The role of research ethics committees in addressing optimism in sample size
calculations: a meta-epidemiological study
#MMPMID41382158
Jansen MS
; Groenwold RHH
; Dekkers OM
Res Integr Peer Rev
2025[Dec]; 10
(1
): 26
PMID41382158
show ga
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.