OBJECTIVES: Population-adjusted indirect comparisons (PAICs) are required to compare treatment efficacy across different therapies where head-to-head trials are unavailable. Treatment effect modifiers (TEMs) and prognostic factors (PFs) need to be adjusted for, and a systematic approach to identify these is recommended by health technology assessment (HTA) agencies. We examined published PAICs on how these variables were determined previously in multiple myeloma (MM).

METHODS: A literature review was conducted to identify published PAICs of OS and PFS in Medline, Embase, Cochrane and HTA submissions (NICE, CADTH and GBA) across 4 MM populations (i.e., newly-diagnosed transplant-eligible (TE) or transplant-ineligible (TIE), relapsed/refractory (RR) with one or more prior line (1PL+) or with prior triple-class exposure (TCE)). The following information were collected and summarized: whether the PAICs were anchored or unanchored, whether the variables were selected by statistical testing and/or by expert opinion, the variables included for adjustment and ranking where it applies.

RESULTS: 59 unique PAICs from 45 peer-reviewed publications and 12 HTA documents were extracted for TE (N=8), TIE (N=10), 1PL+ (N=23) and TCE (N=18). Only 2 PAICs were anchored comparisons. No statistical analyses assessing prognostic strength or effect modification were reported. 59% and 20% of PAICs reported clinical expert informed variable selection and ranking, respectively. Variables included for adjustment differed by population and outcome. Commonly adjusted variables for both OS and PFS were age, sex, ISS/r-ISS stage, cytogenetics, type of MM, and creatinine clearance. In 1PL+ and TCE, refractoriness to prior treatment, prior exposure to anti-myeloma treatment including transplant, time since diagnosis, plasmacytoma were also commonly adjusted. Among PAICs submitted to HTA, feedback on PFs/TEMs selection is lacking.

CONCLUSIONS: Limited information is available on the selection process for PFs/TEMs in MM, and a systematic synthesis of these is lacking. This review is part of our approach to systematically identify PFs/TEMs for future PAICs in MM.