Statistical Methods for Establishing Personalized Treatment Rules in Oncology
作者： Junsheng Ma , Brian P. Hobbs , Francesco C. Stingo
DOI: 10.1155/2015/670691
关键词: Variety (cybernetics) 、 MEDLINE 、 Statistical inference 、 Oncology 、 Point (typography) 、 Scope (project management) 、 Medicine 、 Precision medicine 、 Personalized medicine 、 Process (engineering) 、 Internal medicine
摘要: The process for using statistical inference to establish personalized treatment strategies requires specific techniques data-analysis that optimize the combination of competing therapies with candidate genetic features and characteristics patient disease. A wide variety methods have been developed. However, heretofore usefulness these recent advances has not fully recognized by oncology community, scope their applications summarized. In this paper, we provide an overview establishing optimal rules medicine discuss examples in various medical contexts as emphasis. We also point reader software implementation when available.
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James M. Robins, Optimal Structural Nested Models for Optimal Sequential Decisions Springer, New York, NY. pp. 189- 326 ,(2004) , 10.1007/978-1-4419-9076-1_11
Margaret Pepe, Marshall D Brown, Ying Huang, Holly Janes, Statistical Methods for Evaluating and Comparing Biomarkers for Patient Treatment Selection ,(2013)
Junlong Li, Lihui Zhao, Lu Tian, Tianxi Cai, Brian Claggett, Andrea Callegaro, Benjamin Dizier, Bart Spiessens, Fernando Ulloa-Montoya, Lee-Jen Wei, A predictive enrichment procedure to identify potential responders to a new therapy for randomized, comparative controlled clinical studies Biometrics. ,vol. 72, pp. 877- 887 ,(2016) , 10.1111/BIOM.12461
Matthew Wiener, Andy Liaw, Classification and Regression by randomForest ,(2007)
Chaeryon Kang, Holly Janes, Ying Huang, Rejoinder: Combining biomarkers to optimize patient treatment recommendations Biometrics. ,vol. 70, pp. 719- 720 ,(2014) , 10.1111/BIOM.12192
Richard A Olshen, Charles J Stone, Leo Breiman, Jerome H Friedman, Classification and regression trees ,(1983)
Adam Kapelner, Zachary D. Cohen, Justin Bleich, Richard Berk, Robert J. DeRubeis, Inference for Treatment Regime Models in Personalized Medicine arXiv: Methodology. ,(2014)
Ron Kohavi, A study of cross-validation and bootstrap for accuracy estimation and model selection international joint conference on artificial intelligence. ,vol. 2, pp. 1137- 1143 ,(1995)
Baqun Zhang, Anastasios A. Tsiatis, Marie Davidian, Min Zhang, Eric Laber, Estimating optimal treatment regimes from a classification perspective Stat. ,vol. 1, pp. 103- 114 ,(2012) , 10.1002/STA.411
Chaeryon Kang, Holly Janes, Ying Huang, Combining biomarkers to optimize patient treatment recommendations. Biometrics. ,vol. 70, pp. 695- 707 ,(2014) , 10.1111/BIOM.12191