James Costello
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Crowdsourcing a Better Prostate Cancer Prediction Tool
Knowing the likely course of cancer can influence treatment decisions. Now a new prediction model published today in Lancet Oncology offers a more accurate prognosis for a patient's metastatic castration-resistant prostate cancer. The approach was as novel as the result - while researchers commonly work in small groups, intentionally isolating their data, the current study embraces the call in Joe Biden's "Cancer Moonshot" to open their question and their data, collecting previously published clinical trial data and calling for worldwide collaboration to evaluate its predictive power...
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Research Symbiosis Makes Mathematical Crystal Ball to Gaze into Future of Prostate Cancer Treatment
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 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...
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Winners Announced for Crowdsourcing and Data Sharing Competition to Drive Innovation in Prostate Cancer Research
Industry leaders in biomedical research, oncology data sharing and computational science announced the winners of an innovative research challenge for prostate cancer using previously unavailable clinical data. The Prostate Cancer DREAM Challenge is the first research challenge in prostate cancer to marry crowdsourcing with data sharing, paving a new way to tackle key research questions about metastatic castration-resistant prostate cancer (mCRPC), an advanced form of the disease with poor outcomes. The Challenge called upon the cancer research and computational biology community to find solutions to key open clinical research questions about mCRPC and explore innovative research and modeling approaches. The three specific questions posed were to:
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