{"doi":"10.1093/ije/dyn179","title":"Can trial sequential monitoring boundaries reduce spurious inferences from meta-analyses?","abstract":"<h4>Background</h4>Results from apparently conclusive meta-analyses may be false. A limited number of events from a few small trials and the associated random error may be under-recognized sources of spurious findings. The information size (IS, i.e. number of participants) required for a reliable and conclusive meta-analysis should be no less rigorous than the sample size of a single, optimally powered randomized clinical trial. If a meta-analysis is conducted before a sufficient IS is reached, it should be evaluated in a manner that accounts for the increased risk that the result might represent a chance finding (i.e. applying trial sequential monitoring boundaries).<h4>Methods</h4>We analysed 33 meta-analyses with a sufficient IS to detect a treatment effect of 15% relative risk reduction (RRR). We successively monitored the results of the meta-analyses by generating interim cumulative meta-analyses after each included trial and evaluated their results using a conventional statistical criterion (alpha = 0.05) and two-sided Lan-DeMets monitoring boundaries. We examined the proportion of false positive results and important inaccuracies in estimates of treatment effects that resulted from the two approaches.<h4>Results</h4>Using the random-effects model and final data, 12 of the meta-analyses yielded P > alpha = 0.05, and 21 yielded P </= alpha = 0.05. False positive interim results were observed in 3 out of 12 meta-analyses with P > alpha = 0.05. The monitoring boundaries eliminated all false positives. Important inaccuracies in estimates were observed in 6 out of 21 meta-analyses using the conventional P </= alpha = 0.05 and 0 out of 21 using the monitoring boundaries.<h4>Conclusions</h4>Evaluating statistical inference with trial sequential monitoring boundaries when meta-analyses fall short of a required IS may reduce the risk of false positive results and important inaccurate effect estimates.","journal":"International Journal of Epidemiology","year":2008,"id":8347,"datarank":1.0140622036625142,"base_score":6.760414691083428,"endowment":6.760414691083428,"self_citation_contribution":1.0140622036625142,"citation_network_contribution":0.0,"self_endowment_contribution":1.0140622036625142,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":862,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0447,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2008-09-29","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":73278,"name":"Jørn Wetterslev","orcid":"0000-0001-7778-1771","position":2,"is_corresponding":false},{"id":16535,"name":"Gordon Guyatt","orcid":"0000-0003-2352-5718","position":3,"is_corresponding":false},{"id":148,"name":"John P. A. Ioannidis","orcid":"0000-0003-3118-6859","position":4,"is_corresponding":false},{"id":7329,"name":"Lehana Thabane","orcid":"0000-0003-0355-9734","position":5,"is_corresponding":false},{"id":18197,"name":"Bodil Als-Nielsen","orcid":null,"position":7,"is_corresponding":false},{"id":18198,"name":"Christian Gluud","orcid":"0000-0002-8861-0799","position":8,"is_corresponding":false},{"id":50550,"name":"P.J. Devereaux","orcid":"0000-0003-2935-637X","position":9,"is_corresponding":false},{"id":18199,"name":"Lise Lotte Gluud","orcid":"0000-0002-9462-4468","position":10,"is_corresponding":false},{"id":7078,"name":"Kristian Thorlund","orcid":"0000-0001-5848-3111","position":0,"is_corresponding":true}],"reference_count":61,"raw_metadata":{"citation_network_status":"fetched"},"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":[]}