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dc.contributor.authorRose, Christopher James
dc.contributor.authorOhm, Ingrid Kristine
dc.contributor.authorGiske, Liv
dc.contributor.authorNæss, Gunn Eva
dc.contributor.authorFretheim, Atle
dc.date.accessioned2023-11-28T06:55:53Z
dc.date.available2023-11-28T06:55:53Z
dc.date.created2023-08-30T11:19:08Z
dc.date.issued2023
dc.identifier.citationBMJ Open. 2023, 13 (8), 1-13.en_US
dc.identifier.issn2044-6055
dc.identifier.urihttps://hdl.handle.net/11250/3104873
dc.description.abstractObjectives To 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. Design Systematic 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. Results Among 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. Conclusions Based 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.en_US
dc.language.isoengen_US
dc.rightsNavngivelse-Ikkekommersiell 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/deed.no*
dc.titleEffect modification in network meta-analyses for relapsed/refractory multiple myeloma: Systematic review and meta-analysisen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.doi10.1136/bmjopen-2022-067966
dc.identifier.cristin2170852
dc.source.journalBMJ Openen_US
dc.source.volume13en_US
dc.source.issue8en_US
dc.source.pagenumber1-13en_US


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Navngivelse-Ikkekommersiell 4.0 Internasjonal
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