"Not only could a model like this help identify patients who might benefit more from a different treatment, it also has the potential to immediately impact future clinical trials by improving patient selection through the use of novel patient selection designs. In doing so, the number of patients needed for clinical trials could be reduced, making more efficient use of available resources," says Devin Koestler, PhD, assistant professor of Biostatistics at the University Kansas Medical Center, and one of the first authors of the paper.

The challenge was built to promote and capitalize on the potential of an open question paired with open data.


"The field is definitely moving toward a much more open sharing model of clinical trial data. This project is a great example of how you can gain new knowledge from existing data and how making clinical data open and freely accessible can maximize the use of these valuable data for the benefit of patients," says Laura Elo, PhD, one of the senior authors of the paper, adjunct professor in Biomathematics and research director in Computational Biomedicine and Bioinformatics at Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Finland.

The project was overseen as a collaborative effort between 16 institutions, led by academic research institutions including CU Cancer Center, open-data initiatives including Project Data Sphere, Sage Bionetworks, and the DREAM Challenges, and industry and research partners including Sanofi, AstraZeneca, and the Prostate Cancer Foundation.

Because only 10-20 percent of patients discontinue treatment due to adverse events, no single trial has enrolled enough patients to predict with statistical significance who would discontinue docetaxel - commonly, these trials tested the effectiveness of treatments in the population that was able to finish the regimen and were not designed to answer this secondary question of who would be unable to finish. Had clinical trial results remained firewalled by the academic or industry sponsors, this secondary question would have remained unanswered; however, the decision to open these clinical trial data allowed the current researchers to combine the numbers from four previous trials, pooling over 2,000 patients - enough to start identifying statistically significant patterns.

"The number of clinical trials in Project Data Sphere continue to grow. At the time of this study, there were about 10,000 patients in their database. Now there are over 70,000, meaning that we will be able to explore future questions with even greater accuracy and ask questions that have been unaddressable due to restricted data access," Costello says.

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