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

Journal

Book Volume: 2017

Pages Range: 1-15

Journal Issue: 1

DOI: 10.1200/CCI.17.00018

Abstract

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

How to cite

APA:

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

MLA:

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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