Belantamab Mafodotin Plus Proteasome Inhibition Efficacy Versus Comparators in Early Relapsed Myeloma: A Systematic Review and Network Meta-Analysis.

Introduction

Multiple myeloma (MM) is a hard‐to‐treat hematologic malignancy associated with poor prognosis and quality of life [ 1 , 2 ]. Belantamab mafodotin is an antibody–drug conjugate (ADC) targeting B‐cell maturation antigen with a multi‐modal mechanism of action including direct, ADC‐mediated cytotoxicity, antibody‐dependent cellular cytotoxicity and phagocytosis, and induced immunogenic cell death [ 3 ].

Due to high overall response rates (ORR) reported for belantamab mafodotin monotherapy in DREAMM‐1, ‐2 and ‐3 [ 4 , 5 , 6 ], and preclinical synergy observed between belantamab mafodotin with pomalidomide and with bortezomib [ 7 ], additional phase 3 trials, DREAMM‐7 [ 8 ] and DREAMM‐8 [ 9 ], investigated belantamab mafodotin in different combination regimens versus standard of care. DREAMM‐7 ( NCT04246047 ) evaluated belantamab mafodotin + bortezomib (V) and dexamethasone (d; BVd) versus daratumumab + Vd (DVd) in patients with relapsed/refractory MM (RRMM) who had ≥ 1 prior line of therapy (LOT) and demonstrated a significant benefit in progression‐free survival (PFS) in favor of BVd (hazard ratio [HR] 0.41, 95% confidence interval [CI] 0.31–0.53, p < 0.001): median PFS (95% CI) was 36.6 (28.4–not reached [NR]) versus 13.4 (11.1–17.5) months for BVd versus DVd, respectively. At the primary analysis (median follow‐up: 28.2 months), median overall survival (OS) was not reached in either arm (HR 0.57, 95% CI 0.40–0.80) with follow‐up ongoing. The ORR (95% CI) was 83% (77–87) for BVd and 71% (65–77) for DVd with a doubling of complete response rate or better (35% [29–41] vs. 17% [13–22], respectively) [ 8 ].

Multiple combination regimens are available for MM/RRMM treatment, and regimen choice is complex and multifactorial [ 10 ]. Patients are becoming exposed to commonly used drugs in early LOTs, including the immunomodulatory drug lenalidomide (R) [ 11 , 12 , 13 ] which is a standard in first‐line treatment based on positive outcomes from the FIRST study (Rd vs. R vs. melphalan, prednisone, and thalidomide) [ 14 ] and more recent studies, MAIA (DRd vs. Rd) [ 15 ] and PERSEUS [ 16 ] (D‐VRd vs. [VRd]). The outcomes of these studies are anticipated to increase the likelihood of patients becoming exposed to and refractory to commonly used drugs, including lenalidomide and daratumumab, in earlier stages of disease [ 12 , 17 ], thereby increasing the need for subsequent, alternative regimens with different mechanisms of action to prolong survival outcomes.

Without head‐to‐head studies (other than the comparison to DVd in DREAMM‐7) [ 8 ], indirect treatment comparisons are valuable to evaluate the relative efficacy of BVd against alternative regimens for patients with RRMM who had received at least one prior LOT. Our study indirectly examined BVd efficacy in patients with RRMM relative to other regimens and considered subpopulations with unmet clinical needs.

Methods

This systematic literature review (SLR) and network meta‐analysis (NMA) is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta‐analyses reporting guideline extension statement for systematic reviews, incorporating NMA for healthcare interventions [ 18 ].

Literature Search and Study Selection

A SLR was performed in December 2021 and the last search update was carried out on February 4, 2024, to identify all relevant efficacy data for regimens used in the management of RRMM for patients who had received at least 1 prior LOT (Figure S1A ). The full electronic search strategy is shown in Table S1 . Studies were screened in the title/abstract and full‐text steps according to the Population‐Intervention‐Comparators‐Outcomes‐Study design framework criteria [ 19 ] (listed in Table S2 ). Titles and abstracts identified by the search strategy were independently assessed by two reviewers. Any discrepancies between the two reviewers were resolved by a third senior reviewer. Risk of bias was conducted in the feasibility assessment using the Revised Cochrane risk of bias tool for individually randomized, parallel‐group trials (RoB2.0) [ 20 ]. Heterogeneity in patient population characteristics between the studies was also assessed.

NMA Study Design

Studies identified in the SLR were included in the NMA if they had a connection to the DREAMM‐7 study [ 8 ] and these included regimens that were approved by the U.S. Food and Drug Administration or European Medicines Agency or were likely to be a future Health Technology Assessment comparator to the DREAMM‐7 study. This study used an anchored, indirect/mixed treatment comparison design, where there was a common comparator arm in each trial, allowing a connected network between the trials to be formed. Trials were linked together by the treatment(s) they shared to form connected networks of evidence. Trials/regimens that were not part of the connected evidence networks were excluded from the NMA.

An NMA feasibility assessment was carried out in two stages: Confirmation that a network of studies could be constructed for each outcome (through evaluation of qualitative descriptions) such that an indirect assessment of study outcomes could be carried out. Assessment of clinical and methodological similarity among network studies.

Data Analyses

The primary analysis examined PFS in the intent‐to‐treat (ITT) population as reported in each study. Where data were available, secondary analyses examined OS and ORR in the ITT population, as well as PFS and all other endpoints in the lenalidomide‐exposed and lenalidomide‐refractory populations. Based on available data, subgroup network analyses were also carried out to explore outcomes according to patient characteristics that have the potential to impact the effect of treatment, such as high cytogenetic risk and the number of prior LOTs.

Fixed‐effects and random‐effects models were run following the NMA using National Institute of Health and Care Excellence Decision Support Unit recommended methodology [ 21 ]. For the fixed‐effects model, a normal likelihood and the identity link function were used for time‐to‐event outcomes. The random‐effects models accounted for potential heterogeneity in follow‐up time and dosing regimens between studies included in the NMA, and based on the available evidence, a set of priors for between‐study variance in studies with binomial outcomes was used to inform between‐study standard deviations for time‐to‐event outcomes. HRs and 95% credible intervals (CrI) were computed for BVd relative to each comparator, and binomial likelihood and the logit link function were used for binomial outcomes; odds ratios (OR) and 95% CrIs were computed.

The statistical analyses were run using the multiNMA package version 0.7.0 and R version 4.2.1 or above via Rstudio to perform the analysis. An HR less than 1 indicated BVd was more effective than the comparator and an OR greater than 1 indicated BVd was associated with a greater likelihood of the event (ORR) than the comparator; for these HR/ORs, a CrI excluding 1.0 indicated a high probability that the treatment effect is consistently in favor of BVd.

Statistical fit for each model was assessed by deviance information criterion, the median residual deviance statistic, and the effective number of parameters as a measure of model complexity.

Results

Study Selection and Network Geometry

In total, 12 relevant comparator studies were identified in the SLR (Figure S1B ) [ 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ]; one publication, which was not captured within the SLR, was added afterwards as it reports updated PFS and OS data for the OPTIMISMM trial [ 41 ]. The number of patients per regimen and patient subgroup for each trial are presented in Table 1 . Heterogeneity assessment determined that baseline characteristics between the studies were generally similar (Table S3 ). The overall risk of bias was heterogeneous among included studies, but no studies were regarded as outliers. Based on the risk of bias assessment, it was not recommended to exclude any studies. The network graph of treatment comparisons is presented in Figure S2 .

Intent‐To‐Treat Population Outcomes

A total of 13 studies (including DREAMM‐7) [ 8 ] and 12 comparator regimens [ 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ] were included in the connected network of evidence for PFS, OS, and ORR. All 12 comparator regimens included a proteasome inhibitor (PI) in combination with dexamethasone, either bortezomib with dexamethasone (Vd) or carfilzomib with dexamethasone (Kd). Of note, to facilitate inclusion of the ARROW and GEM_KyCyDex studies in the network, equivalence of the twice‐weekly 27 mg/m 2 Kd regimen in the ARROW study and the 56 mg/m 2 Kd regimen in the ENDEAVOR and CANDOR studies was assumed.

BVd improved PFS versus all comparators (Figure 1A ); all CrIs were below 1, indicating a high probability that the treatment effect consistently favored BVd. Comparisons against regimens of interest included BVd versus daratumumab + Kd (DKd, PFS HRs [95% CrI]: 0.38 [0.24–0.61]), BVd versus isatuximab + Kd (IsaKd, 0.42 [0.26–0.69]), and BVd versus DVd (0.41 [0.31–0.54]).

BVd extended OS versus Vd, cyclophosphamide + Kd (CyKd), DVd, high‐dose Kd (hKd), panobinostat + Vd (PanoVd), PVd, and selinexor + Vd (SVd); CrIs were below 1. Although all results showed numerical improvement, some CrIs spanned 1, including for Kd, IsaKd, cyclophosphamide + Vd (CyVd), elotuzumab + Vd (EVd), and DKd (Figure 1B ) indicating uncertainty about the treatment effect. HRs (95% CrI) reported for comparators of interest versus BVd were DKd: 0.66 (0.39–1.12), IsaKd: 0.66 (0.37–1.18), and DVd: 0.57 (0.40–0.80).

BVd demonstrated numerically superior ORR against all comparators except CyKd, DKd, IsaKd, Kd, and PVd, where ORR CrIs spanned 1 (Figure 1C ). ORs (95% CrI) ranged from 1.12 (0.42–2.97) versus CyKd to 7.47 (2.49–22.65) versus CyVd. ORs (95% CrI) reported for regimens of interest versus BVd were 1.68 (0.76–3.73), 2.30 (0.93–5.71), and 1.94 (1.27–2.99) for DKd, IsaKd, and DVd, respectively.

Lenalidomide‐Exposed and ‐Refractory Subpopulation Outcomes

For both the lenalidomide‐exposed and ‐refractory subpopulations, NMA of OS was not feasible due to a lack of reported data to form a connected network.

For PFS in the lenalidomide‐exposed subpopulation, a total of 8 studies (including DREAMM‐7) [ 8 ] and 8 comparator regimens were included in the connected network of evidence [ 27 , 32 , 36 , 37 , 40 , 41 , 42 , 45 , 47 , 48 ]. BVd resulted in a longer PFS compared with all comparators in the network (Figure 2A ; HR [95% CrI] range: 0.12 [0.07–0.20]– 0.34 [0.17–0.71]), including comparator regimens of interest, DKd (0.34 [0.17–0.71]), IsaKd (0.29 [0.13–0.64]), and DVd (0.29 [0.19–0.43]). BVd improved ORR versus DVd, hKd, DKd, SVd, and Vd (overall OR [95% CrI] range: 1.74 [0.68–4.52]– 8.09 [3.47–19.52]), and with a lesser degree of certainty, versus PVd, as indicated by CrI spanning 1 (Figure 2B ).

For PFS in the lenalidomide‐refractory subpopulation, a total of 8 studies (including DREAMM‐7) [ 8 ] and 8 comparator regimens were included in the connected network of evidence [ 24 , 27 , 32 , 36 , 37 , 38 , 39 , 44 , 46 , 48 ]. BVd improved PFS versus all comparators, with all CrIs reported below 1 (Figure 2C ; HR [95% CrI] range: 0.14 [0.07–0.26] – 0.38 [0.16–0.94]). HRs (95% CrI) reported for comparator regimens of interest versus BVd were 0.37 (0.15–0.89), 0.29 (0.12–0.70), and 0.31 (0.20–0.49) for DKd, IsaKd, and DVd, respectively. The NMA of ORR showed that BVd improved ORR versus all comparators in the network (OR [95% CrI] range: 3.32 [1.61–7.19] – 14.30 [4.42–49.81]). This NMA only allowed comparison to DVd, SVd, and Vd based on data from DREAMM‐7, BOSTON, and CASTOR trials, due to a lack of reported data and the absence of connecting studies which would have allowed for the inclusion of additional trials into the network (Figure 2D ).

1 Prior Line Subpopulation Outcomes

The NMAs conducted for the subgroup analyses by 1 prior line and high‐risk cytogenetics subpopulations only considered PFS to assess the potential for bias resulting from differences in treatment effect modifiers in the studies with data available for these populations.

A total of 10 studies contributed to the network of evidence for the 1 prior line subpopulation [ 8 , 22 , 24 , 27 , 29 , 31 , 32 , 36 , 38 , 40 ]. BVd extended PFS versus all comparators (Figure 3A ; HR [95% CrI] range: 0.13 [0.08–0.22] – 0.52 [0.36–0.76]). HRs (95% CrI) reported for comparator regimens of interest versus BVd were 0.45 (0.21–0.94), 0.42 (0.20–0.88), and 0.52 (0.36–0.76) for DKd, IsaKd, and DVd, respectively.

High‐Risk Cytogenetic Subpopulation Outcomes

A total of 10 studies contributed to the network of evidence for the high‐risk cytogenetic subpopulation [ 8 , 22 , 25 , 27 , 32 , 36 , 37 , 38 , 39 , 49 ]. BVd improved PFS versus all comparators except DKd, where the CrI for the comparison versus BVd spanned 1 (Figure 3B ; HR [95% CrI] range: 0.13 [0.06–0.25] – 0.40 [0.15–1.09]). HRs (95% CrI) reported for comparator regimens of interest versus BVd were 0.40 (0.15–1.09), 0.27 (0.10–0.71), and 0.31 (0.18–0.53) for DKd, IsaKd, and DVd, respectively.

Random‐Effect Models

Results from random‐effects models for the ITT and subgroup analyses were largely consistent with the fixed‐effect models reported here, albeit larger 95% CrIs were reported with the random‐effects models shown in Figures S3‐5 .

Discussion

The head‐to‐head DREAMM‐7 study, which directly compared BVd versus standard of care, DVd, reported a near tripling in median PFS (36.6 months vs. 13.4 months), an early trend toward meaningful OS benefit, and twice as many complete responses or better with BVd compared with DVd (35% vs. 17%) [ 8 ]. In the absence of other direct randomized controlled trials (RCTs), this NMA further supports DREAMM‐7 findings, with BVd exhibiting superior benefit versus DVd [ 8 ]. This NMA indicated that BVd offered the highest PFS, OS, and ORR of the included PI‐based regimens for RRMM in patients who had received at least 1 prior LOT: BVd improved PFS, OS, and ORR compared with IsaKd and DKd, which are both approved for RRMM treatment [ 50 , 51 ].

In this study, all results generated with the fixed‐effects model in the lenalidomide‐exposed and ‐refractory populations were in favor of BVd. As lenalidomide is given until disease progression [ 52 , 53 ] and with frequent use in early LOTs [ 12 ], the proportion of lenalidomide‐refractory patients with MM is anticipated to increase. Clinical trials and real‐world studies show that lenalidomide‐refractory patients have inferior PFS and OS compared with non‐refractory patients, highlighting an area of unmet need [ 13 ]. Use of lenalidomide in the first and second line, and rising daratumumab use are likely leading to a high number of patients who are triple class‐refractory (i.e., to a PI, an immunomodulatory drug, and an anti‐CD28 monoclonal antibody) [ 16 , 54 , 55 ]. Suboptimal treatment outcomes reported in lenalidomide‐ and daratumumab‐treated patients [ 13 , 56 , 57 ] further demonstrate the need for additional therapies. Assessing the comparative effects of alternative regimens is important to illustrate the potential effectiveness of regimens with different mechanisms of action, such as BVd, in lenalidomide‐refractory patients in early lines, as demonstrated in this NMA.

Analyses in subpopulations who had received 1 prior treatment line highlighted that BVd improved PFS versus all other comparators including DVd, IsaKd, and DKd; these results are particularly notable given that IsaKd and DKd had median PFS values of 35.7 and 28.6 months, respectively, in the ITT populations of the IKEMA and CANDOR studies, with these benefits maintained in patients who received 1 prior LOT [ 36 , 38 ]. The long median duration of response (95% CI) reported in the DREAMM‐7 study for BVd (35.6 [30.5‐NR] months) versus DVd (17.8 [13.8–23.6] months) highlights the benefit of BVd in early lines with the potential to prolong the time to subsequent therapies [ 8 ]. Additionally, patients with high‐risk cytogenetics remain a population with high unmet need who may benefit from the identification of effective treatments [ 58 ]. The addition of daratumumab to VRd and Vd resulted in positive outcomes in this patient population [ 16 , 25 ]. The DREAMM‐7 study showed that BVd was effective in patients with high‐risk cytogenetics (HR 0.36 [95% CI 0.22–0.68] in favor of BVd over DVd) [ 8 ]. This NMA demonstrated a PFS benefit with BVd versus other comparator regimens including DVd, DKd, and IsaKd in high‐risk cytogenetic subpopulations.

With increasing treatment options for patients with early RRMM, a need remains for effective treatments in the community setting. Beyond the regimens included in this NMA, chimeric antigen receptor T‐cell (CAR‐T) and bispecific T‐cell engager (BiTE) immunotherapies have shown promising results but have associated risks [ 59 ] and CAR‐Ts are associated with additional patient burden and healthcare costs [ 60 , 61 , 62 ].

BVd has the potential to be used in community settings with minimal upfront requirements, and side effects associated with BVd reported in DREAMM‐7 were generally well tolerated and manageable, with anticipated eye‐related side effects such as blurry vision managed through dose and schedule modifications [ 8 ].

Strengths and Limitations

Overall, large patient numbers were included in the NMAs; some subgroups had low patient numbers, which may have increased uncertainty in the results. It was unfeasible to consider all outcomes in all populations due to the limitations of reporting in the included studies. A potential confounding factor is the lack of reported patient and clinical characteristics data (e.g., PI refractoriness). Moreover, approximately half of the studies included in the NMA did not report race; therefore, it is not known whether those studies reflect a similar race distribution to other myeloma studies. Additionally, common to studies included in this NMA and more widely, several races/ethnic groups have been underrepresented in MM studies [ 63 , 64 ] and this could have impacted the reported benefits of various regimens in MM. This NMA did not compare BVd with CAR‐T/BiTes, as no data permitting the connection of CAR‐T/BiTes to the analysis networks were available at the time of the study. Moreover, an indirect comparison of quality of life between regimens was not carried out. Quality of life, role, and physical functioning were reported to be similar between BVd and DVd in DREAMM‐7 [ 8 , 65 ].

Random‐effects models are used in NMAs to account for between‐study heterogeneity that is not adequately captured by fixed‐effect models. The feasibility assessment for this NMA demonstrated that there was considerable heterogeneity between the studies in the analyses; however, there was only one study per link, which is insufficient to reliably estimate between‐study variance. Therefore, the primary analysis for this NMA used the fixed‐effects model, and the random‐effects model was a secondary analysis. Random‐effects model results were aligned with results from the fixed‐effects model. Additionally, deviance information criterion values and residual deviances were similar across models. Moreover, due to the nature of the network, which was based on the availability of published studies, the strength of the findings is limited by the inclusion of a single study for each of the direct comparisons except for Vd vs. DVd, thereby limiting the robustness of the indirect comparisons. Pending the availability of results of other eligible studies reporting direct comparisons that could be added to the network, this analysis acknowledges the limitations resulting from single study connections in the network.

To our knowledge, this is the first NMA to compare BVd against standard of care therapies and suggests the potential benefit of introducing BVd in earlier lines of RRMM treatment. As more therapies and combination regimens enter the MM treatment landscape, the scope for head‐to‐head RCTs may diminish and become less informative for therapeutic decisions, requiring further NMAs to identify the most effective approach for treating RRMM [ 66 , 67 ].

Author Contributions

All authors were involved in manuscript writing, reviewing, and editing and read and approved the final manuscript. Joshua Richter and Nick Ballew contributed to study conception or design and data interpretation. Ajay Nooka, Paula Rodríguez‐Otero, and Fredrik Schjesvold contributed to data interpretation. Emily Combe, Marianne Scott, Leanne Cooper, Indeg Sly, Molly Purser, and Simon McNamara contributed to study conception or design and data acquisition, analysis, and interpretation. Jacopo Bitetti contributed to data analysis and interpretation. Natalie Boytsov contributed to study conception or design and data analysis and interpretation.

Ethics Statement

The authors have nothing to report.

Consent

The authors have nothing to report.

Conflicts of Interest

Joshua Richter reports consultancy fees from Janssen, Bristol Myers Squibb, Pfizer, Karyopharm, Sanofi, Takeda, Genentech, AbbVie, Regeneron and speaker bureau fees from Janssen, Bristol Myers Squibb, Sanofi, Adaptive Biotechnologies. Ajay Nooka has served on advisory boards and received honoraria from Adaptive Biotechnologies, Amgen, AstraZeneca, Bristol Myers Squibb, Cellectar Biosciences, GSK, Janssen, K36 Therapeutics, ONK Therapeutics, Pfizer, Sanofi, Sebia, and Takeda, has received institutional grant/research support from Aduro Biotech, Amgen, Arch Oncology, Bristol Myers Squibb, Cellectis, Genentech, GSK, Janssen, Karyopharm, Kite Pharma, Merck, Pfizer, and Takeda, and has received grant/research support for investigator‐initiated studies from Amgen, GSK, Janssen, Merck, and Takeda. Paula Rodríguez‐Otero reports consultancy fees from Bristol Myers Squibb, AbbVie, Roche, and Pfizer, has received honoraria from Bristol Myers Squibb, Janssen, Sanofi, GSK, Amgen, Regeneron, and Takeda, and is a member on the board of directors/speaker's bureau/advisory committee for Bristol Myers Squibb, Janssen, Sanofi, GSK, Amgen, Regeneron, Takeda, Kite Pharma, AbbVie, Oncopeptides, Pfizer, and GSK. Fredrik Schjesvold has received consultancy fees from AbbVie, Celgene, GSK, Janssen, Oncopeptides, Sanofi, and Takeda, has received research funding from Celgene, GSK, Janssen, Oncopeptides, Targovax, and Sanofi, and has received honoraria from AbbVie, Amgen, Bristol Myers Squibb, Daiichi Sankyo, GSK, Janssen, Novartis, Oncopeptides, Pfizer, Sanofi, SkylineDx, and Takeda. Eirini Katodritou served in a consulting or advisory role for Amgen and Janssen‐Cilag, received travel funding from Genesis Pharma and Takeda, received honoraria from Amgen, Genesis Pharma, Janssen‐Cilag, and Takeda, and received research funding from Amgen, Genesis Pharma, Janssen‐Cilag, and Takeda. Philippe Moreau served in a consulting or advisory role for Amgen, Celgene, GSK, Janssen, and Takeda, and received honoraria from Amgen, Celgene, GSK, Janssen‐Cilag, Novartis, and Takeda. Emily Combe, Marianne Scott, Leanne Cooper, and Indeg Sly are employees of FIECON. Nick Ballew, Jacopo Bitetti, Natalie Boytsov, Molly Purser, and Simon McNamara are employees of, and hold financial equities in, GSK.

Supporting information

Data S1.

Acknowledgments

Editorial support (in the form of writing assistance, including preparation of the draft manuscript under the direction and guidance of the authors, collating and incorporating authors' comments for each draft, assembling tables and figures, grammatical editing and referencing) was provided by Eithne Maguire, PhD, CMPP, at Fishawack Indicia Ltd. part of Avalere Health, and was funded by GSK. The authors would like to thank OPEN Health for contributions to the literature searches performed in this analysis, and also Oliver Schofield of FIECON for his help with preparing and running the network meta‐analyses.

Data Availability Statement

Data used in the analysis were obtained from resources available in the public domain and previously published reports. Additionally, for their studies, GSK makes available anonymized individual participant data and associated documents from interventional clinical studies that evaluate medicines, upon approval of proposals submitted to: https://www.gsk‐studyregister.com/en .

References

1 E. K. O'Donnell , Y. N. Shapiro , A. J. Yee , et al., “ Quality of Life, Psychological Distress, and Prognostic Perceptions in Patients With Multiple Myeloma ,” Cancer 128 , no. 10 ( 2022 ): 1996 – 2004 . 35167125 10.1002/cncr.34134

2 A. J. Cowan , D. J. Green , M. Kwok , et al., “ Diagnosis and Management of Multiple Myeloma: A Review ,” Journal of the American Medical Association 327 , no. 5 ( 2022 ): 464 – 477 , 10.1001/jama.2022.0003 . 35103762

3 R. Montes de Oca , A. S. Alavi , N. Vitali , et al., “ Belantamab Mafodotin (GSK2857916) Drives Immunogenic Cell Death and Immune‐Mediated Antitumor Responses In Vivo ,” Molecular Cancer Therapeutics 20 , no. 10 ( 2021 ): 1941 – 1955 . 34253590 10.1158/1535-7163.MCT-21-0035 PMC9398105

4 S. Trudel , N. Lendvai , R. Popat , et al., “ Antibody–Drug Conjugate, GSK2857916, in Relapsed/Refractory Multiple Myeloma: An Update on Safety and Efficacy From Dose Expansion Phase I Study ,” Blood Cancer Journal 9 , no. 4 ( 2019 ): 37 . 30894515 10.1038/s41408-019-0196-6 PMC6426965

5 A. K. Nooka , A. D. Cohen , H. C. Lee , et al., “ Single‐Agent Belantamab Mafodotin in Patients With Relapsed/Refractory Multiple Myeloma: Final Analysis of the DREAMM‐2 Trial ,” Cancer 129 , no. 23 ( 2023 ): 3746 – 3760 . 37622738 10.1002/cncr.34987 PMC11055177

6 M. A. Dimopoulos , V. T. M. Hungria , A. Radinoff , et al., “ Efficacy and Safety of Single‐Agent Belantamab Mafodotin Versus Pomalidomide Plus Low‐Dose Dexamethasone in Patients With Relapsed or Refractory Multiple Myeloma (DREAMM‐3): A Phase 3, Open‐Label, Randomised Study ,” Lancet Haematol 10 , no. 10 ( 2023 ): e801 – e812 , 10.1016/S2352-3026(23)00243-0 . 37793771

7 R. M. De Oca , I. Gupta , and C. Shelton , “ Abstract 6711: Combinations of Belantamab Mafodotin With Lenalidomide, Pomalidomide, Bortezomib and/or Dexamethasone Synergize In Vitro and Potentiate In Vivo Anti‐Tumor Activity in Multiple Myeloma ,” Cancer Research 80 , no. 16_Supplement ( 2020 ): 6711 .

8 V. Hungria , P. Robak , M. Hus , et al., “ Belantamab Mafodotin, Bortezomib, and Dexamethasone for Multiple Myeloma ,” New England Journal of Medicine 391 , no. 5 ( 2024 ): 393 – 407 . 38828933 10.1056/NEJMoa2405090

9 M. A. Dimopoulos , M. Beksac , L. Pour , et al., “ Belantamab Mafodotin, Pomalidomide, and Dexamethasone in Multiple Myeloma ,” New England Journal of Medicine 391 , no. 5 ( 2024 ): 408 – 421 . 38828951 10.1056/NEJMoa2403407

10 M. A. Dimopoulos , P. Moreau , E. Terpos , et al., “ Multiple Myeloma: EHA‐ESMO Clinical Practice Guidelines for Diagnosis, Treatment and Follow‐Up(†) ,” Annals of Oncology 32 , no. 3 ( 2021 ): 309 – 322 . 33549387 10.1016/j.annonc.2020.11.014

11 S. Goldman‐Mazur , A. Visram , S. V. Rajkumar , et al., “ Second‐ and Third‐Line Treatment Strategies in Multiple Myeloma: A Referral‐Center Experience ,” Blood Cancer Journal 12 , no. 12 ( 2022 ): 164 . 36473843 10.1038/s41408-022-00757-8 PMC9723783

12 F. Gay , K. M. Kortüm , Y. Gao , et al., “ A Real‐World Study to Assess Treatment Patterns and Outcomes of Patients (pts) With 2L+ Relapsed or Refractory Multiple Myeloma in Italy, Germany, and the United Kingdom ,” Clinical Lymphoma, Myeloma & Leukemia 24 ( 2024 ): S242 .

13 M. A. Hartley‐Brown , K. Weisel , J. Bitetti , et al., “ Multiple Myeloma Refractory to Lenalidomide: A Systematic Literature Review of Trials and Real‐World Evidence ,” British Journal of Haematology 205 , no. 3 ( 2024 ): 780 – 797 . 39031440 10.1111/bjh.19627

14 L. Benboubker , M. A. Dimopoulos , A. Dispenzieri , et al., “ Lenalidomide and Dexamethasone in Transplant‐Ineligible Patients With Myeloma ,” New England Journal of Medicine 371 , no. 10 ( 2014 ): 906 – 917 . 25184863 10.1056/NEJMoa1402551

15 T. Facon , S. K. Kumar , T. Plesner , et al., “ Daratumumab, Lenalidomide, and Dexamethasone Versus Lenalidomide and Dexamethasone Alone in Newly Diagnosed Multiple Myeloma (MAIA): Overall Survival Results From a Randomised, Open‐Label, Phase 3 Trial ,” Lancet Oncology 22 , no. 11 ( 2021 ): 1582 – 1596 . 34655533 10.1016/S1470-2045(21)00466-6

16 P. Sonneveld , M. A. Dimopoulos , M. Boccadoro , et al., “ Daratumumab, Bortezomib, Lenalidomide, and Dexamethasone for Multiple Myeloma ,” New England Journal of Medicine 390 , no. 4 ( 2024 ): 301 – 313 . 38084760 10.1056/NEJMoa2312054

17 F. de Arriba de la Fuente , C. Montes Gaisán , and J. de la Rubia Comos , “ How to Manage Patients With Lenalidomide‐Refractory Multiple Myeloma ,” Cancers (Basel) 15 , no. 1 ( 2022 ): 155 , 10.3390/cancers15010155 . 36612152 PMC9818178

18 B. Hutton , G. Salanti , D. M. Caldwell , et al., “ The PRISMA Extension Statement for Reporting of Systematic Reviews Incorporating Network Meta‐Analyses of Health Care Interventions: Checklist and Explanations ,” Annals of Internal Medicine 162 , no. 11 ( 2015 ): 777 – 784 . 26030634 10.7326/M14-2385

19 M. Amir‐Behghadami and A. Janati , “ Population, Intervention, Comparison, Outcomes and Study (PICOS) Design as a Framework to Formulate Eligibility Criteria in Systematic Reviews ,” Emergency Medicine Journal 37 , no. 6 ( 2020 ): 387 . 32253195 10.1136/emermed-2020-209567

20 J. A. C. Sterne , J. Savović , M. J. Page , et al., “ RoB 2: A Revised Tool for Assessing Risk of Bias in Randomised Trials ,” British Medical Journal 366 ( 2019 ): l4898 , 10.1136/bmj.l4898 . 31462531

21 S. Dias , N. Welton , A. Sutton , and A. Ades , “NICE DSU Technical Support Document 2: A Generalised Linear Modelling Framework for Pairwise and Network Meta‐Analysis of Randomised Controlled Trials,” (2011), https://www.sheffield.ac.uk/nice‐dsu/tsds/full‐list . 27466657

22 W. Fu , W. Li , J. Hu , et al., “ Daratumumab, Bortezomib, and Dexamethasone Versus Bortezomib and Dexamethasone in Chinese Patients With Relapsed or Refractory Multiple Myeloma: Updated Analysis of LEPUS ,” Clinical Lymphoma, Myeloma & Leukemia 23 , no. 1 ( 2023 ): e51 – e58 . 10.1016/j.clml.2022.10.007 36402700

23 J. Lu , W. Fu , W. Li , et al., “ Daratumumab, Bortezomib, and Dexamethasone Versus Bortezomib and Dexamethasone in Chinese Patients With Relapsed or Refractory Multiple Myeloma: Phase 3 LEPUS (MMY3009) Study ,” Clinical Lymphoma, Myeloma & Leukemia 21 , no. 9 ( 2021 ): e699 – e709 . 10.1016/j.clml.2021.04.012 34108127

24 M.‐V. Mateos , P. Sonneveld , V. Hungria , et al., “ Daratumumab, Bortezomib, and Dexamethasone Versus Bortezomib and Dexamethasone in Patients With Previously Treated Multiple Myeloma: Three‐Year Follow‐Up of CASTOR ,” Clinical Lymphoma, Myeloma & Leukemia 20 , no. 8 ( 2020 ): 509 – 518 . 10.1016/j.clml.2019.09.623 32482541

25 P. Sonneveld , A. Chanan‐Khan , K. Weisel , et al., “ Overall Survival With Daratumumab, Bortezomib, and Dexamethasone in Previously Treated Multiple Myeloma (CASTOR): A Randomized, Open‐Label, Phase III Trial ,” Journal of Clinical Oncology 41 , no. 8 ( 2023 ): 1600 – 1609 , 10.1200/JCO.21.02734 . 36413710 PMC10022857

26 M. Kropff , M. Vogel , G. Bisping , et al., “ Bortezomib and Low‐Dose Dexamethasone With or Without Continuous Low‐Dose Oral Cyclophosphamide for Primary Refractory or Relapsed Multiple Myeloma: A Randomized Phase III Study ,” Annals of Hematology 96 , no. 11 ( 2017 ): 1857 – 1866 . 28905189 10.1007/s00277-017-3065-z

27 P. G. Richardson , A. Oriol , M. Beksac , et al., “ Pomalidomide, Bortezomib, and Dexamethasone for Patients With Relapsed or Refractory Multiple Myeloma Previously Treated With Lenalidomide (OPTIMISMM): A Randomised, Open‐Label, Phase 3 Trial ,” Lancet Oncology 20 , no. 6 ( 2019 ): 781 – 794 . 31097405 10.1016/S1470-2045(19)30152-4

28 S. Grosicki , M. Simonova , I. Spicka , et al., “ Once‐Per‐Week Selinexor, Bortezomib, and Dexamethasone Versus Twice‐Per‐Week Bortezomib and Dexamethasone in Patients With Multiple Myeloma (BOSTON): A Randomised, Open‐Label, Phase 3 Trial ,” Lancet 396 , no. 10262 ( 2020 ): 1563 – 1573 . 33189178 10.1016/S0140-6736(20)32292-3

29 J. F. San‐Miguel , V. T. Hungria , S. S. Yoon , et al., “ Panobinostat Plus Bortezomib and Dexamethasone Versus Placebo Plus Bortezomib and Dexamethasone in Patients With Relapsed or Relapsed and Refractory Multiple Myeloma: A Multicentre, Randomised, Double‐Blind Phase 3 Trial ,” Lancet Oncology 15 , no. 11 ( 2014 ): 1195 – 1206 , 10.1016/S1470-2045(14)70440-1 . 25242045

30 J. F. San‐Miguel , V. T. Hungria , S. S. Yoon , et al., “ Overall Survival of Patients With Relapsed Multiple Myeloma Treated With Panobinostat or Placebo Plus Bortezomib and Dexamethasone (The PANORAMA 1 Trial): A Randomised, Placebo‐Controlled, Phase 3 Trial ,” Lancet Haematology 3 , no. 11 ( 2016 ): e506 – e515 , 10.1016/S2352-3026(16)30147-8 . 27751707

31 A. Jakubowiak , M. Offidani , B. Pégourie , et al., “ Randomized Phase 2 Study: Elotuzumab Plus Bortezomib/Dexamethasone vs Bortezomib/Dexamethasone for Relapsed/Refractory MM ,” Blood 127 , no. 23 ( 2016 ): 2833 – 2840 . 27091875 10.1182/blood-2016-01-694604 PMC4900953

32 M. A. Dimopoulos , P. Moreau , A. Palumbo , et al., “ Carfilzomib and Dexamethasone Versus Bortezomib and Dexamethasone for Patients With Relapsed or Refractory Multiple Myeloma (ENDEAVOR): A Randomised, Phase 3, Open‐Label, Multicentre Study ,” Lancet Oncology 17 , no. 1 ( 2016 ): 27 – 38 , 10.1016/S1470-2045(15)00464-7 . 26671818

33 R. Z. Orlowski , P. Moreau , R. Niesvizky , et al., “ Carfilzomib‐Dexamethasone Versus Bortezomib‐Dexamethasone in Relapsed or Refractory Multiple Myeloma: Updated Overall Survival, Safety, and Subgroups ,” Clinical Lymphoma, Myeloma & Leukemia 19 , no. 8 ( 2019 ): 522 – 530.e1 . 10.1016/j.clml.2019.04.018 31160237

34 D. S. Siegel , A. Oriol , P. Rajnics , et al., “ Updated Results From ASPIRE and ENDEAVOR, Randomized, Open‐Label, Multicenter Phase 3 Studies of Carfilzomib in Patients (Pts) With Relapsed/Refractory Multiple Myeloma (RRMM) ,” Clinical Lymphoma, Myeloma & Leukemia 17 , no. 1 ( 2017 ): e142 .

35 S. Z. Usmani , H. Quach , M.‐V. Mateos , et al., “ Final Analysis of Carfilzomib, Dexamethasone, and Daratumumab vs Carfilzomib and Dexamethasone in the CANDOR Study ,” Blood Advances 7 , no. 14 ( 2023 ): 3739 – 3748 . 37163358 10.1182/bloodadvances.2023010026 PMC10368773

36 S. Z. Usmani , H. Quach , M.‐V. Mateos , et al., “ Carfilzomib, Dexamethasone, and Daratumumab Versus Carfilzomib and Dexamethasone for Patients With Relapsed or Refractory Multiple Myeloma (CANDOR): Updated Outcomes From a Randomised, Multicentre, Open‐Label, Phase 3 Study ,” Lancet Oncology 23 , no. 1 ( 2022 ): 65 – 76 , 10.1016/S1470-2045(21)00579-9 . 34871550

37 P. Moreau , M.‐V. Mateos , J. R. Berenson , et al., “ Once Weekly Versus Twice Weekly Carfilzomib Dosing in Patients With Relapsed and Refractory Multiple Myeloma (A.R.R.O.W.): Interim Analysis Results of a Randomised, Phase 3 Study ,” Lancet Oncology 19 , no. 7 ( 2018 ): 953 – 964 . 29866475 10.1016/S1470-2045(18)30354-1

38 T. Martin , M. A. Dimopoulos , J. Mikhael , et al., “ Isatuximab, Carfilzomib, and Dexamethasone in Patients With Relapsed Multiple Myeloma: Updated Results From IKEMA, a Randomized Phase 3 Study ,” Blood Cancer Journal 13 , no. 1 ( 2023 ): 72 , 10.1038/s41408-023-00797-8 . 37156782 PMC10166682

39 B. Puertas , V. González‐Calle , A. Sureda , et al., “ Randomized Phase II Study of Weekly Carfilzomib 70 Mg/m(2) and Dexamethasone With or Without Cyclophosphamide in Relapsed and/or Refractory Multiple Myeloma Patients ,” Haematologica 108 , no. 10 ( 2023 ): 2753 – 2763 . 37102598 10.3324/haematol.2022.282490 PMC10542845

40 M. Mateos , S. Jagannath , S. Delimpasi , et al., “ Impact of Prior Therapies on the Safety and Efficacy of Once Weekly Selinexor, Bortezomib, and Dexamethasone Compared With Twice Weekly Bortezomib and Dexamethasone in Relapsed or Refractory Multiple Myeloma: Results From the Boston Study ,” Blood 136 ( 2020 ): 50 – 52 .32430504

41 M. Beksac , P. Richardson , A. Oriol , et al., “ OA‐44 Pomalidomide, Bortezomib, and Dexamethasone vs Bortezomib and Dexamethasone in Relapsed or Refractory Multiple Myeloma (OPTIMISMM): Final Survival Outcomes From a Randomized, Open‐Label, Phase 3 Trial ,” Clinical Lymphoma, Myeloma & Leukemia 23 ( 2023 ): S27 – S28 .

42 K. C. Weisel , P. Sonneveld , M.‐V. Mateos , et al., “ Efficacy and Safety of Daratumumab, Bortezomib, and Dexamethasone (D‐Vd) Versus Bortezomib and Dexamethasone (Vd) in First Relapse Patients (Pts) With Multiple Myeloma (MM): Four‐Year Update of Castor ,” Blood 134 , no. Supplement_1 ( 2019 ): 3192 , 10.1182/blood-2019-123527 .

43 A. Palumbo , A. Chanan‐Khan , K. Weisel , et al., “ Daratumumab, Bortezomib, and Dexamethasone for Multiple Myeloma ,” New England Journal of Medicine 375 , no. 8 ( 2016 ): 754 – 766 . 27557302 10.1056/NEJMoa1606038

44 X. Leleu , M.‐V. Mateos , S. Jagannath , et al., “ Effects of Refractory Status to Lenalidomide on Safety and Efficacy of Selinexor, Bortezomib, and Dexamethasone (XVd) Versus Bortezomib and Dexamethasone (Vd) in Patients With Previously Treated Multiple Myeloma ,” Journal of Clinical Oncology 39 , no. 15_suppl ( 2021 ): 8024 .

45 P. Moreau , D. Joshua , W. J. Chng , et al., “ Impact of Prior Treatment on Patients With Relapsed Multiple Myeloma Treated With Carfilzomib and Dexamethasone vs Bortezomib and Dexamethasone in the Phase 3 ENDEAVOR Study ,” Leukemia 31 , no. 1 ( 2017 ): 115 – 122 . 27491641 10.1038/leu.2016.186 PMC5220137

46 M. Dimopoulos , H. Quach , M. V. Mateos , et al., “ Carfilzomib, Dexamethasone, and Daratumumab Versus Carfilzomib and Dexamethasone for Patients With Relapsed or Refractory Multiple Myeloma (CANDOR): Results From a Randomised, Multicentre, Open‐Label, Phase 3 Study ,” Lancet 396 , no. 10245 ( 2020 ): 186 – 197 . 32682484 10.1016/S0140-6736(20)30734-0

47 P. Moreau , M.‐A. Dimopoulos , J. Mikhael , et al., “ Isatuximab, Carfilzomib, and Dexamethasone in Relapsed Multiple Myeloma (IKEMA): A Multicentre, Open‐Label, Randomised Phase 3 Trial ,” Lancet 397 , no. 10292 ( 2021 ): 2361 – 2371 . 34097854 10.1016/S0140-6736(21)00592-4

48 A. Spencer , S. Lentzsch , K. Weisel , et al., “ Daratumumab Plus Bortezomib and Dexamethasone Versus Bortezomib and Dexamethasone in Relapsed or Refractory Multiple Myeloma: Updated Analysis of CASTOR ,” Haematologica 103 , no. 12 ( 2018 ): 2079 – 2087 . 30237264 10.3324/haematol.2018.194118 PMC6269293

49 S. Richard , A. Chari , S. Delimpasi , et al., “ Selinexor, Bortezomib, and Dexamethasone Versus Bortezomib and Dexamethasone in Previously Treated Multiple Myeloma: Outcomes by Cytogenetic Risk ,” American Journal of Hematology 96 , no. 9 ( 2021 ): 1120 – 1130 . 34062004 10.1002/ajh.26261 PMC8457116

50 US Food and Drug Administration , “FDA Approves Carfilzomib and Daratumumab With Dexamethasone for Multiple Myeloma,” (2020), https://www.fda.gov/drugs/resources‐information‐approved‐drugs/fda‐approves‐carfilzomib‐and‐daratumumab‐dexamethasone‐multiple‐myeloma .

51 U.S. Food and Drug Administration , “FDA Approves Isatuximab‐Irfc for Multiple Myeloma,” (2021), https://www.fda.gov/drugs/resources‐information‐approved‐drugs/fda‐approves‐isatuximab‐irfc‐multiple‐myeloma .

52 U.S. Food and Drug Administration , “ REVLIMID (lenalidomide) Highlights of the Prescribing Information ,” (2017), https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/021880s049lbl.pdf .

53 European Medicines Agency , “ Revlimid Summary of Product Characteristics ,” https://www.ema.europa.eu/en/documents/product‐information/revlimid‐epar‐product‐information_en.pdf .

54 P. M. Voorhees , D. W. Sborov , J. Laubach , et al., “ Addition of Daratumumab to Lenalidomide, Bortezomib, and Dexamethasone for Transplantation‐Eligible Patients With Newly Diagnosed Multiple Myeloma (GRIFFIN): Final Analysis of an Open‐Label, Randomised, Phase 2 Trial ,” Lancet Haematology 10 , no. 10 ( 2023 ): e825 – e837 . 37708911 10.1016/S2352-3026(23)00217-X

55 F. Gay , W. Roeloffzen , M. A. Dimopoulos , et al., “ Results of the Phase III Randomized Iskia Trial: Isatuximab‐Carfilzomib‐Lenalidomide‐Dexamethasone vs Carfilzomib‐Lenalidomide‐Dexamethasone as Pre‐Transplant Induction and Post‐Transplant Consolidation in Newly Diagnosed Multiple Myeloma Patients ,” Blood 142 , no. Supplement 1 ( 2023 ): 4 .37410508

56 S. McNamara , J. Chorazy , A. Pandey , et al., “ CO75 Clinical Outcomes Associated With Anti‐CD38 Retreatment in Relapsed/Refractory Multiple Myeloma: A Review of the Literature ,” Value in Health 27 , no. 6 ( 2024 ): S31 .

57 U. H. Gandhi , R. F. Cornell , A. Lakshman , et al., “ Outcomes of Patients With Multiple Myeloma Refractory to CD38‐Targeted Monoclonal Antibody Therapy ,” Leukemia 33 , no. 9 ( 2019 ): 2266 – 2275 . 30858549 10.1038/s41375-019-0435-7 PMC6820050

58 P. Sonneveld , H. Avet‐Loiseau , S. Lonial , et al., “ Treatment of Multiple Myeloma With High‐Risk Cytogenetics: A Consensus of the International Myeloma Working Group ,” Blood 127 , no. 24 ( 2016 ): 2955 – 2962 . 27002115 10.1182/blood-2016-01-631200 PMC4920674

59 D. Kegyes , C. Constantinescu , L. Vrancken , et al., “ Patient Selection for CAR T or BiTE Therapy in Multiple Myeloma: Which Treatment for Each Patient? ,” Journal of Hematology & Oncology 15 , no. 1 ( 2022 ): 78 . 35672793 10.1186/s13045-022-01296-2 PMC9171942

60 J. San‐Miguel , B. Dhakal , K. Yong , et al., “ Cilta‐Cel or Standard Care in Lenalidomide‐Refractory Multiple Myeloma ,” New England Journal of Medicine 389 , no. 4 ( 2023 ): 335 – 347 . 37272512 10.1056/NEJMoa2303379

61 N. C. Munshi , L. D. Anderson , Jr. , N. Shah , et al., “ Idecabtagene Vicleucel in Relapsed and Refractory Multiple Myeloma ,” New England Journal of Medicine 384 , no. 8 ( 2021 ): 705 – 716 . 33626253 10.1056/NEJMoa2024850

62 M. Sheykhhasan , A. Ahmadieh‐Yazdi , R. Vicidomini , et al., “ CAR T Therapies in Multiple Myeloma: Unleashing the Future ,” Cancer Gene Therapy 31 , no. 5 ( 2024 ): 667 – 686 . 38438559 10.1038/s41417-024-00750-2 PMC11101341

63 N. Duma , T. Azam , I. B. Riaz , M. Gonzalez‐Velez , S. Ailawadhi , and R. Go , “ Representation of Minorities and Elderly Patients in Multiple Myeloma Clinical Trials ,” Oncologist 23 , no. 9 ( 2018 ): 1076 – 1078 . 29700207 10.1634/theoncologist.2017-0592 PMC6192659

64 S. Fahmawi , C. Schinke , S. Thanendrarajan , et al., “ Under‐Representation of Black Patients With Multiple Myeloma in Studies Supporting International Myeloma Working Group Guidelines ,” Journal of Cancer Policy 37 ( 2023 ): 100433 . 37468042 10.1016/j.jcpo.2023.100433

65 V. Hungria , P. Robak , M. Hus , et al., “Patient‐Reported Outcomes (PROs) from the DREAMM‐7 Randomized Phase 3 Study Comparing Belantamab Mafodotin, Bortezomib, and Dexamethasone (BVd) vs Daratumumab, Bortezomib, and Dexamethasone (DVd) in Patients With Relapsed/Refractory Multiple Myeloma (RRMM),” Paper Presented at: ASCO2024.

66 A. K. Puerto Nino and R. Brignardello‐Petersen , “ How to Read a Network Meta‐Analysis ,” European Urology Focus 9 , no. 5 ( 2023 ): 701 – 704 . 37925328 10.1016/j.euf.2023.10.018

67 I. D. Florez , J. E. De La Cruz‐Mena , and A.‐A. Veroniki , “ Network Meta‐Analysis: A Powerful Tool for Clinicians, Decision‐Makers, and Methodologists ,” Journal of Clinical Epidemiology 176 ( 2024 ): 111537 . 39307403 10.1016/j.jclinepi.2024.111537