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3. 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

Abdallah, Kald, Aittokallio, Tero, Airola, Antti, Anghe, Catalina, Azima, Helia, Baertsch, Robert, Ballester, Pedro J, Bare, Chris, Bhandari, Vinayak, Bot, Brian M, Dang, Cuong C, Dunbar, Maria Bekker-Nielsen, Buchardt, Ann-Sophie, Buturovic, Ljubomir, Cao, Da, Chalise, Prabhakar, Cho, Junwoo, Chu, Tzu-Ming, Coley, R Yates, Conjeti, Sailesh, Correia, Sara, Costello, James C, Dai, Ziwei, Dai, Junqiang, Dargatz, Philip, Delavarkhan, Sam, Deng, Detian, Dhanik, Ankur, Du, Yu, Elangovan, Aparna, Ellis, Shellie, Elo, Laura L, Espiritu, Shadrielle M, Fan, Fan, Farshi, Ashkan B, Freitas, Ana, Fridley, Brooke, Friend, Stephen, Fuchs, Christiane, Gofer, Eyal, Peddinti, Gopalacharyulu, Graw, Stefan, Greiner, Russ, Guan, Yuanfang, Guinney, Justin, Guo, Jing, Gupta, Pankaj, Guyer, Anna I, Han, Jiawei, Hansen, Niels R, Chang, Billy HW, Hirvonen, Outi, Huang, Barbara, Huang, Chao, Hwang, Jinseub, Ibrahim, Joseph G, Jayaswa, Vivek, Jeon, Jouhyun, Ji, Zhicheng, Juvvadi, Deekshith, Jyrkkiö, Sirkku, Kanigel-Winner, Kimberly, Katouzian, Amin, Kazanov, Marat D, Khan, Suleiman A, Khayyer, Shahin, Kim, Dalho, Golinska, Agnieszka K, Koestler, Devin, Kokowicz, Fernanda, Kondofersky, Ivan, Krautenbacher, Norbert, Krstajic, Damjan, Kumar, Luke, Kurz, Christoph, Kyan, Matthew, Laajala, Teemu D, Laimighofer, Michael, Lee, Eunjee, Lesinski, Wojciech, Li, Miaozhu, Li, Ye, Lian, Qiuyu, Liang, Xiaotao, Lim, Minseong, Lin, Henry, Lin, Xihui, Lu, Jing, Mahmoudian, Mehrad, Manshaei, Roozbeh, Meier, Richard, Miljkovic, Dejan, Mirtti, Tuomas, Mnich, Krzysztof, Navab, Nassir, Neto, Elias C, Newton, Yulia, Norman, Thea, Pahikkala, Tapio, Pal, Subhabrata, Park, Byeongju, Patel, Jaykumar, Pathak, Swetabh, Pattin, Alejandrina, Ankerst, Donna P, Peng, Jian, Petersen, Anne H, Philip, Robin, Piccolo, Stephen R, Pölsterl, Sebastian, Polewko-Klim, Aneta, Rao, Karthik, Ren, Xiang, Rocha, Miguel, Rudnicki, Witold R., Ryan, Charles J, Ryu, Hyunnam, Sartor, Oliver, Scherb, Hagen, Sehgal, Raghav, Seyednasrollah, Fatemeh, Shang, Jingbo, Shao, Bin, Shen, Liji, Sher, Howard, Shiga, Motoki, Sokolov, Artem, Söllner, Julia F, Song, Lei, Soule, Howard, Stolovitzky, Gustavo, Stuart, Josh, Sun, Ren, Sweeney, Christopher J, Tahmasebi, Nazanin, Tan, Kar-Tong, Tomaziu, Lisbeth, Usset, Joseph, Vang, Yeeleng S, Vega, Roberto, Vieira, Vitor, Wang, David, Wang, Difei, Wang, Junmei, Wang, Lichao, Wang, Sheng, Wang, Tao, Wang, Yue, Wolfinger, Russ, Wong, Chris, Wu, Zhenke, Xiao, Jinfeng, Xie, Xiaohui, Xie, Yang, Xin, Doris, Yang, Hojin, Yu, Nancy, Yu, Thomas, Yu, Xiang, Zahedi, Sulmaz, Zanin, Massimiliano, Zhang, Chihao, Zhang, Jingwen, Zhang, Shihua, Zhang, Yanchun, Zhou, Fang Liz, Zhu, Hongtu, Zhu, Shanfeng, Zhu, Yuxin, Winner, Kimberly Kanigel, Bare, J Christopher, Neto, Elias Chaibub, Peddinti, Gopal, and Scher, Howard I

Published
2017
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5. De-identifying data in clinical trials: an overview or patient de-identitication practices amid the increased push for sharing of clinical data

Author

Emam, Khaled El and Abdallah, Kald

Subjects
Disclosure of information, Clinical trials -- Information management -- Ethical aspects -- Laws, regulations and rules, General interest, Health, Health Insurance Portability and Accountability Act of 1996
Abstract

There is a recognition within the research community that the re-analysis of clinical trials data can provide new insights compared to the original publications. (1) In addition, the increasing complexity [...]

Published
2015

14. 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

Guinney, Justin, primary, Wang, Tao, additional, Laajala, Teemu D, additional, Winner, Kimberly Kanigel, additional, Bare, J Christopher, additional, Neto, Elias Chaibub, additional, Khan, Suleiman A, additional, Peddinti, Gopal, additional, Airola, Antti, additional, Pahikkala, Tapio, additional, Mirtti, Tuomas, additional, Yu, Thomas, additional, Bot, Brian M, additional, Shen, Liji, additional, Abdallah, Kald, additional, Norman, Thea, additional, Friend, Stephen, additional, Stolovitzky, Gustavo, additional, Soule, Howard, additional, Sweeney, Christopher J, additional, Ryan, Charles J, additional, Scher, Howard I, additional, Sartor, Oliver, additional, Xie, Yang, additional, Aittokallio, Tero, additional, Zhou, Fang Liz, additional, Costello, James C, additional, Anghe, Catalina, additional, Azima, Helia, additional, Baertsch, Robert, additional, Ballester, Pedro J, additional, Bare, Chris, additional, Bhandari, Vinayak, additional, Dang, Cuong C, additional, Dunbar, Maria Bekker-Nielsen, additional, Buchardt, Ann-Sophie, additional, Buturovic, Ljubomir, additional, Cao, Da, additional, Chalise, Prabhakar, additional, Cho, Junwoo, additional, Chu, Tzu-Ming, additional, Coley, R Yates, additional, Conjeti, Sailesh, additional, Correia, Sara, additional, Dai, Ziwei, additional, Dai, Junqiang, additional, Dargatz, Philip, additional, Delavarkhan, Sam, additional, Deng, Detian, additional, Dhanik, Ankur, additional, Du, Yu, additional, Elangovan, Aparna, additional, Ellis, Shellie, additional, Elo, Laura L, additional, Espiritu, Shadrielle M, additional, Fan, Fan, additional, Farshi, Ashkan B, additional, Freitas, Ana, additional, Fridley, Brooke, additional, Fuchs, Christiane, additional, Gofer, Eyal, additional, Peddinti, Gopalacharyulu, additional, Graw, Stefan, additional, Greiner, Russ, additional, Guan, Yuanfang, additional, Guinney, Justin, additional, Guo, Jing, additional, Gupta, Pankaj, additional, Guyer, Anna I, additional, Han, Jiawei, additional, Hansen, Niels R, additional, Chang, Billy HW, additional, Hirvonen, Outi, additional, Huang, Barbara, additional, Huang, Chao, additional, Hwang, Jinseub, additional, Ibrahim, Joseph G, additional, Jayaswa, Vivek, additional, Jeon, Jouhyun, additional, Ji, Zhicheng, additional, Juvvadi, Deekshith, additional, Jyrkkiö, Sirkku, additional, Kanigel-Winner, Kimberly, additional, Katouzian, Amin, additional, Kazanov, Marat D, additional, Khayyer, Shahin, additional, Kim, Dalho, additional, Golinska, Agnieszka K, additional, Koestler, Devin, additional, Kokowicz, Fernanda, additional, Kondofersky, Ivan, additional, Krautenbacher, Norbert, additional, Krstajic, Damjan, additional, Kumar, Luke, additional, Kurz, Christoph, additional, Kyan, Matthew, additional, Laimighofer, Michael, additional, Lee, Eunjee, additional, Lesinski, Wojciech, additional, Li, Miaozhu, additional, Li, Ye, additional, Lian, Qiuyu, additional, Liang, Xiaotao, additional, Lim, Minseong, additional, Lin, Henry, additional, Lin, Xihui, additional, Lu, Jing, additional, Mahmoudian, Mehrad, additional, Manshaei, Roozbeh, additional, Meier, Richard, additional, Miljkovic, Dejan, additional, Mnich, Krzysztof, additional, Navab, Nassir, additional, Neto, Elias C, additional, Newton, Yulia, additional, Pal, Subhabrata, additional, Park, Byeongju, additional, Patel, Jaykumar, additional, Pathak, Swetabh, additional, Pattin, Alejandrina, additional, Ankerst, Donna P, additional, Peng, Jian, additional, Petersen, Anne H, additional, Philip, Robin, additional, Piccolo, Stephen R, additional, Pölsterl, Sebastian, additional, Polewko-Klim, Aneta, additional, Rao, Karthik, additional, Ren, Xiang, additional, Rocha, Miguel, additional, Rudnicki, Witold R., additional, Ryu, Hyunnam, additional, Scherb, Hagen, additional, Sehgal, Raghav, additional, Seyednasrollah, Fatemeh, additional, Shang, Jingbo, additional, Shao, Bin, additional, Sher, Howard, additional, Shiga, Motoki, additional, Sokolov, Artem, additional, Söllner, Julia F, additional, Song, Lei, additional, Stuart, Josh, additional, Sun, Ren, additional, Tahmasebi, Nazanin, additional, Tan, Kar-Tong, additional, Tomaziu, Lisbeth, additional, Usset, Joseph, additional, Vang, Yeeleng S, additional, Vega, Roberto, additional, Vieira, Vitor, additional, Wang, David, additional, Wang, Difei, additional, Wang, Junmei, additional, Wang, Lichao, additional, Wang, Sheng, additional, Wang, Yue, additional, Wolfinger, Russ, additional, Wong, Chris, additional, Wu, Zhenke, additional, Xiao, Jinfeng, additional, Xie, Xiaohui, additional, Xin, Doris, additional, Yang, Hojin, additional, Yu, Nancy, additional, Yu, Xiang, additional, Zahedi, Sulmaz, additional, Zanin, Massimiliano, additional, Zhang, Chihao, additional, Zhang, Jingwen, additional, Zhang, Shihua, additional, Zhang, Yanchun, additional, Zhu, Hongtu, additional, Zhu, Shanfeng, additional, and Zhu, Yuxin, additional

Published
2017
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15. Use of crowdsourced research to develop a prognostic model for first-line metastatic castrate resistant prostate cancer (mCRPC).

Author

Zhou, Fang Liz, primary, Guinney, Justin, additional, Wang, Tao, additional, Bare, J. Christopher, additional, Norman, Thea C, additional, Bot, Brian, additional, Shen, Liji, additional, Winner, Kimberly Kanigel, additional, Friend, Stephen Henry, additional, Abdallah, Kald, additional, Stolovitzky, Gustavo A., additional, Xie, Yang, additional, and Costello, James, additional

Published
2016
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16. Abstract B204: A DREAM Challenge to improve prognostic models in patients with metastatic castrate-resistant prostate cancer

Author

Guinney, Justin, primary, Wang, Tao, additional, Bare, Chris, additional, Norman, Thea, additional, Bot, Brian, additional, Shen, Liji, additional, Winner, Kimberly, additional, Friend, Stephen, additional, Abdallah, Kald, additional, Stolovitzky, Gustavo, additional, Xie, Yang, additional, Zhou, Fang Liz, additional, and Costello, James C., additional

Published
2015
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20. Building a crowd-sourced challenge using clinical trial data.

Author

Zhou, Fang Liz, primary, Guinney, Justin, additional, Abdallah, Kald, additional, Norman, Thea C, additional, Bot, Brian, additional, Costello, James, additional, Shen, Liji, additional, Wang, Tao, additional, Xie, Yang, additional, and Stolovitzky, Gustavo A., additional

Published
2015
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23. A DREAM Challenge to Build Prediction Models for Short-Term Discontinuation of Docetaxel in Metastatic Castration- Resistant Prostate Cancer.

Author

Seyednasrollah, Fatemeh, Koestler, Devin C., Tao Wang, Piccolo, Stephen R., Vega, Roberto, Greiner, Russell, Fuchs, Christiane, Gofer, Eyal, Kumar, Luke, Wolfinger, Russell D., Winner, Kimberly Kanigel, Bare, Chris, Chaibub Neto, Elias, Yu, Thomas, Liji Shen, Abdallah, Kald, Norman, Thea, Stolovitzky, Gustavo, Soule, Howard R., and Sweeney, Christopher J.

Subjects
PREDICTION models, DOCETAXEL, CASTRATION-resistant prostate cancer, PROSTATE cancer patients, DRUG toxicity, CLINICAL trials, CANCER treatment
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-linemCRPCwere 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 adverse treatment 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. A postchallenge 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. [ABSTRACT FROM AUTHOR]

Published
2017
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26. De-identifying Data in Clinical Trials.

Author

El Emam, Khaled and Abdallah, Kald

Subjects
*CLINICAL trials, *DRUG laws, *PERSONALLY identifiable information, *PHARMACEUTICAL industry
Abstract

The article discusses patient de-identification practices related to clinical trials, citing challenges like sharing of clinical data, as of August 2015. Topics include a policy of the European Medicines Agency regarding clinical study reports for drugs that receives approval for marketing; data sharing models for companies undertaking clinical trials; risk associated with de-identification of data like filing complaint by participants of the trials; and personal information in the data.

Published
2015

28. Phase I/II trial of DNA-HSP65 immunotherapy for advanced squamous cell carcinoma of the head and neck: Toxicity and response

Author

Michaluart, Pedro, Abdallah, Kald, Lima, Fanny D., Smith, Rodney B., Moyses, Raquel A., Coelho, Veronica, Victora, Gabriel D., Socorro-Silva, Adalberto, Volsi, Evelyn C., Kalil, Jorge, Carlos Zárate-Bladés, Ferraz, Alberto R., Barreto, Ana K., Chammas, Maria C., Gomes, Regina L., Gebrim, Eloisa, Lica, Arakawa-Sugueno, Fernandes, Kariane P., Lotufo, Paulo, Cardoso, Maria R., and Silvan, Celio L.

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