The chemotherapy docetaxel is widely accepted as a standard therapy for metastatic castration-resistant prostate cancer. But 10-20 percent of patients will have adverse side effects that force discontinuation of treatment. These patients may have been better off with another treatment or alternative dosing of docetaxel in the first place, but who's to know before trying the drug which patients will go on to experience debilitating side effects? A crowdsourced competition asked this as an open question. Today in the Journal of Clinical Oncology Clinical Cancer Informatics, competition organizers and participating teams report their findings: Using open data from four previously conducted clinical trials, teams of international researchers designed mathematical models predicting the likelihood that a patient will discontinue docetaxel treatment due to adverse events. These results represent the first comprehensive effort to make such predictions based on patient clinical characteristics.

Specifically, the challenge was to connect any of 129 baseline clinical measurements to the chance of docetaxel discontinuation. In all, 34 international teams submitted 61 models. Seven of these teams submitted models with similarly high predictive ability and so technically "won" the challenge. The five clinical factors that were most predictive were measures of hemoglobin, alkaline phosphatase, aspartate aminotransferase, prostate specific antigen, and ECOG performance status. The seven successful models all integrated these five factors into various computational frameworks.

Interestingly, after the competition officially ended, these top seven teams decided to collaborate outside the framework of the competition, resulting in refinements that led to a combined model that was more predictive than any of the submissions alone.
"The seven groups from around the world -- Finland, Germany, Canada, Israel and the U.S. -- had never formally met before the challenge. It's a really exciting example of the power of scientific collaboration," says James Costello, PhD, senior author of the paper, investigator at the University of Colorado Cancer Center, assistant professor in the Department of Pharmacology at the CU School of Medicine, and director of Computational and Systems Biology Challenges within the Sage Bionetworks/DREAM organization.

The combined model stratified patients into groups with low and high risk of discontinuing docetaxel due to adverse events, with the high group having more than double the likelihood of discontinuation as the low group.

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