The fragility index can be used for sample size calculations in clinical trials

Objective:The fragility index is a clinically interpretable metric increasingly used to interpret the robustness of clinical trials results that is generally not incorporated in sample size calculation and applied post-hoc. In this manuscript, we propose to base the sample size calculation on the fragility index in a way that supplements the classical prefixed alpha and power cutoffs and we provide a dedicated R software package for the design and analysis tools. Study design and setting: This approach follows from a novel hypothesis testing framework that is based on the fragility index and builds on the classical testing approach. As case studies, we re-analyse the design of two important trials in cardiovascular medicine, the FAME and FAMOUS-NSTEMI trials. Results: The analyses show that approach returns sample sizes which results in a higher power for the P value based test and most importantly a lower and context dependent Type I error rate for the fragility index based test compared to standard tests. Conclusion: Our method allows clinicians to control for the fragility index during clinical trial design. (C) 2021 Elsevier Inc. All rights reserved.

Automated summary

The fragility index, a clinically interpretable metric, is proposed as a supplement to traditional sample size calculations in clinical trial design. By using this approach, higher power and lower error rates can be achieved compared to standard tests.