Supporting reanalysis and reuse of clinical trial data: a case study

Reproducing published findings from clinical trials is a critical component of scientific transparency, yet it remains a challenging and under-practiced task. Despite increasing emphasis on reproducibility and data reuse in research policies, only few real-world examples exist where several teams have reproduced complex analyses using clinical trial data. In this case study, the aim was to reproduce the key findings of a high-impact clinical trial on rectal cancer treatment using shared trial data.

We organized a multi-team datathon, where each team was provided with the same dataset and supporting material, and was tasked to reproduce the results of the CAO/ARO/AIO-04 trial, with optional additional analyses. We contacted the original investigators for access and reuse of the data, as well as information on the clinical and scientific aspects of the study.

Five teams used R or Python to reproduce the statistical results, and the corresponding scripts can be found on Gitlab. The key findings on disease-free survival (DFS) were consistently reproduced by most teams, reinforcing confidence in the main trial conclusions. Result robustness was investigated using different analytical software or statistical models. Some challenges were encountered because supplementary material of the original study was not easily found. Minor reporting issues were also identified in the reproduced paper.

Reproduction of a major oncology clinical trial confirmed the reliability of its main conclusions. Divergences highlighted reporting gaps-such as incomplete protocols and broken links-that future trials should address. This case study demonstrates the value of systematic reproducibility checks for the transparency of clinical research and the challenges in data sharing for reproducibility.