Author(s):
Guinney, Justin ; Wang, Tao ; Laajala, Teemu D. ; Winner, Kimberly Kanigel ; Bare, J. Christopher ; Neto, Elias Chaibub ; Khan, Suleiman A. ; Peddinti, Gopal ; Airola, Antti ; Pahikkala, Tapio ; Mirtti, Tuomas ; Pathak, Swetabh ; Pattin, Alexandrina ; Ankerst, Donna P. ; Jian Peng ; Petersen, Anne H. ; Bot, Brian M. ; Philip, Robin ; Piccolo, Stephen R. ; Pölsterl, Sebastian ; Polewko-Klim, Aneta ; Azima, Helia ; Rao, Karthik ; Xiang Ren ; Rocha, Miguel ; Rudnicki, Witold R. ; Ryu, Hyunnam ; Scherb, Hagen ; Shen, Liji ; Sehgal, Raghav ; Seyednasrollah, Fatemeh ; Jingbo Shang ; Baertsch, Robert ; Bin Shao ; Sher, Howard ; Shiga, Motoki ; Sokolov, Artem ; Söllner, Julia F. ; Lei Song ; Stuart, Josh ; Abdallah, Kald ; Sun, Ren ; Sweeney, Christopher J. ; Ballester, Pedro J. ; Tahmasebi, Nazanin ; Kar-Tong Tan ; Tomaziu, Lisbeth ; Usset, Joseph ; Yeeleng S Vang ; Vega, Roberto ; Vieira, Vítor ; Wang, David ; Norman, Thea ; Difei Wang ; Bare, Chris ; Junmei Wang ; Lichao Wang ; Sheng Wang ; Yue Wang ; Wolfinger, Russ ; Chris Wong ; Zhenke Wu ; Jinfeng Xiao ; Xiaohui Xie ; Friend, Stephen ; Bhandari,Vinayak ; Doris Xin ; Hojin Yang ; Nancy Yu ; Xiang Yu ; Zahedi, Sulmaz ; Zanin, Massimiliano ; Chihao Zhang ; Jingwen Zhang ; Shihua Zhang ; Yanchun Zhang ; Dang,Cuong C. ; Stolovitzky, Gustavo ; Zhu, Hongtu ; Zhu, Shanfeng ; Zhu, Yuxin ; Soule, Howard ; Ryan, Charles J. ; Scher, Howard I. ; Sartor, Oliver ; Xie, Yang ; Aittokallio, Tero ; Dunbar, Maria Bekker-Nielsen ; Fang Liz Zhou ; Costello, James C. ; Anghel, Catalina ; Buchardt, Ann-Sophie ; Buturovic, Ljubomir ; Cao, Da ; Minseong Lim ; Chalise, Prabhakar ; Junwoo Cho ; Tzu-Ming Chu ; Coley, R. Yates ; Conjeti, Sailesh ; Correia, S. ; Dai, Ziwei ; Dai, Junqiang ; Dargatz, Philip ; Delavarkhan, Sam ; Henry Lin ; Deng, Detian ; Dhanik, Ankur ; Yu Du ; Elangovan, Aparna ; Ellis, Shellie ; Elo, Laura L. ; Espiritu, Shadrielle M. ; Fan, Fan ; Farshi, Ashkan B. ; Freitas, Ana Alão ; Xihui Lin ; Fridley, Brooke ; Fuchs, Christiane ; Gofer, Eyal ; Peddinti, Gopalacharyulu ; Graw, Stefan ; Greiner, Russ ; Yuanfang Guan ; Jing Guo ; Gupta, Pankaj ; Guyer, Anna I. ; Jing Lu ; Han, Jiawei ; Hansen, Niels R. ; Chang, Billy H. W. ; Hirvonen, Outi ; Huang, Barbara ; Chao Huang ; Jinseub Hwang ; Ibrahim, Joseph G. ; Jayaswal, Vivek ; Jeon, Jouhyun ; Mahmoudian, Mehrad ; Zhicheng Ji, ; Juvvadi, Deekshith ; Jyrkkiö, Sirkku ; Katouzian, Amin ; Kazanov, Marat D. ; Khayyer, Shahin ; Kim, Dalho ; Golinska, Agnieszka K. ; Koestler, Devin ; Pilatti, F. ; Manshaei, Roozbeh ; Kondofersky, Ivan ; Krautenbacher, Norbert ; Krstajic, Damjan ; Kumar, Luke ; Kurz, Christoph ; Kyan, Matthew ; Laimighofer, Michael ; Lee, Eunjee ; Lesinski, Wojciech ; Miaozhu Li ; Meier, Richard ; Ye Li ; Qiuyu Lian ; Xiaotao Liang ; Miljkovic, Dejan ; Mnich, Krzysztof ; Navab, Nassir ; Yu, Thomas ; Neto, Elias C. ; Newton, Yulia ; Pal, Subhabrata ; Park, Byeongju ; Patel, Jaykumar
Date: 2017
Persistent ID: https://hdl.handle.net/1822/44342
Origin: RepositóriUM - Universidade do Minho
Project/scholarship:
info:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F80925%2F2011/PT;
info:eu-repo/grantAgreement/EC/FP7/259294/EU;
Subject(s): Science & Technology
Description
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 prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods 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 interestnamely, 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 trialENTHUSE M1in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 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 2·394·62, p<0·0001; reference model: 2·56, 1·853·53, 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. Interpretation 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.
European Union within the ERC grant LatentCauses supported the work of C.F and I.K. German Research Foundation (DFG) within the Collaborative Research Centre 1243, subproject A17 awarded to C.F. German Federal Ministry of Education and Research (BMBF) through the Research Consortium e:AtheroMED (Systems medicine of myocardial infarction and stroke) under the auspices of the e:Med Programme (grant # 01ZX1313C) supported the work of D.P.A., P.D., C.F., C.K., I.K., N.K., M.L., H.S. and J.F.S. at the Institute of Computational Biology. NIH Grants RR025747-01, MH086633 and 1UL1TR001111, and NSF Grants SES-1357666, DMS-14-07655 and BCS0826844 supported the work of C.H., J.I., E.L., Y.W., H.Y., H.Z. and J.Z. NSFC Grant Nos. 61332013, 61572139 supported the work of X.L, Y.L, Y.Z., and S.Z. National Natural Science Foundation of China grants [Nos. 61422309, 61379092] was awarded to S.Z. The Patrick C. Walsh Prostate Research Fund and the Johns Hopkins Individualized Health Initiative supported the work of R.Y.C., D.D., Y.D., Z.J., K.R., Z.W. and Y.Z. FCT Ph.D. Grant SFRH/BD/80925/2011 was awarded to S.C. Clinical Persona Inc., East Palo Alto, CA supported the work of L.B. and D.K. The Finnish Cultural Foundation and the Drug Research Doctoral Programme (DRDP) at the University of Turku supported T.D.L. The National Research Foundation Singapore and the Singapore Ministry of Education, under its Research Centres of Excellence initiative, supported the work of J.G. and K.T. A grant from the Russian Science Foundation 14-24-00155 was awarded to M.D.K. A*MIDEX grant (no. ANR-11-IDEX-0001-02) was awarded to P.J.B. NSERC supported the work of R.G. The Israeli Centers of Research Excellence (I-CORE) program (Center No. 4/11) supported the work of E.G. Academy of Finland (grants 292611, 269862, 272437, 279163, 295504), National Cancer Institute (16X064), and Cancer Society of Finland supported the work of T.A. Academy of Finland (grant 268531) supported the work of T.M
