{"doi":"10.1002/jrsm.1708","title":"Impact of trial attrition rates on treatment effect estimates in chronic inflammatory diseases: A meta‐epidemiological study","abstract":"The objective of this meta-epidemiological study was to explore the impact of attrition rates on treatment effect estimates in randomised trials of chronic inflammatory diseases (CID) treated with biological and targeted synthetic disease-modifying drugs. We sampled trials from Cochrane reviews. Attrition rates and primary endpoint results were retrieved from trial publications; Odds ratios (ORs) were calculated from the odds of withdrawing in the experimental intervention compared to the control comparison groups (i.e., differential attrition), as well as the odds of achieving a clinical response (i.e., the trial outcome). Trials were combined using random effects restricted maximum likelihood meta-regression models and associations between estimates of treatment effects and attrition rates were analysed. From 37 meta-analyses, 179 trials were included, and 163 were analysed (301 randomised comparisons; n = 62,220 patients). Overall, the odds of withdrawal were lower in the experimental compared to control groups (random effects summary OR = 0.45, 95% CI, 0.41-0.50). The corresponding overall treatment effects were large (random effects summary OR = 4.43, 95% CI 3.92-4.99) with considerable heterogeneity across interventions and clinical specialties (I<sup>2</sup> = 85.7%). The ORs estimating treatment effect showed larger treatment benefits when the differential attrition was more prominent with more attrition in the control group (OR = 0.73, 95% CI 0.55-0.96). Higher attrition rates from the control arm are associated with larger estimated benefits of treatments with biological or targeted synthetic disease-modifying drugs in CID trials; differential attrition may affect estimates of treatment benefit in randomised trials.","journal":"Research Synthesis Methods","year":2024,"id":6795,"datarank":0.20794415416798362,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.0,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.1681,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-02-13","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":62724,"name":"Caroline M. Moos","orcid":"0000-0003-4997-4319","position":1,"is_corresponding":false},{"id":148,"name":"John P. A. Ioannidis","orcid":"0000-0003-3118-6859","position":2,"is_corresponding":false},{"id":62725,"name":"George Luta","orcid":"0000-0002-4035-7632","position":3,"is_corresponding":false},{"id":62726,"name":"Johannes I. Berg","orcid":null,"position":4,"is_corresponding":false},{"id":24062,"name":"Sabrina Mai Nielsen","orcid":"0000-0003-2857-2484","position":5,"is_corresponding":false},{"id":62727,"name":"Vibeke Andersen","orcid":"0000-0002-0127-2863","position":6,"is_corresponding":false},{"id":24069,"name":"Robin Christensen","orcid":"0000-0002-6600-0631","position":7,"is_corresponding":false},{"id":62723,"name":"Silja Hvid Overgaard","orcid":"0000-0001-6184-2154","position":0,"is_corresponding":true}],"reference_count":31,"raw_metadata":null,"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}