Supporting Reanalysis and Reuse of Clinical Trial Data: A Case Study

BackgroundReproducing 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, few real-world examples exist where independent teams have reproduced complex analyses using clinical trial data. In this case study, the aim was to independently reproduce the key findings of a high-impact clinical trial on rectal cancer treatment using shared trial data. MethodWe 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 analysis. We contacted the original investigators for data access and reuse, and consulted them to understand the study, clinically and scientifically. ResultsFive teams used R or Python to reproduce the statistical results, and the corresponding scripts can be found on Gitlab. All teams reproduced the analyses for primary outcome--disease-free survival (DFS). The key findings on DFS were consistently reproduced, reinforcing confidence in the trial main conclusions. Result robustness was investigated using a different analytical software or statistical models. Nevertheless, challenges were encountered when the supplementary materials were not easily identified. Minor reporting issues were noticed in the reproduced paper. ConclusionReproduction 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 clinical research transparency and challenges in data sharing for reproducibility.