An Investigation of Potential Treatment Effect Modifiers in Multiple Myeloma from Published Randomized Controlled Trials

Purpose:

The purpose of this study was to identify treatment effect modifiers (TEMs) of progression-free survival (PFS) and overall survival (OS) in multiple myeloma (MM) using published data from randomized controlled trials (RCTs).

Background

TEMs are clinical or demographic characteristics which impact the relationship between treatments and outcomes. Effectiveness of treatments vary across different subgroups defined by the TEM. To ensure accurate determination of outcome estimates, it is crucial to obtain a systematic and up-to-date list of potential TEMs prior to conducting clinical trials or cross-trial comparisons, such as population-adjusted indirect comparisons (PAICs), in a dynamically evolving treatment landscape. Currently, such an evaluation of TEMs based on RCTs across MM populations is limited.

Materials and Methods: A literature review was conducted to identify RCTs published between January 1996 and April 2023 for newly-diagnosed (ND) transplant-eligible (TE) or transplant-ineligible (TIE) and relapsed/refractory (RR) MM patient populations. The primary source of information was PubMed, supplemented by searches in ClinicalTrials.gov, other websites (i.e., for drug manufacturer press releases, conferences abstracts/posters/presentations, as well as regulatory reviews from the United States Food and Drug Administration and the European Medicines Agency), and bibliographies of on-topic reviews. Subgroup analyses reporting relative PFS or OS effects of the treatment arm versus control in at least two levels of the subgroup variable were reviewed. Hazard ratios (HRs) and confidence intervals (CIs) for each level were extracted. Treatment effect differences across levels were evaluated by determining the CI of the ratio between HRs from two levels. Potential TEMs were identified within each RCT by noting subgroup variables that were significant at P<0.2. A subgroup variable was considered likely a TEM if it met this threshold in at least three unique RCTs. The 80% CI threshold (P<0.2) was chosen because subgroup analyses in RCTs are generally underpowered due to smaller sample sizes compared to the main analysis.

Results: Data from 65 RCTs were included (NDMM TE = 15, NDMM TIE = 21, RRMM = 29). Variables considered as TEMs for PFS across different MM groups were cytogenetic risk, International Staging System (ISS)/revised-ISS stage, age, and sex. Additional TEMs for NDMM TIE included creatinine clearance and ECOG score; and for RRMM included creatinine clearance, refractory and prior therapy exposure status. The variables considered as TEMs for OS were cytogenetic risk for NDMM TIE; cytogenetic risk, age, ISS/r-ISS stage and geographical region for RRMM. No variable(s) met the threshold of TEM for OS in the NDMM TE population.

Conclusions: This study identified potential patient demographic and clinical characteristics that may affect the likelihood of MM treatment response. These characteristics should be considered in future trial designs and PAICs to minimize potential bias when comparing treatment effects across different MM patient populations.

He:johnson and johnson: Current Employment, Current equity holder in publicly-traded company. Chiang:johnson and johnson: Consultancy. Lin:johnson and johnson: Current Employment, Current equity holder in publicly-traded company. Maringwa:johnson and johnson: Current Employment. Yang:johnson and johnson: Current Employment, Current equity holder in publicly-traded company. Kwong:johnson and johnson: Current Employment, Current equity holder in publicly-traded company. Nair:johnson and johnson: Current Employment, Current equity holder in publicly-traded company. Hashim:johnson and johnson: Current Employment, Current equity holder in publicly-traded company. Samjoo:johnson and johnson: Consultancy.