A DREAM challenge to build prediction models for short-term discontinuation of docetaxel in metastatic castration- resistant prostate cancer

Seyednasrollah F, Wang T, Piccolo SR, Vega R, Greiner R, Fuchs C, Gofer E, Kumar L, Winner KK, Yu T, Shen L, Stolovitzky G, Soule HR, Sweeney CJ, Ryan CJ, Scher HI, Sartor O, Elo LL, Zhou FL, Costello JC, Abdallah K, Airola A, Aittokallio T, Anghel C, Ankerst DP, Azima H, Baertsch R, Ballester PJ, Bare C, Bhandari V, Bot BM, Buchardt AS, Buturovic L, Cao D, Chalise P, Chang BH, Cho J, Chu TM, Yates Coley R, Conjeti S, Correia S, Dai Z, Dai J, Dang CC, Dargatz P, Delavarkhan S, Deng D, Dhanik A, Du Y, Elangovan A, Ellis S, Espiritu SM, Fan F, Farshi AB, Freitas A, Fridley B, Golińska AK, Graw S, Greiner R, Guinney J, Guo J, Gupta P, Guyer AI, Han J, Hansen NR, Hirvonen O, Huang B, Huang C, Hwang J, Ibrahim JG, Jayaswal V, Jeon J, Ji Z, Juvvadi D, Jyrkkiö S, Kanigel-Winner K, Katouzian A, Kazanov MD, Khan SA, Khayyer S, Kim D, Koestler D, Kokowicz F, Kondofersky I, Krstajic D, Persona C, Kurz C, Kyan M, Laajala TD, Laimighofer M, Lee E, Lesiński W, Li M, Li Y, Lian Q, Liang X, Lim M, Lin H, Lin X, Lu J, Mahmoudian M, Manshaei R, Meier R, Miljkovic D, Mirtti T, Mnich K, Navab N, Neto EC, Newton Y, Norman T, Pahikkala T, Pal S, Park B, Patel J, Pathak S, Pattin A, Peddinti G, Peng J, Petersen AH, Philip R, Pölsterl S, Polewko-Klim A, Rao K, Ren X, Rocha M, Rudnicki WR, Ryu H, Scherb H, Sehgal R, Nasrollah FS, Shang J, Shao B, Sher H, Shiga M, Sokolov A, Söllner JF, Song L, Soule H, Stuart J, Sun R, Tahmasebi N, Tan KT, Tomaziu L, Usset J, Vang YS, Vieira V, Wang D, Wang D, Wang J, Wang L, Wang S, Wang Y, Wolfinger R, Wong C, Wu Z, Xiao J, Xie X, Xin D, Yang H, Yu N, Yu X, Zahedi S, Zanin M, Zhang C, Zhang J, Zhang S, Zhang Y, Zhu H, Zhu S, Zhu Y (2017)

Publication Type: Journal article

Publication year: 2017


Book Volume: 2017

Pages Range: 1-15

Journal Issue: 1

DOI: 10.1200/CCI.17.00018


Purpose Docetaxel has a demonstrated survival benefit for patients with metastatic castration-resistant prostate cancer (mCRPC); however, 10% to 20% of patients discontinue docetaxel prematurely because of toxicity-induced adverse events, and the management of risk factors for toxicity remains a challenge. Patients and Methods The comparator arms of four phase III clinical trials in first-linem CRPC were collected, annotated, and compiled, with a total of 2,070 patients. Early discontinuation was defined as treatment stoppage within 3 months as a result of adversetreatment effects; 10% of patients discontinued treatment. We designed an open-data, crowd-sourced DREAM Challenge for developing models with which to predict early discontinuation of docetaxel treatment. Clinical features for all four trials and outcomes for three of the four trials were made publicly available, with the outcomes of the fourth trial held back for unbiased model evaluation. Challenge participants from around the world trained models and submitted their predictions. Area under the precision-recall curve was the primary metric used for performance assessment. Results In total, 34 separate teams submitted predictions. Seven models with statistically similar area under precision-recall curves (Bayes factor≤3) outperformed all other models. Apostchallenge analysis of risk prediction using these seven models revealed three patient subgroups: high risk, low risk, or discordant risk. Early discontinuation events were two times higher in the high-risk subgroup compared with the low-risk subgroup. Simulation studies demonstrated that use of patient discontinuation prediction models could reduce patient enrollment in clinical trials without the loss of statistical power. Conclusion This work represents a successful collaboration between 34international teams that leveraged open clinical trial data. Our results demonstrate that routinely collected clinical features can be used to identify patients with mCRPC who are likely to discontinue treatment because of adverse events and establishes a robust benchmark with implications for clinical trial design.

Involved external institutions

Turku Bioscience FI Finland (FI) University of Texas Southwestern Medical Center (UT Southwestern) US United States (USA) (US) Brigham Young University US United States (USA) (US) Sanofi-Aventis Groupe FR France (FR) IBM Thomas J. Watson Research Center US United States (USA) (US) Prostate Cancer Foundation (PCF) US United States (USA) (US) Veterans Affairs Healthcare System Boston and Harvard Medical School US United States (USA) (US) University of California San Francisco (UCSF) US United States (USA) (US) Tulane University US United States (USA) (US) University of Alberta CA Canada (CA) Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (HMGU) / Helmholtz Munich DE Germany (DE) Hebrew University of Jerusalem IL Israel (IL) University of Colorado Anschutz Medical Campus US United States (USA) (US) Sage Bionetworks US United States (USA) (US) Memorial Sloan Kettering Cancer Center US United States (USA) (US) Toronto Metropolitan University / Ryerson University CA Canada (CA) Regeneron Pharmaceuticals, Inc. US United States (USA) (US) University of Copenhagen DK Denmark (DK) The University of Melbourne AU Australia (AU) Ontario Institute for Cancer Research CA Canada (CA) Johns Hopkins University (JHU) US United States (USA) (US) Jeevomics Private Limited IN India (IN) Turku University Hospital / Turun yliopistollinen keskussairaala (TYKS) FI Finland (FI) Kyungpook National University KR Korea, Republic of (KR) University of Kansas Medical Center US United States (USA) (US) Federal University of Santa Catarina / Universidade Federal de Santa Catarina (UFSC) BR Brazil (BR) Technische Universität München (TUM) DE Germany (DE) York University CA Canada (CA) University of North Carolina at Chapel Hill US United States (USA) (US) Duke University US United States (USA) (US) Fudan University / 复旦大学 CN China (CN) Tsinghua University CN China (CN) University of Illinois at Urbana-Champaign US United States (USA) (US) University of Michigan US United States (USA) (US) Åbo Akademi University FI Finland (FI) Helsingin yliopisto / University of Helsinki FI Finland (FI) National University of Singapore (NUS) SG Singapore (SG) University of California Irvine US United States (USA) (US) Universidade do Minho PT Portugal (PT) Georgetown University Medical Center (GUMC) US United States (USA) (US) University of Cambridge GB United Kingdom (GB) University of California Santa Cruz US United States (USA) (US) University of Pennsylvania US United States (USA) (US) The Chinese University of Hong Kong (CUHK) CN China (CN) SAS Institute US United States (USA) (US) Peking University (PKU) / 北京大学 CN China (CN) CRCM Centre de Recherche en Cancérologie de Marseille FR France (FR) Johannes Wesling Klinikum Minden DE Germany (DE) University of Białystok PL Poland (PL) Alberta Machine Intelligence Institute (Amii) CA Canada (CA) Daegu University / 대구대학교 KR Korea, Republic of (KR) Bristol-Myers Squibb US United States (USA) (US) Institute for Information Transmission Problems of Russian Academy of Sciences (Kharkevich Institute, IITP RAS) / Институт проблем передачи информации имени А. А. Харкевича (ИППИ) РАН RU Russian Federation (RU) Gifu University / 岐阜大学 JP Japan (JP) National Cancer Institute (NCI) US United States (USA) (US) University of Toronto CA Canada (CA) The Innaxis Foundation and Research Institute ES Spain (ES) National Center for Mathematics and Interdisciplinary Sciences (NCMIS) / 中国科学院国家数学与交叉科学中心 CN China (CN)

How to cite


Seyednasrollah, F., Wang, T., Piccolo, S.R., Vega, R., Greiner, R., Fuchs, C.,... Zhu, Y. (2017). A DREAM challenge to build prediction models for short-term discontinuation of docetaxel in metastatic castration- resistant prostate cancer. JCO Clinical Cancer Informatics, 2017(1), 1-15. https://doi.org/10.1200/CCI.17.00018


Seyednasrollah, Fatemeh, et al. "A DREAM challenge to build prediction models for short-term discontinuation of docetaxel in metastatic castration- resistant prostate cancer." JCO Clinical Cancer Informatics 2017.1 (2017): 1-15.

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