DREAMM-2: Indirect Comparisons of Belantamab Mafodotin vs. Selinexor + Dexamethasone and Standard of Care Treatments in Relapsed/Refractory Multiple Myeloma

Multiple myeloma (MM) accounts for approximately 1% of all cancers and 15% of hematologic malignancies with an annual incidence of 86,000 new cases globally [1, 2]. Despite major advances in treatment, MM remains an incurable disease, which requires multiple lines of therapy due to relapse [2, 3]. Available treatments for relapsed refractory MM (RRMM) include immunomodulatory drugs (e.g., lenalidomide and pomalidomide), proteasome inhibitors (PIs; e.g., carfilzomib and ixazomib), monoclonal antibodies (mAbs) targeting CD38 (e.g., daratumumab), and signaling lymphocytic activation molecule F7 (SLAM7; e.g., elotuzumab), the nuclear export protein inhibitors (XPO1; selinexor), alkylators, and steroids [2‐4]. After initial response, patients eventually relapse, and each subsequent relapse is associated with cumulative treatment toxicity and a shorter duration of response, as patients develop refractory disease due to multiple drug resistance mechanisms [2, 5‐7]. Patients with RRMM that is refractory to immunomodulatory agents, PIs, and an anti-CD38 antibody have a particularly poor prognosis [2, 8]. Therefore, novel therapies with alternative modes of action are needed for this population with a high unmet need.

Belantamab mafodotin (belamaf; BLENREP; GSK2857916) is a first-in-class antibody–drug conjugate (ADC) that targets B-cell maturation antigen (BCMA) [9, 10]. It comprises a humanized afucosylated anti-BCMA mAb conjugated to a cytotoxic payload monomethyl auristatin F (MMAF) by a protease-resistant mc linker [9]. Belamaf binds to BCMA and eliminates MM cells by a multimodal mechanism of action, including delivery of MMAF to MM cells, immune-independent ADC mediated apoptosis, and release of markers characteristic of immunogenic cell death as well as immune-dependent mechanisms of action such as antibody-directed cellular cytotoxicity/phagocytosis [9, 10].

In the Phase II, single-arm DRiving Excellence in Approaches to Multiple Myeloma 2 (DREAMM-2 study; NCT03525678), multiply relapsed patients who received single-agent belamaf 2.5 mg/kg every 3 weeks showed an overall response rate (ORR) of 32%, estimated median duration of response (DoR) of 11 months, overall survival (OS) of 13.7 months, and median progression-free survival (PFS) of 2.8 months at a median follow-up of 13 months [9, 11]. On the basis of the DREAMM-2 study, single-agent belamaf (2.5 mg/kg) was recently approved in the USA and European Union for the treatment of adult patients with RRMM who have received at least four prior therapies including an anti-CD38 mAb, a PI, and an immunomodulatory agent [12, 13].

Demonstration of added value is important for novel treatments through comparative evaluations of efficacy and safety, which will inform on cost-effectiveness and enable decisions on payer interactions, clinical care, and reimbursement coverage. In the absence of head-to-head comparisons, data from separate studies can be evaluated via indirect treatment comparisons (ITC). ITC through network meta-analysis is not feasible for single-arm studies because of the network of evidence being disconnected [14]. Instead, population-adjusted ITCs are applicable in this setting, as recommended by the National Institute for Health and Care Excellence (NICE) Decisions Support Unit (DSU) [14].

Matching-adjusted indirect comparisons (MAIC) are a form of population-adjusted ITC that can be used to compare trials with similar designs, definitions, and patient populations. The MAIC method relies on weights assigned to patients in the trial, for which individual patient-level data are available, to match aggregate baseline data from comparator trials, thereby removing population differences that could bias comparisons of treatment outcomes. This provides important information to contextualize data from single-arm studies.

The goal of this post-hoc analysis of the DREAMM-2 study was to conduct ITC of belamaf versus relevant comparators and standard of care (SoC) in similar patient populations. A systematic literature review (SLR) was conducted to identify relevant comparator studies and is being submitted for publication [15]. Results of the SLR were used to assess the feasibility of conducting an ITC using the MAIC method to compare the efficacy and safety of belamaf versus selinexor data from Selinexor Treatment of Refractory Myeloma (STORM) Part 2 [16]. A Bucher ITC analysis was then conducted using the MAIC results for the OS of SoC in a subset of patients in the Monoclonal Antibodies in Multiple Myeloma: Outcomes after Therapy Failure (MAMMOTH) study who were refractory to a PI, an immunomodulatory agent, and daratumumab [8, 17, 18].

The MAIC of belamaf (DREAMM-2) with sel + dex (STORM Part 2) was conducted following a SLR and searching of all relevant evidence. At the time of this research, STORM Part 2 was systematically identified as the only feasible comparator to the DREAMM-2 cohort. However, with the continuous development of new experimental therapies, more treatments may become available in the future requiring additional comparisons. The results of the MAIC analysis suggested that belamaf has a more favorable safety profile for most TEAEs, and patients treated with belamaf experienced a longer OS and DoR than those treated with sel + dex. It has been demonstrated that patients with RRMM typically experience shorter DoR with each subsequent therapy [6]. Therefore, sustaining longer responses with belamaf compared with sel + dex and SoC is particularly encouraging in patients who received ≥ 3 prior therapies and whose MM was triple-class refractory to an immunomodulatory agent, a PI, and an anti-CD38 mAb. Response rates were found to be equivalent in terms of ORR between belamaf and sel + dex. TTR had a numerically worse efficacy profile with belamaf compared with sel + dex. However, the difference was not statistically significant. The steeper decline of the belamaf PFS curve around 4 weeks compared with sel + dex, combined with the similar response rates observed between belamaf and sel + dex, may suggest a faster progression among non-responding patients in the DREAMM-2 versus those in the STORM Part 2 study. However, this could also be attributed to differences in the time schedule of assessment; by trial design, the initial assessment for progressive disease (PD) happened earlier in the DREAMM-2 than the STORM, and therefore PD events were captured earlier in the DREAMM-2 compared with the STORM study.

In a single-arm study, OS, which measures death from any cause, can potentially be driven by other factors including subsequent treatments. The median PFS in the DREAMM-2 trial was 2.8 months (95% CI 1.6, 3.6) and median OS was 13.7 months (95% CI 9.9, not reached [NR]) at the time of the January 2020 data cutoff [9, 11]. In the 2.5 mg/kg cohort of the DREAMM-2 study, median PFS for the 35% of patients who had PD/not established (NE) response was 0.8 months (95% CI 0.7, 0.8), and for the 31% of patients who achieved SD, median PFS was 2.9 months (95% CI 2.1, 3.0). As displayed in Supplementary Fig. 1, this can be contrasted with median PFS NR (95% CI 7.1, NR) in 15% of patients who had a ≥ minimal response (MR)/partial response (PR). Overall, 38 (39%) patients received subsequent anticancer therapy (of these, only 2 received sel). The difference in OS outcomes by responder group is shown in Supplementary Fig. 2. Median OS was 8.7 months (95% CI 1.9, 13.1.9) in patients who had PD/NE and 7.7 months (95% CI 4.7, 13.4) in those who achieved SD. The median OS among patients with ≥ MR/PR was NR (95% CI NR, NR). It is possible that some aspects of the observed survival benefit were driven by post-progression treatments. However, given the proportion of patients receiving subsequent anticancer treatments in the belamaf cohort and the magnitude of differences in outcomes between non-responders and responders, the difference seen in OS is likely to be driven by patients responding to belamaf treatment.

In general, belamaf had a more favorable safety profile than sel + dex for most evaluable hematologic and non-hematologic AEs, with the exception of hypercalcemia. These results were consistent across all models. As hypercalcemia is commonly reported in patients with MM, the difference in incidence between belamaf and sel + dex may be related to disease progression rather than treatment [19, 25]. In addition, dexamethasone used in the sel + dex combination could have had a calcium reduction effect via decreased intestinal calcium absorption. Similarly, dexamethasone may have contributed to the higher hyperglycemia rate in sel + dex. It should be noted that keratopathy was the most frequent treatment-associated AE in DREAMM-2, with 1% of patients in the 2.5 mg/kg cohort discontinuing treatment as a result [11]. Keratopathy was managed with dose modification (47% of patients had dose delays and 25% had dose reductions in the 2.5 mg/kg cohort). Ocular events are known side effects of MMAF-containing ADCs [26]. No keratopathy and hypophosphatasemia events were reported in the STORM Part 2 study so no statistical comparison could be made between the two treatments [9, 16, 24].

In the absence of head-to-head randomized controlled trials, population-adjusted ITCs can be valuable tools to compare efficacy and safety of treatments from separate studies to inform clinical practice and value analyses. However, it is crucial that the included clinical trials have similar patient populations, design, and definitions. In this study, the weighting process for all of these aspects was successful. The ESS achieved was considered satisfactory (65% of original sample size), and there were no extreme MAIC weights, which ensured that the results were not affected disproportionately by only a few patients. This notion was further supported by the similar trend of time to events both before and after the population adjustment.

The current MAIC analyses are subject to potential limitations relating to the comparability of studies. Although both studies had similar trial designs, and population characteristics were weighted successfully, differences in the frequency of assessment for PD between the two studies may have introduced bias in these unanchored ITC. In the STORM Part 2 study, the response and PD assessments were performed on a 4-weekly schedule, while in the DREAMM-2 study, patients were monitored on a 3-weekly schedule. As PFS and TTR were recorded at different scheduled monitoring visits in each study, unanchored comparisons of PFS and TTR may be subject to assessment time bias [27].

Additionally, differences in unobserved patient baseline characteristics can confound comparisons despite matching populations on observed characteristics. Limited data were available for the STORM Part 2 study population on frailty of patients at baseline. Furthermore, certain prognostic factors were not reported in STORM Part 2 (extramedullary disease at baseline, BCMA levels, presence of lytic bone lesions at baseline) and could not be included in the MAIC models (Supplementary Table 1). The two studies could not be balanced for time since diagnosis or mutation-specific factors because of missing data. Different levels of prognostic factors with similar prognosis of outcomes were combined to increase ESS after MAIC weighting, as matching distributions at a more granular level required a larger reduction in the effective sample. Additionally, as the proportion of patients that were refractory to a variety of combinations of active drugs was higher in STORM Part 2 compared with the DREAMM-2 study, the results should be interpreted with caution. However, a sensitivity analysis in which the proportion of patients with penta-refractory disease at baseline were matched across both studies provided similar results (Supplementary Table 1). Furthermore, there was a single trial to inform the comparison between belamaf and sel + dex. If more trials were available for MAIC, HRs for each comparator could have been pooled. Despite these limitations, the MAIC methodology was successfully applied to compare belamaf versus sel + dex and suggests a significant difference in OS, DoR, and most AEs in favor of belamaf.

The ITC of belamaf versus SoC suggests that belamaf significantly prolongs OS over SoC. This analysis relies on the assumption that the two HRs that were compared, i.e., the HR comparing sel + dex versus SoC in Costa et al. [17] and the HR comparing belamaf versus sel + dex after population weighting of the DREAMM-2 and STORM Part 2 populations, are independent from the population in which they have been measured and can, therefore, be compared. We could find no evidence suggesting that this assumption does not hold. In addition, the adjusted HR of sel + dex versus SoC from the MAMMOTH study could be confounded by the use of real-world studies in the comparison. A final consideration is that patients included in the MAMMOTH study may have been excluded from participation in clinical trials because of their fragile health status.

In conclusion, single-agent belamaf represents a new treatment option for multiply relapsed patients with RRMM. In these analyses, the ITC that used MAIC based on the 13-month follow-up of the DREAMM-2 study found belamaf to be significantly more efficacious than sel + dex in terms of OS and DoR. A significantly prolonged OS was also estimated for belamaf compared with SoC, as observed in the MAMMOTH study. The results also revealed a more favorable safety profile for belamaf than sel + dex, as demonstrated by significantly lower incidence of any-grade and Grade 3–4 hematologic AEs (with the exception of lymphopenia) and of most any-grade non-hematologic AEs including fatigue, nausea, hyponatremia, pneumonia, diarrhea, hypokalemia, mental status changes, and decreased appetite. Keratopathy (MECs) was the most common TEAE in DREAMM-2 but was not reported in STORM Part 2. Further comparisons of efficacy and safety can be carried out if suitable data become available.