Daratumumab and antineoplastic therapy versus antineoplastic therapy only for people with newly diagnosed multiple myeloma ineligible for transplant

Objectives

This is a protocol for a Cochrane Review (intervention). The objectives are as follows:

This review aims to determine benefits and harms of daratumumab in addition to antineoplastic therapy compared to antineoplastic therapy only for adults with newly diagnosed multiple myeloma ineligible for transplant.

Background

Description of the condition

Multiple myeloma is a haematological malignancy that originates in the bone marrow. In contrast to other haematological malignancies, multiple myeloma is usually preceded by an age‐progressive benign condition called monoclonal gammopathy of undetermined significance (MGUS), which can progress to smouldering (asymptomatic) myeloma and finally to symptomatic myeloma (Palumbo 2011). The disease is caused when abnormal plasma cells, a type of white blood cell, multiply uncontrollably. Multiple myeloma cells produce an abnormal (monoclonal) immunoglobulin, also called a paraprotein (Palumbo 2011). This immunoglobulin can be found in the blood and urine. One part of these abnormal immunoglobulins is called the light chain, this can also be detected in excessive amounts in the blood and urine (Bence Jones protein) (Corso 1999). Blood and urine tests are therefore a way of diagnosing and monitoring myeloma.

Myeloma cells in the bone marrow fill the space where normal blood cell production (haematopoiesis) occurs. People with multiple myeloma, therefore, are affected by symptoms caused by a reduction in the production of normal red cells (anaemia) and white cells (leukopenia), with an associated antibody deficiency disorder, resulting in an increased risk of infections (Blimark 2015). Furthermore, the disease destroys bone tissue (a process called osteolysis), resulting in bone pain and spontaneous fractures, it also increases the release of calcium into the blood (Panaroni 2017). This hypercalcaemia can cause symptoms including abdominal and bone pain, nausea and confusion.

Myeloma cast nephropathy (light chain cast nephropathy), is the formation of plugs (urinary casts) in the renal tubules caused by large amounts of free light chains passing through the kidney into the urine. This can lead to renal failure, and is the most common cause of kidney injury in myeloma (Gerecke 2016; Röllig 2015).

The revised International Myeloma Working Group diagnostic criteria for multiple myeloma, define myeloma based on the following characteristics (Rajkumar 2014).

• At least 10% of cells in the bone marrow are plasma cells or there is a biopsy‐proven plasmacytoma and there is one or more of the following myeloma defining events.

  • End organ damage caused by the myeloma, specifically:

    • hypercalcaemia

    • renal insufficiency

    • anaemia

    • bone lesions: one or more osteolytic lesions

  • Any one or more of the following biomarkers of malignancy:

    • at least 60% of bone marrow plasma cells are clonal

    • involved:uninvolved serum free light chain ratio ≥ 100

    • > 1 focal lesions on magnetic resonance imaging (MRI) studies

Multiple myeloma is a life‐threatening condition. In 2018 there were 160,000 new cases worldwide (accounting for 0.9% of all cancers), with about 106,000 deaths caused by multiple myeloma (Bray 2018). Five‐year survival of people with myeloma is less than 50%. Ten‐year myeloma survival in the UK has quadrupled in the last 40 years, from 6% to 33% (Cancer Research UK 2018). From 1990 to 2016, the incidence of myeloma has increased by 126%, and the number of deaths caused by multiple myeloma has increased by 94% (Cowan 2018). The global incidence and death rates of multiple myeloma are highest in regions with high incomes like Australasia, North America, and Western Europe (age‐standardized incidence rate of 4.3 per 100,000 persons). Populations with the lowest incidence of multiple myeloma are located in low‐income regions of Asia, Oceania, and sub‐Saharan Africa (age‐standardized incidence rate of 1.2 per 100,000 persons) (Cowan 2018).

Multiple myeloma is divided into three different prognostic subgroups according to both the Durie‐Salmon Staging System (Durie 2006) (Table 1) and the International Staging System (ISS) (Greipp 2005) (Table 2).

Table 1: Durie‐Salmon Staging System

Stage	Criteria	Cell mass
I	All of the following: haemoglobin value > 10 g/dL normal serum calcium value of < 12 mg/dL normal bone structure or one solitary bone lesion only on radiography low M‐component production rates IgG < 5 g/dL IgA < 3 g/dL urine light chain M‐component on electrophoresis of < 4 g/24 h	< 0.6 x 1012 cells/mm2
II	One or more of the following: haemoglobin value of ≤ 10g/dL and ≥ 8.5g/dL normal serum calcium value of ≤ 12mg/dL normal bone structure or one solitary bone lesion only on radiography M‐component production rates IgG ≥ 5 g/dL and ≤ 7 g/dL IgA ≥ 3 g/dL and ≤ 5 g/dL urine light chain M‐component on electrophoresis of ≥ 4 g/24 h and ≤ 12 g/24h	≥ 0.6 x 1012 cells/mm2 and ≤ 1.2 x 1012 cells/mm2
III	One or more of the following: haemoglobin value of < 8.5 g/dL serum calcium value of > 12 mg/dL advanced lytic bone lesions high M‐component production rates IgG > 7 g/dL IgA > 5 g/dL urine light chain M‐component on electrophoresis of > 12 g/24 h	> 1.2 x 1012 cells/mm2

Subclassification of all stages: 'A' as a relatively normal renal function with a serum creatinine value of ≤ 2.0 mg/dL; 'B' as an abnormal renal function with a serum creatinine value of > 2.0 mg/dL (Collins 2004).

Table 2: International Staging System (ISS)

Stage	Criteria
I	Serum beta‐2 microglobulin < 3.5 mg/L plus serum albumin ≥ 3.5 g/dL
II	Not stage I or IIIa
III	Serum beta‐2 microglobulin ≥ 5.5 mg/L

^aThere are two possibilities for stage II: serum beta‐2 microglobulin < 3.5 mg/L and serum albumin < 3.5 g/dL; or serum beta‐2 microglobulin 3.5 mg/L to < 5.5 mg/L irrespective of the serum albumin level (Greipp 2005).

As multiple myeloma is a genetically complex and heterogeneous disease, the International Myeloma Working Group recommends risk stratification by combining the ISS stage (serum beta‐2 microglobulin, serum albumin) and genetic abnormalities (t(4;14), 17p13 and 1q21) detected by fluorescence in situ hybridization (FISH) (Chng 2014). Cytogenetic and molecular genetic aberrations, characterize people with multiple myeloma into two prognostic groups. A high‐risk group, with poorer overall survival (hypodiploid group) associated with t(4;14)(p16;q32) or t(14;16)(q32;q23), and a group with better overall survival (hyperdiploid group) associated with t(11;14)(q13;q32).

Tumour progression of multiple myeloma can lead to four main secondary chromosomal abnormalities: translocations of MYC(8q24); loss or deletion of chromosome 13; deletion of chromosome 17p13; and deletions or amplifications of chromosome 1 (Sawyer 2011). MYC(8q24) mutations occur in up to 45% of people who are affected by multiple myeloma, and can cause shorter overall survival (Merz 2018). Chromosome 13 abnormalities occur in approximately 50% of cases, 85% of these are monosomy 13, while 15% are deletions of part of chromosome 13. Although chromosome 13 abnormalities in isolation are not a negative prognostic factor, when they are associated with other high risk factors like t(4;14), del(17p) or high serum level of ß2–microglobulin, they show an unfavourable prognosis (Paszekova 2014). In addition, deletions of chromosome 13 are co‐responsible for the clonal expansion of multiple myeloma (Sawyer 2011). In approximately 10% of people with multiple myeloma, the deletion of 17p13 is a rare late event, which probably leads to an inactivation of TP53. TP53 is a tumour suppressor gene that transcriptionally controls cell‐cycle progression and apoptosis. In conclusion, the deletion of 17p13 indicates a very poor prognosis with a more aggressive disease, a higher prevalence of extramedullary disease, and shorter overall survival (Sawyer 2011). Chromosome 1 abnormalities frequently occur in multiple myeloma, these usually comprise of deletions of 1p and amplifications of 1q27. People with multiple myeloma and deletions of 1p or a gain or amplification of 1q21 are also associated with poor prognosis (Paszekova 2014).

Description of the intervention

Antineoplastic therapy is a generic term with subdivisions of different modalities, which include chemotherapy as a traditional form as well as newer techniques including hormonal drugs and immunotherapy. Depended on different criteria, modalities can be combined to create a treatment program that is appropriate. A high dose chemotherapy contains cytotoxic drugs, which destroy cancer cells but also normal cells as well as the bone marrow. It can cause to severe adverse events. Usually it is followed by stem cell transplantation to rebuild the bone marrow (Gale 2018; NCI 2020).
The treatment of people with newly diagnosed multiple myeloma depends on the stage of myeloma, symptoms of the disease, results of blood and bone marrow tests, general health and levels of fitness and the personal wishes of the individual who is affected. With a good level of fitness the individual is eligible to receive intensive treatment with high‐dose chemotherapy followed by a stem cell transplant (Röllig 2015). The world wide availability of stem cell transplantation for all indications, not only with respect to multiple myeloma, differs greatly. In 2010, the highest rates of stem cell transplantations per 10 million people took place in Israel (814), Italy (671), Germany (665), Sweden (625), and the Netherlands (614) (Cowan 2018).

People with newly diagnosed multiple myeloma who are not eligible for transplant, due to health problems or poor performance status, receive treatment consisting of two‐, three‐ or multiple‐drug combinations. A recommended first‐line therapy is thalidomide, an immunomodulatory drug, combined with an alkylating agent, such as melphalan or cyclophosphamide, and a corticosteroid, such as prednisolone or dexamethasone (Kumar 2019). If there are contraindications to thalidomide, the individual can receive bortezomib instead (NICE 2018). The combination of bortezomib, melphalan and prednisone shows a median overall survival of 53.1 months and a median progression‐free survival of 17.3 months (Niesvizky 2015). The combination of bortezomib, cyclophosphamide and dexamethasone has a median overall survival of 41.4 months and a median progression‐free survival of 16.7 months (Venner 2015). Another first‐line therapy is lenalidomide as an immunomodulatory drug combined with dexamethasone (Moreau 2017).

In high‐income countries, people with multiple myeloma, who are not eligible for transplant, receive thalidomide‐ or bortezomib‐based therapies combined with melphalan and prednisone, or cyclophosphamide and dexamethasone, or lenalidomide and dexamethasone (Moreau 2017; NICE 2018; Piechotta 2019). In low‐ and middle‐income countries, people with multiple myeloma are treated with melphalan and prednisone, or if it is available with melphalan, prednisone and thalidomide, or bortezomib, melphalan and prednisone (Nwabuko 2017). The aim of the treatment is to achieve a period of stable disease, which is named plateau phase, for as long as possible.

Daratumumab is a newly developed drug and targets CD‐38, a human IgG1k monoclonal antibody. Multiple myeloma cells uniformly over‐express CD‐38, a 46‐kDa type II transmembrane glycoprotein, making myeloma cells a specific target for daratumumab (de Weers 2011).

How the intervention might work

Daratumumab induces the death of myeloma cells via multiple mechanisms, including direct induction of apoptosis (cell death), complement‐ and antibody‐mediated cytotoxicity, and antibody‐dependent cellular phagocytosis (Krejcik 2016). Daratumumab also triggers the activation and clonal expansion of cytotoxic T‐cells, which may provide additional anti‐myeloma effects (Usmani 2016).

Daratumumab has been approved for the treatment of people with relapsed or refractory multiple myeloma (McKeage 2016). People with relapsed or refractory multiple myeloma, who are heavily pretreated before, and are therefore refractory to standard treatments, can receive daratumumab monotherapy (Usmani 2016a). People with relapsed or refractory multiple myeloma, who have already had at least one previous treatment, can receive daratumumab in addition to chemotherapy (Blair 2017). Daratumumab in addition to a proteasome‐inhibitor, such as bortezomib, induces a significantly lengthened progression‐free survival at 12 months compared to standard treatment without daratumumab (60.7% versus 26.9%). Additionally, the same combination shows a higher rate of: overall response (82.9% versus 63.2%); very good partial response (59.2% versus 29.1%); and complete response (19.2% versus 9.0%) (Palumbo 2016).

A combination of daratumumab with an immunomodulatory drug, such as lenalidomide, in people with relapsed or refractory multiple myeloma shows comparable results. This combination significantly lengthened progression‐free survival at 12 months (83.2% versus 60.1%) and overall response (92.9% versus 76.4%), compared to lenalidomide only (Dimopoulos 2016). Daratumumab is also effective in triple relapsed/refractory myeloma patients, with a median overall survival of 16.7 months (Boyle 2019).

The most frequent adverse event is an infusion reaction, with a prevalence of approximately 50%; 92% of these reactions arise with the first dose of therapy. Mostly, these infusion reactions are grade 1 or 2, whereas grade 3 shows an incidence of 5% to 10% (McCullough 2018). Besides infusion reactions, the most commonly (> 20%) reported adverse events include fatigue, nausea, anaemia, back pain, cough, upper respiratory tract infection, thrombocytopenia and neutropenia (Usmani 2016a).

Why it is important to do this review

As mentioned above, daratumumab has shown remarkable benefits for people with relapsed disease. It is now important to understand whether there is also an advantage for individuals with newly diagnosed myeloma, who are ineligible for a stem cell transplant. Additionally, an assessment of potential harms is also essential to guide clinical decision making. By combining results of randomized controlled trials, we will overcome the limitations of individual studies, such as small sample sizes and a lack of statistical power.

Objectives

This review aims to determine benefits and harms of daratumumab in addition to antineoplastic therapy compared to antineoplastic therapy only for adults with newly diagnosed multiple myeloma ineligible for transplant.

Methods

Criteria for considering studies for this review

Types of studies

We will consider only randomized controlled trials (RCTs). We will exclude quasi‐randomized trials (e.g. treatment allocation alternate or by date of birth) as randomization is the best way to prevent systematic differences between baseline characteristics of participants in different intervention groups in terms of both known and unknown (or unmeasured) confounders. In case we identify cross‐over trials, we will include only the first period to avoid carry‐over effects.

We will include full‐texts, abstract publications and studies reported in trial registries, if sufficient information is available on study design, characteristics of participants and interventions. We will not exclude trials if they fit all the other inclusion criteria but do not report our pre‐planned outcomes. There will be no limitation with respect to the length of follow‐up. If results in trials are not available from publications, we will contact authors of those trials to obtain the missing data.

Types of participants

We will include trials on adult (≥ 18 years) participants with a confirmed diagnosis of multiple myeloma. We will apply no gender or ethnicity restrictions. We will consider only people with newly diagnosed multiple myeloma who are not considered candidates for high‐dose chemotherapy with stem cell transplantation. We will exclude trials with less than 80% adult participants, unless there are subgroup analyses of adults with multiple myeloma.

Types of interventions

The intervention will consist of daratumumab added to antineoplastic therapy versus the same antineoplastic therapy alone. Participants in both study arms should receive the same antineoplastic therapy, such as the same chemotherapeutic agent, immunomodulatory drug or proteasome inhibitor in the same dose and the same number of cycles.

Types of outcome measures

We will include all studies fitting the above mentioned inclusion criteria, irrespective of whether outcomes of interest are reported or not.

Primary outcomes

• Overall survival

  • Defined as time from random treatment assignment within a study to death from any cause or to last follow‐up.

For this outcome, measured as a hazard ratio (HR), we will evaluate the longest follow‐up available within each study. We will perform subgroup analyses for different lengths of follow‐up.

Secondary outcomes

We will analyse the following as secondary outcomes.

• Quality of life, if validated tools were used, measured at certain periods:

  • short (1 to 3 months)

  • medium (6 to 9 months)

  • long (12 months and longer)

• Progression‐free survival (longest follow‐up available)

• Rate of complete remission (after treatment)

• On‐study mortality

• Adverse events (haematological toxicity, infection, diarrhoea, cardiac and pulmonary failure, nausea)

• Minimal residual disease negativity

Search methods for identification of studies

Electronic searches

We will adapt search strategies as suggested in the Cochrane Handbook for Systematic Reviews of Interventions (Lefebvre 2019). We will not apply any language restrictions, so as to reduce the risk of language bias. We will start the search from 2010, as daratumumab was mentioned for the first time in 2011 (de Weers 2011).

We will search the following databases and sources.

• Databases of medical literature

  • Cochrane Central Register of Controlled Trials (CENTRAL) (the Cochrane Library, latest issue) (Appendix 1)

  • MEDLINE (Ovid) (2010 to present) (Appendix 2)

  • Embase

• Study registries

  • EU clinical trials register: www.clinicaltrialsregister.eu

  • World Health Organization (WHO): apps.who.int/trialsearch

  • ClinicalTrials.gov: clinicaltrials.gov

  • ISRCTN: www.isrctn.com

• Conference proceedings of annual meetings of the following societies for abstracts, if not included in CENTRAL (2010 to present)

  • American Society of Hematology

  • American Society of Clinical Oncology

  • European Hematology Association

Searching other resources

• Handsearching of references

  • References of all identified trials and relevant review articles; current treatment guidelines

Data collection and analysis

Selection of studies

Two review authors (PL, NS) will independently screen results of search strategies for eligibility for this review by reading all abstracts. In cases of disagreement, we will obtain the full‐text publication. If no consensus can be reached, we will involve a third review author to come to a consensus (Lefebvre 2019).

We will document the process of study selection in a flow chart, as recommended by the PRISMA statement (Moher 2009), showing total numbers of retrieved references and numbers of included and excluded studies.

Data extraction and management

Two review authors (PL, NS) will independently extract data according to the Cochrane Handbook for Systematic Reviews of Interventions (Li 2019). We will contact authors of individual studies to ask for additional information, if required. We will use a standardized data extraction form containing the following items.

• General information

  • Author, title, source, publication date, country, language, duplicate publications

• Quality assessment

  • 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, 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 (multiple‐agent standard treatment (intensity of regimen, number of cycles))

• Interventions

  • Dose and cycles of daratumumab; type, dose and cycles of standard treatment; duration of follow‐up

• Outcomes

  • Overall survival, quality of life, progression‐free survival, rate of complete remission, on‐study mortality, adverse events, minimal residual disease negativity

Assessment of risk of bias in included studies

Two review authors (PL, NS) will independently assess risk of bias for each study using the following criteria, as outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011).

• Sequence generation

• Allocation concealment

• Blinding (participants, personnel, outcome assessors)

• Incomplete outcome data

• Selective outcome reporting

• Other sources of bias

We will make a judgement for each criterion, using one of the following categories.

• 'Low risk': if the criterion is adequately fulfilled in the study (i.e. the study is at low risk of bias for the given criterion).

• 'High risk': if the criterion is not fulfilled in the study (i.e. the study is at high risk of bias for the given criterion).

• 'Unclear': if the study report does not provide sufficient information to allow a clear judgement, or if risk of bias is unknown for one of the criteria listed above.

Measures of treatment effect

We will use intention‐to‐treat data. For binary outcomes, we will extract number of participants 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 will extract hazard ratios (HRs) and 95% confidence intervals (CIs) from published data according to Parmar 1998 and Tierney 2007. We will calculate continuous outcomes as mean differences (MDs) with standard errors when assessed with the same instruments; otherwise we will calculate standardized mean differences (SMDs) with standard errors (SEs).

Unit of analysis issues

As recommended in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2019), we will combine arms of studies with multiple treatment groups as long as they can be regarded as subtypes of the same intervention. When arms cannot be pooled this way, we will compare each arm with the common comparator separately. For pair wise meta‐analysis, we will split the 'shared' group into two or more groups with smaller sample size, and include two or more (reasonably independent) comparisons. For this purpose, for dichotomous outcomes, both the number of events and the total number of participants will be divided up, and for continuous outcomes, the total number of participants will be divided up with unchanged means and standard deviations (SDs).

Dealing with missing data

As suggested in the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2019), many potential sources of missing data must be taken into account: at study level, at outcome level and at summary data level. First, it is important to distinguish between 'missing at random' and 'not missing at random'. We will contact the original investigators to request missing data. If data are still missing, we will make explicit assumptions regarding any methods used, for example, that the data are assumed to be missing at random, or that missing values are assumed to have a particular value, such as a poor outcome. We will impute missing data for participants lost to follow‐up after randomization (dichotomous data) by assuming poor outcomes (worst‐case scenario) for missing individuals. We will perform sensitivity analysis to assess how sensitive results are to reasonable changes in assumptions made. We will address the potential impact of missing data on findings of the review in the Discussion section.

Assessment of heterogeneity

We will assess heterogeneity of treatment effects between trials using the Chi² test with a significance level of P value < 0.1. We will use the I² statistic to quantify possible heterogeneity (I² > 30% moderate heterogeneity, I² > 75% considerable heterogeneity) (Deeks 2019). We will explore potential causes of heterogeneity by performing sensitivity and subgroup analyses.

Assessment of reporting biases

In meta‐analyses with 10 or more trials, we will investigate potential publication bias by generating a funnel plot and will test statistics by using a linear regression test (Page 2019). We will consider a P value less than 0.1 as significant for this test.

Data synthesis

Should we consider the data sufficiently similar to be combined, we will pool results by applying meta‐analyses while using the fixed‐effect model, and we will use the random‐effects model as a sensitivity analysis for the primary outcome. When trials are clinically too heterogenous to be combined (e.g. various types of diseases), we will perform only subgroup analyses without calculating an overall estimate. When different tools are used to evaluate quality of life, we will calculate SMDs to perform a meta‐analysis. We will perform analyses according to recommendations provided in the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2019), and we will use the statistical software of Cochrane for analysis (Review Manager 2014).

We will create a 'Summary of findings' table on absolute risks in each group according to the GRADE system (GRADEpro GDT; Schünemann 2019). In the 'Summary of findings' table, we will summarize the evidence on overall survival, quality of life (at the end of treatment), progression‐free survival, on‐study mortality and adverse events (during treatment).

Subgroup analysis and investigation of heterogeneity

We will perform subgroup analyses using the following characteristics if data are available.

• Antineoplastic therapy consisting of two drugs versus antineoplastic therapy consisting of three drugs

• Follow‐up (short‐term (< 1 year) versus long‐term ≥1 year)

• Cytogenetic risk (high risk versus standard risk)

  • Cytogenetic high‐risk subgroup is defined by the presence of del(17p), t(4;14), t(14;16), del(13q) by conventional karyotype and hypodiploidy (Jimenez‐Zepeda 2016)

• International staging system (I versus II versus III)

Sensitivity analysis

We will perform the following sensitivity analyses.

• Trials being at low or uncertain risk of bias for all domains for the primary outcome

• Random‐effects modelling for the primary outcome

History

Protocol first published: Issue 4, 2020

Appendices

Appendix 1. CENTRAL search strategy

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	daratumumab*
#13	darzalex*
#14	human CD38
#15	#12 or #13 or #14
#16	#11 and #15 in Trials

Appendix 2. MEDLINE search strategy

#	Search
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	daratumumab*.tw,kf,ot,nm.
13	darzalex*.tw,kf,ot,nm.
14	human CD38.tw,kf,ot.
15	or/12‐14
16	11 and 15
17	randomized controlled trial.pt.
18	controlled clinical trial.pt.
19	randomi?ed.ab.
20	placebo.ab.
21	drug therapy.fs.
22	randomly.ab.
23	trial.ab.
24	groups.ab.
25	or/17‐24
26	exp ANIMALS/ not HUMANS/
27	25 not 26
28	16 and 27

Contributions of authors

Peter Langer (PL): conception and writing of the protocol

Ina Monsef (IM): clinical expertise and advice

Prof Dr Dr h.c. Christof Scheid (CS): clinical expertise and advice

PD Dr Nicole Skoetz (NS): methodological and clinical expertise and advice, proofreading

All review authors have read and accepted the final version of this protocol.

Sources of support

Internal sources

• Universtiy Hospital of Cologne, Department I of Internal Medicine, Germany

External sources

• No sources of support supplied

Declarations of interest

Peter Langer (PL): none known

Ina Monsef (IM): none known

Prof Dr Dr h.c. Christof Scheid (CS): The author has received honoraria and travel support from Janssen, Celgene, Novartis, Bristol Myers Squibb and Takeda and research support from Janssen and Takeda.

PD Dr Nicole Skoetz (NS): none known

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