SynthesisBMJ open2023
Effect modification in network meta-analyses for relapsed/refractory multiple myeloma: systematic review and meta-analysis.
Synthesis in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Identification of treatment effect modifiers and prognostic factors in newly diagnosed and relapsed or refractory multiple myeloma.Journal of comparative effectiveness research · 2025Article
- Increasing transparency in indirect treatment comparisons: is selecting effect modifiers the missing part of the puzzle? A review of methodological approaches and critical considerations.Journal of comparative effectiveness research · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo systematically review and meta-analyse the evidence for effect modification by refractory status and number of treatment lines in relapsed/refractory multiple myeloma (RRMM); and to assess whether effect modification is likely to invalidate network meta-analyses (NMA) that assume negligible modification.
designSystematic review, meta-analysis and simulation. DATA SOURCES: We systematically searched the literature (e.g., OVID Medline) to identify eligible publications in February 2020 and regularly updated the search until January 2022. We also contacted project stakeholders (including industry) ELIGIBILITY CRITERIA: Phase 2 and 3 randomised controlled trials reporting stratified estimates for comparisons with at least one of a prespecified set of treatments relevant for use in Norwegian RRMM patients. OUTCOMES: We used meta-analysis to estimate relative HRs (RHRs) for overall survival (OS) and progression-free survival (PFS) with respect to refractory status and number of treatment lines. We used the estimated RHRs in simulations to estimate the percentage of NMA results expected to differ significantly in the presence versus absence of effect modification.
resultsAmong the 42 included publications, stratified estimates were published by and extracted from up to 18 (43%) publications and on as many as 8364 patients. Within-study evidence for effect modification is very weak (p>0.05 for 47 of 49 sets of stratified estimates). The largest RHR estimated was 1.32 (95% CI 1.18 to 1.49) for the modifying effect of refractory status on HR for PFS. Simulations suggest that, in the worst case, this would result in only 4.48% (95% CI 4.42% to 4.54%) of NMA estimates differing statistically significantly in the presence versus absence of effect modification.
conclusionsBased on the available evidence, effect modification appears to be sufficiently small that it can be neglected in adequately performed NMAs. NMAs can probably be relied on to provide estimates of HRs for OS and PFS in RRMM, subject to caveats discussed herein.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.