Sample size estimation in clinical trials using ventilator-free days as the primary outcome: a systematic review

Abstract

Abstract Background Ventilator-free days (VFDs) are a composite endpoint increasingly used as the primary outcome in critical care trials. However, because of the skewed distribution and competitive risk between components, sample size estimation remains challenging. This systematic review was conducted to systematically assess whether the sample size was congruent, as calculated to evaluate VFDs in trials, with VFDs’ distribution and the impact of alternative methods on sample size estimation. Methods A systematic literature search was conducted within the PubMed and Embase databases for randomized clinical trials in adults with VFDs as the primary outcome until December 2021. We focused on peer-reviewed journals with 2021 impact factors greater than five. After reviewing definitions of VFDs, we extracted the sample size and methods used for its estimation. The data were collected by two independent investigators and recorded in a standardized, pilot-tested forms tool. Sample sizes were calculated using alternative statistical approaches, and risks of bias were assessed with the Cochrane risk-of-bias tool. Results Of the 26 clinical trials included, 19 (73%) raised “some concerns” when assessing risks of bias. Twenty-four (92%) trials were two-arm superiority trials, and 23 (89%) were conducted at multiple sites. Almost all the trials (96%) were unable to consider the unique distribution of VFDs and death as a competitive risk. Moreover, significant heterogeneity was found in the definitions of VFDs, especially regarding varying start time and type of respiratory support. Methods for sample size estimation were also heterogeneous, and simple models, such as the Mann–Whitney–Wilcoxon rank-sum test, were used in 14 (54%) trials. Finally, the sample sizes calculated varied by a factor of 1.6 to 17.4. Conclusions A standardized definition and methodology for VFDs, including the use of a core outcome set, seems to be required. Indeed, this could facilitate the interpretation of findings in clinical trials, as well as their construction, especially the sample size estimation which is a trade-off between cost, ethics, and statistical power. Systematic review registration PROSPERO ID: CRD42021282304. Registered 15 December 2021 (https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021282304).