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.
abstract: 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 prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease.
  
  
  
  Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone.
  
  
  
  50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·39-4·62, p<0·0001; reference model: 2·56, 1·85-3·53, p<0·0001). The new model was validated further on the ENTHUSE M1 cohort with similarly high performance (iAUC 0·768). Meta-analysis across all methods confirmed previously identified predictive clinical variables and revealed aspartate aminotransferase as an important, albeit previously under-reported, prognostic biomarker.
  
  
  
  Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.
  
  
  
  Sanofi US Services, Project Data Sphere.
authors.affiliation: Sage Bionetworks, Seattle, WA, USA.
authors.forename: Justin
authors.initials: J
authors.lastname: Guinney
authors.affiliation: Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA; Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA.
authors.forename: Tao
authors.initials: T
authors.lastname: Wang
authors.affiliation: Department of Mathematics and Statistics, University of Turku, Turku, Finland; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
authors.forename: Teemu D
authors.initials: TD
authors.lastname: Laajala
authors.affiliation: Department of Pharmacology and Computational Biosciences Program, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA.
authors.forename: Kimberly Kanigel
authors.initials: KK
authors.lastname: Winner
authors.affiliation: Sage Bionetworks, Seattle, WA, USA.
authors.forename: J Christopher
authors.initials: JC
authors.lastname: Bare
authors.affiliation: Sage Bionetworks, Seattle, WA, USA.
authors.forename: Elias Chaibub
authors.initials: EC
authors.lastname: Neto
authors.affiliation: Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
authors.forename: Suleiman A
authors.initials: SA
authors.lastname: Khan
authors.affiliation: Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
authors.forename: Gopal
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authors.lastname: Peddinti
authors.affiliation: Department of Information Technology, University of Turku, Turku, Finland.
authors.forename: Antti
authors.initials: A
authors.lastname: Airola
authors.affiliation: Department of Information Technology, University of Turku, Turku, Finland.
authors.forename: Tapio
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authors.lastname: Pahikkala
authors.affiliation: Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland; Department of Pathology (HUSLAB), Helsinki University Hospital, Helsinki, Finland.
authors.forename: Tuomas
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authors.lastname: Mirtti
authors.affiliation: Sage Bionetworks, Seattle, WA, USA.
authors.forename: Thomas
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authors.lastname: Yu
authors.affiliation: Sage Bionetworks, Seattle, WA, USA.
authors.forename: Brian M
authors.initials: BM
authors.lastname: Bot
authors.affiliation: Sanofi, Bridgewater, NJ, USA.
authors.forename: Liji
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authors.lastname: Shen
authors.affiliation: AstraZeneca, Gaithersburg, MD, USA.
authors.forename: Kald
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authors.lastname: Abdallah
authors.affiliation: Sage Bionetworks, Seattle, WA, USA.
authors.forename: Thea
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authors.lastname: Norman
authors.affiliation: Sage Bionetworks, Seattle, WA, USA.
authors.forename: Stephen
authors.initials: S
authors.lastname: Friend
authors.affiliation: IBM T J Watson Research Center, IBM, Yorktown Heights, NY, USA.
authors.forename: Gustavo
authors.initials: G
authors.lastname: Stolovitzky
authors.affiliation: Prostate Cancer Foundation, Santa Monica, CA, USA.
authors.forename: Howard
authors.initials: H
authors.lastname: Soule
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Sweeney
authors.affiliation: Genitourinary Medical Oncology Program, Division of Hematology and Oncology, University of California, San Francisco, CA, USA.
authors.forename: Charles J
authors.initials: CJ
authors.lastname: Ryan
authors.affiliation: Genitourinary Oncology Services, Department of Medicine, Sidney Kimmel Center for Prostate and Urologic Cancers, Memorial Sloan-Kettering Cancer Center and Weill Cornell Medical College, New York, NY, USA.
authors.forename: Howard I
authors.initials: HI
authors.lastname: Scher
authors.affiliation: Tulane Cancer Center, Tulane University, New Orleans, LA, USA.
authors.forename: Oliver
authors.initials: O
authors.lastname: Sartor
authors.affiliation: Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA; The Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA; Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA.
authors.forename: Yang
authors.initials: Y
authors.lastname: Xie
authors.affiliation: Department of Mathematics and Statistics, University of Turku, Turku, Finland; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
authors.forename: Tero
authors.initials: T
authors.lastname: Aittokallio
authors.affiliation: Sanofi, Bridgewater, NJ, USA.
authors.forename: Fang Liz
authors.initials: FL
authors.lastname: Zhou
authors.affiliation: Department of Pharmacology and Computational Biosciences Program, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA; University of Colorado Comprehensive Cancer Center, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA. Electronic address: james.costello@ucdenver.edu.
authors.forename: James C
authors.initials: JC
authors.lastname: Costello
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use*; D001499:Bayes Theorem; D063045:Crowdsourcing; D000077143:Docetaxel; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009367:Neoplasm Staging; D049451:Nomograms; D011241:Prednisone / Q000008:administration & dosage; D011379:Prognosis; D064129:Prostatic Neoplasms, Castration-Resistant / Q000188:drug therapy / Q000401:mortality* / Q000556:secondary; D015996:Survival Rate; D043823:Taxoids / Q000008:administration & dosage; D055815:Young Adult
chemical_list: D043823:Taxoids; D000077143:Docetaxel; D011241:Prednisone