{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["14(10)"],"submitter":["He J"],"pubmed_abstract":["<b>Aim:</b> We aimed to identify variables that affect the prognosis and treatment effect in multiple myeloma (MM). <b>Materials & methods:</b> Published literature of randomized controlled trials (RCTs) and population-adjusted indirect comparisons (PAICs) in newly diagnosed (ND) and relapsed/refractory (RR) MM populations reporting overall survival (OS) and progression-free survival (PFS) were identified. Possible treatment effect modifiers (TEMs) were evaluated based on the ratio between effect estimates of different strata within subgroups for OS and PFS among eligible RCTs. Potential prognostic factors (PFs) were identified using the lists of covariates adjusted for in PAICs meeting the eligibility criteria. <b>Results:</b> Sixty-five RCTs and 59 PAICs were included for synthesis. In N"],"journal":["Journal of comparative effectiveness research"],"pagination":["e240180"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12465902"],"repository":["biostudies-literature"],"pubmed_title":["Identification of treatment effect modifiers and prognostic factors in newly diagnosed and relapsed or refractory multiple myeloma."],"pmcid":["PMC12465902"],"pubmed_authors":["Keng MJ","Kwong WJ","Yang L","He J","Hashim M","Samjoo IA","Lin X","Maringwa J","Nair S","Chiang K"],"additional_accession":[]},"is_claimable":false,"name":"Identification of treatment effect modifiers and prognostic factors in newly diagnosed and relapsed or refractory multiple myeloma.","description":"<b>Aim:</b> We aimed to identify variables that affect the prognosis and treatment effect in multiple myeloma (MM). <b>Materials & methods:</b> Published literature of randomized controlled trials (RCTs) and population-adjusted indirect comparisons (PAICs) in newly diagnosed (ND) and relapsed/refractory (RR) MM populations reporting overall survival (OS) and progression-free survival (PFS) were identified. Possible treatment effect modifiers (TEMs) were evaluated based on the ratio between effect estimates of different strata within subgroups for OS and PFS among eligible RCTs. Potential prognostic factors (PFs) were identified using the lists of covariates adjusted for in PAICs meeting the eligibility criteria. <b>Results:</b> Sixty-five RCTs and 59 PAICs were included for synthesis. In N","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Oct","modification":"2026-06-03T21:22:05.641Z","creation":"2026-05-01T03:10:58.738Z"},"accession":"S-EPMC12465902","cross_references":{"pubmed":["40793976"],"doi":["10.57264/cer-2024-0180"]}}