Research Article: Observed intervention effects for mortality in randomised clinical trials: a methodological study protocol
Abstract:
Introduction It is essential to choose a realistic anticipated intervention effect when calculating a sample size for a randomised clinical trial. Unfortunately, anticipated intervention effects are often inflated, when compared with the ‘true’ intervention effects. This is documented for mortality in critical care trials. A similar pattern might exist across different medical specialties. This study aims to estimate the range of observed intervention effects for all-cause mortality in trials included in Cochrane Reviews, within each Cochrane Review Group. Methods and analysis We will include randomised clinical trials assessing all-cause mortality as an outcome. Trials will be identified from Cochrane Reviews published in the Cochrane Database of Systematic Reviews. Cochrane Reviews will be clustered according to the registered Cochrane Review Group (eg, Anaesthesia, Emergency and Critical Care) and the statistical analyses will be conducted for each Cochrane Review Group and overall. The median relative risk and IQR for all-cause mortality and the proportion of trials with a relative all-cause mortality risk within seven different ranges will be reported (relative risk below 0.70, 0.70–0.79, 0.80–0.89, 0.90–1.09, 1.10–1.19, 1.20–1.30 and above 1.30). Subgroup analyses will explore the effects of original design, sample size, risk of bias, disease, intervention type, follow-up length, participating centres, funding type, information size and outcome hierarchy. Ethics and dissemination Since we will use summary data from trials already approved by relevant ethical committees, this study does not require ethical approval. Regardless of our findings, the results will be published in an international peer-reviewed journal.
Introduction:
Sample size and power estimations are pivotal elements when planning and designing randomised clinical trials. 1 2 To calculate a sample size, it is necessary to quantify an anticipated intervention effect. Large, anticipated intervention effects lead to relatively small sample sizes and small anticipated intervention effects lead to relatively large sample sizes. Different methods to estimate anticipated intervention effects are available, as described in the Difference ELicitation in TriAls reviews. 3 4…
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