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Agreement was moderate between data-based and opinion-based assessments of biases affecting randomized trials within meta-analyses.


ABSTRACT: BACKGROUND AND OBJECTIVE:Randomized trials included in meta-analyses are often affected by bias caused by methodological flaws or limitations, but the degree of bias is unknown. Two proposed methods adjust the trial results for bias using empirical evidence from published meta-epidemiological studies or expert opinion. METHODS:We investigated agreement between data-based and opinion-based approaches to assessing bias in each of four domains: sequence generation, allocation concealment, blinding, and incomplete outcome data. From each sampled meta-analysis, a pair of trials with the highest and lowest empirical model-based bias estimates was selected. Independent assessors were asked which trial within each pair was judged more biased on the basis of detailed trial design summaries. RESULTS:Assessors judged trials to be equally biased in 68% of pairs evaluated. When assessors judged one trial as more biased, the proportion of judgments agreeing with the model-based ranking was highest for allocation concealment (79%) and blinding (79%) and lower for sequence generation (59%) and incomplete outcome data (56%). CONCLUSION:Most trial pairs found to be discrepant empirically were judged to be equally biased by assessors. We found moderate agreement between opinion and data-based evidence in pairs where assessors ranked one trial as more biased.

SUBMITTER: Turner RM 

PROVIDER: S-EPMC7482431 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Agreement was moderate between data-based and opinion-based assessments of biases affecting randomized trials within meta-analyses.

Turner Rebecca M RM   Rhodes Kirsty M KM   Jones Hayley E HE   Higgins Julian P T JPT   Haskins Jessica A JA   Whiting Penny F PF   Hróbjartsson Asbjørn A   Caldwell Deborah M DM   Morris Richard W RW   Reeves Barnaby C BC   Worthington Helen V HV   Boutron Isabelle I   Savović Jelena J  

Journal of clinical epidemiology 20200513


<h4>Background and objective</h4>Randomized trials included in meta-analyses are often affected by bias caused by methodological flaws or limitations, but the degree of bias is unknown. Two proposed methods adjust the trial results for bias using empirical evidence from published meta-epidemiological studies or expert opinion.<h4>Methods</h4>We investigated agreement between data-based and opinion-based approaches to assessing bias in each of four domains: sequence generation, allocation conceal  ...[more]

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