Disparity between statistical and clinical significance in published randomised controlled trials indexed in PubMed: a protocol for a cross-sectional methodological survey.

Abstract

The commonly used frequentist paradigm of null hypothesis statistics testing with its reliance on the p-value and the corresponding notion of 'statistical significance' has been under ongoing criticism. Misinterpretation and misuse of the p-value have contributed to publication bias, unreliable studies, frequent false positives, fraud and mistrust in results of scientific studies. While p-values themselves are still useful, part of the problem may be the confusion between statistical and clinical significance. In randomised controlled trials of health interventions, this confusion could lead to erroneous conclusions about treatment efficacy, research waste and compromised patient outcomes. The extent to which clinical and statistical significance of published randomised clinical trials do not match is not known. This is a protocol for a methodological study to understand the extent of the problem of disparities between statistical and clinical significance in published clinical trials, and to identify and assess the factors associated with discrepant results in these studies. A methodological survey of published randomised controlled trials is planned. Trials published between 2018 and 2022 and their protocols will be searched and screened for inclusion, with a planned sample size of 500 studies. The reported minimum clinically important difference, the study effect size and confidence intervals will be used to assess clinical importance of trial results. Comparison of statistical significance and clinical importance of the trial results will be used to determine disparity. Data will be analysed to estimate the outcomes, and factors associated with disparate study results will be assessed using logistic regression analysis. Ethical approval for the study has been granted by Stellenbosch University's Health Research Ethics Committee. This is part of a larger study towards a PhD in Biostatistics and will be disseminated as a thesis, conference abstract and peer-reviewed manuscript.