Improving clinical trial interpretation with ACCEPT analyses
Abstract
Effective decision making from randomised controlled clinical trials relies on robust interpretation of the numerical results. However, the language we use to describe clinical trials can cause confusion both in trial design and in comparing results across trials. ACceptability Curve Estimation using Probability Above Threshold (ACCEPT) aids comparison between trials (even where of different designs) by harmonising reporting of results, acknowledging different interpretations of the results may be valid in different situations, and moving the focus from comparison to a pre-specified value to interpretation of the trial data. ACCEPT can be applied to historical trials or incorporated into statistical analysis plans for future analyses. An online tool enables ACCEPT on up to three trials simultaneously.
Cite
@article{arxiv.2203.11164,
title = {Improving clinical trial interpretation with ACCEPT analyses},
author = {Michelle N. Clements and Ian R. White and Andrew J. Copas and Victoria Cornelius and Suzie Cro and David T Dunn and Matteo Quartagno and Rebecca M. Turner and Conor D. Tweed and A. Sarah Walker},
journal= {arXiv preprint arXiv:2203.11164},
year = {2022}
}