Structured template and reporting tool for real world evidence (STaRT-RWE) was developed by a team led by professor Shirley V Wang of Brigham and Women's Hospital, Harvard Medical School, which is to plan and report on the implementation of real world evidence (RWE) studies on the safety and efficacy of treatments. The template, published in the journal BMJ in January 2021, has been endorsed by the International Society of PharmacoEpidemiology and the Transparency Initiative promoted by the International Society of Pharmacoeconomics and Outcome Research. This article interprets its entries to promote the understanding and application of STaRT-RWE by domestic scholars engaged in real world study, and help to improve the transparency, repeatability, and accuracy of RWE research.
Objective To review the current application of sample size estimation in real-world studies (RWS), analyse parameter settings and commonly used methods, and provide methodological guidance for researchers conducting RWS. Methods First, ClinicalTrials.gov was searched to identify RWS with documented sample size calculations. Key information was extracted for descriptive analysis. Secondly, critical parameters and common estimation methods for RWS sample size calculations were systematically reviewed, and strategies were proposed for addressing common challenges. Finally, relevant international reporting standards were interpreted. Results The literature review included 44 clinical trials with a wide range of sample sizes (30 to 30 400 cases). While most studies detailed the sample size estimation process, the parameter settings were often incomplete and many failed to adequately consider the characteristics of real-world data. Therefore, we proposed key parameters for RWS sample size estimation, including effect size, significance level and statistical power. Researchers should also consider issues such as heterogeneity, confounding factors and data quality. This study clarified the essential elements of reporting sample size estimation. Conclusion Methodological guidance for real-world evidence sample size estimation is lacking. We advise researchers to standardise reporting procedures for sample size estimation in future studies and to set parameters reasonably based on research objectives, study design types and data characteristics. This will enhance the transparency and scientific rigour of real-world evidence.