The role of research ethics committees in addressing optimism in sample size calculations: a meta-epidemiological study

研究伦理委员会在解决样本量计算中的乐观倾向方面的作用:一项元流行病学研究

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Abstract

BACKGROUND: Sample size calculations are critical in clinical trial design, yet hypothesised effect sizes are often overly optimistic, leading to underpowered studies. Research ethics committees (RECs) assess trial protocols, including sample size justification, but their role in mitigating optimism bias in sample size calculations is not well studied. METHODS: We descriptively analysed 50 clinical trial protocols approved by a Dutch REC (2015-2018) with available primary outcome results. We examined REC comments on sample size calculations, protocol modifications during ethics review and amendments, and discrepancies between target and observed effect sizes. For comparability, effect sizes were standardised. RESULTS: Nine (18%) trials received REC comments on sample size calculations, mainly addressing calculation errors (n = 5), missing parameters (n = 2), or other methodological considerations (n = 3), with only three comments (6%) requesting effect size justification. Seven (14%) trials modified their sample size calculation during ethics review, mostly in response to REC comments, and 10 (20%) trials made modifications in amendments. In total, 40 (80%) trials overestimated their target effect size. Across all trials, the target effect size was overestimated by a median of 0.22 [IQR: 0.03 - 0.41]. Changes during ethics review led to less overestimation for only one trial, which reflected the correction of a calculation error rather than a reassessment of assumptions. CONCLUSIONS: Optimism in sample size calculations is common, but the influence of REC feedback on reducing overestimation appears limited. As this was a small, descriptive study from a single Dutch REC in 2015-2018, findings may not generalise to other settings or more recent practice. Future research should validate these findings and may help identify characteristics associated with overestimation, supporting RECs in recognising trials at risk of being underpowered.

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