Presentation (CTI)

OBJECTIVES: The treatment landscape for relapsed or refractory multiple myeloma (RRMM) is crowded and rapidly evolving. Indirect treatment comparisons (ITCs) are frequently used to generate external comparative efficacy because it is infeasible for head-to-head trials to include all relevant comparators. Recent ITCs face increasing challenges due to differences in trial patient populations, driven by resistance to immunomodulatory agents and the expanding use of anti-CD38 monoclonal antibodies in earlier lines. To better understand these challenges, a comprehensive review of recent NICE submissions in RRMM was conducted.
METHODS: Twelve NICE submissions in RRMM, published between November 2020 and November 2025 were reviewed. Full-text screening of committee papers and guidance was conducted to identify the ITC approaches applied and key critiques related to deriving out-of-trial comparative efficacy.
RESULTS: Of the twelve submissions reviewed, three submissions were excluded because only within-trial comparison were considered. Among the nine included submissions, half were based on single-arm trials. One submission conducted a network meta-analysis (NMA); three employed unanchored matching-adjusted indirect comparisons (MAICs); three used both approaches; one applied inverse probability of treatment weighting; and one conducted an unanchored MAIC and a simulated treatment comparison. No single approach was consistently preferred by the committee. Instead, evaluation focused on the suitability of the selected approach given the available evidence, and whether key treatment effect modifiers were appropriately identified and adjusted for. Key critiques included high-risk bias due to violations of the proportional hazards assumption and small effective sample sizes, particularly in unanchored MAICs. Additional concerns included immature survival data, lack of adjustment for treatment crossover, heterogeneity within the evidence network, and remarkably differences in treatment landscapes across trials.
CONCLUSIONS: For ITCs in RRMM, improved handling of non-proportional hazards, thorough assessment of heterogeneity/inconsistency across trial populations, and robust identification and adjustment of effect modifiers are crucial to support decision making.