Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.

@article{Guinney2017PredictionOO,
  title={Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.},
  author={Justin Guinney and Tao Wang and Teemu Daniel Laajala and Kimberly Kanigel Winner and J. Christopher Bare and Elias Chaibub Neto and Suleiman A. Khan and Gopal Peddinti and Antti Airola and Tapio Pahikkala and Tuomas Mirtti and Thomas Yu and Brian M. Bot and Liji Shen and Kald Abdallah and Thea C. Norman and Stephen H. Friend and Gustavo Stolovitzky and Howard R. Soule and Christopher J. Sweeney and Charles J. Ryan and Howard I. Scher and Oliver A Sartor and Yang Xie and Tero Aittokallio and Fang Liz Zhou and James C. Costello},
  journal={The Lancet. Oncology},
  year={2017},
  volume={18 1},
  pages={
          132-142
        }
}
BACKGROUND Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for… CONTINUE READING
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