Model structure diagram

Abbreviations: 1L = first-line; 2L = second-line; AL = amyloid light-chain; CR = complete
response; FDT = fixed daratumumab treatment; NR = no response; PR = partial response;
Tx = treatment; VGPR = very good partial response.

4.1.1.1.1

Decision Tree

Within the decision tree, all patients are either alive on first-line treatment andare stratified based by hematologic response (ie, CR, very good partial
response [VGPR], or partial/no response [PR/NR]), or dead. End-stage organ
failure was not considered in the decision tree, as very few organ deterioration
events were reported in the ANDROMEDA trial during the first three cycles oftreatment initiation, suggesting that organ failure is a consequence of diseaseprogression that would occur in the long-term rather than during the first three85

cycles of the model. In the main analysis, patients exit the decision tree after
three cycles. This timeframe was included in the model and selected for themain analysis because it aligns with our understanding of current clinicalpractice in Japan whereby patients that do not achieve, at minimum, VGPR
would switch to a subsequent line of therapy (78-80). As stated earlier, patients
who do not achieve ≥VGPR are at serious risk of irreparable organ damage.
Rather than waiting for a deepening of response, a change of therapy offers thebest chance to achieve a deep response and prolong survival. It is therefore
common clinical practice to switch therapy after 3 cycles of treatment if a deep
response is not achieved. Given this, patients achieving PR and NR werecombined because these patients would switch to another treatment regimen
without undergoing an observation period or continuing with their current
therapy.
The option to exit the decision tree after six months was included for flexibility,
based on the six-month responder landmark analysis in the ANDROMEDA trial
and the time by which a patient’s best hematologic response is expected to be
fully established (78, 79). Six-month exit from the decision tree was exploredas a scenario analysis (Section 5.1.2.2.2).
4.1.1.1.2

Markov Model

Upon exit from the decision tree, patients are stratified into one of three
Markov models based on their hematologic response achieved (ie, CR, VGPR, or
PR/NR) as outlined in Figure 4.1. Patients flow through the individual healthstates in an irreversible manner; that is, they can remain in their current stateor transition to a progressive state but they cannot transition back to a healthstate they previously transitioned from. The health states for patients achieving
CR or VGPR differ from patients achieving PR or NR, as described below. For
information pertaining to health state transition probabilities, please refer to
Section 4.2.1.4.
Patients Achieving CR or VGPR:
As outlined in Figure 4.1 and Table 4.1, the Markov models for CR and VGPR
have five identical health states: (1) 1L Tx, (2) Off Tx/FDT, (3) 2L Tx, (4) Endstage Organ Failure, (5) Death. The first health state (1L Tx) is relevant only asa recurring health state when the three-month exit from the decision tree is86selected, because patients with CR or VGPR will remain on-treatment for an
additional three cycles (regardless of their respective treatment arm), after
which they will transition to the ‘Off Tx/FDT’ or ‘End-stage Organ Failure’ states.
While in the ‘Off Tx/FDT’ health state, patients in the DCyBorD arm receive
daratumumab monotherapy for a fixed treatment duration (up to a maximum of
24 cycles) whereas patients in the CyBorD arm stop any treatment and areobserved (ie, have completed their 6 cycles of therapy). Patients in the
DCyBorD arm who remain in the ‘Off Tx/FDT’ health state beyond a maximumof 24 cycles of daratumumab (and who have not transitioned to ‘2L Tx’ or ‘Endstage Organ Failure’) will no longer receive drug therapy and associated costs(similar to CyBorD patients). Regardless of their treatment arm, patients in the‘Off Tx/FDT’ health state can remain in their current health state or transition to‘2L Tx’ or ‘End-stage Organ Failure’ as per transition probabilities derived using
ANDROMEDA data.
In the ‘2L Tx’ health state, patients will start receiving second-line treatment.
Patients can either remain in this health state or transition to ‘End-stage Organ
Failure’.
The ‘End-stage Organ Failure’ health state encompasses patients with majororgan deterioration that require hemodialysis due to end-stage renal failure.
Patients can remain alive within this health state (up to the end of the time
horizon) or die.
At any cycle, patients can die and move from any health state to the absorbing‘Death’ state.
Patients Achieving Partial Response or No Response:
As outlined in Figure 4.1 and Table 4.1, the Markov model for patientsachieving PR or NR has three health states: (1) 2L Tx, (2) End-stage Organ
Failure, (3) Death. The primary difference between the Markov models for
PR/NR and for CR or VGPR is the absence of the ‘1L Tx’ and ‘Off Tx/FDT’ healthstates. According to published literature and our understanding of current
clinical practice in Japan, patients who do not achieve a satisfactory response(ie, PR or NR) early in their treatment course should immediately switch to adifferent treatment regimen (66, 80-82). Thus, those with PR or NR
87

Patients enter this state fromCR, VGPR, PR/NR utilities



Second-line drug therapy

the ‘1L Tx’ health state
Patients can remain in thishealth state or may transition
to ‘2L Tx’, ‘End-stage Organ
Failure’, or ‘Death’‘2L Tx’

Represents patients receiving
second-line therapy due torelapsed (for CR or VGPR) or
refractory (for PR/NR) disease
Patients can enter this healthstate only from the ‘Off
Tx/FDT’ state (for CR or VGPR)

costs (one-time cost)

Incidental healthcare
resource use costs†

CR, VGPR, PR/NR utilities

‘2L Tx’ utility decrement



Recurring end-stage organ

or directly from the decision
tree (for PR/NR)
Patients can remain in thishealth state or transition to‘End-stage Organ Failure’ or‘Death’ states‘End-

Represents patients thatstage

progress to end-stage organ

failure costs (ie,Organfailure.

hemodialysis)

Failure’Patients can enter this healthresource use costs†

state from the ‘1L Tx’ (for CR
or VGPR), ‘Off Tx/FDT’ (for CR
or VGPR), or ‘2L Tx’ healthstates (for CR, VGPR, or

CR, VGPR, PR/NR utilitiesEnd-stage organ failure
health state utility

PR/NR)
Patients can remain in thishealth state until the end of
the simulation or transition to‘Death’90

Incidental healthcare

decrement

Hemodialysis utility
decrement

*All costs and decrements are recurring (ie, per-cycle) unless specifically stated otherwise.
**Reflects costs associated with routine/planned disease monitoring and assessments.
†Reflects costs associated with additional incidental healthcare resource utilization, forexample, emergency room visits.
Abbreviations: 1L = first-line; 2L = second-line; AE = adverse event; AL = amyloid lightchain; CR = complete response; CyBorD = cyclophosphamide, bortezomib, anddexamethasone; DCyBorD = daratumumab, cyclophosphamide, bortezomib, anddexamethasone; FDT = fixed daratumumab treatment; NR = no response; PR =partial
response; Tx = treatment; VGPR = very good partial response.

A half-cycle correction was applied to the calculation of LYs and QALYs and tocertain costs to avoid over- or under-estimating the value of a health state inalignment with patients transitioning part way through a cycle. Half-cycle
corrections are used to reflect the fact that some patient transitions can occur
at any point within the cycle (ie, at cycle start or cycle end). A half-cycle
correction is used with the expectation that patients will, on average, transition
about half-way through a model cycle. Therefore, half of the costs and benefits
are assigned in each state to avoid under- or over-estimating the value of thehealth state. In the model, half-cycle corrections have been applied byaveraging the costs and benefits between two cycles. A half-cycle correction
was applied to first-line drug therapy costs, first-line drug administration costs,
first-line co-medication costs, healthcare resource use costs, disease monitoring
costs, recurring end-stage, and organ failure costs. Costs that were applied as a
one-time cost (ie, AE management, second-line drug therapy, and end of life)
were not half-cycle corrected since the timing of events within that cycle isirrelevant.
4.1.2 Model assumptions
Several assumptions were required in the model and are summarized in Table
4.2.

91

patient outcomes and clinical practice
are similar for both (66, 80)).
Very few MOD events occurred in thefirst data cut of the trial (February
2020; median follow-up: 11.4
months) (78), supporting that end
Major organ failure is not captured instage organ failure would happen in

the decision tree (first 3 months). It

long-term. Further, patients withis captured in the Markov model.

severe organ involvement (NYHAclassification IIIB or IV heart failure )were not suitable for DCyBorD or
CyBorD treatment and were excluded
from the study population.
Published OS curves from Kastritis etal., (2020) were available up to a

A retrospective study Kastritis et al.,maximum of ~12 years (71). To(2020) was used to estimate the OS

project long-term survival over the

associated with different hematologic

lifetime time horizon, methodologicalresponses independent of treatment.

best practices were followed for

The OS curves for PR/NR, VGPR, andCR were generated based on
independent extrapolations of theirraw KM data.

extrapolating and choosing the mostclinically valid distributions. The
proportional hazards assumption did
not hold for the KM curves; therefore,
separate extrapolations were
performed for CR, VGPR, PR, and NR.
With this approach, the resulting
long-term survival also appeared
clinically valid.

Risk of mortality of patients with AL
amyloidosis in the model cannot belower than the risk of mortality of thegeneral population.

93

Japanese general populationmortality rates (86) were
implemented in the model such thatthe extrapolations will be adjusted toensure that the hazard of death ateach cycle did not drop below that of
the general population (ie, predictedsurvival could not exceed general
population).
There is not enough long-term trial
data to indicate when/if health statespecific mortality risks and transition
probabilities change over time. Since
mortality risk by health state canchange once patients finish
Mortality distributions (from cycles 46 and from cycle 7+) and transition
probabilities are assumed to beconstant over time.

treatment, mortality distributions
pre- and post-cycle 6 were
estimated. Very few deaths were
captured in the trial after cycle 6 dueto short follow-up; therefore, a fixed
distribution assumption was applied.
The KM curves used to estimate thetransition probabilities were generally
linear, and thus it was a pragmatic
assumption to use a constantprobability.
Due to lack of data to inform thistransition probability from the

The transition probabilities for ‘1L Tx’

ANDROMEDA study, we assumed theto ‘End-stage Organ Failure’ are thetransition probability of ‘2L Tx’ tosame for ‘2L Tx’ to ‘End-stage Organ‘End-stage Organ Failure’ should be

Failure’.

at least the same as the transition
probability for ‘1L Tx’ to ‘End-stage
Organ Failure’.

All patients with VGPR and CR will

As outlined in the ANDROMEDA

complete the full six cycles ofprotocol, patients were to receive 6

treatment. Patients with PR/NR will

cycles of CyBorD (CyBorD arm) or 6

immediately switch to a subsequent

cycles of DCyBorD followed by up to94therapy after three cycles of

18 cycles of daratumumab

treatment if three-month exit frommonotherapy, unless they had athe decision tree is selected (as in the

suboptimal (≤PR) hematologic

main analysis).

response and could be switched toanother therapy after 3 cycles inaccordance with clinical expert
feedback on real-world practices (24,79, 80). Since there is no clinicalrationale for patients with deep
hematologic response (≥VGPR) to
change their treatment regimen, it
was assumed that all patients in the
CyBorD treatment arm with VGPR or
CR would receive up to the full 6
cycles of CyBorD and then cease
treatment. Similarly, all patients inthe DCyBorD arm with VGPR or CR
were assumed to receive the first six
cycles of DCyBorD (in alignment with
the ANDROMEDA CSR) (78). After the
first 6 cycles, patients in the
DCyBorD arm could continue withdaratumumab monotherapy inaccordance with the values specified
on “Time on Treatment” sheet.

For any drug with multiple modes of

IV infusion may cause fluid volume

administration, IV was not selected

overload in patients with AL

as the administration route of choice

amyloidosis and would, therefore, notfor estimating cost of administration.

be appropriate in these patients.

Drug wastage and RDI were
accounted for in drug costs.
Subsequent therapy costs are applied
95

Important to accurately calculate thetrue (real-world) treatment cost foran average patient.
The duration of second-line therapy

as a one-time cost.

was poorly reported in the literature.
As such, the cost of subsequent
therapy was applied as a one-time
tariff to avoid overestimating costs.
Real-world evidence and clinicalexpert feedback indicate that mostSubsequent therapy costs for ‘2L Tx’
health state reflect patients receiving
one subsequent line of therapy.

patients do not receive multiple linesof subsequent therapy (70, 87-89).
Furthermore, the majority of patients() in the ANDROMEDA trial

only received one subsequent line oftherapy (78).
Best available data sources in AL
amyloidosis:
Rd: Sanchorawala et al., (2007)(median number of cycles completed
by study subjects was 6) (90);BMd: Palladini et al., (2014) (median
number of treatment cycles received
The number of cycles of treatment

was 4) (91);used to calculate second-line therapy

CyBorD: ANDROMEDA protocol

costs was 6 for Rd, 4 for BMd, 6 for(assumed the maximum number of

CyBorD, 4 for TCd, and 6 forcycles per the ANDROMEDA protocol)

DCyBorD.

(24);
TCd: Venner et al., (2014) (median
number of treatment cycles received
was 4); Wechalekar et al., (2007)(76, 92);
DCyBorD: ANDROMEDA protocol(although daratumumab could be
administered up to a maximum of 24
cycles, a total of 6 cycles was used in96the model as a conservative
assumption since long-term
administration/adherence data are
not available from the ANDROMEDA
trial) (24).
The utility decrement applied for ‘2L
Tx’ is the difference between themean utility value prior to reaching a‘progressive disease’ state and themean utility value once in a‘progressive disease’ state according
to ANDROMEDA IPD.

Due to the paucity of data for
decrements attributable to these
health states, this was a simplifying
assumption whereby ‘progressive
disease’ is analogous to commencing
second-line treatment.
Grade 3-4 AEs were assumed to be
costly/severe events that could
require hospitalization and utility

AE management costs/disutilities
reflect grades 3 and 4 events and areapplied as a one-time upfront
cost/disutility in the first cycle.

decrements. AEs were assumed to betreatment-emergent and because
treatment is a fixed course of therapy
with limited duration, AE
management costs and disutilities
were applied in the first cycle suchthat they would apply to all patientsthat received treatment.
AL Amyloidosis a designated

Incidental healthcare resource use(proportion of patients requiring each
item and usage frequency) for
patients in ‘2L Tx’ and ‘End-stage
Organ Failure’ health states is
equivalent to that of patients in the‘1L Tx’ health state.

intractable disease with low
prevalence in Japan. We attempted toleverage MDV data to inform
incidental healthcare resource use byhealth state (see Appendix H).
However, due to a paucity of datafrom the database, the incidental
healthcare resource use for ‘2L Tx’and ‘End-stage Organ Failure’ health974.2 Parameters Used in the Analysis
Table 4.3 provides a summary of the model inputs used in the main analysis.
Please refer to the corresponding sections for additional details.

99

Discount rate - effects

2.0%

N/A

N/A

Discount rate - costs

2.0%

N/A

N/A

Both cost and effectiveness should be discounted at a
rate of 2% per year as per current C2H guidelines (43).

Patient Characteristics
Starting age (years)

NormalProportion male

Beta

Mean weight (kg)NormalMean age and the proportion of male subjects are
based on all subjects included in the ANDROMEDA
study (78). Starting patient age and the proportion ofmale subjects were closely aligned with the Japanese
population reported by Shimazaki et al., (2018) (19)(median age: 65; percent male subjects: 58.8%);
therefore, ANDROMEDA values were used to inform theMean body surface area

Normal(m2)

main analysis. Body weight and BSA is based on the
Asian subjects included in the ANDROMEDA study(n=60) to better reflect Japanese patientcharacteristics (98).

Efficacy Data
DCyBorD arm:
Hematologic responseand death distribution at
three months (exit from
101

CR:
VGPR:
PR/NR:

N/A

N/A

ANDROMEDA IPD post hoc analysis (18-month
landmark data cut, data on file) (98).

decision tree)

Dead:

CyBorD arm:

CR:

Hematologic responseand death distribution at
three months (exit fromdecision tree)

VGPR:
PR/NR:

N/A

N/A

Dead:
After digitizing and extrapolating the PR and NR KM
curves from Kastritis et al., (2020), the Weibull

PR/NR survival function

Weibull

N/A

N/A

parametric survival function was a good visual fit to the
PR and NR KM data and generated the curve of best-fit
for the larger proportion of patients with PR/NR (71).
According to clinical validity, visual assessment, andCR survival function

Exponential

N/A

N/A

curve fit statistics, the Exponential parametric survival
function generated the curve of best-fit for patientswith CR (71).
According to clinical validity, visual assessment, and

VGPR survival function

Log-logistic

N/A

N/A

curve fit statistics, the Log-logistic parametric survival
function generated the curve of best-fit for patientswith VGPR (71).

Proportion of patients in
102

Beta

ANDROMEDA IPD post hoc analysis (18-monthused to inform treatment discontinuation applicable inthe model.
CyBorD Time on

Cycles 1-6:

Treatment

100%

Cycles 1-6: assumption that patients achieving CR or
N/A

N/A

VGPR will continue their current treatment regimen to a
maximum of 6 cycles.

First-line Drug Costs
DCyBorD (Cycles 1-2)

￥ 1,937,112.40

DCyBorD (Cycles 3-6)

￥ 1,046,984.40

DCyBorD (Cycle 7+)￥ 445,064.00

CyBorD￥ 156,856.40

N/A

N/A

N/A

N/A

N/A

N/A

NHI Price List, (2022) (99).

First-line Drug Dosing
Cycles 1-2:
1,800 mg; 4administrations
Daratumumab

per cycle
Cycles 3-6:
1,800 mg; 2administrations
per cycle

104

Aligned with product label (25) and ANDROMEDA
protocol (24).

Cycle 7+: 1,800mg; 1administration
per cycle
1.3 mg/m2; 4Bortezomib

administrations

N/A

N/A

N/A

N/A

N/A

N/A

per cycle
300 mg/m2; 4Cyclophosphamide

administrations
per cycle
40 mg; 4

Dexamethasone

administrations
per cycle

First-line Drug Relative Dose Intensity (RDI)
DCyBorD RDI(daratumumab)
DCyBorD RDI

Beta
Beta

(bortezomib)
DCyBorD RDI
105

Beta

ANDROMEDA CSR (data on file) (78).

(cyclophosphamide)
DCyBorD RDI

Beta(dexamethasone)
CyBorD RDI

Beta(bortezomib)
CyBorD RDI

Beta(cyclophosphamide)
CyBorD RDI

Beta(dexamethasone)First-line Drug Administration Costs per cycle
DCyBorD (Cycles 1-2)

￥ 3,120.00

312

Gamma

DCyBorD (Cycles 3-6)

￥ 2,680.00

268

Gamma

DCyBorD (Cycles 7+)￥ 220.00

22

Gamma

CyBorD￥ 2,240.00

224

Gamma

Unit costs: Saeki et al., (2020) (100), Japan MHLW
Medical Fee Schedule, (2022) (101), NHI Price List,(2022) (99).
Frequency: ANDROMEDA protocol (24).

First-line Co-medication Costs
DCyBorD￥ 1,907.80

190.78Gamma

Unit costs: NHI Price List, (2022) (99).

CyBorD￥ 1,663.20

166.32

Gamma

Type and frequency: ANDROMEDA protocol (24).

106

First line (Routine) Disease Monitoring Costs
1L Tx￥ 23,618.90

2367.89

Gamma

Unit costs: Japan MHLW Medical Fee Schedule, (2022)

FDT￥ 8,798.90

882.89Gamma(101).

Off Tx￥ 5,360.00

536.00Gamma

Type and frequency: ANDROMEDA protocol (24).

10106.9

Gamma

Cost per event: Japan MHLW Medical Fee Schedule,

Adverse Event Management Costs
DCyBorD￥ 101,069.34

3384￥ 68,610.25

6861.02(2022) (101), Inoue et al., (2020) (102), NHI Price List
Gamma

495

2022 (99), Usami et al., (2014) (103), Akashi et al.,(2012) (104), MDV data analysis (See Appendix H)(94).

CyBorD

Proportion of patients experiencing AEs: Janssen Data
on File 2021 (ANDROMEDA 18-month landmark
analysis) (105).

AE Utility Decrements
DCyBorD

Gamma

Decrement per event: Nafees et al., (2008) (106),
Onouchi et al., (2014) (107), Beusterien et al., (2010)(108), Ishida et al., (2012) (109), Stein et al., (2018)

CyBorD

Gamma(110), Shiroiwa et al., (2009) (111), Brown et al.,(2001) (112), Saito et al., (2014) (113), Sullivan et al.,107(2011) (114), Usami et al., (2014) (103), Akashi et al.,(2012) (104), Inoue et al., (2020) (102).
Proportion of patients experiencing AEs: Janssen Data
on File 2021 (ANDROMEDA 18-month landmark
analysis) (105).
Second-line Drug Therapy Costs
Rd:
Second-line drug
therapy proportions for
DCyBorD patients

Second-line drug
therapy proportions for
CyBorD patients

BMd:

%

TCd:

%

Rd:

%

N/A

N/A

%

Best available data sources from: Shimazaki et al.,(2018) (19); Janssen Japan internal assumption.

%

CyBorD:
TCd:

N/A

%

CyBorD:

BMd:

N/A

%

%

DCyBorD: %Second-line drug
therapy costs for
DCyBorD patients108￥ 1,323,417.67

132341.
7668

Unit cost: ANDROMEDA CSR (78), NHI Price List,
Gamma(2022) (99).
Proportion of 2L patients receiving regimen: Shimazaki

Second-line drug
therapy costs for CyBorD￥ 1,667,882.67

patients

166788.
2668

et al., (2018) (19), Janssen Japan Internal Assumption.
Gamma

End-stage Organ Failure Costs
Unit cost: Takura et al., (2019) (115).
Proportion of patients requiring treatment:
Recurring organ failure
costs per cycle￥ 353,434.64

35343.4
6388

Gamma

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95),
MDV database analysis (See Appendix H, Data onFile) (94).

Incidental Healthcare Resource Use Costs
1L Tx

Off Tx/FDT

2L Tx

End-stage Organ Failure

109￥ 91,319.33￥ 50,258.17￥ 91,319.33￥ 91,319.33

9131.93

Gamma

3401
5025.81

Unit cost: Japan MHLW Medical Fee Schedule, (2022)
Gamma

6914
9131.93

visit code: A002) (101), MDV database analysis (See
Gamma

3401

Appendix H, Data on File) (94).
Proportion of patients requiring item: Janssen Japan

3401
9131.93(101) (inpatient hospitalization code: A105, outpatient

Gamma

Data on File, (2021) (116).

End of Life Costs
Costs associated with

￥ 662,205.59

66220.5

Gamma

Japan Medical Association, (2007) (117).

CR

Beta

ANDROMEDA IPD (primary analysis; February 2020;

VGPR

Beta

final month of life

5901

Utilities

Beta

median follow-up: 11.4 months, data on file) reanalysis with Japanese tariff (95).
Utility value assigned to VGPR is the mean of utility
value of CR (PR/NR) and PR ().

PR/NR utility value is weighted average of PR and NR
utility values (
utility(%*PR utility (

)+

%*NR

))§

ANDROMEDA IPD (primary analysis; February 2020;
2L Tx health state utility
decrement

Gamma

median follow-up: 11.4 months, data on file) reanalysis with Japanese tariff; utility decrement
associated with 'progressed disease' (95).
Calculated as the difference between the baseline

End-stage organ failure
health state utility
decrement
110

Gamma

utility value for all ANDROMEDA patients and the utility
value from patients with advanced chronic heart failure
listed for heart transplant per Emin et al., (2016)

(118).
Recurring utility value decrement applied to all patients
Hemodialysis utility
decrementcommencing hemodialysis. Calculated as the difference
0.1

0.01

Gamma

between patients with chronic kidney disease prehemodialysis and after commencing hemodialysis per
Wyld et al., (2012) (119).

Transition Probabilities†
CR transition probability(cycle 4-6): 1L Tx to

Dirichlet

Dirichlet

Dirichlet

Dirichlet

End-stage Organ Failure

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

CR transition probability(cycle 4-6): 1L Tx to Off
Tx/FDT

to ‘End-stage organ failure’ will remain on 1L Tx for

CR transition probability(cycle 4-6): Remain in

All patients with CR in ‘1L Tx’ that have not transitioned

Dirichlet

Dirichlet

Dirichlet

Dirichlet

cycles 4-6.

1L Tx
CR transition probability(cycle 4-6): Off Tx/FDT
to End-stage Organ
Failure111

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

ANDROMEDA IPD (12-month landmark analysis;

CR Transition probability(cycle 4-6): Off Tx/FDT

Dirichlet

Dirichlet

November 2020; median follow-up: 20.3 months, data

to 2L Tx

on file) (120).

CR Transition probability

All patients with CR in ‘Off Tx/FDT’ who have not(cycle 4-6): Remain in

Dirichlet

Dirichlettransitioned to ‘2L Tx’ or ‘End-stage organ failure’ willremain in the ‘Off Tx/FDT’ health state.

Off Tx/FDT
CR transition probability(cycle 4-6): 2L Tx to
End-stage Organ

Dirichlet

Dirichlet

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

Failure‡All patients with CR in ‘2L Tx’ who have not

CR transition probability(cycle 4-6): Remain in

Dirichlet

Dirichlettransitioned to ‘End-stage organ failure’ will remain on
2L Tx.

2L Tx
VGPR transition
probability (cycle 4-6):
1L Tx to End-stage

Dirichlet

Dirichlet

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

Organ Failure
All patients with VGPR in ‘1L Tx’ that have not

VGPR transition
probability (cycle 4-6):
1L Tx to Off Tx/FDT
112

Dirichlet

Dirichlettransitioned to ‘End-stage organ failure’ will remain in‘1L Tx’ for cycles 4-6.

VGPR transition
probability (cycle 4-6):

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Remain in 1L Tx
VGPR transition
probability (cycle 4-6):
Off Tx/FDT to End-stage

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

Organ Failure
ANDROMEDA IPD (12-month landmark analysis;

VGPR transition
probability (cycle 4-6):

Dirichlet

Dirichlet

November 2020; median follow-up: 20.3 months, data

Off Tx/FDT to 2L Tx

on file) (120).

VGPR transition

All patients with VGPR in ‘Off Tx/FDT’ that have notprobability (cycle 4-6):

Dirichlet

Dirichlettransitioned to ‘2L Tx’ or ‘End-stage organ failure’ willremain in the ‘Off Tx/FDT’ health state.

Remain in Off Tx/FDT
VGPR transition
probability (cycle 4-6):
2L Tx to End-stage

Dirichlet

Dirichlet

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

Organ Failure‡
All patients with VGPR in ‘2L Tx’ that have not

VGPR transition
probability (cycle 4-6):
Remain in 2L Tx
113

Dirichlet

Dirichlettransitioned to ‘End-stage organ failure’ will remain in
2L Tx.

PR/NR transition
probability (cycle 4-6):
1L Tx to End-stage

Dirichlet

Dirichlet

Dirichlet

Dirichlet

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

Organ Failure
PR/NR transition
probability (cycle 4-6):
1L Tx to 2L Txtransitioned to ‘End-stage organ failure’ will transition

PR/NR transition
probability (cycle 4-6):

All patients with PR/NR in ‘1L Tx’ that have not

Dirichlet

Dirichlet

Dirichlet

Dirichlet

to ‘2L Tx’.

Remain in 1L Tx
PR/NR transition
probability (cycle 4-6):
2L Tx to End-stage

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

Organ Failure‡
All patients with PR/NR in ‘2L Tx’ that have not

PR/NR transition
probability (cycle 4-6):

Dirichlet

Dirichlet‘2L Tx’.

Remain in 2L Tx
CR transition probability(cycle 7+): 1L Tx to
End-stage Organ Failure
114

transitioned to ‘End-stage organ failure’ will remain in

Dirichlet

Dirichlet

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

CR transition probability(cycle 7+): 1L Tx to Off

Dirichlet

Dirichlet

Tx/FDT

have not transitioned to end-stage organ failure) will

CR transition probability(cycle 7+): Remain on

All patients remaining in the ‘1L Tx’ health state (ie,Dirichlet

Dirichlet

Dirichlet

Dirichlettransition to the ‘Off Tx/FDT’ health state after cycle 6.

1L Tx
CR transition probability(cycle 7+): Off Tx/FDT
to End-stage Organ

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

FailureANDROMEDA IPD (12-month landmark analysis;

CR Transition probability(cycle 7+): Off Tx/FDT

Dirichlet

Dirichlet

November 2020; median follow-up: 20.3 months, data

to 2L Tx

on file) (120).

CR Transition probability

All patients with CR in ‘Off Tx/FDT’ who have not(cycle 7+): Remain in

Dirichlet

Dirichlettransitioned to ‘2L Tx’ or ‘End-stage organ failure’ willremain in the ‘Off Tx/FDT’ health state.

Off Tx/FDT
CR transition probability(cycle 7+): 2L Tx to
End-stage Organ
Failure‡115

Dirichlet

Dirichlet

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

All patients with CR in ‘2L Tx’ who have not

CR transition probability(cycle 7+): Remain on

Dirichlet

Dirichlettransitioned to ‘End-stage organ failure’ will remain inthe ‘2L Tx’ health state.

2L Tx
VGPR transition
probability (cycle 7+):
1L Tx to End-stage

Dirichlet

Dirichlet

Dirichlet

Dirichlet

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

Organ Failure
VGPR transition
probability (cycle 7+):
1L Tx to Off Tx/FDT

transitioned to ‘End-stage organ failure’ will transition

VGPR transition
probability (cycle 7+):All patients with VGPR in ‘1L Tx’ who have not

Dirichlet

Dirichlet

Dirichlet

Dirichlet

to the ‘Off Tx/FDT’ health state after cycle 6.

Remain on 1L Tx
VGPR transition
probability (cycle 7+):
Off Tx/FDT to End-stage

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

Organ Failure
ANDROMEDA IPD (12-month landmark analysis;

VGPR transition
probability (cycle 7+):
Off Tx/FDT to 2L Tx
116

Dirichlet

Dirichlet

November 2020; median follow-up: 20.3 months, dataon file) (120).

All patients with VGPR in ‘Off Tx/FDT’ who have not

VGPR transition
probability (cycle 7+):

Dirichlet

Dirichlettransitioned to ‘2L Tx’ or ‘End-stage organ failure’ willremain in the ‘Off Tx/FDT’ health state.

Remain in Off Tx/FDT
VGPR transition
probability (cycle 7+):
2L Tx to End-stage

Dirichlet

Dirichlet

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

Organ Failure‡
VGPR transition
probability (cycle 7+):All patients with VGPR in ‘2L Tx’ who have not
Dirichlet

Dirichlettransitioned to ‘End-stage organ failure’ will remain inthe ‘2L Tx’ health state.

Remain on 2L Tx
PR/NR transition
probability (cycle 7+):
1L Tx to End-stage

Dirichlet

Dirichlet

Dirichlet

Dirichlet

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

Organ Failure
PR/NR transition
probability (cycle 7+):All patients with PR/NR in ‘1L Tx’ who have not

1L Tx to 2L Txtransitioned to ‘End-stage organ failure’ will transition

PR/NR transition

to ‘2L Tx’ since the patients failed to achieve CR orprobability (cycle 7+):
Remain on 1L Tx
117

Dirichlet

Dirichlet

VGPR.

PR/NR transition
probability (cycle 7+):
2L Tx to End-stage

Dirichlet

Dirichlet

ANDROMEDA IPD (primary analysis; February 2020;
median follow-up: 11.4 months, data on file) (95).

Organ Failure‡
All patients with PR/NR in ‘2L Tx’ who have not

PR/NR transition
probability (cycle 7+):

Dirichlet

Dirichlettransitioned to ‘End-stage organ failure’ will remain on
2L Tx.

Remain on 2L Tx
Mortality Distributions
Mortality Distribution(cycles 4-6): 1L Tx

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Mortality Distribution(cycles 4-6): Off 1L
Tx/FDT
Mortality Distribution(cycles 4-6): 2L Tx

ANDROMEDA IPD (primary analysis; February 2020;
Dirichlet

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Mortality Distribution(cycles 4-6): End-stage
Organ Failure
Mortality Distribution
118

median follow-up: 11.4 months, data on file) (95).

(cycles 7+): 1L Tx
Mortality Distribution(cycles 7+): Off 1L

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Dirichlet

Tx/FDT
Mortality Distribution(cycles 7+): 2L Tx
Mortality Distribution(cycles 7+): End-stage
Organ Failure
Mortality Distribution,
Decision tree (Assigning
end of life costs): CR
Mortality Distribution,
Decision tree (Assigning
end of life costs): VGPR
Mortality Distribution,
Decision tree (Assigning
end of life costs): PR/NR* Only applicable if a probabilistic analysis is run.
** The proportion of patients remaining on treatment decreases gradually from119

% (cycle 7) to% (cycle 24) as observed in the

ANDROMED trial (18-month landmark analysis IPD) (98); patient proportions for cycles 8-23 are located on the ‘Time on Treatment’ sheet in
the model.
† CR and VGPR criteria as defined in the ANDROMEDA CSR (78); transition probabilities are applicable to both DCyBorD and CyBorD.
§ Weighting applied in the calculation of the PR/NR utility value was derived using the number of patients for which the respective utility values

were recorded. For PR and NR, there wereapplied for PR was

andmeasures, respectively (combined total of% and the weight applied for NR was

measures). Therefore, the weighting%.

‡ Due to a limited number of MOD-PFS events reported, a simplifying assumption was made whereby the transition probabilities for ‘2L Tx’ to‘End-stage Organ Failure’ were assumed equivalent to those from ‘1L Tx’ to ‘End-stage Organ Failure’.
Abbreviations: 1L = first-line; 2L = second-line; AE = adverse event; AL = amyloid light-chain; C2H = Center for Outcomes Research andEconomic Evaluation for Health; CR = complete response; CSR = clinical study report; CyBorD = cyclophosphamide, bortezomib, anddexamethasone; DCyBorD = daratumumab, cyclophosphamide, bortezomib, and dexamethasone; FDT = fixed daratumumab treatment; HR =hazard ratio; IPD = individual participant data; kg = kilogram; KM = Kaplan-Meier; m = meter; mg = milligram; MHLW = Ministry of Health,
Labor, and Welfare; N/A = not applicable; NR = no response; PR = partial response; RDI = relative dose intensity; SD = standard deviation; Tx= treatment; VGPR = very good partial response.

1204.2.1 Efficacy Parameters
Efficacy parameters in the model were derived from three studies:
ANDROMEDA, Kastritis et al., (2020), and Palladini et al., (2012). As describedin Section 4.1.1.1, the model structure was developed based on the use ofhematologic response as a measure of treatment efficacy. Therefore, to informthe model, decision tree data and OS curves stratified by hematologic response
were needed. Hematologic response data from ANDROMEDA was used to informparameters for the decision tree (see Section 4.2.1.1). However, because%of patients were still alive in the ANDROMEDA trial at the time of the firstclinical cut-off (February 2020; median follow-up: 11.4 months), statisticallyrobust long-term extrapolation of effectiveness was limited by the ANDROMEDAOS KM data immaturity. As such, external published data (ie, Kastritis et al.,[2020] and Palladini et al., [2012]) identified through a targeted literaturesearch was used to inform long-term OS in the Markov model (see Section
4.2.1.1).
Kastritis et al., (2020) was a retrospective study aimed to evaluate thesignificance of an early and deep hematologic response in patients treated firstline with bortezomib-based regimens (71). Data from this study was used to
inform long-term OS in the main analysis (ie, 3-month decision tree exit).
The study by Palladini et al., (2012) was a retrospective study aimed to identify
and validate criteria for response to first-line treatment in AL amyloidosis (74).
Data from this study is used to inform long-term OS in the model only if 6month decision tree exit is selected (included as a scenario analysis in Section
5.1.2.2). A summary of the three studies used to inform OS in the model isprovided in Table 4.4.

121

Mp (2.4%)
Other (11.1%)
Median Follow-up

11.4 months (primary

48 months

33 months

The Kaplan-Meier method

Descriptive statistics were

Survival was calculated from the time

was used to estimate time-reported as medians with rangeof evaluation of response.

to-event distributions.

values.

Hazard ratios and 95% CIs

All efficacy analyses are on an ITT

were estimated using abasis, unless otherwise specified.

analysis)
Statistical Methods

stratified Cox proportional
hazards regression model.
The infusion-related
reaction rate and rates ofvery good partial responseor better were compared
between groups using astratified Cochran-MantelHansel test.

Cox models were fitted to compute
HRs and 95% CIs for death.
To measure model performance, theFor between groups comparisons

Harrell concordance statistic and thethe chi-square test was used.

Royston explained variation wereTime to event was calculated fromcomputed.

the date of first treatment until

The ability of the selected responsethe date of death or other event

criteria to identify groups of patientsor until the date of last follow up

with different survival was tested in

if the respective event has not

the validation cohort.

occurred. Analyses were
performed using SPSS.

Survival curves were plotted using
the Kaplan-Meier method.
STATA 11 and MedCalc 11 were used123

for computation.
Age (median, years)

64.0 (range: 34-87)

65 (range: 40-84)

63 (IQR: 55-71)

Sex (% male)

58.0%

57%

59.9%

Organ Involvement (#,2 (range:1-6)

NR

2 (IQR: 1-2)

59.0%

70%

68.1%

71.4%

69%

64.8%

8.0%

19%

16%

I

23.2%

18%

30.9%

II

40.2%

52.5%

43.7%

III

NR

29.5%*

25.4%

IIIa

34.5%

18%

NR

IIIb

2.1%

11.5%

NR

NT-proBNP (ng/L,

2307.9 (range: 51-12950)

NR

1587 (IQR: 351-4,670)

187.1 (range: 1-9983)

194 (range: 50-8987)

157 (IQR: 70-460)

median)Kidney (%)
Heart (%)
Liver (%)
Mayo Cardiac Stage (%)

median)dFLC (mg/L, median)124

* Calculated based on the percentage of patients with Mayo stage IIIa and IIIb.
Abbreviations: ASCT = autologous stem cell transplant; CI = confidence interval; CyBorD = cyclophosphamide, bortezomib, dexamethasone;
DCyBorD = daratumumab, cyclophosphamide, bortezomib, dexamethasone; dFLC = difference in free light-chains; HR = hazard ratio; IQR =interquartile range; ITT = intent-to-treat; Md = melphalan, dexamethasone; Mp = melphalan, prednisone; NT-proBNP = N-terminal
prohormone B-type natriuretic peptide; OS = overall survival; RCT = randomized controlled trial.
Sources: ANDROMEDA CSR (78), Kastritis et al., (2021) (50), Kastritis et al., (2020) (71), Palladini et al., (2012) (74).

125

4.2.1.1 Modelling Effectiveness in the Decision Tree
The decision tree highlighted the treatment benefit of DCyBorD; that is,affording patients deeper hematologic response earlier in the treatment course.
Patient-level data from the ANDROMEDA 18-month landmark analysis (May2021; median follow-up: 25.8 months) (98) was used to inform the decision
tree with respect to the proportion of patients in each treatment group
achieving CR, VGPR, and PR/NR or who died within each one-month window(assumed to be equal to one model cycle). Of note, a two-month window wasused to capture hematologic response data at the decision tree exit timepoint(ie, cycle 3 in the main analysis) to be consistent with the assumed method forreporting landmark CR rate in the ITT landmark analysis. In essence, thedecision tree reflects a snapshot of patients’ hematologic response status ateach assessment timepoint. For any instance where an alive patient’s
hematologic response status was not reported in a particular cycle, they wereclassified as PR/NR (a simplistic assumption that was applied equally to both
treatment groups in order to avoid overestimating treatment benefit). The
patient distribution within the 3-month decision tree is shown in126

Table 4.5.

127

4.2.1.2 Modelling Effectiveness in the Markov Model
Survival curve extrapolation was performed as described in the NICE TechnicalSupport Document (TSD) 14 for survival analysis for economic evaluations(121). Cox proportional hazard assumptions were tested for OS data, andpairwise hazard ratios (HRs) were calculated (see Appendix D). Parametersand model fit statistics (ie, Akaike’s information criterion [AIC], Bayesian
information criterion [BIC]) were calculated for each curve type and arepresented below in Table 4.6. A list of all parametric survival functions,
extrapolation parameters, and covariance matrices used in the model arepresented in Appendix E.

129

Within the decision tree (see Section 4.2.1.1), the number of deaths in eachcycle was dependent on treatment (as reported in the ANDROMEDA trial),
rather than on hematologic response. In contrast, OS in the Markov model was
dictated by depth of hematologic response as a surrogate for OS, according to
the KM curves published by Kastritis et al., (2020) (71). That is, OS isdependent on the survival curves stratified by CR, VGPR, and PR/NR regardlessof which treatment regimen patients receive. Therefore, the distribution ofhematologic response achieved at the end of the decision tree was assumed to
predict treatment-specific OS over time. This assumption is supported by thewealth of evidence supporting the relationship between depth of hematologic
response and improved OS (21, 32, 33, 62, 68-70, 72-74, 76, 84, 85), and isaligned with the goal of AL amyloidosis treatment to achieve the besthematologic response possible (66).
Overall Survival for 3-month PR/NR:
After digitizing and extrapolating the PR and NR KM curves based on thereconstructed pseudo-IPD from Kastritis et al., (2020) (71), the curves werevisually assessed. The PR KM curve and its associated curve extrapolations arepresented in Figure 4.2 and the survival rate over time for patients with PR ispresented in Table 4.7. The NR KM curve and its associated extrapolations arepresented in Figure 4.3 and the survival rate over time for patients with NR ispresented in Table 4.8. All curves were shown to appropriately fit the PR and
NR KM data, but the Exponential, Weibull, and Gamma extrapolations appeared
most clinically plausible and were further considered for the main analysis.
According to ANDROMEDA IPD (18-month landmark analysis; May 2021;
median follow-up 25.8 months, data on file) (98), patients that achieve PR
comprise% of all patients that are PR or NR at the three-month landmark

irrespective of treatment arm. Because patients with PR represented a larger
proportion of the weighting applied in generating the blended PR/NR curve inthe main analysis, AIC and BIC values for the PR curve were used to determine
which parametric survival function should be used for the blended PR/NR curve.
According to AIC and BIC (Table 4.6), the Weibull parametric survival function
was the best statistical fit and was therefore selected for the main analysis. Of
note, the Weibull survival function was also clinically plausible and a good visual
fit to the NR KM curve.
131

133

*Only the starting number at risk was reported by Kastritis et al., (2020) (71); all remaining
numbers at risk were generated by creating pseudo-IPD during the curve extrapolation
process according to the methods described by Guyot et al., (2012) (122).
**Because pseudo-IPD was used in the curve extrapolation process, the number of censors
is not available.
Abbreviations: IPD = individual patient data; NR = not reported.

134

136

*Only the starting number at risk was reported by Kastritis et al., (2020) (71); all remaining
numbers at risk were generated by creating pseudo-IPD during the curve extrapolation
process according to the methods described by Guyot et al., (2012) (122).
**Because pseudo-IPD was used in the curve extrapolation process, the number of censors
is not available.
Abbreviations: IPD = individual patient data; NR = not reported.

137

*Only the starting number at risk was reported by Kastritis et al., (2020) (71); all remaining
numbers at risk were generated by creating pseudo-IPD during the curve extrapolation
process according to the methods described by Guyot et al., (2012) (122).
**Because pseudo-IPD was used in the curve extrapolation process, the number of censors
is not available.
Abbreviations: IPD = individual patient data; NR = not reported.

140

142

*Only the starting number at risk was reported by Kastritis et al., (2020) (71); all remaining
numbers at risk were generated by creating pseudo-IPD during the curve extrapolation
process according to the methods described by Guyot et al., (2012) (122).
**Because pseudo-IPD was used in the curve extrapolation process, the number of censors
is not available.
Abbreviations: IPD = individual patient data; NR = not reported.

4.2.1.3 Mortality Distribution
Within the Markov model, the extrapolated OS curves were used to determine
the transitions to death (ie, the number of patients who died between cycles n
and n+1). The number of patients alive in each health state per cycle wasdetermined using both mortality distribution and transition probabilities.
The probability of survival determined the number of deaths per cycle, but notwhich health states those deaths came from. Instead of assuming an equal riskof death across health states, the state-specific probabilities of mortality fromthe trial were used. In addition, because early, sudden deaths (while ontreatment) are possible in patients with AL amyloidosis, two different mortality
distributions were considered in the model to account for the potential change
in early vs. long-term health state-specific probabilities of mortality. All deaths
that occurred over the trial period (during the first 6-months and from post-6143

trial and are described further below. Given the current data availability fromthe trial, constant transition probabilities were used.
The transition probability to ‘End-stage Organ Failure’ was generated using
ANDROMEDA IPD pertaining to time-to-MOD-PFS (which included hematologic
progression and major organ deterioration events but excluded deaths
according to the primary analysis; February 2020; median follow-up: 11.4
months, data on file) (95) stratified by hematologic response irrespective oftreatment arm (note that the stratification of hematologic response was basedon the 3-month timepoint due to larger sample size for generating the curves).
Since extrapolation would be highly uncertain due to the lack of long-term
events, constant hazard rates were instead calculated from the curves (Figure4.7) and converted to a per-cycle probability. The monthly probability for MODPFS stratified by hematologic response is presented in Table 4.13 and the
MOD-PFS rate over time for patients with CR, VGPR, and PR/NR is presented inAppendix F.
Because patients from ‘1L Tx’, ‘Off Tx/FDT’, and ‘2L Tx’ can all transition to‘End-stage Organ Failure’ at any given cycle, the monthly probability of MODPFS was further stratified based on the distribution of MOD-PFS events(excluding deaths) that occurred by health state (Table 4.13). Owing to someunrealistic values for patients on second-line therapy (eg, no MOD-PFS eventsoccurred for patients with VGPR), a simplifying (and likely conservative)
assumption was made whereby the transition probabilities for ‘2L Tx’ to ‘Endstage Organ Failure’ were assumed equivalent to those for ‘1L Tx’ to ‘End-stage
Organ Failure’ for all hematologic responses (Table 4.13).
Ideally, the transition probabilities would be based strictly on events pertaining
to cardiac or renal failure; however, as there were too few such events
observed in ANDROMEDA at the time of CUA development, MOD-PFS (excluding
death) was used to allow for sufficiently robust re-analyses. Although apotential limitation of using MOD-PFS is the risk of overestimating the transition
probabilities to ‘End-stage Organ Failure’, this was considered a simplistic
assumption implemented due to data immaturity.

1464.2.3 Details of QOL values
An SLR was conducted in January 2022 (see Section 3) with the intention ofidentifying any sources reporting HRQoL values for subjects being treated with
DCyBorD for newly diagnosed AL amyloidosis. However, only the ANDROMEDA
trial was identified in the SLR. The ANDROMEDA clinical trial collected patientreported outcomes (PROs), including the EuroQol-5 dimension-5 level (EQ-5D5L) instrument, the short-form 36 (SF-36) questionnaire, and European
Organization for Research and Treatment of Cancer Quality of Life
Questionnaire (EORTC-QLQ-C30). An additional targeted literature search was
performed to identify utility values related to other proxy malignancies, organ
failure, and/or chemotherapy treatment. This targeted search was successful in
identifying utility values that were not available in ANDROMEDA. Therefore,
EuroQol-5-dimension (EQ-5D) utility values in the model were sourced fromboth ANDROMEDA and published literature sources. A summary of utility values
included in the model are presented in Sections 4.2.3.1, 4.2.3.2, 4.2.3.3,
and 4.2.3.4. The model also includes the option for incorporating age-adjusted
utility values as a baseline value in the calculation of QALYs according to themethods of Ara and Brazier (2010) (125); however, age-adjusted utility values
were not implemented in the main analysis.

155any timepoint in ANDROMEDA

February 2020;(with Japan-specific utility

median follow-up:

weights applied).

11.4 months, data onfile) (95); see
Section 4.2.3.1.

Calculated by subtracting the

ANDROMEDA IPD

individual mean utility values(primary analysis;

before reaching a progressed

February 2020;

disease state from the mean
‘2L Tx’ health state

Globalutility value once diseaseprogression has occurred based

EQ-5D-5L(VAS)

on ANDROMEDA IPD (withmedian follow-up:
11.4 months, data onfile) (95); see
Section 4.2.3.3.

Japan-specific utility weights
applied).

‘End-stage organ
failure’ health
state

157

Calculated as the difference

ANDROMEDA IPD

between the baseline utility(primary analysis;
February 2020;

value for all ANDROMEDA
UK

patients and the utility value

EQ-5D (VAS)

median follow-up:

from patients with advanced

11.4 months, data on

chronic heart failure listed forfile) (95); Emin et al.,heart transplant per Emin et(2016) (118); seeal., (2016) (118).

Section 4.2.3.3.

Utility decrement from apublished SLR of utility-based
HRQoL in chronic kidney
Patients receiving
hemodialysis

disease treatments. Calculated
Various*as the difference between
patients with chronic kidneydisease pre-hemodialysis andSF-36 andSF-12 used
to calculate

Wyld et al., (2012)
N=207**(119); see Section
4.2.3.4.

EQ-5D

after commencing
hemodialysis.
Disutility: assumed
equal to neutropenia
Lymphopenia (AEDisutility)

N/A

Assumed to be equivalent to

N/Ac

N/A†

Duration of AE:
assumed equal tothat of neutropenia.

neutropenia;
See Section 4.2.3.2.
Neutropenia (AEDisutility)

158

UK

Utility decrement from a(decrement)

published study reportingal., (2008) (106)Japan

health state utility values for

Duration of AE:

SG

N=100

Disutility: Nafees et(duration)

patients receiving treatment forOnouchi et al., (2014)non-small cell lung cancer.

(107);

Duration of decrement sourced

See Section 4.2.3.2.

from published study on
Japanese patients receiving
treatment for neuropathic pain.
Utility decrement from apublished study reporting utility
UK
Pneumonia (AE(decrement)

Disutility)Japan(duration)

Disutility: Beusterienvalues for patients receiving
treatment for chronic
lymphocytic leukemia.

SG

N=89

et al., (2010) (108);
Duration of AE: Ishida

Duration of decrement sourced

et al., (2012) (109);

from published study on

See Section 4.2.3.2.

healthcare-associatedpneumonia.
USA
Diarrhoea (AE(decrement)

Disutility)Japan(duration)

159

Utility decrement from a

Disutility: Stein et al.,published study reporting utility(2018) (110);values for patients receiving

DCE

N=300

Duration of AE:

treatment for acute myeloid

Shiroiwa et al., (2009)

leukemia.

(111);

Duration of decrement sourced

See Section 4.2.3.2.

from published costeffectiveness study on thetreatment of colon cancer.
Utility decrement from apublished study reporting utility
values for patients receiving
UK

treatment for advanced breast

Edema (AE(decrement)cancer.

Disutility)

Japan

Duration of decrement sourced(duration)from published study on

Disutility: Brown et
SG

N=30

al., (2001) (112);
Duration of AE: Saito
et al., (2014) (113);
See Section 4.2.3.2.

patients receiving treatment forsecondary lower limb
lymphedema.
Utility decrement from a
UK
Hypokalemia (AE(decrement)

Disutility)Japan(duration)

scores including a wide varietyof chronic conditions.
Duration of decrement sourced
from published study on
patients receiving treatment

160

Disutility: Sullivan et

published catalogue of EQ-5D
EQ-5D

N=1,037

al., (2011) (114)
Duration of AE: Usamiet al., (2014) (103);
See Section 4.2.3.2.

with liposomal-amphotericin B.

Utility decrement from apublished catalogue of EQ-5D
UKscores including a wide variety

Syncope (AE(decrement)of chronic conditions.

Disutility)

Japan

Duration of decrement sourced(duration)from published case report of a

Disutility: Sullivan et
EQ-5D

N=183

al., (2011) (114);
Duration of AE: Akashi
et al., (2012) (104);
See Section 4.2.3.2.

patient with syncope resulting
from atrioventricular block.
Utility decrement from apublished catalogue of EQ-5D
UK
Cardiac failure (AE(decrement)

Disutility)Japan(duration)

scores including a wide variety

Disutility: Sullivan etof chronic conditions.

al., (2011) (114);

Duration of decrement sourced

EQ-5D

N=590

Duration of AE: Inouefrom published cost-et al., (2020) (102);

effectiveness study on

See Section 4.2.3.2.

transcatheter aortic valve
implantation.
* This study was a systematic review and meta-analysis; therefore, no specific country is associated with the utility value reported.
** The 207 utility estimates reported for this study included a combination of hemodialysis and peritoneal dialysis; however, the utility value

161

used in the model was specific to hemodialysis.
† Disutility values for lymphopenia were assumed to be equal to those for neutropenia.
Abbreviations: AE = adverse event; CR = complete response; CyBorD = cyclophosphamide, bortezomib, and dexamethasone; DCE = discrete
choice experiment; DCyBorD = daratumumab, cyclophosphamide, bortezomib, and dexamethasone; EQ-5D = EuroQol-5 Dimension
questionnaire; EQ-5D-5L = EuroQol-5 Dimension-5 Level questionnaire; HRQoL = health-related quality of life; SF-12 = short-form 12 healthsurvey; SF-36 = short-form 36 health survey; SG = standard gamble; TEAE = treatment emergent adverse event; UK = United Kingdom; USA= United States of America; VAS = visual analog scale; VGPR = very good partial response.

162

4.2.3.2 Utility Decrements for Adverse Events
Health state utility values in the model were the same regardless of treatment,
but disutilities associated with AEs were included to distinguish between
patients receiving DCyBorD and CyBorD. Utility decrements associated with all
grade ≥3 AEs that occurred in at least 5% of patients in either treatment arm
were included in the main analysis. Disutilities associated with treatmentrelated AEs in AL amyloidosis were not identified in the SLR. As such, a broad
literature search was conducted to identify AE disutility values related tooncology and/or chemotherapy. This search was successful in identifying
published literature sources to inform each AE utility decrement and Japanesedata sources were used wherever possible.
The AE disutility value and the length of its application (duration of each grade≥3 AE) were used to calculate the average QALY lost per event. The average
QALY lost per event and the proportion of patients experiencing the respective
AEs was then used to calculate the average QALY lost per patient (Table 4.23).
The total QALYs lost per treatment arm (Table 4.23) was calculated as a sumof the average QALYs lost per patient and was applied in cycle one to all
patients in each treatment arm (aligns with how AE costs were also applied).
The impact of this one-time decrement is assumed to be minimal, given thattreatment is a fixed course of therapy with limited duration.

164

(2011) (114).
Duration: Usami et al.,(2014) (103).
Decrement: Assumed samedecrement as neutropenia
Lymphopenia

0.09

8

0.002

0.00030.0002(106).
Duration: Onouchi et al.,(2014) (107).
Decrement: Nafees et al.,Neutropenia

0.09

8

0.002

0.00010.0001(2008) (106).
Duration: Onouchi et al.,(2014) (107).
Decrement: Beusterien etPneumonia

0.2

15

0.008

0.00070.0004al., (2010) (108).
Duration: Ishida et al.,(2012) (109).
Decrement: Sullivan et al.,Syncope0.0039200.00020.00001

0.00001(2011) (114).
Duration: Akashi et al.,166

(2012) (104).
* The AE disutility value and the length of its application were used to calculate the average QALY lost per event (eg, for cardiac failure, average
QALY lost per event = 0.1034 x (30/365 year) ≈ 0.008). It was assumed that the duration of grade ≥3 AEs would not last an entire cycle.
Abbreviations: AE = adverse event; CyBorD = cyclophosphamide, bortezomib, and dexamethasone; DCyBorD = daratumumab,
cyclophosphamide, bortezomib, and dexamethasone; QALY = quality adjusted life-year.

167cycles. Because CyBorD is not administered beyond six cycles, time ontreatment data do not apply after cycle 6.

180

4.2.4.2 First-line Disease Monitoring Costs
Monitoring of treated patients included routine (or pre-planned) laboratory tests
that occurred while a patient was in the ‘1L Tx’ or ‘Off Tx/FDT’ health state. The
frequency of routine disease monitoring varied depending on whether a patient
was receiving drug therapy (DCyBorD or CyBorD), receiving daratumumab
monotherapy (ie, FDT), or receiving no treatment (24). Specific tests and theirassociated frequencies for DCyBorD and for CyBorD were as outlined in the
ANDROMEDA clinical trial protocol (24).
For patients in the ‘1L Tx’ and ‘Off Tx/FDT’ health states (Table 4.39 andTable 4.40), all routine disease monitoring items were applicable to 100% of
the patient population except for hepatitis B virus (HBV; the proportion was
based on the weighted mean percentage of patients with prior exposure to HBV
per baseline serology as reported in the ANDROMEDA CSR (78). For patientsthat were off-treatment (ie, cycle 7+ in the CyBorD arm and patients in the
DCyBorD arm post-daratumumab monotherapy), the frequency of routine
disease monitoring was reduced compared to patients receiving daratumumab
monotherapy for a fixed treatment duration (Table 4.41). These patients did
not undergo hematology or serum chemistry assessments or HBV
deoxyribonucleic acid (DNA) tests. For all remaining routine disease monitoring
items, the frequency of administration was the same as for patients treatedwith daratumumab monotherapy for a fixed treatment duration. Notably,routine physician visits to assess disease status were captured (along withincidental physician visits) on the ‘Healthcare Resource Use’ sheet (additional
details provided in Section 4.2.4.6).
The unit cost for each routine disease monitoring item was sourced from theJapan Medical Fee Schedule (101). All unit costs are summarized in Table
4.42. The frequency of use for each resource (Table 4.39, Table 4.40, andTable 4.41) and the unit costs (Table 4.42) were used to calculate the totalroutine disease monitoring cost per cycle for each health state (Table 4.43).

182

Serum Chemistry
Assessment

per Cycle

ANDROMEDA protocol (24).
Assumption based on ANDROMEDA protocol

HBV DNA Test

per Cycle

Troponin T Test

per Cycle

ANDROMEDA protocol (24).

per Cycle

ANDROMEDA protocol (24).

per Cycle

ANDROMEDA protocol (24).

per Cycle

ANDROMEDA protocol (24).

per Cycle

ANDROMEDA protocol (24).

Serum Disease
Evaluation
Urine Disease
Evaluation
Serum FLC
Assessment
NT-proBNP Assay(24).

* HBV testing occurred every 12 weeks for up to 6 months after the last dose of study treatment (24); HBV testing was assumed not to occur
while ‘Off Tx’ as a simplifying assumption.
Abbreviations: DNA = deoxyribonucleic acid; FLC = free light-chains; HBV = Hepatitis B Virus; NT-proBNP = N-terminal prohormone brain
natriuretic peptide.

186

Pneumonia

Syncope￥333,400.00

database analysis for MM (May 2021)(2021) (94); see Appendix H

Cost to treat pneumonia per MDV

MDV analysis, Data on Filedatabase analysis for MM (May 2021)(2021) (94); see Appendix H

Cost of 20-day inpatient
hospitalization

Akashi et al., (2012) (104);
Japan MHLW Medical Fee
Schedule 2022 (101).

Abbreviations: MDV = Medical Data Vision; mg = milligrams; MM = multiple myeloma; N/A = not applicable.

190

Second-line drug therapy dosage and administration frequencies were sourced
from published literature of patients with AL amyloidosis rather than theirproduct monographs because no indicated dosing regimen for second-line drugs
exists in AL amyloidosis. Costs of second-line therapy drugs were sourced fromthe Japan MHLW NHI Price List (99). To determine the DCyBorD-specificsubsequent therapy cost, the total costs for Rd, BMd, CyBorD, and TCd were
calculated based on the proportion of patients receiving each regimen (Table
4.46) and the dosage and administration frequencies (Table 4.47) and cost of
the individual drug components (Table 4.48). The total second-line therapy
cost was applied to all DCyBorD patients that commenced second-line therapy.
A similar approach was taken to determine the total cost of second-line
treatment for patients that received first-line CyBorD.

193department (ie, an average ofvisits per cycle), 1.05 inpatient

hospitalizations (ie, an average of

inpatient hospitalizations per cycle),

and an average of 49.2 non-emergency department outpatient visits (ie, anaverage ofoutpatient visits per cycle) (93). Patients in their second-year

post-diagnosis had a reported annual average of 0.63 emergency department
visits (ie, an average of

emergency department visits per cycle), 0.57

inpatient hospitalizations (ie, an average of

inpatient hospitalizations per

cycle), and 39.7 outpatient visits (ie, an average ofoutpatient visits per

cycle) (93). In the model, a simplifying assumption was made whereby the
relative reductions in first- and second-year post-diagnosis healthcare resource
use from Quock et al., (2018) (93) for each of emergency room (ER) visits (13.7%), inpatient hospitalizations (-45.7%), and outpatient visits (-19.3%)
were applied to ‘1L Tx’ values sourced from the Japanese AL amyloidosis
database to estimate the healthcare resource use for patients in the ‘Off
Tx/FDT’ health state. The resulting frequency of resource utilization for ‘Off
Tx/FDT’ wasemergency room visits,

inpatient hospitalizations, andoutpatient visits per cycle.
A summary of incidental healthcare resource use frequencies used in the modelis presented in Table 4.55. Healthcare resource unit costs and frequencies
were used to calculate the health state-associated costs per cycle as outlined inTable 4.56.

2025.1.2 Sensitivity analysis
5.1.2.1 One-way sensitivity analysis
A one-way sensitivity analyses was performed to identify parameters to which themodel results (in terms of ICER) are most sensitive (ie, model drivers) by adjusting thedefault value to a low and high value. All inputs were varied by increasing or decreasing
the default value by 20% (except where estimates could not exceed 100% or anotherwise specified maximum value) with the exception of the discount rate for costand effects which were varied at 0% (low value) and 4% (high value). The one-way
sensitivity inputs are summarized in Table 5.3. Patient distributions within the decision
tree and transition probabilities were not incorporated into the one-way sensitivity
analyses, as one input cannot be varied without also varying the other dependent
inputs.
The results of the one-way sensitivity analyses for DCyBorD versus CyBorD suggestthat the top five model drivers were the CR utility value, the daratumumab unit cost,
the discounting rate for effects, the PR/NR utility value, and the ongoing organ failure
support cost per cycle. These results make sense, as the CR utility value, daratumumab
unit cost, and discounting rate for effects value would affect the incremental QALYs
and/or incremental costs for the DCyBorD arm, whereas the PR/NR utility value andongoing organ failure support cost per cycle would more so affects the CyBorD arm.
Notably, when inputted as 0% and 4%, the discounting of costs was not identified as asignificant model driver. Results of the one-way sensitivity analysis are presented inTable 5.3. The resulting tornado diagram plots the most impactful parameters in order,
based on the greatest percent change from the main analysis, and is presented in
Figure 5.1.

207

DCyBorD RDI(bortezomib)￥5,626,171.29￥5,626,171.29

DCyBorD RDI(Dexamethasone)￥5,625,505.32￥5,626,171.29

CyBorD RDI(Cyclophosphamide)￥5,626,687.72￥5,625,913.07

CyBorD RDI(bortezomib)￥5,626,171.29￥5,626,171.29

CyBorD RDI(Dexamethasone)￥5,626,743.55￥5,626,171.29￥5,625,366.57￥5,626,976.00￥5,625,307.83￥5,627,034.75￥5,625,910.87￥5,626,431.71￥5,627,287.89￥5,625,054.68￥5,622,806.27￥5,629,536.31￥5,627,000.37￥5,625,342.21￥5,618,717.51￥5,633,625.07￥5,447,892.09￥5,804,450.48￥5,608,780.93￥5,643,561.64

DCyBorD Drug Admin
Costs (Cycles 1-2)

￥3,120.00￥2,496.00￥3,744.00

DCyBorD Drug Admin
Costs (Cycles 3-6)

￥2,680.00￥2,144.00￥3,216.00

DCyBorD Drug Admin
Costs (Cycles 7+)￥220.00￥176.00￥264.00

CyBorD Drug Admin
Costs￥2,240.00￥1,792.00￥2,688.00￥1,907.80￥1,526.24￥2,289.36

Co-medication cost for
CyBorD

￥1,663.20￥1,330.56￥1,995.84

Healthcare resource use- 1L Tx￥91,319.33￥73,055.47￥109,583.20

Healthcare resource use- Off Tx/FDT￥50,258.17￥40,206.54￥60,309.80

Healthcare resource use- 2L Tx￥91,319.33￥73,055.47￥109,583.20

Co-medication cost for
DCyBorD

209

Healthcare resource use- End-stage organ
failure￥91,319.33￥73,055.47￥109,583.20

DCyBorD AE
management costs￥101,069.34￥80,855.47￥121,283.21

CyBorD AE
management costs￥68,610.25￥54,888.20￥82,332.30

DCyBorD AE disutility

0.001962086

0.001569669

CyBorD AE disutility

0.001172057

1L Tx disease
monitoring costs￥5,698,641.41￥5,553,701.17￥5,615,251.40￥5,637,091.17￥5,633,584.18￥5,618,758.40

0.002354503￥5,624,978.85￥5,627,364.24

0.000937646

0.001406469￥5,626,883.84￥5,625,458.92￥23,618.90￥18,895.12￥28,342.68￥5,624,243.44￥5,628,099.14

1L FDT disease
monitoring costs￥8,798.90￥7,039.12￥10,558.68￥5,615,755.87￥5,636,586.71

Off Tx disease
monitoring costs￥5,360.00￥4,288.00￥6,432.00￥5,613,467.21￥5,638,875.37

DCyBorD subsequent
therapy cost

1,323,417.67￥1,058,734.13￥1,588,101.20￥5,548,638.50￥5,703,704.07

1,667,882.67￥1,334,306.13￥2,001,459.20￥5,744,220.71￥5,508,121.86￥353,434.64￥282,747.71￥424,121.57￥5,906,653.51￥5,345,689.06￥5,942,807.46￥5,626,171.29￥5,628,080.22￥5,624,262.36

CR utility value￥7,932,073.66￥4,358,987.06

VGPR utility value￥5,573,301.91￥5,680,053.33

PR/NR utility value￥5,112,894.67￥6,254,002.15

CyBorD subsequent
therapy cost
Ongoing organ failure
support cost per cycle
Proportion of patientsrequiring hemodialysis
End of life cost

210

￥662,205.59￥529,764.47￥794,646.71

2L Tx utility decrement￥5,622,234.11￥5,630,113.98

End-stage organ failure
decrement￥5,705,308.00￥5,549,199.91￥5,660,608.43￥5,592,150.62

Hemodialysis utility
decrement

0.10000.08000.1200* High value tested is not 20% greater than the default value so as to not exceed a pre-specified maximum value.
Abbreviations: 1L = first-line; 2L = second-line; AE = adverse event; CR = complete response; CyBorD = cyclophosphamide, bortezomib,
dexamethasone; DCyBorD = daratumumab, cyclophosphamide, bortezomib, dexamethasone; FDT = fixed daratumumab treatment; ICER =incremental cost-effectiveness ratio; RDI = relative drug intensity; Tx = treatment; NR = no response; PR = partial response; VGPR = very
good partial response.

211

Figure 5.1. Tornado diagram depicting results of one-way sensitivity analysis

Abbreviations: 2L – second-line; CR = complete response; CyBorD = cyclophosphamide, bortezomib, dexamethasone; DCyBorD =daratumumab, cyclophosphamide, bortezomib, dexamethasone; FDT = fixed daratumumab treatment; ICER = incremental cost-effectivenessratio; NR = no response; PR = partial response; Tx = treatment; VGPR = very good partial response.

2125.1.2.2 Scenario analyses
5.1.2.2.1

Asian subgroup analysis

As an alternative to the main analysis (which involved the ANDROMEDA ITT
population), a scenario analysis was conducted using Asian subjects from the
ANDROMEDA trial (N=60; DCyBorD n=29; CyBorD n=31). In this subgroup analysis,
parameters pertaining to patient demographics, hematologic response stratification in
the decision tree, and weighting for the PR/NR combined curve were revised to reflect
the subjects residing in Asian countries. A summary of the parameters used to informthe Asian subgroup analysis is presented in Table 5.4. Compared to main analysis,using the Asian subgroup data resulted in a reduction in the ICER by ￥1,021,664.91(~18%) given that, based on the ANDROMEDA-derived hematologic response data inthe decision tree, Asian subjects in the DCyBorD arm have more rapid and deeper
hematologic response compared to the DCyBorD arm of the ITT population. As such,the model predicts that Asian subjects incur greater incremental costs (￥1,188,274.88),
LYs (0.81), and QALYs (0.67) compared to the model using the ITT population
parameters. Despite the increase in incremental costs in the Asian subgroup analysis,
the incremental QALYs gained offset the incremental costs, resulting in a reduced ICER
compared to the main analysis. A summary of results of the Asian subgroup analysis ispresented in Table 5.5.

213

5.1.2.2.2
Scenario analyses to test uncertainty in model inputs andassumptions
To test the impact of uncertainty in key model inputs and assumptions, several scenario
analyses were conducted based on the ANDROMEDA ITT population. The inputs andresults are summarized in Table 5.6. In general, DCyBorD is associated with higher
total costs and total QALYs in all scenarios. Shortening the time horizon led to a ~18%
increase in the main analysis ICER because the lifetime LY and QALY benefits associatedwith DCyBorD could not be fully accrued in this scenario. Selecting six-month exit fromthe decision tree resulted in a large (~19%) reduction in the ICER due to increased LYs
and QALYs gained from using OS data from Palladini et al., (2012) (74), which showed
higher survival rates relative to the OS curves from Kastritis et al., (2020) (71). The
scenario varying the proportion of CyBorD patients receiving second-line TCd (14% to19%) and DCyBorD (5% to 0%) resulted in a ~2% increase in the main analysis ICER.
Conversely, the scenario varying the proportion of CyBorD patients receiving secondline TCd (14% to 9%) and DCyBorD (5% to 10%) resulted in a ~2% decrease in themain analysis ICER. Importantly, using alternate survival functions to extrapolate OS
for CR, VGPR, and/or PR/NR did not have a large impact on the ICER (range￥5,595,917.14 to ￥5,742,501.19), supporting the robustness of the results irrespectiveof which survival function is selected.

215

5.1.2.3 Probabilistic sensitivity analysis
The PSA shows the overall uncertainty of the cost-effectiveness results for D-VCd
compared to VCd. Common distributions used in a PSA are beta, gamma, log-normal,
normal, and Dirichlet (133). The choice of distribution was selected based onrecommendations by Briggs et al., (2006) (133). Survival estimates were sampledusing Cholesky decomposition matrices.
For all inputs, when possible, the standard error (SE; alternatively, standard deviation[SD] or 95% confidence interval [CI] were used to calculate SE) from the data source
were used to define parameter uncertainty. Otherwise, when not reported, the SE wasassumed to be 10% of the default value. This was assumed to represent a reasonable
degree of uncertainty and provided realistic values. Mean deterministic values (ie, point
estimates), SEs, and distribution types used for each parameter included in the PSA areprovided in Table 5.7. The PSA was conducted using 3,000 iterations (the maximum
number of iterations in the model is 10,000).
The results of the PSA were aligned with the deterministic main analysis and arepresented in Table 5.8. The mean total incremental costs from the PSA were
marginally higher than the deterministic results; however, the overall trends in relative
costs were the same. The mean total incremental QALYs from the PSA were lower thanthe deterministic analysis; however, the overall trends remained unchanged. In
comparing the deterministic and probabilistic ICERs, the overall conclusion regarding
cost effectiveness remained unchanged; that is, when compared to CyBorD, DCyBorD
was more costly and more effective and did not exceed the threshold (for products
requiring special consideration) of ￥7,500,000 per QALY.

218

The incremental cost-effectiveness plane (or scatter plot) of incremental costs versus
incremental QALYs for DCyBorD versus CyBorD from 3,000 iterations is presented in
Figure 5.2. All probabilistic iterations were in the North-East quadrant indicating that
DCyBorD was more costly and more effective than CyBorD. The cost-effectivenessacceptability curve (CEAC), showing the probability of being the most cost-effective
therapy at different willingness to pay thresholds, is presented in Figure 5.3. At awillingness to pay threshold greater than ￥6,200,000, DCyBorD had a higher probabilityof being more cost-effective than CyBorD.

219

See Section
CR survival function

Exponential

N/A

N/A

N/A

0.1.1.1; Kastritis etal., (2020) (71).
See Section

VGPR survival
function

Log-logistic

N/A

N/A

N/A

0.1.1.1; Kastritis etal., (2020) (71).
See Section
0.1.1.1;
ANDROMEDA IPD 18month landmark

Proportion pts PR (atexit from decision
tree)

Beta

analysis (May 2021;
median follow-up
25.8 months, data onfile) (98).

DCyBorD Treatment
duration (# months)

221

See Section
24.00

0

N/A

N/A

4.2.4.1.5;

ANDROMEDA
protocol (24).

See Section
CyBorD Treatment
duration (# months)

4.2.4.1.5;
6.00

0

N/A

N/A

ANDROMEDA
protocol (24).

First-line Drug Therapy Costs

DCyBorD (Cycles 1-2)

See Section￥ 1,937,112.40

4.2.4.1.1; Japan
DCyBorD (Cycles 3-6)
DCyBorD (Cycle 7+)￥ 1,046,984.40

N/A

N/A

N/A
MHLW NHI Price List,￥ 445,064.00(2022) (99).
See Section
4.2.4.1.1; Japan

CyBorD￥ 156,856.40

N/A

N/A

N/A

MHLW NHI Price List,(2022) (99).

222

First-line Drug Dosing
Cycles 1-2:
1,800 mg; 4administrations
per cycle
Daratumumab

Cycles 3-6:
1,800 mg; 2administrations
per cycle

See Section
N/A

N/A

N/A

4.2.4.1.1; Kastritis
et al., (2021) (50).

Cycle 7+:1,800 mg; 1
administration
per cycle
See Section
Cyclophosphamide

300 mg/m2; 4administrations
per cycle

N/A

N/A

N/A

et al., (2021) (50).

1.3 mg/m2; 4Bortezomib

Dexamethasone

administrations

See Section
N/A

N/A

N/A

4.2.4.1.1; Kastritis

per cycle

et al., (2021) (50).

40 mg;

See Section

administrations
per cycle

223

4.2.4.1.1; Kastritis

N/A

N/A

N/A

4.2.4.1.1; Kastritis
et al., (2021) (50).

First-line Drug RDI
See Section
DCyBorD RDI

4.2.4.1.1;
Beta(Daratumumab)

ANDROMEDA CSR(78).
See Section

DCyBorD RDI

4.2.4.1.1;
Beta(Cyclophosphamide)

ANDROMEDA CSR(78).
See Section

DCyBorD RDI(Bortezomib)

4.2.4.1.1;
Beta

ANDROMEDA CSR(78).
See Section

DCyBorD RDI(Dexamethasone)

Beta

4.2.4.1.1;
ANDROMEDA CSR
(78).

224

See Section
CyBorD RDI

4.2.4.1.1;

Beta(Cyclophosphamide)

ANDROMEDA CSR(78)
See Section

CyBorD RDI

4.2.4.1.1;
Beta(Bortezomib)

ANDROMEDA CSR(78).
See Section

CyBorD RDI

4.2.4.1.1;
Beta(Dexamethasone)

ANDROMEDA CSR(78).

First-line Drug Administration Costs
DCyBorD
administration costs(Cycles 1-2)

225

See Section￥3,120.00￥312.00

Gamma￥2,866.08

4.2.4.1.2;

DCyBorD
administration costs

ANDROMEDA￥ 2,680.00￥268.00

Gamma￥2,727.64(Cycles 3-6)

MHLW Medical Fee
Schedule (101); NHI

DCyBorD
administration costs

protocol (24); Japan￥220.00￥22.00Gamma￥269.33￥2,240.00￥224.00

Gamma￥2,331.96

Price List (99).

(Cycles 7+)
CyBorD
administration costs
First-line Co-medication Costs
See Section
4.2.4.1.3;
ANDROMEDA
DCyBorD Co￥1,907.80
medication costs￥190.78

Gamma￥1,970.11

protocol (24);ANDROMEDA CSR(78); NHI Price List
(99).

226

See Section
4.2.4.1.3;
ANDROMEDA
CyBorD Co-￥1,663.20￥166.32

Gamma￥1,692.46

protocol (24);medication costs
ANDROMEDA CSR(78); NHI Price List
(99).
First-line Disease Monitoring Costs

1L Tx￥23,618.90￥2,361.89

Gamma￥27,056.10

See Section
4.2.4.1.5;

FDT￥8,798.90￥879.89

Gamma￥8,047.15

ANDROMEDA
protocol (24);ANDROMEDA CSR

Off Tx￥5,360.00￥536.0Gamma￥5,727.54(78); Japan MHLW
Medical Fee Schedule
(101)

227

AE Management Costs
See Section
4.2.4.3;
ANDROMEDA IPD 18month landmark
DCyBorD￥101,069.34￥10,106.93

Gamma￥106,951.98

analysis (May 2021;
median follow-up
25.8 months, data onfile) (98); Inoue,
2020 (102); JapanMHLW Medical Fee
Schedule (codeA002) (101); Janssen

CyBorD￥68,610.25￥6,861.04

Gamma￥65,640.24

Japan Data on File2021 (116); Akashi
et al., (2012) (104);
Usami et al., (2014)228

(103); NHI Price List
(99).

AE Utility Decrements
See Section
4.2.3.2; Sullivan etal., (2011) (114);
DCyBorD

0.001962086

0.000196209

Gamma

0.001915308

Stein et al., (2008)(110); Brown et al.,(2001) (112); Nafees
et al., (2008) (106);
Beusterien et al.,(2010) (108); Inoue

CyBorD

0.001172057

0.000117206

Gamma

0.001150156

et al., (2020) (102);
Shiroiwa et al.,(2009) (111); Saito
et al., (2014) (113);229

Usami et al., (2014)(103); Onouchi etal., (2014) (107);
Ishida et al., (2012)(109); Akashi et al.,(2012) (104).

Second-line Drug Therapy Costs
See Section
4.2.4.4;
ANDROMEDA
Protocol (24);
DCyBorD￥1,323,417.67￥132,341.77

Gamma￥1,460,213.23

Shimazaki et al.,(2018) (19); JSH
clinical guidelines(130); Janssen Japan
internal assumption;
NHI Price List (99);230

Sanchorawala et al.,(2007) (90); Palladini
et al., (2014) (91);
Venner et al., (2014)(92); Wechalekar etal., (2007) (76).
See Section
4.2.4.4;
ANDROMEDA
Protocol (24);Shimazaki et al.,
CyBorD

￥1,667,882.67￥166,788.27

Gamma￥1,642,205.58(2018) (19); JSH
clinical guidelines(130); Janssen Japan
internal assumption;
NHI Price List (99);
Sanchorawala et al.,(2007) (90); Palladini231

et al., (2014) (91);
Venner et al., (2014)(92); Wechalekar etal., (2007) (76).
End-stage Organ Failure Costs
See Section
4.2.4.5;
ANDROMEDA IPD
Recurring end-stageorgan failure costs(primary analysis￥353,434 .64

per cycle￥35,343.46

Gamma￥349,103.45

February 2020,
median follow-up:
11.4 months, data onfile) (95); Takura etal., (2019) (115).

Healthcare Resource Use Costs

232

See Section
4.2.4.6; NHI Price
List (99); Japan
1L Tx￥91,319.33￥9,131.93

Gamma￥88.308.16

MHLW Medical Fee
Schedule (101);
Janssen Japan Data
on File 2021 (116).
See Section
4.2.4.6; JapanMHLW Medical Fee

Off Tx/FDT￥50,258.17￥5,025.82

Gamma￥50,503.92

Schedule (101); NHI
Price List (99);
Janssen Japan Data
on File 2021 (116).
See Section

2L Tx￥91,319.33￥9,131.93

Gamma￥80,713.41

4.2.4.6; NHI Price
List (99); Japan233

MHLW Medical Fee
Schedule (101);
Janssen Japan Data
on File 2021 (116).
See Section
4.2.4.6; JapanMHLW Medical Fee
End-stage Organ￥91,319.33￥9,131.93

Gamma￥82,896.25

Schedule (101); NHI

FailurePrice List (99);
Janssen Japan Data
on File 2021 (116).
End of Life Costs
See Section
Costs associated withfinal month of life

4.2.4.7; Japan￥662,205.59￥66,220.56

Gamma￥466,209.24

Medical Association(2007) (117).

234

Utilities
See Section
4.2.3.1;
ANDROMEDA IPD(primary analysis;CR

Beta
February 2020;
median follow-up:
11.4 months, data onfile) (95).
See Section
4.2.3.1;
ANDROMEDA IPD(primary analysis;

VGPR

Beta
February 2020;
median follow-up:
11.4 months, data onfile) (95).

235

See Section
4.2.3.1;
ANDROMEDA IPD(primary analysis;
PR/NR

Beta
February 2020;
median follow-up:
11.4 months, data onfile) (95).
See Section
4.2.3.3;
ANDROMEDA IPD

2L Tx health stateutility decrement

Gamma(primary analysis;
February 2020;
median follow-up:
11.4 months, data onfile) (95).

236See Section
4.2.3.3;
ANDROMEDA IPD
End-stage organ(primary analysis;

failure health state

Gamma

February 2020;

utility decrement

median follow-up:
11.4 months, data onfile) (95); Emin etal., (2016) (118).
See Section

Hemodialysis utility

0.1

0.01

Gamma

0.116676643

4.2.3.4; Wyld et al.,decrement(2012) (119).
Parametric Survival Functions

NR: Weibull Shape

Cholesky

Cholesky

See Section 0.1.1.1

Decomposition

Decomposition

and Appendix E;

Cholesky

Cholesky

Kastritis et al.,Decomposition

Decomposition(2020) (71).

NR: Weibull Scale

237

Cholesky

CholeskyDecomposition

Decomposition

Cholesky

CholeskyDecomposition

Decomposition

Cholesky

CholeskyDecomposition

Decomposition

VGPR: Log-logistic

Cholesky

Choleskyand Appendix E;

Shape

Decomposition

Decomposition

Kastritis et al.,

VGPR: Log-logistic

Cholesky

Cholesky

Scale

Decomposition

Decomposition

PR: Weibull Shape

PR: Weibull Scale

CR: Exponential Rate
See Section 0.1.1.1(2020) (71).

Transition Probabilities
DCyBorD CR

See Section

transition probability

4.2.1.4;(cycle 7+): 1L Tx to

Dirichlet

Dirichlet

ANDROMEDA IPD

End-stage Organ(primary analysis;

FailureFebruary 2020;238

median follow-up:
11.4 months, data onfile) (95).
DCyBorD CR
transition probability

See Section
Dirichlet

Dirichlet(cycle 7+): 1L Tx to

4.2.1.4.

Off Tx/FDT
DCyBorD CR
See Section

transition probability(cycle 7+): Remain

Dirichlet

Dirichlet

4.2.1.4.

on 1L Tx
See Section

DCyBorD CR

4.2.1.4;transition probability(cycle 7+): Off
Tx/FDT to End-stage
Organ Failure

Dirichlet

Dirichlet

ANDROMEDA IPD(primary analysis;
February 2020;
median follow-up:

239

11.4 months, data onfile) (95).

See Section
4.2.1.4;
DCyBorD CR

ANDROMEDA IPD

Transition probability(18-month landmark
Dirichlet

Dirichlet(cycle 7+): Offanalysis; May 2021;

Tx/FDT to 2L Tx

median follow-up:
25.8 months, data onfile) (98).

DCyBorD CR
Transition probability(cycle 7+): Remain in
Off Tx/FDT

240

See Section
Dirichlet

Dirichlet

4.2.1.4.

See Section
4.2.1.4;

DCyBorD CR

ANDROMEDA IPD
transition probability(cycle 7+): 2L Tx to(primary analysis;
Dirichlet

Dirichlet
February 2020;

End-stage Organ

median follow-up:
Failure11.4 months, data onfile) (95).
DCyBorD CR
See Section

transition probability(cycle 7+): Remain

Dirichlet

Dirichlet

4.2.1.4.

on 2L Tx
DCyBorD VGPR

See Section

transition probability

4.2.1.4;(cycle 7+): 1L Tx to

Dirichlet

Dirichlet

ANDROMEDA IPD

End-stage Organ(primary analysis;

FailureFebruary 2020;241

median follow-up:
11.4 months, data onfile) (95).
DCyBorD VGPR
transition probability

See Section
Dirichlet

Dirichlet(cycle 7+): 1L Tx to

4.2.1.4.

Off Tx/FDT
DCyBorD VGPR
See Section

transition probability(cycle 7+): Remain

Dirichlet

Dirichlet

4.2.1.4.

on 1L Tx
See Section

DCyBorD VGPR

4.2.1.4;transition probability(cycle 7+): Off
Tx/FDT to End-stage
Organ Failure

Dirichlet

Dirichlet

ANDROMEDA IPD(primary analysis;
February 2020;
median follow-up:

242

11.4 months, data onfile) (95).
See Section
4.2.1.4;ANDROMEDA
DCyBorD VGPR

IPD (12-monthtransition probability

landmark analysis;
Dirichlet

Dirichlet(cycle 7+): Off

November 2020;

Tx/FDT to 2L Tx

median follow-up:
20.3 months, data onfile) (120).

DCyBorD VGPR
See Section

transition probability
Dirichlet

Dirichlet(cycle 7+): Remain in

4.2.1.4.

Off Tx/FDT
DCyBorD VGPR
transition probability(cycle 7+): 2L Tx to243

See Section
Dirichlet

Dirichlet

4.2.1.4;
ANDROMEDA IPD

End-stage Organ(primary analysis;

FailureFebruary 2020;
median follow-up:
11.4 months, data onfile) (95).

DCyBorD VGPR
transition probability(cycle 7+): Remain in

See Section
Dirichlet

Dirichlet

4.2.1.4.

2L Tx
See Section
4.2.1.4;

DCyBorD PR/NR

ANDROMEDA IPD
transition probability(primary analysis;(cycle 7+): 1L Tx to
End-stage Organ

Dirichlet

Dirichlet
February 2020;
median follow-up:

Failure11.4 months, data onfile) (95).

244See Section
4.2.1.4;ANDROMEDA
DCyBorD PR/NR

IPD (12-monthtransition probability

landmark analysis;
Dirichlet

Dirichlet(cycle 7+): 1L Tx to

November 2020;

2L Tx

median follow-up:
20.3 months, data onfile) (120).

DCyBorD PR/NR
See Section

transition probability(cycle 7+): Remain

Dirichlet

Dirichlet

4.2.1.4.

on 1L Tx
DCyBorD PR/NR

See Section

transition probability

4.2.1.4;(cycle 7+): 2L Tx to

Dirichlet

Dirichlet

ANDROMEDA IPD

End-stage Organ(primary analysis;

FailureFebruary 2020;245

median follow-up:
11.4 months, data onfile) (95).
DCyBorD PR/NR
transition probability

See Section
Dirichlet

Dirichlet(cycle 7+): Remain

4.2.1.4.

on 2L Tx
See Section
4.2.1.4;
DCyBorD CR

ANDROMEDA IPD

transition probability(cycle 4-6): 1L Tx to

Dirichlet

Dirichlet(primary analysis;
February 2020;

End-stage Organ
median follow-up:
Failure11.4 months, data onfile) (95).
DCyBorD CR
transition probability

246

See Section
Dirichlet

Dirichlet

4.2.1.4.

(cycle 4-6): 1L Tx to
Off Tx/FDT
DCyBorD CR
transition probability

Dirichlet

Dirichlet(cycle 4-6): Remain in

See Section
4.2.1.4.

1L Tx
See Section
4.2.1.4;

DCyBorD CR

ANDROMEDA IPD
transition probability(cycle 4-6): Off(primary analysis;
Dirichlet

Dirichlet
February 2020;

Tx/FDT to End-stage

median follow-up:
Organ Failure
11.4 months, data onfile) (95).
See Section
DCyBorD CR
Transition probability

247

Dirichlet

Dirichlet

4.2.1.4;ANDROMEDA
IPD (12-month(cycle 4-6): Off

landmark analysis;

Tx/FDT to 2L Tx

November 2020;
median follow-up:
20.3 months, data onfile) (120).

DCyBorD CR
Transition probability(cycle 4-6): Remain in

See Section
Dirichlet

Dirichlet

4.2.1.4.

Off Tx/FDT
See Section
4.2.1.4;

DCyBorD CR

ANDROMEDA IPD
transition probability(primary analysis;(cycle 4-6): 2L Tx to
End-stage Organ

Dirichlet

Dirichlet
February 2020;
median follow-up:

Failure11.4 months, data onfile) (95).

248DCyBorD CR
transition probability

Dirichlet

Dirichlet(cycle 4-6): Remain in

See Section
4.2.1.4.

2L Tx
See Section
4.2.1.4;
DCyBorD VGPR
ANDROMEDA IPD
transition probability(cycle 4-6): 1L Tx to(primary analysis;
Dirichlet

Dirichlet
February 2020;

End-stage Organ
median follow-up:
Failure11.4 months, data onfile) (95).

DCyBorD VGPR
transition probability(cycle 4-6): 1L Tx to
Off Tx/FDT

249

Dirichlet

Dirichlet

See Section
4.2.1.4.

DCyBorD VGPR
transition probability

Dirichlet

Dirichlet(cycle 4-6): Remain in

See Section
4.2.1.4.

1L Tx
See Section
4.2.1.4;
DCyBorD VGPR
ANDROMEDA IPD
transition probability(cycle 4-6): Off(primary analysis;
Dirichlet

Dirichlet
February 2020;

Tx/FDT to End-stage
median follow-up:
Organ Failure

11.4 months, data onfile) (95).
See Section

DCyBorD VGPR

4.2.1.4;ANDROMEDA

transition probability
Dirichlet(cycle 4-6): Off
Tx/FDT to 2L Tx

Dirichlet

IPD (12-month
landmark analysis;
November 2020;250

median follow-up:
20.3 months, data onfile) (120).
DCyBorD VGPR
transition probability

See Section
Dirichlet

Dirichlet(cycle 4-6): Remain in

4.2.1.4.

Off Tx/FDT
See Section
4.2.1.4;
DCyBorD VGPR

ANDROMEDA IPD

transition probability(cycle 4-6): 2L Tx to

Dirichlet

Dirichlet(primary analysis;
February 2020;

End-stage Organ
median follow-up:
Failure11.4 months, data onfile) (95).
DCyBorD VGPR
transition probability

251

See Section
Dirichlet

Dirichlet

4.2.1.4.

(cycle 4-6): Remain in
2L Tx
See Section
4.2.1.4;

DCyBorD PR/NR

ANDROMEDA IPD
transition probability(primary analysis;(cycle 4-6): 1L Tx to

Dirichlet

Dirichlet
February 2020;

End-stage Organ

median follow-up:

Failure11.4 months, data onfile) (95).
See Section
DCyBorD PR/NR

4.2.1.4;transition probability
Dirichlet

Dirichlet

ANDROMEDA IPD(cycle 4-6): 1L Tx to(12-month landmark

2L Tx

analysis; November
2020; median follow-

252up: 20.3 months,
data on file) (120).
DCyBorD PR/NR
transition probability

Dirichlet

Dirichlet(cycle 4-6): Remain in

See Section
4.2.1.4.

1L Tx
See Section
DCyBorD PR/NR

4.2.1.4;ANDROMEDA

transition probability

IPD (primary(cycle 4-6): 2L Tx to

Dirichlet

Dirichlet

analysis; FebruaryEnd-stage Organ

2020; median follow-

Failureup: 11.4 months,
data on file) (95).

DCyBorD PR/NR
transition probability

See Section
Dirichlet(cycle 4-6): Remain in
2L Tx

253

Dirichlet
4.2.1.4.

Mortality Distribution:
Dirichlet

Dirichlet

Dirichlet

Dirichlet

1L Tx
Mortality Distribution:
Off 1L Tx/FDT
See Section

Mortality Distribution:
Dirichlet

Dirichlet

2L Tx

4.2.1.3;
ANDROMEDA IPD

Mortality Distribution:
End-stage Organ(primary analysis;
Dirichlet

Dirichlet

Failuremedian follow-up:

Mortality Distribution,

11.4 months, data on

Decision tree
Dirichlet

Dirichlet

Dirichlet

Dirichlet(Assigning end of life
costs): CR
Mortality Distribution,
Decision tree

254

February 2020;file) (95).

(Assigning end of life
costs): VGPR
Mortality Distribution,
Decision tree

Dirichlet

Dirichlet(Assigning end of life
costs): PR/NR*CR and VGPR criteria as defined in the ANDROMEDA CSR (78).
Abbreviations: 1L = first-line; 2L = second-line; AE = adverse event; C2H = Core2 Health; CR = complete response; CSR = clinical study
report; CyBorD = cyclophosphamide, bortezomib, dexamethasone; DCyBorD = daratumumab, cyclophosphamide, bortezomib,
dexamethasone; FDT = fixed daratumumab treatment; IPD = individual patient data; m = meter; mg = milligrams; MHLW = Ministry of
Health Labor and Welfare; NA = not applicable; N/A = not applicable; NR = no response; PR = partial response; PSA = probabilistic
sensitivity analysis; RDI = relative dose intensity; SD = standard deviation; SE = standard error; Tx = treatment; VGPR = very good partial
response.

255

Figure 5.3. Cost-effectiveness acceptability curve

Abbreviations: CyBorD = cyclophosphamide, bortezomib, dexamethasone; DCyBorD = daratumumab,
cyclophosphamide, bortezomib, dexamethasone.

5.1.3 Validity of the analysis
The model underwent internal validation for model calculations and logic testing by themodel programmer, as well as a thorough review of all calculations and data inputs for
accuracy and logic by a reviewer not involved with the initial model programming andby another health economic vendor.
Treatment-specific survival results (for patients who receive DCyBorD and for patients
who receive CyBorD) predicted from the model were, moreover, compared withobserved outcomes from ANDROMEDA. For example, the 3-month hematologic
response distribution of patients on DCyBorD or CyBorD and the extrapolated OS curves
for CR, VGPR, and PR/NR reproduced a similar number of patients alive by 6 months as
observed in the pivotal trial (note that OS estimates from ANDROMEDA at longer
timepoints were not considered for validation, given that median follow-up time at the257

primary analysis data cut-off was <12 months). Furthermore, the recommended OS
extrapolation functions produced survival estimates that were similar to those frompublished studies reporting survival outcomes in bortezomib-treated AL amyloidosis
populations in an assessment of external validation of the CyBorD arm. For example,
the 1-year OS rates for patients with newly diagnosed AL amyloidosis who were treatedwith bortezomib-based regimens ranged from 66% to 80% (BMD, 15% Mayo stage III)
(77, 134, 135). Our model predicted a similar 1-year OS of 77% for CyBorD.
A targeted literature search revealed a paucity of Japanese (and/or Asian) studies
reporting OS for patients newly diagnosed with AL amyloidosis treated with bortezomibbased regimens. Most studies identified were not appropriate for model validation
purposes due to (a) differences in population (ie, a relapsed/refractory patient
population) (136) or (b) small sample sizes in the enrolled population (68, 137) or in
the population treated with bortezomib-based regimens (70) leading to OS curves withlarge “steps” from which it would be inappropriate to extrapolate long-term survival
estimates. One recent retrospective study reported OS for 20 patients (65% of whomwere newly diagnosed) treated with bortezomib and dexamethasone (Bd) (138). The 1year OS rate for these patients was 90% which suggests the model-predicted 1-year OSof 77% may be a conservative estimate for the Japanese patient population.
Our model predicted a CyBorD median OS of 3.45 years and 64%, 54%, and 46%
survival at 2-years, 3-years, and 4-years, respectively, which aligns with real-world
median OS values (range from 40.51 months [3.38 years] (72) to 72 months [6 years](135)) and OS rates at 2-years (range from 47% (123) to 62% (33)), 3-years (range
from 42% (123) to 55%) (33), and 4-years (range from 38% (123) to 43% (72)).
Importantly, the model was validated with clinical and HTA experts at a global advisoryboard in June 2021 with seven experts (three clinicians and four health economists).

258

This included a review of the model face validity in terms of model design, modelledsurvival rates by treatment (with extrapolations from the 3-month landmark OS curves
from Kastritis et al., [2020] (71)), appropriateness of data sources, and key input
estimates and clinical assumptions about AL amyloidosis. Overall, the advisors felt thatthe global model design and assumptions were sound and that the results could beseen as a conservative estimate of the anticipated survival gains from ANDROMEDA.
Clinician feedback about the disease that was relevant for model design is provided inAppendix B.
Owing to the lack of any published economic models and data sources with long-term
patient outcomes in AL amyloidosis treated with DCyBorD, the model could not undergocross validation or predictive validation.

259

7

Implementation system

Not applicable.

262

8
1.

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Details of comparators(50, 54, 63)

Study design (50)

Blinding method (50)
Primary endpoint (50,54, 63)Key secondary
endpoints (54, 63)277

the start of subsequent therapy, or for a
maximum of 24 cycles from the start of thetrial, whichever occurred first.
 Each cycle consisted of 28 days.
 Cyclophosphamide componento Dosing: 300 mg/m2 of cyclophosphamide.
o Patients received cyclophosphamide as anoral or IV weekly dose for a maximum of 6
28-day cycles.
 Bortezomib componento Dosing: 1.3 mg/m2 of bortezomib.
o Patients received bortezomib via SC
injection weekly for a maximum of 6 28day cycles.
 Dexamethasone component*o Dosing: 40 mg of dexamethasone weekly.
o Patients received dexamethasone as anoral or IV weekly dose for a maximum of 6
28-day cycles.
 CyBorD group (ITT population): n = 193
 CyBorD group (Asian subgroup): n=31
 Cyclophosphamide componento Dosing: 300 mg/m2 of cyclophosphamide.
o Patients received cyclophosphamide as anoral or IV weekly dose for a maximum of 6
cycles.
 Bortezomib componento Dosing: 1.3 mg/m2 of bortezomib.
o Patients received bortezomib via SC
injection weekly for a maximum of 6
cycles.
 Dexamethasone component*o Dosing: 40 mg of dexamethasone weekly.
o Patients received dexamethasone as anoral or IV weekly dose for a maximum of 6
28-day cycles.
Phase 3 randomized controlled trial.
 Randomization was stratified according to cardiac
stage (I, II, or IIIA on the basis of the European
modification of the Mayo Clinic Cardiac Staging
System (33)), availability of transplantation in thelocal country, and renal function.
Open label Hematologic complete response






MOD-PFS
Organ response
OS
Hematologic complete response at 6-months
Hematologic VGPR or better

Statistical methods(50)

Sample size (54, 63)

Follow-up period (54,63)
Baseline characteristics(for entire Asian subpopulation) (54, 63)

Treatment duration for
Asian subgroup (54,63)
Efficacy for Asian
subgroup (54, 63)

Time to/duration of hematologic complete
response Time to next treatment
 Reduction in fatigue
 The Kaplan-Meier method was used to estimate
time-to-event distributions.
 Hazard ratios and 95% CIs were estimated using
a stratified Cox proportional hazards regression
model.
 The infusion-related reaction rate and rates ofvery good partial response or better werecompared between groups using a stratified
Cochran-Mantel-Hansel test.
 DCyBorD ITT Population (n=195)
 DCyBorD Asian patients (n=29)
 CyBorD ITT population (n=193)
 CyBorD Asian patients (n=31)
ITT Population: Median, 11.4 months (range 0.03 to
21.3 months)
Asian subgroup: Median, 9.4 months**
 Subjects were recruited from China, Japan, andKorea.
 Median age was 66 years 70% and 58% had heart and kidney involvement,
respectively.
 60% had ≥2 organs involved.
 Cardiac stage I, II and IIIA/B were 28%, 28%,
and 43%, respectively.
DCyBorD group vs CyBorD group (median) 9.2 months vs 5.3 months
Overall hematologic complete response rate
 59% for DCyBorD and 10% for CyBorD (OR,13.2; 95% CI, 3.3-53.7; p<0.0001).
VGPR or better rate DCyBorD vs CyBorD achieved higher rates of very
good partial response or better (≥VGPR; 93% vs61%).
MOD-PFS MOD-PFS favored DCyBorD-treated patients (HR0.21; 95% CI, 0.06-0.75, P=0.0079).
OS

Safety in Asian
population (54, 63)278

A total of 12 deaths occurred (DCyBorD, n=3;
CyBorD, n=9).
Most common (≥10%) Grade 3-4 TEAEs
 Lymphopenia (DCyBorD: 35%; CyBorD: 32%)
 Neutropenia (DCyBorD: 10%; CyBorD: 3%)










Conclusion (54, 63)

Diarrhea (DCyBorD: 10%; CyBorD: 7%)
Pneumonia (DCyBorD: 7%; CyBorD: 10%)
Cardiac failure (DCyBorD: 7%; CyBorD: 10%)
Hypokalemia (DCyBorD: 7%; CyBorD: 10%)
Anemia (DCyBorD: 3%; CyBorD: 10%)
Thrombocytopenia (DCyBorD: 3%; CyBorD: 10%)Hypoalbuminemia (DCyBorD: 3%; CyBorD: 10%)
Syncope (DCyBorD: 3%; CyBorD: 10%)

TEAEs leading to treatment discontinuation
 Occurred in 1 patient in each treatment arm.
Addition of DCyBorD was superior to CyBorD alone in
Asian patients, resulting in deeper hematologic
responses and improved clinical outcomes.

*For patients who were older than 70 years of age, were underweight (body-mass index [the weight inkilograms divided by the square of the height in meters], <18.5), or had hypervolemia, poorly
controlled diabetes mellitus, or previous unacceptable side effects associated with glucocorticoid
therapy, dexamethasone could be administered at a dose of 20 mg weekly at the discretion of their
physician.
**Range not reported for Asian subgroup.
Abbreviations: CI = confidence interval; CyBorD = cyclophosphamide, bortezomib, dexamethasone;
DCyBorD = DCyBorD = daratumumab, cyclophosphamide, bortezomib, dexamethasone; eGFR =estimated glomerular filtration rate; HR = hazard ratio; ITT = intent-to-treat; m = meter; mg =milligrams; min = minute; mL = milliliter; OR = odds ratio; OS = overall survival; TEAE = treatmentemergent adverse event.

279

Appendix B

Clinical feedback on model design

Since no economic models were developed previously for AL amyloidosis, clinician
validation (including an advisor from Japan) was influential in supporting thedevelopment of a decision tree and Markov model with multiple health states in order toappropriately reflect the patient journey through the disease course and current clinicalpractice (eg, hematologic response as the goal of therapy, timing of when to switch
treatments). Clinical expert opinions were collected in various occasions including anadvisory board, the experts are from Australia, Brazil, Canada, China, Japan, UK, and
US. A summary of clinical feedback received pertaining to the model design ispresented in Table B.1.

280

Early death is the major driver of treatment discontinuation.
Most deaths are from arrythmias (sudden death due to cardiac dysfunction) and will
occur while patients are on 1L Tx.
End-stage organ failure

Solid organ transplant is extremely rare.
Costs in end-stage organ failure will be attributed to dialysis.
Patients may progress to end-stage organ failure from any preceding health state.

Abbreviations: 1L = first-line; AL = amyloid light-chain; CR = complete response; NA = not applicable; NR = no response; OS = overall
survival; PR = partial response; Tx = treatment; VGPR = very good partial response.

282

Appendix C

Correlation Between Hematologic Response and Overall Survival

In the context of AL amyloidosis, achieving a swift and deep hematologic response is
the goal of first-line therapy as it prevents further organ damage and improves survival(66). Hematologic response is assessed at each cycle of the treatment course as an
early response measure is used by clinicians to evaluate treatment efficacy due to its
prognostic correlation with OS (74). Better OS in patients with hematologic responsecompared with those who had no response has been observed in numerous publishedstudies (including studies based in Japan) (27, 33, 67, 69, 71-76), and univariate andmultivariate analyses have found hematologic response to be a predictor of survival(33, 67, 69, 71, 74, 76). Indeed, a 2012 retrospective study including 816 patientsdiagnosed with AL amyloidosis between 2002-2010 reported that hematologic response
had a prognostic correlation with OS with significant differences in survival based on
patient three- or six-month hematologic response (Figure C.1) (74). Since the adventof bortezomib-based treatment regimens in 2010, similar trends in OS have been
observed with respect to hematologic response. A 2015 study of 230 newly diagnosed
patients treated with CyBorD reported significantly higher OS among patients that
achieved ≥VGPR compared to either PR or NR (Figure C.2) (33). Similarly, a 2020
study of 227 patients treated upfront with bortezomib-based regimens showedsignificantly better OS for patients that achieving CR or VGPR at both one- and threemonth landmarks (Figure C.3) (71).

283

Figure C.1. OS by hematologic response as reported by Palladini et al., (2012)(A) OS based on patient six-month hematologic response; (B) OS based on patient three-month
hematologic response.
Abbreviations: aCR = amyloid complete response; NR = no response; OS = overall survival; PR =partial response; py = person-year; VGPR = very good partial response.
Source: Palladini et al., (2012) (74).

Figure C.2. OS by hematologic response as reported by Palladini et al., (2015)

Abbreviations: CR = complete response; NR = no response; OS = overall survival; PR = partial284response; VGPR = very good partial response.
Source: Palladini et al., (2015) (33).

285

Figure C.3. OS by hematologic response as reported by Kastritis et al., (2020) (71)Abbreviations: CR = complete response; NR = no response; OS = overall survival; PR = partial response; VGPR = very good partial response.
Source: Kastritis et al., (2020) (31).

286Appendix D

Log-cumulative Hazard Plots for OS per Kastritis et al., (2020)(71)

Figure D.1. Log-cumulative hazard plot for OS: CR vs. NR ()

Abbreviations: CR = complete response; NR = no response; OS = overall survival.

287

Figure D.2. Log-cumulative hazard plot for OS: CR vs. PR ()

Abbreviations: CR = complete response; OS = overall survival; PR = partial response.

288

Figure D.3. Log-cumulative hazard plot for OS: VGPR vs. NR ()

Abbreviations: NR = no response; OS = overall survival; VGPR = very good partial response.

289

Figure D.4. Log-cumulative hazard plot for OS: VGPR vs. PR ()

Abbreviations: OS = overall survival; PR = partial response; VGPR = very good partial response.

Figure D.5. Log-cumulative hazard plot for OS: PR vs. NR ()

Abbreviations: NR = no response; OS = overall survival; PR = partial response.

290

Appendix E

Extrapolation parameters and covariance matrix

Appendix E.1 Parametric survival functions

291

Appendix E.2 Extrapolation parameters and covariance matrices for
Kastritis et al., (2020) (71)Note: all curve extrapolation covariance matrices were generated using
Cholesky decomposition matrices.

292

Generalized
gamma

294

-

-

-

-

-

Generalized
gamma

298

-

-

-

-

-

Generalized
gamma

302

-

-

-

-

-

Generalized
gamma

306

-

-

-

-

-

*Only the starting number at risk was reported by Kastritis et al., (2020) (71); all remaining
numbers at risk were generated by creating pseudo-IPD during the curve extrapolation
process according to the methods described by Guyot et al., (2012) (122).
**Because pseudo-IPD was used in the curve extrapolation process, the number of censors
is not available.

311

Abbreviations: IPD = individual patient data; MOD-PFS = major organ deterioration
progression-free survival; NR = not reported.

312315

*Only the starting number at risk was reported by Kastritis et al., (2020) (71); all remaining
numbers at risk were generated by creating pseudo-IPD during the curve extrapolation
process according to the methods described by Guyot et al., (2012) (122).
**Because pseudo-IPD was used in the curve extrapolation process, the number of censors
is not available.
Abbreviations: IPD = individual patient data; NR = not reported.

316

Appendix H

Medical Data Vision (MDV) database analysis

Table H.1. Methodology for MDV database analysis
Item
Data source

Description
Retrospective claims data obtained from the Medical Data
Vision (MDV) database were analyzed from 01 January 2003 to
31 Aug 2020. The MDV database comprises standardized
health-care insurance claims data provided by hospitals inJapan, which is using the Japanese Diagnosis and Procedure
Combination (DPC) fixed-payment reimbursement system forover 36 million individuals since the year 2003 and contains
about 6 hundred patients with AL amyloidosis.

Study Adult patients (age 20 or above) with a diagnosis of AL

Design andAmyloidosis

wereconsidered

for

this

analysis.

AL

Patient

Amyloidosis diagnosis was defined as the presence of at

Population

least one record with a confirmed AL amyloidosis diagnosis
code (ICD-10 code E858 in combination with the Japanesedisease code 8845844).
 Index diagnosis date was defined as the date on which thepatient had first record of confirmed AL amyloidosis
diagnosis. The baseline period was the 3-month period
before the index diagnosis date and the follow-up period
consisted of ≥60 days from the index diagnosis date;however, patients who died within this 60-day period were
included for fairness consideration.

Outcomes
evaluated Emergency Room Visit: Proportion of Patients Requiring
Item, Frequency of Resource Utilization
 Inpatient Hospitalization: Proportion of Patients Requiring
Item, Length of hospitalization, Frequency of Resource
Utilization
 Outpatient Visit: Proportion of Patients Requiring Item,
Frequency of Resource Utilization

317

 Adverse event cost: [Cost of adverse event from Multiple
Myeloma HTA submission is leveraged in this submission]Abbreviations: AL = amyloid light-chain; DPC = Diagnosis and Procedure Combination; HTA= health technology assessment; MDV = Medical Data Vision.

318

Table H.2. Protocol for Estimating incidental medical Resource Utilization
Costs in the AL Amyloidosis
Steps

Description

Emergency Room Visit
Step 1
Step 2
Step 3

Identify the first diagnosis of AL amyloidosis in the database,then identify the 1st AL amyloidosis regimen following thediagnosis
Identify the 1st AL amyloidosis regimen and its firstadministration date (D1)
Identify the 2nd AL amyloidosis regimen and its firstadministration date (D2)

Step 4

Identify the 3rd AL amyloidosis regimen and its firstadministration date (D3)

Step 5

Identify the first record of ESRF disease name after D1 and its
first record date (ESRF_start)

Step 6

Identify the end of timeframe – either the end of follow up ordeath (End_date)

Step 7

Exclude patients who died within 6 months from the firstdiagnosis

Step 8Calculate the % patients who experienced an emergency room
visit between D1 and D3, to estimate % of patient requiring ER
in the following health states, ‘1L Tx’, ‘Off Tx/FDT’, and ‘2L Tx’

Step 9Calculate the % patients who experienced an emergency room
visit between ESRF_start and End_date to estimate % of patient
requiring ER in the health state of ESRF

Step 10Frequency of utilization of ER is calculated for ‘1L Tx’, ‘2L Tx’,and ESRF. The frequency is converted to frequency per 28-day
cycle.ii Due to a paucity of data, emergency room visit
frequencies for ‘2L Tx’ and ‘End-stage Organ Failure’ wereassumed equivalent to ‘1L Tx’. The frequency of ER utilizationfor ‘Off Tx/FDT’ was estimated based on the percent reductionin emergency room utilization between the first- and secondyears post-diagnosis per Quock et al., (2018) (93).iii

Calculating the frequency of events per 28-day cycle involved dividing the number of events by theentire duration during which the events occurred and multiplying by 28 (ie, [n events/duration indays)]*28).

ii

iii

Relative reductions in HCRU between the first- and second-years post-diagnosis with AL amyloidosis
were used as a proxy by which to estimate the reduction in HCRU between ‘1L Tx’ and ‘Off Tx/FDT’.
For example, the relative reduction in emergency room visits (per 28-day cycle) between first- and319

StepsDescription

Inpatient Hospitalization

Step 1

Calculate the % patients who experienced an inpatient
hospitalization between D1 and D3, to estimate % of patient
requiring hospitalization in the following health states: ‘1L Tx’,
‘Off Tx/FDT’, and ‘2L Tx’.

Step 2

Calculate the % patients who experienced an inpatient
hospitalization between ESRF_start and End_date to estimate %of patient requiring hospitalization in the health state of ESRF .

Step 3Extract the records of hospitalization and calculate the average
length of hospitalization.

Step 4Frequency of utilization of inpatient hospitalizations calculatedfor ‘1L Tx’, ‘2L Tx’, and ESRF. The frequency is converted tofrequency per 28-day cycle.iv Due to a paucity of data, theinpatient hospitalization frequencies for ‘2L Tx’ and ‘End-stage
Organ Failure’ were assumed equivalent to ‘1L Tx’. The
frequency of hospitalization utilization for ‘Off Tx/FDT’ wasestimated based on the percent reduction in inpatient
hospitalizations between the first- and second-years postdiagnosis per Quock et al., (2018) (93).v

Outpatient Visit

Step 1

Calculate the % patients who experienced an outpatient visit
between D1 and D3, to estimate % of patient requiring
outpatients in the following health states, ‘1L Tx’, ‘Off Tx/FDT’,and ‘2L Tx’.

Step 2

Calculate the % patients who experienced an outpatient visit
between ESRF_start and End_date to estimate % of patient
requiring outpatients in the health state of ESRF.

Step 3Frequency of utilization of outpatient visit was calculated for ‘1LTx’, ‘2L Tx’, and ‘End-stage Organ Failure’. The frequency issecond-year post-diagnosis was calculated to be. This reduction was applied to values for ‘1L
Tx’ from the MDV database analysis to obtain an estimated 28-day frequency of emergency room
visits in the ‘Off Tx/FDT’ health state (ie,).
iv
Calculating the frequency of events per 28-day cycle involved dividing the number of events by theentire duration during which the events occurred and multiplying by 28 (ie, [n events/duration indays)]*28).
v

Relative reductions in HCRU between the first- and second-years post-diagnosis with AL amyloidosis
were used as a proxy by which to estimate the reduction in HCRU between ‘1L Tx’ and ‘Off Tx/FDT’.
For example, the relative reduction in inpatient visits (per 28-day cycle) between first- and secondyear post-diagnosis was calculated to be 0.543. This reduction was applied to values for ‘1L Tx’ from
the MDV database analysis to obtain an estimated 28-day frequency of inpatient visits in the ‘Off
Tx/FDT’ health state (ie,).

320StepsDescription
converted to frequency per 28-day cycle.vi Due to a paucity of
data, outpatient visit frequencies for ‘2L Tx’ and ‘End-stage
Organ Failure’ were assumed equivalent to ‘1L Tx’. The
frequency of outpatient visit utilization for ‘Off Tx/FDT’ wasestimated based on the percent reduction in outpatient visits
between the first- and second-years post-diagnosis per Quocket al., (2018) (93).vii

Adverse event cost [Cost of adverse event from Multiple Myeloma HTA submission isleveraged in this submission]
Step 1

Identify the first diagnosis of MM in the database, then identify
the 1st MM regimen following the diagnosis.

Step 2

Identify the 1st MM regimen and its first administration date
(MM_D1)

Step 3

Identify the first record of AE disease name after MM_D1 and its
first record date (AE_start)

Step 4

Identify the sequentially continuous record of AE as monthly
from AE_start and identify the last of the record in the sequence
as AE end record (AE_end)

Step 5

Identify the date one month before from the AE_start(AE_oneM_before)

Step 6

Identify AE-related drug cost items between AE_start andAE_end and exclude AE-related drug cost items which occurred
between AE_oneM_before and AE_start

Step 7

Calculate AE-related drug cost between AE_start and AE_end(NDMM_AE_cost)

Step 8

Identify the 2nd MM regimen and its first administration date
(MM_D2)

Step 9Repeat the steps to calculate AE cost after MM_D2(RRMM_AE_cost)

Step 10Calculate the weighted average cost from NDMM_AE_cost and
RRMM_AE_costvi
Calculating the frequency of events per 28-day cycle involved dividing the number of events by theentire duration during which the events occurred and multiplying by 28 (ie, [n events/duration indays)]*28).
vii

Relative reductions in HCRU between the first- and second-years post-diagnosis with AL amyloidosis
were used as a proxy by which to estimate the reduction in HCRU between ‘1L Tx’ and ‘Off Tx/FDT’.
For example, the relative reduction in outpatient visits (per 28-day cycle) between first- and secondyear post-diagnosis was calculated to be. This reduction was applied to values for ‘1L Tx’ from
the MDV database analysis to obtain an estimated 28-day frequency of outpatient visits in the ‘Off
Tx/FDT’ health state (ie,).

321Abbreviations: AE = adverse event; AL = amyloid light-chain; ER = emergency room; ESRF = Endstage renal failure, FDT = fixed daratumumab treatment; HTA = health technology assessment; MDV= Medical Data Vision; NDMM = newly diagnosed multiple myeloma, RRMM = relapsed and refractory
multiple myeloma.

322