Proposal for the Inclusion of Bortezomib, Lenalidomide Or

Home , Lenalidomide, Pomalidomide, Proteasome inhibitor

Proposal for the Inclusion of Bortezomib, Lenalidomide and Thalidomide in the WHO Model List of Essential Medicines for the First-Line Treatment of Multiple Myeloma

Report prepared by: Vanessa Piechotta, Marius Goldkuhle, Prof. Dr. med. Christof Scheid, PD Dr. med. Nicole Skoetz

Involved actors:

(1) Department I of Internal Medicine

Director: Prof. Dr. med. Michael Hallek

University Hospital of Cologne

Kerpener Str. 62

50937 Cologne

Germany

(2) Cochrane Cancer

CONTENT

List of abbreviations ...... 2

General Items ...... 5 1. Summary statement of the proposal for inclusion, change or deletion 5 2. Relevant WHO technical department and focal point 5 3. Name of organizations consulted and supporting the application 5 4. International Nonproprietary Name and Anatomical Therapeutic Chemical code of the medicine 5 5. Dose forms and strengths proposed for inclusion; including adult and age-appropriate paediatric dose forms/strengths 5 6. Whether listing is requested as an individual medicine or as representative of a pharmacological class 10

Treatment details, public health relevance and evidence appraisal and synthesis ...... 11 7. Treatment details (requirements for diagnosis, treatment and monitoring) 11 Diagnosis ...... 11 First-line treatment with bortezomib ...... 11 First-line treatment with lenalidomide ...... 12 First-line treatment with thalidomide ...... 12 Monitoring ...... 12 8. Information supporting the public health relevance 13 9. Review of benefits: summary of evidence of comparative effectiveness 15 Methodological approach ...... 15 Description of studies ...... 15 Risk of Bias ...... 17 Efficacy of the interventions ...... 20 10. Review harms and toxicity: summary of evidence of safety 28 Safety of the interventions ...... 28 Summary of Findings (SoF) ...... 48 11. Summary of available data on comparative cost and cost-effectiveness of the medicine. 51

Regulatory information ...... 56 12. Summary of regulatory status and market availability of the medicine 56 13. Availability of pharmacopoeial standards (British Pharmacopoeia, International Pharmacopoeia, United States Pharmacopoeia, European Pharmacopoeia) 58

References ...... 59

Appendix 1: Methodological approach ...... 66

Appendix 2: Search strategies ...... 75 1

LIST OF ABBREVIATIONS AE Adverse events

ASCT Autologous stem cell transplantation

ATC Anatomical therapeutic chemical

BNF British National Formulary

CI Confidence interval

CR Complete response

CRAB Calcemia, renal, anemia, bone lesions

CT Computed tomography

CTD Cyclophosphamide thalidomide dexamethasone

CTDa Cyclophosphamide thalidomide dexamethasone (attenuated)

DALY Disability-adjusted life-years

DDD Defined Daily Dose

EMA European Medicines Agency

EML Essential Medicines List

ESMO - MCBS European Society for Medical Oncology Magnitude of Clinical Benefit Scale

EU European Union

FDA Food and Drug Administration

FDF finished dosage form

GBP Great British Pound

GRADE Grading of Recommendations Assessment, Development and Evaluation

HC Health Canada

HIC High-income country

HR Hazard ratio

HTA Health Technology Assessment

ICER Incremental cost-effectiveness ratio

IFNγ Interferon gamma

IL Interleukin

INN International Nonproprietary Name

i.v. Intravenous

LIC Low-income country

LMIC Low- and middle-income country

MA Meta-analysis

MD Mean Differences

MDCT Multi-detector computed tomography

MIC Middle-income country

MM Multiple myeloma

MP Melphalan, prednisone

MPc Melphalan, prednisone continuous

MPT Melphalan, prednisone, thalidomide

MPR-R Melphalan, prednisone, lenalidomide (revlimid), followed by lenalidomide (revlimid) maintenance

MR Minimal response

MRI Magnetic resonance imaging

NHS National Health Service

NICE National Institute for Health and Care Excellence

NK Natural killer

NMA Network meta-analysis

OS Overall survival

PET Positron emission tomography

PFS Progression-free survival

PMDA (Japanese) Pharmaceuticals and Medical Devices Agency

PR Partial response

QALY Quality-adjusted life-years

RCD Lenalidomide (revlimid), cyclophosphamide, dexamethasone

RCPc Lenalidomide (revlimid), cyclophosphamide, prednisone continuous

RCT Randomised controlled trial

RD Lenalidomide (revlimid), dexamethasone

RDc Lenalidomide (revlimid), dexamethasone continuous

RMP Lenalidomide (revlimid), melphalan, prednisone

RMPc Lenalidomide (revlimid), melphalan, prednisone continuous

RR Risk ratio

SAE Serious adverse events 3

s.c. Subcutaneous

SLiM Sixty, light, magnetic

SD Standard deviation

SoF Summary of Findings

SR Systematic review

TCD Thalidomide, cyclophosphamide, dexamethasone

TDc Thalidomide, dexamethasone continuous

TGA Therapeutic Goods Administration

TMP Thalidomide, melphalan, prednisone

TMPc Thalidomide, melphalan, prednisone continuous

TNF- α Tumor necrosis factor-α

UI Uncertainty interval

UK United Kingdom

USA United States of America

VMP Bortezomib (velcade), melphalan, prednisone

VMPc Bortezomib (velcade), melphalan, prednisone continuous

VRD Bortezomib (velcade), lenalidomide (revlimid), dexamethasone

VRDc Bortezomib (velcade), lenalidomide (revlimid), dexamethasone continuous

VTDc Bortezomib (velcade), thalidomide, dexamethasone continuous

VTMP Bortezomib (velcade), thalidomide, melphalan, prednisone

VTPc Bortezomib (velcade), thalidomide, prednisone continuous

WHO World Health Organization

GENERAL ITEMS 1. Summary statement of the proposal for inclusion, change or deletion This application advocates the inclusion of bortezomib, lenalidomide and thalidomide in the core list of essential medicines for the treatment of newly diagnosed multiple myeloma patients in non-transplant settings. Studies of combination regimens of the indicated medicines showed significant, clinically meaningful prolongation of overall and progression free survival, yet an increased number of adverse events.

Multiple myeloma (MM) is the second most common haematological malignancy with a global incidence of 138,509 (95% uncertainty interval [UI]: 121,000 to 155,480) and an age-standardized incidence rate of 2.1 per 100,000 population (95% UI: 1.8 to 2.3) in 2016. Since 1990, the incidence rate increased by 126% worldwide (1). 2. Relevant WHO technical department and focal point Lorenzo Moja, Technical Officer, EML Secretariat 3. Name of organizations consulted and supporting the application  Department I of Internal Medicine, University Hospital of Cologne  Cochrane Cancer 4. International Nonproprietary Name and Anatomical Therapeutic Chemical code of the medicine International Nonproprietary Name (INN)

Bortezomib

Lenalidomide

Thalidomide

Anatomical Therapeutic Chemical (ATC)

In the ATC classification system, bortezomib, lenalidomide and thalidomide are classified as “antineoplastic and immunomodulating agents”. Furthermore bortezomib is classified as “other neoplastic agents” and can be identified by the ATC code: L01XX32 (2). Lenalidomide and thalidomide are further classified as “other immunosuppressant” and can be identified by the ATC codes: L04AX04 and L04AX02, respectively (3). 5. Dose forms and strengths proposed for inclusion; including adult and age-appropriate paediatric dose forms/strengths Internationally / On the global market, bortezomib is currently available in different vial sizes (ranging from 1 mg to 3.5 mg) (cf. table 1). Before intravenous (i.v.) or subcutaneous (s.c.) injection, the lyophilized drug needs to be reconstituted. For reconstitution, 1 ml of sterile 9 mg/ml (0.9%) sodium chloride solution per 1 mg of the drug needs to be added to the bortezomib containing vial (4).

Lenalidomide and thalidomide are both internationally available in different capsule sizes (ranging from 5 mg to 25 mg, or 50 mg to 200 mg, respectively) (cf. tables 2 and 3). The capsules are to be taken orally (5).

Tables 1, 2, and 3 show the current market availability of bortezomib, lenalidomide, and thalidomide, respectively. The tables include available dosage forms, dosage strengths and packaging presentations for all suppliers, when available.

Table 1: Current international market availability (FDFs) of bortezomib (6)

Country of Supplier Dosage form Dosage Packaging registration presentation India PMV Life lyophilised 1 mg, 3.5 vial Science Pvt. Ltd. powder for mg injection India Accure Labs Pvt. lyophilized 2 mg / Ltd. injection

India Flagship Biotech injection 2 mg, 3.5 / International mg Pvt. Ltd. India Jodas Expoim lyophilized 2 mg, 3.5 / Pvt. Ltd. injection mg

India Nishchay injection 2 mg vial Pharmaceuticals Pvt. Ltd. India Panacea Biotec injection 3.5 mg vial Limited

India Vinkem Labs lyophilized 3.5 mg / Ltd. injection

Iran CinnaGen Co injectable 3.5 mg vial

USA Apotex inc vial 3.5 mg vial

USA Accord injectable, 3.5 mg vial Healthcare INC intravenous, subcutaneous USA Actavis LLC injection 2.5 mg/ml, vial 2.5 mg/1.4 ml USA Fresenius Kabi powder, 3.5 mg vial USA intravenous

USA Hospira Inc powder 2.5 mg vial intravenous, subcutaneous USA Millennium injectable, 3.5 mg vial Pharms intravenous, subcutaneous 6

Country of Supplier Dosage form Dosage Packaging registration presentation USA Pharmascience injection 3.5 mg vial Inc.

Canada Actavis pharma powder for 3.5 mg vial company solution Canada Janssen inc. powder for 3.5 mg vial solution

Canada DR. Reddys powder for 3.5 mg vial laboratories ltd. solution

Canada Pharmascience powder for 3.5 mg vial inc solution

Canada Teva Canada powder for 3.5 mg i.v. 3.5 ml limited solution s.c. 1.4 ml

Australia Janssen- Cilag / / 1 Pty Ltd

UK Seacross freeze dried 3.5 mg vial pharmaceuticals powder

Poland Adamed Sp. / / / z.o.o.

Turkey Biem ilac sanayi lyophilized 3.5 mg vial ve ticaret a.s powder for IV/SC injectable solution Sweden Accord powder for 3.5 mg / Healthcare Ltd. solution

Sweden Sandoz A/S powder for 3.5 mg / solution

Sweden Janssen-Cilag powder for 1 mg, 3.5 / International NV injectable mg solution Italy Janssen Cilag 3 mg 1 unit 3.5 mg vial International nv parenteral use

Switzerland Janssen Cilag AG dried powder 1 mg, 3.5 / for solution mg

Norway Janssen-Cilag powder for 3.5 mg Hood glass International Injection fluid, resolution

Country of Supplier Dosage form Dosage Packaging registration presentation South Africa Janssen injection 3.5 mg/ml vial Pharmaceutica (Pty) Ltd South Africa Janssen POI 1 mg/ml vial Pharmaceutica (Pty) Ltd South Africa Accord injection 100 mg 10x1 mg/10 Healthcare (Pty) ml Ltd

Table 2: Current international market availability (FDFs) of lenalidomide (7)

Country of Supplier Dosage form Dosage Packaging registration presentation India Accure Labs Pvt. capsule 5 mg, 10 mg, / Ltd. 15 mg, 25 mg India Flagship Biotech capsule 5 mg, 10 mg, / International 20 mg, Pvt. Ltd India Globela Pharma capsule 5 mg, 10 mg, / Pvt. Ltd. 15 mg, 25 mg India Jodas Expoim capsule 5 mg, 10 mg, / Pvt. Ltd 15 mg, 25 mg India Nishchay capsule 5 mg, 10 mg 10 capsules Pharmaceuticals Pvt. Ltd. Iran CinnaGen Co capsule 10 mg, 25 / mg

USA Celgene capsule 2.5 mg, 5 / mg, 10 mg, 15 mg, 20 mg, 25 mg Canada Celgene Inc capsule 5 mg, 15 mg, 100 25 mg

Canada Celgene Inc capsule 2.5 mg, 20 21 mg

Australia Celgene Pty capsule 5 mg, 10 mg, 21 Limited 15 mg, 25 mg Portugal Bluepharma – / / / industria farmaceutica, s.a 8

Country of Supplier Dosage form Dosage Packaging registration presentation Spain Chemo capsule, 2.5 mg, 5 / pellet mg, 10 mg, 15 mg, 20 mg, 25 mg Latvia Grindeks AS capsule 5 mg, 10 mg, / 15 mg, 25 mg Portugal Tecnimede capsule 2.5 mg, 5 / mg, 7.5 mg, 10 mg, 20 mg, 25 mg Sweden Celgene Europe capsule 2.5 mg, 5 / Ltd mg, 7.5 mg, 10 mg, 15 mg, 20 mg, 25 mg Italy Celgene Europe capsule 2.5 mg, 5 21 limited mg, 10 mg, 15 mg, 25 mg Switzerland Celgene GmbH capsule 5 mg, 10 mg, 21 15 mg, 25 mg Norway Celgene Europe capsule 2.5 mg, 5 blister Ltd mg, 7.5 mg, 10 mg, 15 mg, 20 mg, 25 mg South Africa Key Oncologics capsule 5 mg, 10 mg, 21x1 mg (Pty) Ltd 15 mg, 25 mg

Table 3: Current international market availability (FDFs) of thalidomide (8)

Country of Supplier Dosage form Dosage Packaging registration presentation

India Accure Labs Pvt. capsule 50 mg, 100 / Ltd. mg

India Cadila capsule 50 mg, 100 10 capsules Pharmaceuticals mg Limited India Flagship capsule 50 mg, 100 / International mg, 200 mg Pvt. Ltd India Nishchay capsule 100 mg 30 Pharmaceuticals Pvt. Ltd. 9

Country of Supplier Dosage form Dosage Packaging registration presentation

USA Celgene capsule 50 mg, 100 / mg, 150 mg, 200 mg Canada Celgene Inc. capsule 50 mg, 100 28 mg, 200 mg

Australia Celgene Pty capsule 50 mg, 100 28 Limited mg

Spain Medichem S.A. capsule 50 mg /

Sweden Celgene Europe capsule 50 mg / Ltd.

Italy Celgene Europe capsule 50mg 28 limited

Norway Celgene Europe capsule 50 mg blister ltd

South Africa Key Oncologics capsule 50 mg 28x1 mg (Pty) Ltd

6. Whether listing is requested as an individual medicine or as representative of a pharmacological class This application covers selected medicines out of the pharmacological class “antineoplastic and immunomodulating agents”(□). Specifically, it refers to the proteasome inhibitor bortezomib and the immunomodulatory drugs lenalidomide and thalidomide.

This application is restricted to the listed medicines, due to the reason that other medicines out of the pharmacological class are still under evaluation for multiple myeloma treatment in on-going randomized controlled trials (e.g. NCT01335399, NCT01668719, NCT01863550, NCT01850524, NCT02874742, NCT01734928, NCT02576977, NCT03170882), and not yet approved for first-line treatment.

TREATMENT DETAILS, PUBLIC HEALTH RELEVANCE AND EVIDENCE APPRAISAL AND SYNTHESIS 7. Treatment details (requirements for diagnosis, treatment and monitoring) Diagnosis Early diagnosis of the condition is complicated by widely varying symptoms. Some patients with MM might be symptom-free, while others present common symptoms like bone pain (mostly in the back, hips or skull), fractures, symptoms of light chain amyloidosis, or high blood levels of calcium. The latter might, inter alia, lead to kidney problems, abdominal pain, or extreme thirst (9). The International Myeloma Working Group has revised the criteria for myeloma diagnosis in 2014. They compose of clonal bone marrow plasma cells ≧ 10% or biopsy-proven or extramedullary plasmacytoma and one (or more) myeloma defining events (cf. Table 4) (10).

Table 4: Myeloma defining events (10)

CRAB criteria HyperCalcemia > 2.75 mmol/L (> 11 mg/dL)

Renal insufficiency creatine clearance < 40mL per min or serum creatine > 177 µmol/L (> 2 mg/dL)

Anemia haemoglobin value < 100 g/L

Bone lesions One or more osteolytic lesions on skeletal radiography, computer tomography (CT), or positron emission tomography-computer tomography (PET-CT) Biomarkers of malignancy (SLiM criteria)

Clonal bone marrow ≧ 60 (Sixty) % plasma cell %-age

Involved to uninvolved ≧ 100 serum free Light chain ratio Focal lesions on < 1 Magnetic resonance imaging (MRI) studies

First-line treatment with bortezomib According to the “bortezomib in multiple myeloma and lymphoma” Canadian practice guideline of 2013 (11) and the NICE technology appraisal guidance [TA228] of 2011 on “Bortezomib and thalidomide for the first‑line treatment of multiple myeloma” (12), bortezomib should be administered for first-line treatment of non-transplant MM patients as the following:

 For previously untreated, transplant ineligible MM patients, the combination of bortezomib, melphalan, and prednisone is a recommended first-line treatment option and preferred over treatment with melphalan and prednisone alone.  The recommended dose and schedule of bortezomib is 1.3 mg/m² subcutaneous (twice) weekly during cycles 1 to 4 (on days 1, 4, 8, 11, 22, 25, 29, and 32) and once weekly during cycles 5 to 9 (on days 1, 8, 22, and 29).  Oral melphalan 9 mg/m² and prednisone 60 mg/m² are to be given on days 1 through 4 of the first week of each cycle.  A total of nine 6-week treatment cycles is given.

First-line treatment with lenalidomide According to the “Lenalidomide in multiple myeloma” Canadian practice guideline of 2013 (13), lenalidomide should be administered for first-line treatment of previously untreated symptomatic MM patients as the following:

 Combination of lenalidomide and dexamethasone is an acceptable first-line treatment option in patients of any age.  The recommended dose of lenalidomide is 25 mg/day on days 1 to 28 every 35-day cycle for the first three cycles, followed by 25 mg/day on days 1 to 21 every 28-day cycle thereafter  Alternatively 28-day cycle dosing from the start, if preferred.  The use of low-dose dexamethasone, 40 mg/day on days 1, 8, 15 and 22 of a 28-day cycle, is preferred for safety.  Some patients with acute myeloma complications such as acute renal dysfunction, hypercalcemia, or hyperviscosity syndrome may benefit from high-dose dexamethasone (i.e., 40 mg/day on days 1 to 4, 9 to 12, and 17 to 20 of a 28-day cycle). First-line treatment with thalidomide According to the “Thalidomide in multiple myeloma” Canadian evidence-based education and information recommendations of 2010 (14), thalidomide (T) should be administered in combination with melphalan (M) and prednisone (P) for first-line treatment of previously untreated symptomatic MM patients. This recommendation was based on a meta-analysis (MA), which shows a superior OS of MPT-treated patients compared to MP-treated patients (HR: 0.62; Confidence Intervall (CI) 0.50 to 0.77). As per the NICE technology appraisal guidance [TA228] of 2011 “Bortezomib and thalidomide for the first‑line treatment of multiple myeloma” (12), the recommended dose is 200 mg daily, taken orally. A maximum of 12 6-week treatment cycles should be used. Monitoring In accordance with the NICE guideline [NG35] “Myeloma: diagnosis and management” (15), patients who completed initial myeloma therapy should be monitored at least every three months, during which risk factors for disease progression (high-risk fluorescence in-situ hybridization, impaired renal function, disease presentation) should be taken into account. Monitoring should comprise assessment of myeloma, and treatment-related symptoms, and multiple laboratory tests (full blood count, renal function, bone profile, serum immunoglobulins and serum electrophoresis, and, if appropriate, serum-free light-chain assay). Multiple myeloma patients should not be offered skeletal surveys routinely for disease monitoring. Taking into account previous imaging tests, one of the following can be considered: whole-body MRI, whole- body low-dose CT, whole-body CT, spinal MRI, fluorodeoxyglucose (FDG) PET-CT. 12

8. Information supporting the public health relevance Cancer is one of the most common non-communicable diseases worldwide with an estimated incidence of 18.1 million new cases in 2018 (16). Around the globe, cancer is the second leading cause of mortality and will account for an estimate of 9.6 million deaths in 2018 (17). About 70% of the global cancer cases occur in low- and middle-income countries (LMICs). Main reasons for a higher mortality, relative to incidence rates, in these regions are late-stage presentation and lack of access to diagnosis and treatment. Treatment services are available in less than 30% of LMICs, compared to over 90% in high-income countries.

Multiple myeloma is the second most common haematological malignancy and accounts for 2.1% of all cancer deaths in the US (18),(19). In 2018, there will be an estimated amount of 159,985 (0.9%) new MM cases and 106,105 (1.1%) MM deaths, worldwide (16). Incidence rates are higher in LMICs than in high income countries (HIC) (cf. Figure 1). Globally, myeloma caused 2.1 million disability-adjusted life-years (DALYs) in 2016 (1). Globally, the incidence rate increased by 126% between 1990 and 2016 and is strongly related to age (20), (1). Based on the latest statistics in the US, the median age of myeloma diagnosis across all races and both genders is 69 years (19).

Figure 1: Estimated incidence rates of MM in 2018 (21)

In HICs, autologous stem cell transplantation (ASCT) is routinely used for younger patients with a good general state of health. However, ASCT is not available in many LMICs (16). Lack of access to general and specialized healthcare leads to wide disparities in survival rates between HICs and LMICs. In the UK, 47% of diagnosed MM patients are predicted to survive at least five years (32.5% at least 10 years) (20). In comparison, a 5-year survival rate of only 7.6% was recently reported in Nigeria (22).

In non-transplant settings (no transplant-accessibility or transplant-ineligibility), the introduction of so-called “novel agents”, such as immunomodulatory drugs and proteasome inhibitors, lead to an improvement in the overall survival of patients. A retrospective analysis of 631 patients, who received an initial therapy of bortezomib, lenalidomide, or thalidomide, reported a median OS of 7.3 years (95% CI: 5.9; not reached). In comparison, a median OS of 3.8 years (95% CI: 3.1; 4.6) was reported for 425 patients, whose initial therapy did not include novel-agents (23). 13

Proteasome inhibitors and immunomodulatory drugs belong to a new generation of anti‐cancer agents that work by targeting the microenvironment of the tumour, like specific cell receptors, proteins and signalling pathways (24).

European medicines agency- authorised proteasome inhibitors for myeloma treatment include the first-in class agent bortezomib, and the second generation agents carfilzomib, and ixazomib (carfilzomib and ixazomib only used in relapsed or refractory myeloma). The mode of action in the treatment of MM is generally similar for all proteasome inhibitors and based on the supreme sensitivity of myeloma cells to the inhibition of the 26S proteasome, which is a critical complex of the ubiquitin-proteasome system and responsible for regulation and degradation of the majority of intracellular proteins. These proteins are involved in cell cycle progression, cell growth, and survival. In MM, the ubiquitin-proteasome system is dysregulated, resulting in an upregulated activity of proteasome 26S. The upregulated activity of the proteasome leads to an exorbitant decay of specific relevant substrates, like the tumour suppressor p53 and the inhibitor of nuclear factor-κB, IκB. The continuous activity of the nuclear factor-κB transcription pathway enables myeloma cells to proliferate rapidly and drive the tumour progression. Inhibition of the 26S proteasome leads to multiple downstream effects, resulting in growth arrest and cell death. As cancer cells have an increased level of proteasome activity in general, the pro-apoptotic effects of proteasome inhibitors can therefore be directly targeted (25), (26).

Immunomodulatory drugs are glutamic acid derivates presenting a wide range of biological activities. Their anti-myeloma properties comprise of their immunomodulatory, anti-angiogenic, anti-inflammatory, and anti-proliferative properties, though their exact mechanism of action remains unclear. Immunomodulatory drugs used in clinical practice to treat MM are thalidomide and its analogues, lenalidomide and pomalidomide (the latter only used in relapsed or refractory myeloma) (27). Despite their similar structure, thalidomide, lenalidomide, and pomalidomide differ in their pharmacological properties (28). The immunomodulatory activities are based on the upregulation of T-cell (CD4+ and CD8+) and natural killer T-cell production and downregulation of regulatory T-cells, leading to an increased proliferation of natural killer (NK) cells and raised cytotoxicity (24), (27). The T-cell proliferative effects of lenalidomide are 50 to 2000 times higher than of thalidomide, and the effectiveness of T-cell interleukin 2 (IL-2) and interferon gamma (IFNγ) production augmentation is 300 to more than 1200 times higher (27). Likewise, lenalidomide is more effective in decreasing the production of tumour necrosis factor alpha (TNF- α), IL-1β, IL-6, and IL-12 compared to thalidomide (28). Increasing NK cell proliferation enhances death of myeloma cell lines. In addition to the potentiation of NK cell proliferation, lenalidomide (not thalidomide) likely enhances antibody-dependent cellular cytotoxicity and natural cytotoxicity of NK cells, resulting in induced myeloma cell death (27). The cytotoxic capacities of lenalidomide originate from multiple mechanisms, comprising, inter alia, the inhibition of nuclear factor-κB, downregulation of C/EBPβ (resulting in a decreased IFN regulatory factor 4 production), activation of caspases, augmented expression of pro-apoptotic factors and likewise deduction of anti-apoptotic factors, and the interruption of the PI3K/Akt pathway (28).

Combination therapies of proteasome inhibitors, immunomodulatory drugs and corticosteroids result in synergistic or enhanced activity of the anti-cancer agents on anti-myeloma properties (25). Corticosteroids are likely to enhance anti-cancer activity through the downregulation of IL- 6-induced signalling pathways. Synergistic effects of proteasome inhibitors and immunomodulatory drugs are likely due to the combined effects of overlapping activation of caspase pathways, the activation of the pro-apoptotic BH-3 protein BIM, the downregulation of IFN regulatory factor 4, the proto-oncogene MYC, and the apoptosis regulator MCL1 in myeloma cells, and the inhibition of myeloma cell migration and angiogenesis (25). 14

9. Review of benefits: summary of evidence of comparative effectiveness Methodological approach The full methodological approach underlying the following evidence synthesis is described in Appendix 1. Briefly, to compare the effectiveness of various first-line treatments for transplant- ineligible MM patients a Rapid Cochrane Network Meta-Analysis was conducted. The respective protocol was submitted to PROSPERO on November 28th, 2018. The objective was to compare the efficacy and safety of bortezomib, lenalidomide, and thalidomide in different treatment regimens versus the former standard treatment consisting of melphalan and prednisone, which is still used in many LMICs.

We systematically searched the Cochrane Central Register of Controlled Trials, MEDLINE, international study registries, conference proceedings, and checked the reference lists of retrieved reviews and articles. The search was conducted from 1998 until present (June 2018). Randomized controlled trials that studied our pre-specified treatments (cf. appendix) for the use of transplant-ineligible newly diagnosed MM patients were considered for inclusion. Two authors independently screened the search results and extracted the data. Data synthesis was performed by a NMA, using the frequentist approach. Risk of bias in included studies was assessed using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (29). The certainty of evidence for outcomes within the NMA was rated according to the GRADE approach (30). Additionally, to measure the clinical benefit of the treatments, the European Society for Medical Oncology Magnitude of Clinical Benefit Scale (ESMO-MCBS) was applied (31). We used the median OS across all studies in the network of our comparator of interest (MP) and the estimated treatment effect (HR) of the NMA to calculate the median NMA-survival for each treatment regimen. The clinical benefit was assessed according to the ESMO Magnitude of Clinical Benefit Scale v1.1, Form 2a: “for therapies that are not likely to be curative with primary endpoint of OS, if median OS with the standard treatment >24 months” (32). Description of studies The results of the electronic search are illustrated in Figure 2. Twenty-six RCTs were eligible for inclusion (Myeloma XI (33), EMN01 (34), FIRST (35), ECOG E1A06 (36), MM-015 (37), HOVON 87 (38), Myeloma IX (39), GBRAM0002 (40), Kim 2007 (41), Ludwig 2009 (42), TMSG (43), HOVON 49 (44), IFM 99-06 (45), GISMM2001-A (46), MM03 (47), IFM 01/01 (48), NMSG #12 (49), Katsuoka 201 3(50), UPFRONT (51), VISTA (52), GEM2005 (53), Mookerje 2017 (54), SWOG S0777 (55), E1A05 (56), GIMEMA-MM-03-05 (57), NCT01274403 (58)). The trials included a total of 11,403 randomized participants from Europe, Asia, North- and South America, and the Pacific region, with a median age ranging from 52 to 78.5 years. The first patient enrolment started in August 2001 (42) and several trials are still ongoing (33), (38), (54). Most trials (80%) included patients with a diagnosis of MM according to the International Staging System. The participants were followed by a median of 17.1 to 72 months. In addition to the differentiation between drug combinations, treatment regimens were differentiated into fixed therapy (first-line therapy was stopped after a pre-specified amount of therapy cycles) and continuous therapy (first-line treatment followed by maintenance therapy, continuous first-line therapy, or continuous first- line therapy until a plateau phase [response] was reached). Accordingly, the included participants

were randomized to a total of 21 different treatment regimens: MP, MPc, RCD, RCPc, RD, RDc, RMP, RMPc, TCD, TDc, TMP, TMPc, VD, VDc, VMP, VMPc, VRD, VRDc, VTDc, VTMPc, VTPc1.

Figure 2: Flow Chart

1 c: continuous therapy, C: cyclophosphamide, D: dexamethasone, M: melphalan, P: prednisone, T: thalidomide, R: lenalidomide, V: bortezomib

Risk of Bias The summary of the methodological quality of the included studies for all assessed domains across included studies and per included study is presented in Figure 3 and Figure 4, respectively.

Figure 3: Risk of bias graph: judgement from the review authors regarding each risk of bias item, presented as percentages across all included studies

Figure 4: Risk of bias graph: judgement from the review authors regarding each risk of bias item, presented as percentages across all included studies 18

Selection Bias In total, 14 of 25 included studies (56%) reported a central randomization process and were therefore judged at low risk of bias. The remaining 11 studies (44%) did not provide enough information to assess sequence generation and allocation concealment and risk of selection bias was therefore judged to be unclear.

Performance Bias As in general randomized controlled trials in oncology are performed as open-label, participants and personnel were presumed not to be blinded, if not other specified. However, 3 of 25 studies (12%) reported to be double-blind and were therefore judged to be at low risk of bias. The remaining 22 studies (88%), were either declared or presumed as open-label trial and were therefore judged to be at high risk of bias.

Detection Bias Blinding of outcome assessment was assessed in three outcome categories: overall survival, progression free survival, and safety outcomes. The outcome overall survival is not dependent on the outcome assessor as patients are either alive or dead at the time of overall survival assessment. Therefore the risk of bias in this category was judged to be low for all studies.

Progression free survival and safety outcomes can be dependent on the outcome assessor. Studies were presumed not to be blinded for outcome assessment, if not other specified. As mentioned above, blinding was described in 3 of 25 studies 12%) and risk of bias was therefore judged as low. The remaining 22 studies were judged to be at high risk of bias.

Attrition Bias Missing outcome data were assessed in two categories: time to event data, and safety outcomes. Study discontinuation was precisely reported in 22 of 25 studies (88%) and balanced between arms. Furthermore Kaplan-Meier curves were provided. Risk of bias for incomplete survival data was judged to be at low risk for these studies. The remaining 3 studies (12%) did not provide Kaplan-Meier curves or study-flow-charts. As information was insufficient, risk of bias for incomplete survival data was judged to be unclear for these studies.

Safety outcomes were judged to be at low risk of bias, if all reported patients received at least one study drug. This was applicable for all included studies.

Reporting Bias In total, 16 of 25 included (64%) studies reported all primary and secondary outcomes as pre- specified in their protocol. In these studies, risk of bias for selective reporting was judged as low. However, primary and secondary outcomes were not reported as pre-specified in 3 studies and risk of bias for selective reporting was judged to be high. Pre-specified primary and secondary outcomes have been altered in one study (43). Response rate was supposed to be evaluated after 12 months, but was reported after four 6-week cycles. Furthermore time to progression was supposed to be evaluated, but disease free survival was reported instead. One study conducted an unplanned interim analysis (40). As interim results suggested inferior efficacy of one arm over the other two arms, only descriptive results were further reported. Furthermore, more than 10% of data was missing, without explanations in one arm. One study did not report progression free survival, overall response rate, and quality of life, although previously specified (52). Risk of Bias for selective reporting was unclear in 6 Studies, 5 of which were abstracts only. The remaining study did not report duration of response, although previously specified (59). As response rate and complete response have been reported as pre-specified, risk of bias was judged to be unclear.

Other Bias Other Bias was detected in 3 of 25 studies (12%) and judged to be high. One study closed enrollment prematurely due to slow accrual (56), one study conducted an unplanned interim analysis (40) and further altered analysis of results, and in one study were safety data reviewed twice a year unblinded by an independent data and safety monitoring committee (55). In the remaining 22 studies was no other bias assumed and therefore risk judged to be low. Efficacy of the interventions Overall Survival (OS) Overall survival was reported in 23 studies (18 two-arm studies, 5 three-arm studies), and analysis was conducted with 22 studies. One study (54) and two direct comparisons of a three-arm study (40) were excluded, since the HR was not reported and could not be estimated. OS was measured for all 21 treatment regimens and a total of 11,071 patients. However, the network was not fully connected and consists of three subnetworks comprising 30 pairwise comparisons (cf. Figure 5).

Figure 5: Network graph for outcome overall survival. Any two treatments are connected by a line when there is at least one study comparing the two treatments. Line width: number of patients

We performed a network meta-analysis for OS- subnetworks 1 and 2 (OS-subnetwork 3 consists out of 2 treatment regimens, only). Results for all network comparisons, including the ranking of treatments are shown in Table 5, and Figure 6, per OS-subnetwork. Moderate heterogeneity (I²= 53.9%) was observed between studies in OS-subnetwork 1. Continuous VRDc (HR: 0.49 [95% CI: 0.26; 0.92]), VTMP (HR: 0.49 [95% CI: 0.26; 0.93]), fixed RD (HR: 0.63 [95% CI: 0.40; 0.99]), and TMP (HR: 0.75 [95% CI: 0.58; 0.97]) showed a significant, clinically meaningful improvement of overall survival compared to MP, respectively.

Table 5: Results of NMA for the outcome OS. Treatments are ordered by P-Score (descending). Upper triangle: direct estimate. Lower triangle: network estimate

OS- Subnetwork 1 No. of studies: 19. No. of treatments: 15. No. of pairwise comparisons: 25. No. of designs: 14 Qtotal=17.36, df=8, p=0.027 / Qwithin=7.54, df=5, p=0.18 / Qbetween=12.35, df=3, p=0.006; I²=53.9%, Tau²=0.0381 Treatment Effects: 0.71 [0.44, VRDc . . 1.15] ...... 0.70 [0.43, 1.01 [0.41, 2.48] VTMPc . . 1.13] ...... 0.78 0.98 0.77 [0.35, [0.65, [0.51, 0.79 [0.42, 1.48] 1.71] RD 1.49] . . 1.16] ...... 0.70 0.90 1.07 0.78 0.98 [0.33, [0.60, [0.70, [0.52, [0.59, 0.71 [0.44, 1.15] 1.50] 1.35] RDc . 1.63] 1.18] 1.64] ...... 0.70 0.90 1.00 0.70 [0.43, [0.48, [0.55, [0.45, 0.71 [0.33, 1.51] 1.13] 1.69] 1.79] VMP ...... 1.07] . . . 0.66 0.85 0.94 0.94 1.16 [0.29, [0.49, [0.63, [0.48, [0.69, 0.67 [0.35, 1.26] 1.50] 1.48] 1.41] 1.84] RCPc . 1.95] ...... 0.65 0.83 0.92 0.93 0.98 1.08 0.66 [0.32, [0.56, [0.64, [0.56, [0.59, [0.49, [0.49, 0.65 [0.36, 1.20] 1.30] 1.24] 1.32] 1.53] 1.62] TMP . . . 2.40] 0.88] . . . 0.59 0.75 0.84 0.84 0.89 0.91 0.95 0.95 0.79 [0.28, [0.45, [0.56, [0.48, [0.55, [0.61, [0.67, [0.54, [0.45, 0.59 [0.31, 1.11] 1.23] 1.25] 1.25] 1.47] 1.42] 1.35] RMPc 1.33] . . 1.67] . 1.38] . 0.52 0.67 0.75 0.75 0.79 0.81 0.89 0.92 1.06 [0.25, [0.39, [0.47, [0.42, [0.46, [0.53, [0.66, [0.66, [0.64, 0.53 [0.27, 1.03] 1.10] 1.16] 1.18] 1.33] 1.35] 1.24] 1.21] TMPc 1.28] . 1.75] . . . 0.48 0.62 0.68 0.69 0.73 0.74 0.82 0.92 0.65 [0.21, [0.33, [0.39, [0.35, [0.39, [0.43, [0.52, [0.66, [0.38, 0.49 [0.23, 1.03] 1.09] 1.17] 1.21] 1.33] 1.37] 1.28] 1.29] 1.28] MPc . . . . 1.11] 0.48 0.62 0.69 0.69 0.73 0.74 0.82 0.92 1.00 1.12 0.92 [0.23, [0.35, [0.40, [0.39, [0.39, [0.48, [0.49, [0.54, [0.54, [0.73, [0.61, 0.49 [0.24, 1.00] 1.02] 1.10] 1.17] 1.22] 1.36] 1.14] 1.37] 1.56] 1.87] TCD 1.72] 1.39] . . 0.49 0.63 0.69 0.70 0.74 0.75 0.83 0.93 1.01 1.01 0.82 [0.26, [0.40, [0.47, [0.45, [0.44, [0.58, [0.58, [0.64, [0.61, [0.69, [0.47, 0.49 [0.26, 0.92] 0.93] 0.99] 1.03] 1.07] 1.23] 0.97] 1.19] 1.35] 1.67] 1.48] MP . 1.44] .

0.44 0.57 0.63 0.63 0.67 0.68 0.75 0.85 0.92 0.92 0.91 [0.19, [0.28, [0.32, [0.31, [0.32, [0.38, [0.39, [0.43, [0.44, [0.61, [0.52, 0.45 [0.20, 1.02] 1.04] 1.15] 1.23] 1.28] 1.42] 1.24] 1.46] 1.65] 1.95] 1.39] 1.60] RCD . . 0.43 0.55 0.61 0.62 0.65 0.67 0.73 0.82 0.90 0.89 0.89 0.97 [0.19, [0.29, [0.34, [0.31, [0.34, [0.38, [0.44, [0.47, [0.47, [0.47, [0.53, [0.46, 0.43 [0.20, 0.94] 0.98] 1.07] 1.12] 1.21] 1.27] 1.16] 1.22] 1.44] 1.72] 1.69] 1.48] 2.08] RMP . 0.31 0.40 0.44 0.44 0.47 0.48 0.53 0.59 0.65 0.64 0.64 0.70 0.72 [0.12, [0.17, [0.20, [0.19, [0.20, [0.22, [0.26, [0.31, [0.38, [0.28, [0.31, [0.28, [0.31, 0.31 [0.12, 0.79] 0.83] 0.92] 0.97] 1.04] 1.08] 1.03] 1.07] 1.12] 1.11] 1.47] 1.33] 1.76] 1.68] TDc OS- Subnetwork 2 No. of studies: 2. No. of treatments: 4. No. of pairwise comparisons: 4. No. of designs: 2 Qtotal=0, df=0, p=n.a./ Qwithin=0, df=0, p=n.a./ Qbetween=0, df=0, p=n.a.; I²=n.a., Tau²=n.a. Treatment Effects: VMPc 0.92 [0.65, 1.29] 0.89 [0.64, 1.25] 0.67 [0.49, 0.91] 0.92 [0.65, 1.29] VTDc 0.98 [0.70, 1.38] . 0.89 [0.64, 1.25] 0.98 [0.69, 1.38] VDc . 0.67 [0.49, 0.91] 0.73 [0.46, 1.16] 0.75 [0.47, 1.18] VTPc

(a)

(b)

Figure 6: Forest plot for the outcome OS. (a) OS- Subnetwork 1. Reference treatment: MP. (b) OS- Subnetwork 2. Reference treatment: VMPc. Treatments are ordered by P-Score (descending)

The confidence in estimates for overall survival could be rated for RD, TMP, VMP, and VRDc. The use of RD, TMP, and VRDc for first-line treatment of multiple myeloma patients likely results in a large increase in overall survival. The use of VMP as initial myeloma therapy may result in a large increase in overall survival (cf. table 12).

The proportion of direct evidence ranged from 0 to 100%. The test for disagreement showed significant disagreement between direct and indirect estimates in closed loops for RCPc-RDc- RMPc (p = 0.0148) and MP-TMP (p = 0.0453).

The clinical benefit of the treatments was assessed according to the ESMO-MCBS (31). The magnitude of clinical benefit was graded as 4 (survival benefit compared to comparator >9 months (32)) for VRDc, VTMPc, RD, RDc, VMP, RCPc, and TMP (cf. table 6).

Table 6: Estimated difference in median OS, based on the median overall survival over all studies in the network of MP (35.9 months) Median OS Intervention NMA HR Estimated* Estimated ESMO of MP in median OS OS score(32) months in months difference in months 35.9 VRDc 0.49 (0.26; 0.92) 73.3 (39.0 to 138.1) 37.4 4

VTMPc 0.49 (0.26; 0.93) 73.3 (38.6 to 138.1) 37.4 4

RD 0.63 (0.40; 0.99) 57.0 (36.3 to 89.8) 21.1 4

RDc 0.69 (0.47; 1.03) 52.0 (34.9 to 76.4) 16.1 4

VMP 0.70 (0.45; 1.07) 51.3 (33.6 to 79.8) 15.4 4

RCPc 0.74 (0.44; 1.23) 48.5 (29,2 to 81.6) 12.6 4

TMP 0.75 (0.58; 0.97) 47.9 (37.0 to 61.9) 12.0 4

RMPc 0.83 (0.58; 1.19) 43.3 (30.2 to 61.9) 7.4 3

TMPc 0.93 (0.64; 1.35) 38.6 (26.6 to 56.1) 2.7 1

TCD 1.01 (0.69; 1.48) 35.5 (24.3 to 52.0) -0.4 1

RCD 1.10 (0.63; 1.92) 32.6 (18.7 to 57.0) -3.3 1

RMP 1.13 (0.67; 1.89) 31.8 (19.0 to 53.6) -4.1 1

TDc 1.57 (0.75; 3.27) 22.9 (11.0 to 47.9) -13 1

*Estimated median OS = MP-median OS/NMA-HR

Progression-free survival (PFS) Twenty-three studies (18 two-arm studies, 5 three-arm studies) reported the outcome PFS, of which 21 studies were included in analysis. Two studies (41), (54) and two direct comparisons of a three-arm study (40) were excluded, since no HR was reported and data was not sufficient to estimate the missing value. PFS was measured for all 21 treatment regimens and a total of 10,389 patients. However, the network was not fully connected and consists of four subnetworks comprising 29 pairwise comparisons (cf. Figure 7).

Figure 7: Network graph for the outcome PFS. Any two treatments are connected by a line when there is at least one study comparing the two treatments. Line width: number of patients

We performed NMA for PFS-subnetworks 1 and 2 (subnetwork 3 and 4 consist out of two treatment regimens, only). Results for all network comparisons, including the ranking of treatments are shown in Table 7, per PFS-subnetwork. Moderate heterogeneity (I²= 55.3%) was observed between studies in PFS-subnetwork 1. In general, continuous treatment regimens were superior to fixed MP, and 7 out of 11 compared bortezomib, lenalidomide, or thalidomide combinations showed a significant improvement of PFS compared to MP, respectively (cf. Figure 8).

Table 7: Results of NMA for the outcome PFS. Treatments are ordered by P-Score (descending). Upper triangle: direct estimate. Lower triangle: network estimate

PFS- Subnetwork 1 No. of studies: 17. No. of treatments: 13. No. of pairwise comparisons: 23. No. of designs: 12 Qtotal=17.89, df=8, p=0.022 / Qwithin=6.06, df=5, p=0.30 / Qbetween=11.80, df=3, p=0.008; I²=55.3%, Tau²=0.0269 Treatment Effects: 0.71 [0.48, VRDc . 1.06] ...... 0.77 0.80 1.00 0.80 0.49 0.40 [0.46, [0.54, [0.76, [0.53, [0.31, [0.25, 1.29] RMPc 1.20] 1.32] 1.19] . . . . 0.80] 0.64] . . 0.71 0.92 1.00 0.69 0.70 [0.48, [0.67, [0.71, [0.48, [0.49, 1.06] 1.27] RDc . 1.40] . 0.98] 1.00] . . . . . 0.70 0.90 0.98 0.84 0.62 [0.40, [0.70, [0.67, [0.63, [0.41, 1.20] 1.15] 1.42] TMPc . 1.11] . . . . 0.93] . . 0.67 0.87 0.95 0.97 [0.40, [0.60, [0.68, [0.63, 1.13] 1.26] 1.32] 1.49] RCPc ...... 0.58 0.75 0.82 0.84 0.87 0.77 [0.31, [0.52, [0.51, [0.63, [0.52, [0.49, 1.08] 1.10] 1.31] 1.11] 1.45] MPc . . 1.21] . . . . 0.55 0.71 0.77 0.79 0.81 0.94 1.01 0.56 0.89 [0.33, [0.51, [0.57, [0.55, [0.54, [0.60, [0.71, [0.44, [0.44, 0.90] 0.98] 1.04] 1.12] 1.22] 1.47] TMP 1.43] . . 0.72] 1.78] . 0.53 0.68 0.74 0.76 0.78 0.90 0.96 [0.31, [0.45, [0.52, [0.48, [0.49, [0.53, [0.68, 0.89] 1.04] 1.04] 1.18] 1.23] 1.53] 1.35] RD . . . . .

0.45 0.58 0.63 0.64 0.67 0.77 0.82 0.85 [0.21, [0.32, [0.33, [0.38, [0.34, [0.49, [0.43, [0.43, 0.96] 1.04] 1.21] 1.10] 1.32] 1.21] 1.55] 1.71] TDc . . . . 0.41 0.53 0.57 0.59 0.61 0.70 0.75 0.78 0.91 0.80 [0.22, [0.35, [0.35, [0.37, [0.35, [0.41, [0.48, [0.45, [0.45, [0.51, 0.77] 0.81] 0.94] 0.93] 1.04] 1.20] 1.18] 1.34] 1.84] RMP 1.24] . . 0.34 0.44 0.48 0.49 0.51 0.59 0.63 0.65 0.76 0.84 0.82 [0.20, [0.33, [0.35, [0.36, [0.34, [0.39, [0.50, [0.44, [0.41, [0.56, [0.57, 0.58] 0.60] 0.67] 0.67] 0.77] 0.89] 0.78] 0.96] 1.41] 1.26] MP 1.17] . 0.32 0.41 0.44 0.45 0.47 0.54 0.58 0.60 0.70 0.77 0.92 0.96 [0.17, [0.27, [0.28, [0.29, [0.28, [0.32, [0.40, [0.37, [0.35, [0.46, [0.67, [0.68, 0.57] 0.63] 0.69] 0.70] 0.78] 0.91] 0.83] 0.98] 1.40] 1.30] 1.27] TCD 1.35] 0.30 0.39 0.43 0.44 0.45 0.52 0.55 0.58 0.68 0.74 0.88 0.96 [0.15, [0.23, [0.24, [0.25, [0.24, [0.28, [0.34, [0.32, [0.31, [0.40, [0.55, [0.68, 0.60] 0.68] 0.74] 0.76] 0.83] 0.97] 0.91] 1.04] 1.46] 1.38] 1.41] 1.35] RCD PFS- Subnetwork 2 No. of studies: 2. No. of treatments: 4. No. of pairwise comparisons: 4. No. of designs: 2 Qtotal=0, df=0, p=n.a./ Qwithin=0, df=0, p=n.a./ Qbetween=0, df=0, p=n.a.; I²=n.a., Tau²=n.a. Treatment Effects: VTPc . 0.83 [0.61, 1.15] . 0.87 [0.56, 1.34] VTDc 0.96 [0.72, 1.28] 0.89 [0.67, 1.19] 0.83 [0.61, 1.15] 0.96 [0.72, 1.28] VMPc 0.93 [0.71, 1.23] 0.78 [0.51, 1.19] 0.89 [0.67, 1.19] 0.93 [0.71, 1.23] VDc

(a)

(b)

Figure 8: Forest plot for the outcome PFS. (a) PFS-subnetwork 1. Reference treatment: MP. (b) PFS-subnetwork 2. Reference treatment: VMPc. Treatments are ordered by P-Score (descending)

The confidence in estimates for PFS could be rated for RD, TMP, and VRDc, and could not be rated for VMP, because VMP was not connected to MP in the network. The use of RD, TMP, and VRDc for first-line treatment of MM patients likely results in a large increase in PFS (cf. table 12).

The proportion of direct evidence ranged from 0 to 100%. The test for disagreement showed almost significant disagreement between direct and indirect estimates in closed loops for MP- TMP (p= 0.0594). 10. Review harms and toxicity: summary of evidence of safety Safety of the interventions Adverse events (AE) grade 3 and 4 Adverse events grade 3 and 4 were reported in nine studies (7 two-arm studies, 2 three-arm studies), for 13 treatment regimens and a total of 3318 patients. However, the included studies did not fulfil the similarity assumption and are therefore not comparable in NMA. Decisive effect modifiers to withdraw the assumption for similarity were different supportive therapies and various reporting styles of grade 3 and 4 AEs (e.g. different length of treatment, AEs occurring in >5% or >10% of the patients, differentiation between non-haematologic and haematologic AEs). Pairwise comparisons are illustrated in Figure 9, per trial.

Figure 9: Pairwise comparisons for outcome grade 3 or 4 adverse events

Serious adverse events (SAEs) Serious adverse events were reported in eight studies (5 two-arm studies, 3 three-arm studies) and were measured for 14 treatment regimens and a total of 7306 patients. However, the network was not fully connected and consists out of 3 subnetworks comprising 14 pairwise comparisons (cf. Figure 10).

Figure 10: Network graph for the outcome SAEs. A line connects any two treatments when there is at least one study comparing the two treatments. Line width: number of patients

We performed NMA for all SAE-subnetworks. Results for all network comparisons, including the ranking of treatments are shown in Table 8. Global approach to check for inconsistency and heterogeneity between studies was not applicable.

Table 8: Results of NMA for the outcome SAEs. Treatments are ordered by P-Score (descending). Upper triangle: direct estimate. Lower triangle: network estimate

SAE-subnetwork 1 No. of studies: 3. No. of treatments: 5. No. of pairwise comparisons: 5. No. of designs: 3 Qtotal=0, df=0, p=n.a./ Qwithin=0, df=0, p=n.a./ Qbetween=0, df=0, p=n.a.; I²=n.a., Tau²=n.a. Treatment Effects:

TMP 0.88 [0.78, 0.98] . 0.70 [0.64, . 0.78] 0.88 [0.78, RD 0.98 [0.65, 0.80 [0.73, . 0.98] 1.49] 0.88] 0.86 [0.56, 0.98 [0.65, 1.49] VRD . . 1.32] 0.70 [0.64, 0.80 [0.73, 0.88] 0.82 [0.53, RDc 0.90 [0.75, 1.09] 0.78] 1.26] 0.63 [0.51, 0.73 [0.59, 0.89] 0.74 [0.46, 0.90 [0.75, VRDc 0.78] 1.18] 1.09]

SAE-subnetwork 2 No. of studies: 2. No. of treatments: 4. No. of pairwise comparisons: 4. No. of designs: 2 Qtotal=0, df=0, p=n.a./ Qwithin=0, df=0, p=n.a./ Qbetween=0, df=0, p=n.a.; I²=n.a., Tau²=n.a. Treatment Effects:

VMPc 0.95 [0.78, 1.18] 0.87 [0.72, 0.50 [0.31, VMPc 1.07] 0.81] 0.95 [0.78, VDc 0.92 [0.75, . 0.95 [0.78, 1.18] 1.18] 1.11] 0.87 [0.72, 0.92 [0.75, 1.11] VTDc . 0.87 [0.72, 1.07] 1.07] 0.50 [0.31, 0.52 [0.31, 0.88] 0.57 [0.34, VTPc 0.50 [0.31, 0.81] 0.81] 0.96]

SAE-subnetwork 3 No. of studies: 3. No. of treatments: 5. No. of pairwise comparisons: 5. No. of designs: 3 Qtotal=0, df=0, p=n.a./ Qwithin=0, df=0, p=n.a./ Qbetween=0, df=0, p=n.a.; I²=n.a., Tau²=n.a. Treatment Effects:

MP 0.90 [0.68, 1.19] 0.83 [0.63, 0.78 [0.65, . 1.10] 0.94] 0.90 [0.68, RMP 0.93 [0.71, . . 1.19] 1.21] 0.83 [0.63, 0.93 [0.71, 1.21] RMPc . 0.79 [0.67, 0.93] 1.10]

0.78 [0.65, 0.87 [0.62, 1.22] 0.94 [0.68, VMP . 0.94] 1.31] 0.66 [0.48, 0.73 [0.54, 1.00] 0.79 [0.67, 0.84 [0.58, TMPc 0.91] 0.93] 1.21]

Relative risk for patients to experience at least one SAE appears to be similar across therapy regimens (cf. Figure 11).

(a)

(b)

(c)

Figure 11: Forest plot for the outcome SAEs. (a) SAE-subnetwork 1. Reference treatment: RD. (b) SAE-subnetwork 2. Reference treatment: VMPc. SAE-subnetwork 3. Reference treatment: MP. Treatments are ordered by P-Score (descending)

The confidence in estimates for SAEs could only be rated for VMP as RD, TMP, and VRDs are not connected to MP in the network. VMP as initial therapy for MM probably increases occurrence of SAEs slightly (cf. SoF table).

Infections Infections were reported in 15 studies (11 two-arm studies, 4 three-arm studies), for 17 treatment regimens and a total of 7470 patients. However, the network was not fully connected and consists out of three subnetworks comprising 23 pairwise comparisons (cf. Figure 12).

Figure 12: Network graph for the outcome infections. Any two treatments are connected by a line when there is at least one study comparing the two treatments. Line width: number of patients

We performed NMA for infections-subnetworks 1 and 2 (infections-subnetwork 3 consisted out of 2 treatment regimens, only). Results for all network comparisons, including the ranking of treatments are shown in Table 9, per infections-subnetwork. Moderate heterogeneity (I²= 34.8 %) was observed between studies for infections-subnetwork 1.

Table 9: Results of NMA for outcome infections. Treatments are ordered by P-Score (descending). Only subnetworks with > 1 designs. Upper triangle: direct estimate. Lower triangle: network estimate

Infections-subnetwork 1 No. of studies: 12. No. of treatments: 11. No. of pairwise comparisons: 18. No. of designs: 9 Qtotal=7.67, df=5, p=0.18/ Qwithin=2.72, df=3, p=0.44/ Qbetween=4.95, df=2, p=0.08; I²=34.8%, Tau²=0.0713 Treatment Effects: 0.50 0.57 0.72 0.48 0.17 [0.26, [0.29, [0.29, [0.20, [0.04, MP 0.96] . 1.11] . . 1.79] . . 1.12] 0.82] 0.60 0.77 0.53 [0.34, [0.43, [0.30, 1.07] TMP . . . 1.37] . 0.94] . . . 0.60 1.00 0.58 0.71 [0.23, [0.40, [0.26, [0.30, 1.54] 2.48] RCPc . . . 1.33] 1.65] . . . 0.57 0.94 0.94 [0.29, [0.39, [0.30, 1.11] 2.27] 3.00] TCD ...... 0.50 0.83 0.84 0.89 0.65 [0.19, [0.31, [0.28, [0.28, [0.39, 1.30] 2.26] 2.49] 2.84] MPc . . . . . 1.08] 0.50 0.83 0.83 0.89 1.00 0.69 [0.24, [0.47, [0.32, [0.32, [0.34, [0.39, 1.07] 1.46] 2.17] 2.44] 2.92] RD . 1.21] . . . 0.40 0.66 0.66 0.70 0.79 0.79 1.22 0.66 0.91 [0.21, [0.33, [0.30, [0.27, [0.37, [0.36, [0.56, [0.30, [0.49, 0.77] 1.34] 1.47] 1.80] 1.70] 1.76] RMPc 2.65] . 1.48] 1.67] 0.37 0.61 0.62 0.65 0.74 0.74 0.93 0.95 [0.19, [0.37, [0.27, [0.25, [0.28, [0.43, [0.49, [0.48, 0.73] 1.03] 1.39] 1.70] 1.95] 1.28] 1.78] RDc 1.88] . .

0.35 0.58 0.58 0.62 0.70 0.70 0.88 0.95 [0.13, [0.25, [0.20, [0.19, [0.21, [0.29, [0.34, [0.48, 0.92] 1.38] 1.69] 2.01] 2.30] 1.68] 2.26] 1.88] VRDc . . 0.34 0.57 0.57 0.60 0.68 0.68 0.86 0.92 0.98 [0.16, [0.23, [0.20, [0.21, [0.24, [0.25, [0.40, [0.37, [0.31, 0.75] 1.39] 1.64] 1.69] 1.94] 1.84] 1.82] 2.28] 3.04] RMP . 0.33 0.54 0.54 0.58 0.65 0.65 0.82 0.88 0.94 0.96 [0.15, [0.23, [0.21, [0.20, [0.39, [0.25, [0.46, [0.38, [0.32, [0.38, 0.73] 1.29] 1.44] 1.65] 1.08] 1.68] 1.46] 2.04] 2.76] 2.41] TMPc Infections-subnetwork 2 No. of studies: 2. No. of treatments: 4. No. of pairwise comparisons: 4. No. of designs: 2 Qtotal=0, df=0, p=n.a./ Qwithin=0, df=0, p=n.a./ Qbetween=0, df=0, p=n.a.; I²=n.a., Tau²=n.a. Treatment Effects: VTPc . 0.11 [0.01, 0.86] . 0.12 [0.02, 1.03] VTDc 0.89 [0.55, 1.45] 0.75 [0.47, 1.19] 0.11 [0.01, 0.86] 0.89 [0.55, 1.45] VMPc 0.84 [0.54, 1.30] 0.09 [0.01, 0.76] 0.75 [0.47, 1.19] 0.84 [0.54, 1.30] VDc

The RR for infections tends to be slightly higher for patients receiving lenalidomide-based therapies compared to patients receiving thalidomide-based therapies. Furthermore, the RR for infections are significantly higher for patients receiving continuous therapies, compared to fixed duration MP (RR: 2.51 [95% CI: 1.30; 4.84] to 3.05 [95% CI: 1.36; 6.83] (cf. Figure 13).

(a)

(b)

Figure 13: Forest plot for the outcome infections. (a) Infections-subnetwork 1. Reference treatment: MP. (b) Infections-subnetwork 2. Reference treatment: VMPc. Treatments are ordered by P-Score (descending)

Polyneuropathy Polyneuropathies were reported in 18 studies (13 two-arm studies, 5 three-arm studies), for 19 treatment regimens and a total of 8978 patients. However, the network was not fully connected and consists out of 2 subnetworks comprising 28 pairwise comparisons (cf. Figure 14).

Figure 14: Network graph for the outcome polyneuropathy. Any two treatments are connected by a line when there is at least one study comparing the two treatments. Line width: number of patients

We performed NMA for both polyneuropathy-subnetworks. Results for all network comparisons, including the ranking of treatments are shown in Table 10, per polyneuropathy-subnetwork. Low heterogeneity (I²= 3.4 %) was observed between studies for polyneuropathy-subnetwork 1.

Table 10: Results of NMA for the outcome polyneuropathy. Treatments are ordered by P-Score (descending). Upper triangle: direct estimate. Lower triangle: network estimate

Polyneuropathy-subnetwork 1 No. of studies: 16. No. of treatments: 15. No. of pairwise comparisons: 24. No. of designs: 12 Qtotal=6.21, df=6, p=0.40/ Qwithin=4.10, df=4, p=0.39/ Qbetween=2.11, df=2, p=0.35; I²=3.4%, Tau²=0.0248 Treatment Effects: 0.38 [0.23, RCD . . 0.62] ...... 0.50 [ 0.99 0.12 0.05, [0.31, [0.05, 5.07] RD 3.16] ...... 0.30] . . . . 0.39 [ 0.78 [ 0.86 0.83 0.12 0.04, 0.26, [0.26, [0.25, [0.05, 3.85] 2.40] RDc . . 2.90] . . 2.79] . 0.30] . . . . 0.38 [ 0.77 [ 0.98 [ 0.19 0.17 0.23, 0.08, 0.10, [0.02, [0.02, 0.62] 7.38] 9.13] TCD . . . . . 1.71] 1.34] . . . . 0.28 [ 0.57 [ 0.72 [ 0.74 [ 0.66 0.53 0.33 0.05 0.01 0.03, 0.16, 0.26, 0.08, [0.23, [0.19, [0.11, [0.00, [0.00, 2.90] 1.99] 2.04] 7.20] MP . . 1.90] 1.48] . 0.96] 0.83] 0.19] . . 0.26 [ 0.52 [ 0.66 [ 0.68 [ 0.91 [ 0.96 0.02, 0.11, 0.21, 0.06, 0.25, [0.30, 3.16] 2.38] 2.09] 7.85] 3.34] RCPc . . 3.05] ...... 0.25 [ 0.51 [ 0.65 [ 0.67 [ 0.90 [ 0.98 [ 0.10 0.01, 0.04, 0.06, 0.03, 0.08, 0.08, [0.01, 6.67] 6.88] 7.55] 16.79] 9.76] 12.13] MPc . . . . 0.80] . . . 0.22 [ 0.45 [ 0.57 [ 0.58 [ 0.79 [ 0.86 [ 0.87 [ 0.81 0.02, 0.10, 0.17, 0.05, 0.29, 0.22, 0.08, [0.33, 2.63] 1.98] 1.96] 6.54] 2.12] 3.43] 9.79] RMP 2.00] ......

0.20 [ 0.40 [ 0.51 [ 0.52 [ 0.70 [ 0.77 [ 0.78 [ 0.89 [ 0.14 0.02, 0.10, 0.19, 0.05, 0.30, 0.25, 0.08, 0.37, [0.05, 2.14] 1.50] 1.36] 5.31] 1.64] 2.33] 7.45] 2.15] RMPc . . 0.36] . . . 0.07 [ 0.14 [ 0.18 [ 0.19 [ 0.25 [ 0.28 [ 0.28 [ 0.32 [ 0.36 [ 0.89 0.01, 0.03, 0.04, 0.02, 0.05, 0.04, 0.02, 0.05, 0.07, [0.24, 0.69] 0.69] 0.85] 1.71] 1.24] 1.74] 4.58] 1.93] 1.91] TD 3.25] . . . . 0.06 [ 0.13 [ 0.16 [ 0.17 [ 0.23 [ 0.25 [ 0.25 [ 0.29 [ 0.32 [ 0.89 [ 0.01, 0.05, 0.07, 0.02, 0.09, 0.07, 0.02, 0.08, 0.11, 0.24, 0.54] 0.31] 0.37] 1.34] 0.56] 0.90] 2.95] 0.98] 0.91] 3.25] TMP . . . . 0.03 [ 0.05 [ 0.07 [ 0.07 [ 0.09 [ 0.10 [ 0.10 [ 0.11 [ 0.13 [ 0.36 [ 0.40 [ 0.00, 0.01, 0.02, 0.01, 0.03, 0.02, 0.01, 0.03, 0.05, 0.06, 0.10, 0.32] 0.25] 0.24] 0.80] 0.30] 0.41] 0.80] 0.40] 0.32] 2.31] 1.54] TMPc . . . 0.00 [ 0.01 [ 0.01 [ 0.01 [ 0.01 [ 0.01 [ 0.01 [ 0.01 [ 0.02 [ 0.04 [ 0.05 [ 0.13 [ 0.48 0.20 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.01, [0.23, [0.01, 0.12] 0.14] 0.16] 0.31] 0.19] 0.27] 0.50] 0.28] 0.30] 1.12] 0.96] 2.62] VMP 0.97] 3.70] 0.00 [ 0.00 [ 0.00 [ 0.00 [ 0.01 [ 0.01 [ 0.01 [ 0.01 [ 0.01 [ 0.02 [ 0.02 [ 0.06 [ 0.48 [ 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.23, 0.06] 0.07] 0.08] 0.16] 0.10] 0.14] 0.25] 0.15] 0.16] 0.57] 0.50] 1.35] 0.97] VTMPc . 0.00 [ 0.00 [ 0.00 [ 0.00 [ 0.00 [ 0.00 [ 0.00 [ 0.00 [ 0.00 [ 0.01 [ 0.01 [ 0.03 [ 0.20 [ 0.42 [ 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.01, 0.02, 0.07] 0.09] 0.11] 0.17] 0.13] 0.17] 0.28] 0.19] 0.20] 0.69] 0.64] 1.69] 3.70] 8.45] VD Polyneuropathy-subnetwork 2 No. of studies: 2. No. of treatments: 4. No. of pairwise comparisons: 4. No. of designs: 2 Qtotal=0, df=0, p=n.a./ Qwithin=0, df=0, p=n.a./ Qbetween=0, df=0, p=n.a.; I²=n.a., Tau²=n.a. Treatment Effects: VMPc 0.88 [0.57, 1.33] 0.75 [0.33, 1.72] 0.72 [0.48, 1.08] 0.88 [0.57, 1.33] VDc . 0.82 [0.56, 1.21] 0.75 [0.33, 1.72] 0.86 [0.34, 2.17] VTPc . 0.72 [0.48, 1.08] 0.82 [0.56, 1.21] 0.96 [0.38, 2.42] VTDc

The RR for polyneuropathies is the highest for patients receiving bortezomib-based therapies (RR: 88.22 [95% CI: 5.36; 1451.11] to 441.08 [95% CI: 7.74; 25 145.52] compared to MP). Furthermore, the RR for polyneuropathy appears to be smaller for patients receiving lenalidomide-based therapies, compared to patients receiving thalidomide-based therapies. (cf. Figure 15).

(a)

(b)

Figure 15: Forest plot for the outcome polyneuropathy. (a) Polyneuropathy-subnetwork 1. Reference treatment: MP. (b) Polyneuropathy-subnetwork 2. Reference treatment: VMPc. Treatments are ordered by P-Score (descending)

The proportion of direct evidence ranged from 0 to 100%. The test for disagreement showed no significant difference between direct and indirect estimates.

Thromboembolism Thromboembolism was reported in 14 studies (13 two-arm studies, 1 three-arm study), and could be analysed with data from 13 studies. One study was excluded due to zero events. Thromboembolism was reported for 13 treatment regimens and a total of 4277 patients. However, the network was not fully connected and consists out of 3 subnetworks comprising 15 pairwise comparisons (cf. Figure 16).

Figure 16: Network graph for the outcome thromboembolism. Any two treatments are connected by a line when there is at least one study comparing the two treatments. Line width: number of patients

We performed a NMA for thromboembolism-subnetwork 1 (thromboembolism-subnetworks 2 and 3 consisted out of two treatment regimens, only). Results for all network comparisons, including the ranking of treatments are shown in Table 11. Low heterogeneity (I²= 26.9 %) was observed between studies for thromboembolism-subnetwork 1.

Table 11: Results of NMA for the outcome thromboembolism. Treatments are ordered by P-Score (descending). Only subnetworks with > 1 designs. Upper triangle: direct estimate. Lower triangle: network estimate

Thromboembolism-subnetwork 1 No. of studies: 11. No. of treatments: 9. No. of pairwise comparisons: 13. No. of designs: 7 Heterogeneity / inconsistency: Q=5.47, df=4, p=0.24; I²=26.9%, Tau²=0.1107 Treatment Effects:

0.67 [0.10, 0.36 [0.16, 0.14 [0.03, MP 4.49] 0.81] . . . 0.67] . . 0.67 [0.10, 0.38 [0.11, 4.49] VMP . 1.27] . . . . . 0.36 [0.16, 0.54 [0.07, 0.81] 4.23] TMP ...... 0.26 [0.03, 0.38 [0.11, 0.71 [0.06, 2.43] 1.27] 7.69] VTMPc . . . . . 0.19 [0.03, 0.28 [0.02, 0.52 [0.07, 0.73 [0.04, 0.73 [0.29, 1.17] 3.90] 3.83] 13.36] MPc . 1.80] . . 0.15 [0.03, 0.23 [0.02, 0.43 [0.06, 0.60 [0.04, 0.83 [0.27, 0.88 [0.46, 0.87] 2.98] 2.86] 10.29] 2.53] RMPc 1.69] . . 0.14 [0.03, 0.20 [0.02, 0.37 [0.06, 0.53 [0.03, 0.73 [0.29, 0.88 [0.46, 0.67 [0.11, 0.56 [0.08, 0.67] 2.41] 2.24] 8.39] 1.80] 1.69] TMPc 4.20] 4.09] 0.09 [0.01, 0.13 [0.01, 0.25 [0.02, 0.35 [0.01, 0.48 [0.06, 0.59 [0.08, 0.67 [0.11, 0.84 [0.14, 1.04] 2.96] 3.25] 9.77] 3.77] 4.14] 4.20] TCDc 5.18]

0.08 [0.01, 0.11 [0.00, 0.21 [0.01, 0.30 [0.01, 0.41 [0.05, 0.50 [0.06, 0.56 [0.08, 0.84 [0.14, 0.98] 2.72] 3.05] 8.94] 3.62] 4.00] 4.09] 5.18] TDc

The RR for thromboembolism is higher for patients receiving continuous therapy compared to fixed duration therapy (RR: 3.91 [95% CI: 0.41; 37.12] to 13.09 [95% CI: 1.03; 167.25] compared to MP). Furthermore, patients receiving a thalidomide-based therapy have a greater risk for thromboembolism compared to patients receiving bortezomib- or lenalidomide-based therapies, or MP (cf. Figure 17).

Figure 17: Forest plot for the outcome thromboembolism. Thromboembolism-subnetwork 1. Reference treatment: MP. Treatments are ordered by P-Score (descending)

As the only closed loop in the subnetwork consists of multi-arm studies, there is no indirect evidence.

Withdrawals due to adverse events The amount of patients, who stopped assigned therapy and terminated their participation in the study due to AE, were reported in 16 studies (11 two-arm studies, 5 three-arm studies), for 19 treatment regimens and a total of 7052 patients. However, the network was not fully connected and consists of 2 subnetworks comprising 26 pairwise comparisons (cf. Figure 18).

Figure 18: Network graph for the outcome withdrawals due to AEs. Any two treatments are connected by a line when there is at least one study comparing the two treatments. Line width: number of patients

We performed NMA for both withdrawals due to AEs-subnetworks. Results for all network comparisons, including the ranking of treatments, are shown in Table 12. Low heterogeneity (I²= 25.5 %) was observed between studies for withdrawals due to AEs- subnetwork 1.

Table 12: Results of NMA for the outcome withdrawals due to AEs. Treatments are ordered by P-Score (descending). Only subnetworks with > 1 designs. Upper triangle: direct estimate. Lower triangle: network estimate

Withdrawals due to AEs- Subnetwork 1 No. of studies: 14. No. of treatments: 15. No. of pairwise comparisons: 22. No. of designs: 12 Qtotal=5.37, df=4, p=0.25/ Qwithin=0.93, df=2, p=0.62/ Qbetween=4.44, df=2, p=0.11; I²=25.5%, Tau²=0.0392 Treatment Effects: 0.76 0.29 [0.16, [0.18, MPc . . 3.48] . . . . 0.48] ...... 0.83 0.94 0.38 0.33 0.25 0.32 [0.37, [0.55, [0.16, [0.14, [0.09, [0.17, 1.85] MP 1.60] . . 0.91] 0.78] . 0.71] . . . 0.61] . . 0.78 0.94 0.82 [0.30, [0.55, [0.48, 2.04] 1.60] VMP . 1.39] ...... 0.76 0.91 0.97 [0.16, [0.16, [0.16, 3.48] 5.10] 5.88] TDc ...... 0.64 0.77 0.82 0.85 [0.21, [0.36, [0.48, [0.13, 1.92] 1.63] 1.39] 5.56] VTMPc ...... 0.39 0.47 0.50 0.52 0.61 0.87 [0.16, [0.22, [0.20, [0.09, [0.21, [0.45, 0.97] 0.99] 1.25] 3.06] 1.76] RMP 1.69] ...... 0.37 0.45 0.48 0.49 0.58 0.95 0.85 0.59 0.47 [0.19, [0.25, [0.22, [0.09, [0.23, [0.50, [0.52, [0.33, [0.27, 0.72] 0.78] 1.03] 2.60] 1.49] 1.80] RMPc . 1.39] 1.05] . 0.83] . . . 0.30 0.37 0.39 0.40 0.48 0.78 0.82 0.76 0.67 [0.07, [0.09, [0.09, [0.05, [0.10, [0.17, [0.20, [0.21, [0.19, 1.38] 1.43] 1.69] 3.47] 2.27] 3.45] 3.28] TD . . 2.75] . 2.34] . .

0.29 0.35 0.38 0.39 0.46 0.75 0.79 0.97 [0.18, [0.19, [0.16, [0.08, [0.17, [0.35, [0.50, [0.23, 0.48] 0.67] 0.86] 1.94] 1.23] 1.61] 1.24] 4.06] TMPc ...... 0.25 0.30 0.32 0.33 0.40 0.65 0.68 0.83 0.86 0.80 [0.11, [0.15, [0.13, [0.06, [0.14, [0.28, [0.39, [0.20, [0.43, [0.48, 0.59] 0.61] 0.78] 1.92] 1.11] 1.47] 1.18] 3.41] 1.72] RCPc . 1.34] . . . 0.23 0.28 0.30 0.31 0.36 0.59 0.62 0.76 0.79 0.92 0.88 [0.06, [0.09, [0.09, [0.04, [0.10, [0.17, [0.20, [0.21, [0.24, [0.29, [0.33, 0.84] 0.84] 1.01] 2.27] 1.38] 2.09] 1.94] 2.75] 2.59] 2.94] TCD . 2.31] . . 0.22 0.27 0.28 0.29 0.35 0.57 0.60 0.73 0.75 0.88 0.96 0.76 0.81 0.42 [0.10, [0.15, [0.13, [0.05, [0.13, [0.26, [0.36, [0.19, [0.40, [0.53, [0.33, [0.46, [0.49, [0.23, 0.50] 0.48] 0.63] 1.65] 0.91] 1.22] 0.98] 2.77] 1.43] 1.45] 2.79] RDc 1.26] 1.35] 0.77] 0.20 0.24 0.26 0.27 0.32 0.52 0.55 0.67 0.69 0.80 0.87 0.92 1.07 [0.09, [0.14, [0.12, [0.05, [0.13, [0.23, [0.30, [0.19, [0.34, [0.42, [0.33, [0.58, [0.65, 0.47] 0.42] 0.55] 1.54] 0.80] 1.16] 0.98] 2.34] 1.38] 1.53] 2.31] 1.45] TMP 1.75] . 0.20 0.24 0.25 0.26 0.31 0.51 0.54 0.65 0.68 0.79 0.86 0.90 0.98 [0.08, [0.12, [0.11, [0.04, [0.11, [0.21, [0.28, [0.17, [0.32, [0.40, [0.29, [0.55, [0.61, 0.49] 0.47] 0.60] 1.56] 0.85] 1.21] 1.03] 2.51] 1.45] 1.57] 2.53] 1.47] 1.59] RD . 0.09 0.11 0.12 0.12 0.15 0.24 0.25 0.31 0.32 0.37 0.40 0.42 0.46 0.47 [0.03, [0.05, [0.04, [0.02, [0.05, [0.09, [0.11, [0.07, [0.13, [0.17, [0.12, [0.23, [0.22, [0.21, 0.25] 0.26] 0.32] 0.77] 0.45] 0.63] 0.55] 1.33] 0.76] 0.81] 1.37] 0.77] 0.98] 1.02] VRDc Withdrawals due to AEs- Subnetwork 2 No. of studies: 2. No. of treatments: 4. No. of pairwise comparisons: 4. No. of designs: 2 Qtotal=0, df=0, p=n.a./ Qwithin=0, df=0, p=n.a./ Qbetween=0, df=0, p=n.a.; I²=n.a., Tau²=n.a. Treatment Effects: VDc 0.89 [0.67, 1.18] 0.86 [0.65, 1.14] . 0.89 [0.67, 1.18] VMPc 0.97 [0.74, 1.27] 0.68 [0.37, 1.25] 0.86 [0.65, 1.14] 0.97 [0.74, 1.27] VTDc . 0.60 [0.31, 1.18] 0.68 [0.37, 1.25] 0.70 [0.36, 1.37] VTPc

The RR to discontinue assigned therapy was greater for patients receiving double or triple drug combinations compared to MP alone (RR: 1.06 [95% CI: 0.63; 1.81] to 8.92 [95% CI: 3.82; 20.84]). Study withdrawal was similar across bortezomib-, lenalidomide-, and thalidomide- based regimens. There seems to be no clear difference between double versus triple drug combinations or between fixed duration versus continuous therapy (cf. Figure 19).

(a)

(b)

Figure 19: Forest plot for the outcome withdrawals due to AEs. (a) Subnetwork 1. Reference treatment: MP. (b) Subnetwork 2. Reference treatment: VMPc. Treatments are ordered by P- Score (descending).

The confidence in estimates for withdrawals due to AEs was rated for RD, TMP, VMP, and VRDc. RD, TMP, and VRDc for first-line treatment of MM results in a large increase in withdrawals due to AEs. The use of VMP as initial therapy for MM probably results in little to no difference in withdrawals due to AEs, compared to MP (cf. Table 12).

The proportion of direct evidence ranged from 0 to 100%. The test for disagreement showed no significant difference between direct and indirect estimates.

Summary of Findings (SoF) The SoF for the main comparisons are presented in Table 12. The main comparisons are RD, TMP, VMP, and VRDc versus MP, respectively. The GRADE approach (30) was used to rate the certainty of evidence in four selected outcomes for the main comparisons. The outcomes OS, PFS, SAEs and withdrawals due to AEs were chosen because they were seen as the crucial outcomes to decide whether a treatment should be applied or not.

Table 12: Summary of Findings

Multiple drug combinations of bortezomib, lenalidomide, and thalidomide for first-line treatment in transplant-ineligible multiple myeloma patients Patient or population: newly diagnosed, symptomatic multiple myeloma patients Setting: non-transplant Intervention: RD, TMP, VMP, VRDc Comparison: MP Outcomes Effects and 95% confidence intervals in the effects. Main comparator is MP Risk with MP* Risk with RD Risk with TMP Risk with VMP Risk with VRDc Overall survival Median overall survival NMA-median OS: 57.0 NMA-median OS: 47.9 NMA-median OS: 51.3 NMA-median OS: 73.3 over all studies in the (36.3 to 89.8) months (37.0 to 61.9) months (33.6 to 79.8) months (39.0 to 138.1) months network: 35.9 months NMA-HR: 0.63 (95%-CI: NMA-HR: 0.75 (95%-CI: NMA-HR: 0.70 (95%-CI: NMA-HR: 0.49 (95%-CI: 0.40; 0.99) 0.58; 0.97) 0.45; 1.07) 0.26; 0.92) ⨁⨁⨁◯ moderate ⨁⨁⨁◯ moderate ⨁⨁◯◯ low confidence ⨁⨁⨁◯ moderate confidence in estimates confidence in estimates in estimates due to confidence in estimates due to inconsistency of due to inconsistency of inconsistency of I²=53.9% due to inconsistency of I²=53.9% (downgrade I²=53.9% (downgrade (downgrade minus 1), I²=53.9% (downgrade minus 1) minus 1) imprecision (downgrade minus 1) minus 1) Progression-free Median progression free NMA-median PFS: 25.2 NMA-median PFS: 26.0 Risk not available because NMA-median PFS: 48.2 survival survival over all studies (17.1 to 37.3) months (21.0 to 32.8) months VMP is not connected to (28.3 to 82.0) months included in the network: MP in the network. 16.4 months NMA-HR: 0.65 (95%-CI: NMA-HR: 0.63 (95%-CI: NMA-HR not available, NMA-HR: 0.34 (95%-CI: 0.44; 0.96) 0.50; 0.78) because VMP is not 0.20; 0.58) connected to MP in the network.

Multiple drug combinations of bortezomib, lenalidomide, and thalidomide for first-line treatment in transplant-ineligible multiple myeloma patients Patient or population: newly diagnosed, symptomatic multiple myeloma patients Setting: non-transplant Intervention: RD, TMP, VMP, VRDc Comparison: MP Outcomes Effects and 95% confidence intervals in the effects. Main comparator is MP Risk with MP* Risk with RD Risk with TMP Risk with VMP Risk with VRDc ⨁⨁⨁◯ moderate ⨁⨁⨁◯ moderate Confidence in estimates ⨁⨁⨁◯ moderate confidence in estimates confidence in estimates can not be assessed, confidence in estimates due to inconsistency of due to inconsistency of because VMP is not due to inconsistency of I²=55.3% (downgrade I²=55.3% (downgrade connected to MP in the I²=55.3% (downgrade minus 1). minus 1). network. minus 1). Serious adverse Mean risk over all studies Risk not available, Risk not available, NMA-risk: 46.2% (38.3 to Risk not available, because events included in the network: because RD is not because TMP is not 55.6) VRDc is not connected to 36.1 % (177/490) connected to MP in the connected to MP in the MP in the network. network. network. NMA-RR not available, NMA-RR not available, NMA-RR: 1.28 (95%-CI: NMA-RR not available, because RD is not because TMP is not 1.06; 1.54) because VRDc is not connected to MP in the connected to MP in the connected to MP in the network. network. network. Confidence in estimates Confidence in estimates ⨁⨁⨁◯ moderate Confidence in estimates can not be assessed, can not be assessed, confidence in estimates. can not be assessed, because RD is not because TMP is not Downgrade minus 1 for because VRDc is not connected to MP in the connected to MP in the risk of bias. connected to MP in the network. network. network. Withdrawals due Mean risk over all studies NMA-risk: 38.5% (19.6 to NMA-risk: 37.7% (22.1 to NMA-risk: 9.75% (5.8 to NMA-risk: 82.1% (35.1 to to adverse events included in the network: 75.44) 64.5) 16.7) 191.7) 9.2% (77/837) NMA-RR: 4.18 (95%-CI: NMA-RR: 4.10 (95%-CI: NMA-RR: 1.06 (95%-CI: NMA-RR: 8.92 (95%-CI: 2.13; 8.20) 2.40; 7.01) 0.63; 1.81) 3.82; 20.84) ⨁⨁⨁⨁ high confidence ⨁⨁⨁⨁ high confidence ⨁⨁⨁◯ moderate ⨁⨁⨁⨁ high confidence in estimates. in estimates. confidence in estimates. in estimates.

11. Summary of available data on comparative cost and cost-effectiveness of the medicine. A scoping review was undertaken for economic evidence that addressed treatment regimens based on bortezomib, thalidomide or lenalidomide as first-line therapy in MM. The electronic search was undertaken on PubMed in November 2018 including the keywords: myeloma, cost- effectiveness, cost-benefit, cost-utility, cost-analysis, ICER, QALY, DALY, burden. The search yielded 896 results. These results were screened for cost evidence on first-line treatment strategy involving at least one of the three substances lenalidomide, thalidomide or bortezomib in patients who were ineligible for stem cell transplantation. Further, we assessed Health Technology Assessment (HTA) reports by NICE and screened the references of the included studies. We identified two eligible cost-analyses, one cost-impact analysis and one retrospective, claims-based study available in full-text format.

A systematic review (SR) by Picot et al. from 2011 evaluated the cost-effectiveness of bortezomib and thalidomide in combination regimens with an alkylating agent and a corticosteroid for the first-line treatment of patients suffering from MM, who were not eligible for stem cell transplantation (60). The review authors did not identify any eligible full-texts of economic evaluations. A HTA report by NICE from 2011 evaluated bortezomib and thalidomide for the first- line treatment of MM, and was based on the SR by Picot et al. (12, 60). Besides the SR, both reports included three economic models by NICE from the UK’s health system perspective. Two models were provided by the manufactures of the drugs and a third by an assessment team of NICE. A Markov Model developed by Celgene, the manufacturer of thalidomide, compared the cost-effectiveness of TMP with VMP and MP, respectively. The model included four stages: pre- progression without AEs, pre-progression with AEs, post-progression and death; and addressed a lifetime horizon (30 years). Data for treatment effects was adapted from three RCTs, while cost and resource data stem from a variety of sources including manufacturer initiated surveys among practitioners the British National Formulary (BNF) and NHS reference costs. Costs represent 2008 GBP. The resulting incremental costs per QALY of the base-case were 23,381 GBP for MPT compared to MP alone and 303,845 GBP for VMP compared to MP. Janssen, the manufacturer of bortezomib, presented a cost-utility analysis to compare VMP with either MPT, thalidomide, cyclophosphamide and attenuated dexamethasone (CTDa) or MP, respectively. The model comprised four stages: before response to treatment; response to treatment without progression; post-progression; and death. Data on clinical effectiveness stem from a variety of RCTs or, for MP, from MA of RCTs. When necessary, data, such as for PFS, were extrapolated for longer-timeframes. QALY values were set to 0.77 (stage 1), 0.81 (stage 2), and 0.61 (stage 3), respectively, without a description of the source of the given values. It showed base-case cost- effectiveness results of 8912 GBP per QALY for MPT versus MP, 2,234 GBP for CTDa versus MP and 10,498 GBP for VMP versus MP. The model, which was undertaken by the NICE assessment group, comprised three stages: treatment, post-treatment and post-progression. It consisted of cycles of six weeks and a 30 years horizon. Data on clinical effectiveness and health-related quality of life were included from the respective SR by Picot et al. (60). Cost data were derived from the BNF, RCTs included in the SR and expert opinion. Modelling by the assessment team resulted in additional costs of 9174 GBP per QALY for MPT versus MP, 33,216 GBP for CTDa versus MP and 29,837 GBP. Particularly the prices per additional QALY gain for bortezomib were substantially higher as calculated by the manufacturer. More detailed results for the base-cases of all models are given in Table 13. An assessment of the three models by Cooper et al. identified the HR for the comparison of MPT versus MP and the cost of bortezomib as the most influential factors responsible for the differences in the models (61).

Table 13: Base-case results for the three cost models included in the HTA report of bortezomib and thalidomide for the first‑line treatment of MM by NICE (12)

Model Intervention Comparator Inclusion of Incremental Incremental ICER source adverse effect cost in GBP, (costs/ events in the (QALYs) 2008 QALY) analysis Celgene MPT MP Yes, 0.85 19,768 23,381 treatment costs and utility increment Celgene VMP MPT Yes, 0.07 21,483 303,845 treatment costs and utility increment Janssen MPT MP (7 cycles) Yes, 0.55 4888 8912 (thalidomide treatment at 150 costs mg/day) Janssen CTDa MP (7 cycles) Yes, 0.21 10,905 2234 (thalidomide treatment at 167 costs mg/day) Janssen VMP MP (7 cycles) Yes, 1.17 12,242 10,498 (bortezomib treatment at 31.5 vials) costs NICE MPT MP Yes, 1.22 11,207 9174 assessment treatment group costs NICE CTDa MP Yes, 0.26 8592 33,216 assessment treatment group costs

NICE VMP MP Yes, 1.20 35,749 29,837 assessment (bortezomib treatment group at one vial costs per administario n)

Garrison et al. conducted cost-effectiveness analysis to compare MP with VMP, MPT, MP together with RMP and MP with MPR-R using a Markov model that represents the US taxpayer’s perspective (62). Clinical effectiveness data were derived from RCTs (VISTA, IFM99-06 and MM- 015). The hypothetical cohort consisted of patients suffering from MM who were ineligible to transplantation and had an average age of 70 years. The model consisted of seven stages. Treatment related AEs were included in the model in costs and incremental utilities. Information on costs were obtained from the literature. Costs, as well as health outcomes, were discounted at 3% and costs were adjusted to represent 2010 US dollars. Table 14 represents the monthly costs for on-treatment stages, which comprised stable disease and minimal response (MR), partial

response (PR) and complete response (CR). The costs for MP alone very lower with regard to drug costs, overall medical costs and the estimated costs for the management of AEs. MPT had the highest cost in all three domains. Table 15 gives an overview of the 20-year costs for the three regimens. Similarly, the total cost for a treatment duration of 20-years was lowest for MP. The total cost over 20-years for treatment with VMP and MPT where almost or over twice as high as with MP alone. Table 16 illustrates the cost-effectiveness data. Compared to VMP, MP was more effective with regard to costs per life-year and cost per QALY, while compared to MPT, VMP was cost saving.

Table 14: Monthly costs for the on treatment stages stable disease and MR, PR and CR derived from Garrison et al. (62)

Monthly costs for on-treatment stages (in 2010 US$) VMP MP MPT Per-protocol 4,464 108 6,090 drug Per-protocol 960 123 478 medical Total AE 2,476 2,165 3,522 management

Table 15: Discounted 20-year direct medical costs derived from Garrison et al. (62)

Discounted 20-year direct medical cost (in 2010$ US dollars) Intervention On treatment Drug Total (including treatment free intervals, progressive disease and second line therapy) VMP 70,363 39,754 119,102

MP 16,109 728 63,294

MPT 93,504 56,435 142,452

Table 16: Cost-effectiveness of MP and MPT in comparison to VMP derived from Garrison et al. (62)

Cost effectiveness compared to VMP Cost Life year QALYs Incremental Incremental cost per life cost per QALY year VMP-MP 55,808 1.323 0.945 42,169 59,076

VMP-MPT 23,350 0.047 0.043 VMP cost VMP cost saving saving

A cost-impact model by Schey et al. addressed the total costs associated with first-line treatment of newly diagnosed MM who were ineligible for stem cell transplant (63). It was based on trial data and funded by the manufacturer of lenalidomide, Celgene. Total costs were modelled over five years in the EU5 (France, Germany, Italy, Spain, United Kingdom) based on trial data for treatment duration and treatment of progression. The authors evaluated and compared three scenarios. A baseline-scenario represented the 2017 uptake of lenalidomide in the assessed countries. The market-shares in this scenarios where 64% for bortezomib, 25% for thalidomide and 11% for lenalidomide. In a hypothetical situation represented a steady increase of the uptake of lenalidomide to 50% of the market in year five. In a second hypothetical situation, the authors evaluated a 20% increased uptake of the triple regimen carfilzomib, lenalidomide, and dexamethasone as a second-line of treatment. Direct drug costs were averaged from the listing prices across the five countries. Data on the monthly treatment-line costs were taken from the assessment of real-world treatment cost of relapsed and refractory MM by Gaultney et al. and adjusted for first-line application (64).

The assumed annual treatment costs for the baseline scenario raged between 40,692€ and 40,781€ per patient and year, while the total costs for an increased uptake of lenalidomide ranged between 41,559€ and 44,139€ per patient and year. The difference between both situations rose relatively steady from 2.13% of the total cost of the baseline scenario in year one to 8.23% of the baseline scenario in year five. Across all three scenarios the total treatment cost in the fifth year of treatment were lowest for the baseline situation (40,781€ per patient and year). For the increase uptake of lenalidomide in first line therapy, the annual costs per patient in year five were 44,139€ or +8% of the baseline cost. For the 20% uptake of the triplet regimen as second-line treatment, the total increase in year five in total cost per patient and year were 52,528€ or +29% of the respective cost in the baseline scenario.

A retrospective study by Arikian et al. based on US claims data from 2006 to 2013 assessed patient monthly direct cost and cost patterns over quarterly time periods for patients with newly diagnosed MM treated with either bortezomib or lenalidomide based regimens (65). The study was conducted by the manufacturer of lenalidomide, Celgene. Claims for stem cell transplantation and regimens, combining bortezomib and lenalidomide, were not included. Patient healthcare costs were adjusted to 2014 US$. Costs were evaluated for 444 patients with newly diagnosed MM treated first-line with lenalidomide and 737 with bortezomib, for which data from treatment initiation until next treatment was available. For patients with first line treatment of lenalidomide the monthly treatment cost decreased steadily from 15,090 US$ in the first to the third month since start of treatment to 5266 US$ in month 19 or longer. In patients treated with first-line bortezomib the monthly costs fell from 16,126 US$ in the first three months of treatment to 4833 US$ in the 19th month or longer. Multivariable regression unadjusted for factors such as age, sex, 54

number of prescriptions before index date for the beginning of first-line treatment, previous cancer history, etc. showed mean total cost of 7534 $US (standard deviation (SD) 3207) for patients treated first-line with lenalidomide, compared to 10,763 $US (SD 3938) in patients receiving first-line bortezomib. Monthly pharmacy costs included in the total monthly cost in the unadjusted analysis were 4101 $US (SD 1931) and 4855 $US (SD 2431) for lenalidomide and bortezomib, respectively. In the adjusted analysis total monthly cost for first-line treatment with lenalidomide and bortezomib were 7641 $US (SD 3101) and 10,808 $US (SD 5043). The monthly pharmacy costs included in the adjusted monthly total cost were 4175 $US (SD 1637) for patients receiving lenalidomide compared to 4040 $US (SD 2774) in patients treated with bortezomib.

REGULATORY INFORMATION 12. Summary of regulatory status and market availability of the medicine Bortezomib, lenalidomide, and thalidomide are approved worldwide and in various jurisdictions such as:

Australian Government, Department of Health, Therapeutic Goods Administration (TGA)

 Bortezomib is licensed in Australia for the treatment of: o “VELCADE, in combination with melphalan and prednisone is indicated for the treatment of patients with previously untreated multiple myeloma who are not candidates for high dose chemotherapy.” o “VELCADE, as part of combination therapy, is indicated for induction therapy prior to high dose chemotherapy with autologous stem cell rescue for patients under 65 years of age with previously untreated multiple myeloma.” o “VELCADE is also indicated for the treatment of multiple myeloma patients who have received at least one prior therapy, and who have progressive disease.”(66)  Lenalidomide is licensed in Australia for the treatment of: o “Revlimid is indicated for the treatment of patients with newly diagnosed multiple myeloma who are ineligible for autologous stem cell transplantation.” o “Revlimid is indicated for the maintenance treatment of patients with newly diagnosed multiple myeloma who have undergone autologous stem cell transplantation.” o “Revlimid in combination with dexamethasone is indicated for the treatment of multiple myeloma patients whose disease has progressed after one therapy.”(67)  Thalidomide is licensed in Australia for the treatment of: o “Thalomid in combination with melphalan and prednisone is indicated for the treatment of patients with untreated multiple myeloma aged 65 years and over or ineligible for high dose chemotherapy. “ o “Thalomid in combination with dexamethasone is indicated for induction therapy prior to high dose chemotherapy with autologous stem cell rescue, for the treatment of patients with untreated multiple myeloma. “ o “Thalomid, as monotherapy, is indicated for the treatment of multiple myeloma after failure of standard therapies.”(68)

European Medicines Agency (EMA)

 Bortezomib is licensed in the European Union (EU) for the treatment of: o “Velcade is used to treat multiple myeloma, a blood cancer, in the following groups of patients: . Previously untreated adults who cannot have high-dose chemotherapy with a blood stem-cell transplant. In these patients, Velcade is used in combination with melphalan and prednisone; . Previously untreated patients who are going to receive high-dose chemotherapy followed by a blood stem-cell transplant. In this group of patients, Velcade is used in combination with dexamethasone, or with dexamethasone plus thalidomide; . Adults whose disease is getting worse after at least one other treatment and who have already had, or cannot undergo, a blood stem-cell transplant.

o Velcade is either used on its own in these patients or in combination with pegylated liposomal doxorubicin or dexamethasone.”(69)  Lenalidomide is licensed in the EU for the treatment of: o “In multiple myeloma, a cancer of a type of white blood cells called plasma cells, Revlimid is used: . On its own, in adults who have had a stem cell transplant (a procedure where the patient’s bone marrow is cleared of cells and replaced by stem cells from a donor) to stop the progression of the cancer; . In combination with dexamethasone (an anti-inflammatory medicine), for the treatment of adults with previously untreated (newly diagnosed) multiple myeloma, who cannot have stem cell transplantation; . In combination with melphalan (a cancer medicine) and prednisone (an anti- inflammatory medicine) for the treatment of adults with previously untreated multiple myeloma, who cannot have stem cell transplantation; . In combination with dexamethasone, in adults whose disease has been treated at least once in the past.”(70)  Thalidomide is licensed in the EU for the treatment of: o “Thalidomide Celgene is used to treat multiple myeloma (a cancer of the bone marrow) in combination with the cancer medicines melphalan and prednisone in patients who have not been treated for multiple myeloma before. It is used in patients aged over 65 years, and in younger patients if they cannot be treated with high-dose chemotherapy (anticancer treatments).”(71)

US Food and Drug Administration (FDA)

 Bortezomib is licensed in the USA for the treatment of: o “The Food and Drug Administration has approved Velcade to treat a type of cancer called multiple myeloma. Velcade should only be used in people who have already been treated with two other types of chemotherapy (drugs used to kill cancer cells), and whose cancer has still progressed on the most recent therapy.”(72)  Lenalidomide is licensed in the USA for the treatment of: o “Revlimid (lenalidomide) is a prescription medicine approved in combination with dexamethasone to treat patients with multiple myeloma (a type of cancer of the bone marrow) who already have had prior therapy.”(73)  Thalidomide is licensed in the USA for the treatment of: o “Thalomid (thalidomide) is a prescription medicine taken, with the medicine dexamethasone, to treat people who have been newly diagnosed with multiple myeloma. Thalomid is also used to treat people when new lesions of leprosy flare up.”(74)

Japanese Pharmaceuticals and Medical Devices Agency (PMDA)

 Bortezomib is licensed in Japan for the treatment of: o “A drug with a new route of administration indicated for the treatment of multiple myeloma.”(75) o “ A drug with a new indication and a new dosage for the treatment of multiple myeloma.”(76) o “Drug containing a new active ingredient indicated for treatment of relapsed or refractory multiple myeloma.”(77)  Lenalidomide is licensed in Japan for the treatment of: 57

o Lenalidomide hydrate: “Drugs with a revised indication for the treatment of multiple myeloma.”(78) o “A drug with a new active ingredient indicated for the treatment of relapsed or refractory multiple myeloma.”(79)  Thalidomide is licensed in Japan for the treatment of: o “A drug containing a new active ingredient indicated for the treatment of relapsed or refractory multiple myeloma.”(80)

Health Canada (HC)

 Bortezomib is licensed in Canada for the treatment of: o “VELCADE® is used for the treatment of adult patients with: . Previously untreated Multiple Myeloma (MM) who are unsuitable for stem cell transplantation as part of combination therapy. MM is a cancer of the bone marrow . Previously untreated MM who are suitable for stem cell transplantation as part of a medically recognized combination therapy for initial treatment prior to stem cell transplant. . Relapsed MM” (81)  Lenalidomide is licensed in Canada for the treatment of: o “REVLIMID® is used with dexamethasone to treat patients with multiple myeloma who are not eligible for stem cell transplant.”(82)  Thalidomide is licensed in Canada for the treatment of: o “THALOMID® is used in combination with melphalan and prednisone in the treatment of patients with previously untreated MM who are 65 years of age or older.”(83)

13. Availability of pharmacopoeial standards (British Pharmacopoeia, International Pharmacopoeia, United States Pharmacopoeia, European Pharmacopoeia) Thalidomide is included in the United States Pharmacopoeia, bortezomib or lenalidomide are not mentioned (84).

Bortezomib, lenalidomide and thalidomide are not mentioned in the British, European or International Pharmacopoeia.

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APPENDIX 1: METHODOLOGICAL APPROACH Types of studies

We included studies if they are RCTs with > one treatment arm. We included both full‐text and abstract publications if sufficient information on study design, characteristics of participants and interventions provided. In the case of cross-over trials, only the first period of the trial was analysed. There was no limitation with respect to the length of follow-up.

We excluded studies that were non-randomised, case reports and clinical observations.

Types of participants

Studies included trials involving adult patients according to the definition in the studies (usually ≧ 18 years of age), with a newly confirmed diagnosis of multiple myeloma, irrespective of type and stage of cancer and gender. We included trials that included patients receiving a combination therapy of at least one novel agent (bortezomib, lenalidomide, thalidomide) and a corticosteroid (dexamethasone, or (melphalan/)prednisone) in at least one treatment arm for first-line treatment of non-transplant myeloma patients or as induction therapy before high dose chemotherapy. We assumed that patients who fulfil the inclusion criteria were equally eligible to be randomised to any of the interventions we planned to compare.

We excluded trials including participants receiving neither bortezomib, lenalidomide, or thalidomide (triple or double combination) in at least one treatment arm, trials including participants receiving no corticosteroid, and trials including relapsed or refractory multiple myeloma patients.

Types of interventions

Nowadays, the recommended treatment for transplant-ineligible newly diagnosed multiple myeloma patients is either a double or a triple drug-combination therapy (85), (86), which consists of:

 Double drug combination: o Immunomodulatory drug: lenalidomide, thalidomide or o Proteasome inhibitor: bortezomib o Respectively in combination with a glucocorticoid: dexamethasone or prednisone (co- administered with melphalan)  Triple drug combination: o Immunomodulatory drug, e.g. thalidomide in combination with proteasome inhibitor, e.g. bortezomib, or o Immunomodulatory drug, e.g. thalidomide in combination with immune-suppressor, e.g. cyclophosphamide, o Or proteasome inhibitor, e.g. bortezomib in combination with immune-suppressor, e.g. cyclophosphamide o Respectively in combination with a glucocorticoid: dexamethasone or prednisone (co- administered with melphalan)

Combinations of these interventions at any dose and by any route were compared to each other in a full network. We will included all RCTs comparing in at least two study arms one of the above mentioned intervention of interest. As the aim of this review is to inform an application for the list of essential medicines, the focus of this review was to compare the efficacy and safety of bortezomib, lenalidomide and thalidomide. Therefore, in the case we identified additional new 66

drugs for first-line treatment of multiple myeloma, these will be included into the network in an update of this review and not further considered in this rapid review.

We assume that any participant that meets the inclusion criteria was, in principle, equally likely to be randomised to any of the eligible interventions. We planned to group interventions by evaluating different drug doses together as one drug of interest, according to the product characteristics.

We excluded trials evaluating the efficacy and safety of the interventions of interest for relapsed/refractory multiple myeloma patients, supportive treatment during stem cell transplantation, and/or maintenance therapy. Agents used for medicative therapy to treat myeloma in following lines of therapy might be the same as for first-line treatment, but to include clinically homogenous trials to answer the research question, we focused on first-line only.

Comparison of direct interest

Randomised controlled trials comparing directly the efficacy and safety of double and triple combination therapies of the agents of interest (bortezomib, lenalidomide, thalidomide) for first- line treatment of multiple myeloma patients are limited. Therefore there was high uncertainty whether their efficacy is comparable, and if not, which one is more effective and/or safer.

Additional interventions to supplement the analysis

Included trials should be comparable in terms of clinical and methodological criteria to hold for transitivity (87). Therefore, we excluded trials evaluating in only one arm an intervention of interest, but in the control arm different types of therapy (e.g. autologous stem cell transplantation).

Types of outcome measures

We included all trials fitting the inclusion criteria mentioned above, irrespective of reported outcomes. We estimated the relative ranking of the competing interventions according to each of the following outcomes.

Primary outcomes

 Overall survival  Progression-free survival

Secondary outcomes

 Grade 3 or 4 adverse events (with a special focus on polyneuropathy, neutropenia, anaemia, thrombocytopenia, thromboembolism, and infections)  Serious adverse events  Quality of life if measured at certain periods: short (1-3 months)medium (6-9 months)long (12 months and longer)

Search methods for identification of studies

Electronic searches

We searched the following databases without language restrictions. We searched for all possible comparisons formed by the interventions of interest. We started the search in 1998, as thalidomide has been mentioned the first time for myeloma treatment in 1999 (88).

 The Cochrane Central Register of Controlled Trials (CENTRAL) (via the Cochrane Library, latest issue)  MEDLINE (via Ovid, 1998 to present)

Medical subject headings (MeSH) or equivalent and text word terms were used. There were no language restrictions. Searches were tailored to individual databases. The search strategy for CENTRAL and MEDLINE is in Appendix 2.

Searching other resources

In addition, we searched the following databases/sources:

 Study registries: o EU clinical trials register: https://www.clinicaltrialsregister.eu/ctr-search/search o World health organisation: http://apps.who.int/trialsearch/ o Clinicaltrials.gov: https://clinicaltrials.gov/ o ISRCTN: http://www.isrctn.com/  Conference proceedings of annual meetings of the following societies for abstracts, if not included in CENTRAL (2010 to present). o American Society of Hematology o American Society of Clinical Oncology o European Hematology Association  We checked reference lists of reviews and retrieved articles for additional studies and we performed citation searches on key articles.

Data collection and analysis

Selection of studies

Two review authors independently screened the results of the search strategies for eligibility for this review by reading the abstracts using Endnote software. We coded the abstracts as either 'retrieve' or 'do not retrieve'. In the case of disagreement or if it was unclear whether we should retrieve the abstract or not, we obtained the full- text publication for further discussion. Independent review authors eliminated studies that clearly did not satisfy the inclusion criteria, and obtained full-text copies of the remaining studies. Two review authors read these studies independently to select relevant studies, and in the event of disagreement, a third author adjudicated. We did not anonymise the studies before assessment. We included a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart in the full review that shows the status of identified studies (89) as recommended in Part 2, Section 11.2.1 of the Cochrane Handbook for Systematic Reviews of Interventions (90). We included studies in the review irrespective of whether measured outcome data were reported in a ‘usable’ way.

Data extraction and management

Two review authors extracted data using a standardised data extraction form developed in Excel. If the authors were unable to reach a consensus, we consulted a third review author for final decision. If required, we contacted the authors of specific studies for supplementary information (91). After agreement has been reached, we entered data into Review Manager (92). We extracted the following information.

 General information: Author, title, source, publication date, country, language, duplicate publications.

 Quality assessment: Sequence generation, allocation concealment, blinding (participants, personnel, outcome assessors), incomplete outcome data, selective outcome reporting, other sources of bias.  Study characteristics: Trial design, aims, setting and dates, source of participants, inclusion/exclusion criteria, comparability of groups, subgroup analysis, treatment cross- overs, compliance with assigned treatment, length of follow-up.  Participant characteristics: Newly diagnosed individuals, ineligible for transplant, cytogenetic subtype, additional diagnoses, age, gender, ethnicity, number of participants recruited/allocated/evaluated, participants lost to follow-up, type of treatment (multi-agent standard treatment (intensity of regimen, number of cycles))  Interventions: type, dose and cycles of treatment; duration of follow-up.  Outcomes: Overall survival, progression-free survival, grade 3 and 4 adverse events, serious adverse events, quality of life, polyneuropathy, neutropenia, anaemia, thrombocytopenia, thromboembolism, and infections.  Notes: Sponsorship/funding for trial and notable conflict of interest of review authors

We collated multiple reports of the same study, so that each study rather than each report was the unit of interest in the review. We collected characteristics of the included studies in sufficient detail to populate a table of ‘Characteristics of included studies’ in the full review.

Data on potential effect modifiers

We extracted from each included study data on the following:

 intervention and population characteristics that may act as effect modifiers  year of publication

Assessment of risk of bias in included studies

This section is taken from the PaPaS template for protocols.

Two review authors independently assessed risk of bias for each study, using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (93) and adapted from those used by the Cochrane Pregnancy and Childbirth Group, with any disagreements resolved by discussion. We completed a 'Risk of bias' table for each included study using the 'Risk of bias' tool in RevMan (92).

We assessed the following for each study.

 Random sequence generation (checking for possible selection bias): We assessed the method used to generate the allocation sequence as: low risk of bias (any truly random process, e.g. random number table; computer random number generator); unclear risk of bias (method used to generate sequence not clearly stated). Studies using a non-random process (e.g. odd or even date of birth; hospital or clinic record number) were excluded.  Allocation concealment (checking for possible selection bias): The method used to conceal allocation to interventions prior to assignment determines whether intervention allocation could have been foreseen in advance of, or during recruitment, or changed after assignment. We assessed the methods as: low risk of bias (e.g. telephone or central randomisation; consecutively numbered sealed opaque envelopes); unclear risk of bias (method not clearly stated). Studies that do not conceal allocation (e.g. open list) were excluded.  Blinding of participants and personnel (checking for possible performance bias). We assessed the methods used to blind study participants and personnel from knowledge of which 69

intervention a participant received. We assessed methods as: low risk of bias (study states that it was blinded and describes the method used to achieve blinding, such as identical tablets matched in appearance or smell, or a double-dummy technique); unclear risk of bias (study states that it was blinded but did not provide an adequate description of how it was achieved). Studies that were not double-blinded are considered to have high risk of bias.  Blinding of outcome assessment (checking for possible detection bias). We assessed the methods used to blind study participants and outcome assessors from knowledge of which intervention a participant received. We assessed the methods as: low risk of bias (study has a clear statement that outcome assessors were unaware of treatment allocation, and ideally describes how this was achieved); unclear risk of bias (study states that outcome assessors were blind to treatment allocation, but lacks a clear statement on how it was achieved). Studies where outcome assessment were not blinded were considered as having a high risk of bias. We assessed blinding of outcome assessment in three separate outcome-categories: o Not dependent on outcome assessor: overall survival o Partly dependent on outcome assessor: progression free survival o Dependent on outcome assessor: safety outcomes  Incomplete outcome data (checking for possible attrition bias due to the amount, nature and handling of incomplete outcome data). We assessed the methods used to deal with incomplete data in two separate outcome categories: o time to event data: low risk (censored Kaplan-Meier curves were provided and study discontinuations were described and balanced between arms); unclear risk (neither Kaplan-Meier curves, nor flow-charts were accessible); high risk (‘last observation carried forward’ analysis) o safety data: low risk (safety data was only reported for patients, who received at least one study drug); high risk (intention-to-treat population was used to report safety data, however it was stated that participants changed to the other study arm or stopped the study before they received the first dose); unclear risk (it was not described, which population was used to report safety outcomes)  Selective reporting (checking for reporting bias). We assessed whether primary and secondary outcome measures were pre-specified and whether these were consistent with those reported: low risk of bias ( study protocol is available and all of the study’s pre-specified (primary and secondary) outcomes that were of interest in the review have been reported in the pre-specified way, or the study protocol was not available but it was clear that the published reports include all expected outcomes, including those that were pre-specified); unclear risk of bias (insufficient information to permit judgement of ‘low risk’ or ‘high risk'); high risk of bias (not all of the study’s pre-specified primary outcomes have been reported or one or more primary outcomes is reported using measurements, analysis methods or subsets of the data that were not pre-specified or one or more reported primary outcomes were not pre-specified or one or more outcomes of interest in the review are reported incompletely so that they cannot be entered in a meta-analysis, or the study report fails to include results for a key outcome that would be expected to have been reported for such a study).

Measures of treatment effect

Relative treatment effect

We used intention-to-treat data. For binary outcomes, we extracted number of patients and number of events per arm and calculate risk ratios (RRs) with 95% confidence intervals (CIs) for each trial. For time-to-event outcomes, we extracted hazard ratios (HRs) from published data according to Parmar 1998 and Tierney 2007 (94), (95). We calculated continuous outcomes as 70

mean differences (MDs) when assessed with the same instruments; otherwise we calculated standardised mean differences (SMDs) with 95%CIs.

Relative treatment ranking

We obtained a treatment hierarchy using P scores (96). P scores allow ranking treatments on a continuous zero to 1 scale in a frequentist network meta-analysis.

Unit of analysis issues

Studies with multiple treatment groups

As recommended in Chapter 16.5.4 of the Cochrane Handbook for Systematic Reviews of Interventions (97), for studies with multiple treatment groups we combined arms as long as they could be regarded as subtypes of the same intervention.

When arms could not be pooled this way, we included multi-arm trials using an network meta- analysis approach that accounts for the within-study correlation between the effect sizes by re- weighting all comparisons of each multi-arm study (98), (99). For pairwise meta-analysis, we treated multi-arm studies as multiple independent comparisons and did not combine these data in any analysis.

Dealing with missing data

As suggested in Chapter 16 of the Cochrane Handbook for Systematic Reviews of Interventions (97), we took the following steps to deal with missing data.

Whenever possible, we contacted the original investigators to request relevant missing data. If the number of participants evaluated for a given outcome was not reported, we used the number of participants randomised per treatment arm as the denominator. If only percentages but no absolute number of events were reported for binary outcomes, we calculated numerators using percentages. If estimates for mean and standard deviations were missing, we calculated these statistics from reported data whenever possible, using approaches described in Chapter 7.7 of the Cochrane Handbook for Systematic Reviews of Interventions (91). If standard deviations were missing and we were not able to calculate them from reported data, we calculated values according to a validated imputation method (100). If data was not reported numerically but graphically, we estimated missing data from figures. We performed sensitivity analyses to assess how sensitive results were to imputing data in some way. We addressed in the Discussion section the potential impact of missing data on findings of the review.

Assessment of heterogeneity

Assessment of clinical and methodological heterogeneity within treatment comparisons

To evaluate the presence of clinical heterogeneity, we generated summary statistics for the important clinical and methodological characteristics across all included studies. Within each pairwise comparison, we assessed the presence of clinical heterogeneity by visually inspecting the similarity of these characteristics.

Assessment of transitivity across treatment comparisons

To infer about the assumption of transitivity, we assessed whether the included interventions are similar when they were evaluated in RCTs with different designs; for example, whether double- drug combinations are administered the same way in studies comparing them to other double- drug combinations and in those comparing double-drug combinations to triple-drug 71

combinations. Furthermore, we compared the distribution of the potential effect modifiers across the different pairwise comparisons.

Assessment of statistical heterogeneity and inconsistency

To evaluate the presence of heterogeneity and inconsistency in the entire network, we gave the generalised heterogeneity statistic Qtotal and the generalised I² statistic, as described in Schwarzer 2015 (101). We used the decomp.design command in the R package netmeta (102), (103) for decomposition of the heterogeneity statistic into a Q statistic for assessing the heterogeneity between studies with the same design and a Q statistic for assessing the designs inconsistency to identify the amount of heterogeneity/inconsistency within as well as between designs.

To evaluate the presence of inconsistency locally, we compared direct and indirect treatment estimates of each treatment comparisons. This can serve as a check for consistency of a network meta-analysis (104). For this purpose, we used the netsplit command in the R package netmeta, which enables the splitting of the network evidence into direct and indirect contributions (102), (103). For each treatment comparison, we presented direct and indirect treatment estimates plus the network estimate using forest plots. In addition, for each comparison we gave the z-value and P value of test for disagreement (direct versus indirect). It should be noted that in a network of evidence there may be many loops and with multiple testing there is an increased likelihood that we might find an inconsistent loop by chance. Therefore, we were cautious deriving conclusions from this approach.

If we have found substantive heterogeneity and/or inconsistency, we explored possible sources by performing pre-specified sensitivity and subgroup analyses (see below). In addition, we reviewed the evidence base, reconsider inclusion criteria as well as discussed the potential role of unmeasured effect modifiers to identify further sources.

Assessment of reporting biases

In pairwise comparisons with at least 10 trials, we examined the presence of small-study effects graphically by generating funnel plots. We used linear regression tests (105) to test for funnel plot asymmetry. A P value less than 0.1 was considered significant for this test (106). We examined the presence of small-study effects for the primary outcome only. Moreover, we searched study registries, to identify completed, but not published trials.

Data synthesis

Methods for direct treatment comparisons

Pairwise comparisons are part of the network meta-analysis, thus we did not plan to perform pairwise meta-analysis in addition. In order to outline available direct evidence, we provided forest plots for pairwise comparisons, without giving an overall estimate. Only in case data is not sufficient to be combined in a network meta-analysis, e.g. in case of inconsistency, we performed pairwise meta-analyses according to recommendations provided in Chapter 9 of the Cochrane Handbook for Systematic Reviews of Interventions (107). We used random-effects models. We used the R package meta (102), (101) for statistical analyses. When trials were clinically too heterogeneous to be combined, we performed only subgroup analyses without calculating an overall estimate.

Methods for indirect and mixed comparisons

Was the data considered sufficiently similar to be combined, we performed a network meta- analysis using the frequentist weighted least squared approach described by Rücker 2012 (98). We used a random-effects model, taking into account the correlated treatment effects in multi- arm studies. We assumed a common estimate for the heterogeneity variance across the different comparisons. To evaluate the extent to which treatments are connected, we gave a network plot for our primary and secondary outcomes. For each comparison, we gave the estimated treatment effect along with its 95% CI. We graphically presented the results using forest plots, with Melphalan/Prednisone as reference. We used the R package netmeta (102), (103) for statistical analyses.

GRADE

Quality of the evidence

Two review authors independently rated the quality of each outcome. We used the GRADE (Grades of Recommendation, Assessment, Development and Evaluation) system to rank the quality of the evidence using the GRADEprofiler Guideline Development Tool software (108), and the guidelines provided in Chapter 12.2 of the Cochrane Handbook for Systematic Reviews of Interventions (109) and specifically for network meta-analyses (30).

The GRADE approach uses five considerations (study limitations, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of the body of evidence for each outcome. The GRADE system uses the following criteria for assigning grade of evidence.

 High = we are very confident that the true effect lies close to that of the estimate of the effect.  Moderate = we are moderately confident in the effect estimate; the true effect is likely to be close to the estimate of effect, but there is a possibility that it is substantially different.  Low = our confidence in the effect estimate is limited; the true effect may be substantially different from the estimate of the effect.  Very low = we have very little confidence in the effect estimate; the true effect is likely to be substantially different from the estimate of effect.

The GRADE system uses the following criteria for assigning a quality level to a body of evidence (Chapter 12, (109)).

 High: randomised trials; or double-upgraded observational studies.  Moderate: downgraded randomised trials; or upgraded observational studies.  Low: double-downgraded randomised trials; or observational studies.  Very low: triple-downgraded randomised trials; or downgraded observational studies; or case series/case reports.

We will decrease grade if:

 serious (-1) or very serious (- 2) limitation to study quality;  important inconsistency (- 1);  some (-1) or major (- 2) uncertainty about directness;  imprecise or sparse data (- 1);  high probability of reporting bias (- 1).

'Summary of findings' table

We will include a 'summary of findings' table to present the main findings in a transparent and simple tabular format. In particular, we will include key information concerning the quality of evidence, the magnitude of effect of the interventions examined, and the sum of available data on the outcomes OS, PFS, serious adverse events, and withdrawals due to adverse events for the comparisons RD, TMP, VMP, VRDc versus MP, respectively.

Subgroup analysis and investigation of heterogeneity

We considered performing subgroup analyses using the following characteristics.

 Follow-up (short-term (< 1 year) versus long-term >= 1 year)  Multiple myeloma international staging system (I,II, III)  Age (<75 vs. >75)  Region (low- and middle-income vs. high-income)

Sensitivity analysis

To test the robustness of the results, we conducted fixed-effect pairwise and network meta- analyses. We reported the estimates of the fixed-effect only if they have shown a difference to the random-effects model. We explored the influence of quality components with regard to low and high risk of bias.

APPENDIX 2: SEARCH STRATEGIES Search strategy CENTRAL:

ID Search

#1 MeSH descriptor: [Multiple Myeloma] explode all trees

#2 myelom*

#3 MeSH descriptor: [Plasmacytoma] explode all trees

#4 plasm*cytom*

#5 plasmozytom*

#6 plasm* cell myelom*

#7 myelomatosis

#8 MeSH descriptor: [Leukemia, Plasma Cell] explode all trees

#9 (plasma* near/3 neoplas*)

#10 kahler*

#11 #1 or #2 or #3 or #4 or #5 or #6 or #7 or #8 or #9 or #10

#12 #11 in Trials

Search strategy MEDLINE:

# searches

1 exp MULTIPLE MYELOMA/

2 myelom$.tw,kf,ot.

3 exp PLASMACYTOMA/

4 plasm?cytom$.tw,kf,ot.

5 plasmozytom$.tw,kf,ot.

6 plasm$ cell myelom$.tw,kf,ot.

7 myelomatosis.tw,kf,ot.

8 LEUKEMIA, PLASMA CELL/

9 (plasma$ adj3 neoplas$).tw,kf,ot.

10 kahler*.tw,kf,ot.

11 or/1-10

12 randomized controlled trial.pt.

13 controlled clinical trial.pt.

14 randomi?ed.ab.

15 placebo.ab.

16 clinical trials as topic.sh.

17 randomly.ab.

18 trial.ti.

19 or/12-18

20 exp ANIMALS/ not HUMANS/

21 19 not 20

22 11 and 21