title: Statistical Methods for Establishing Personalized Treatment Rules in Oncology.
abstract: The process for using statistical inference to establish personalized treatment strategies requires specific techniques for data-analysis that optimize the combination of competing therapies with candidate genetic features and characteristics of the patient and disease. A wide variety of methods have been developed. However, heretofore the usefulness of these recent advances has not been fully recognized by the oncology community, and the scope of their applications has not been summarized. In this paper, we provide an overview of statistical methods for establishing optimal treatment rules for personalized medicine and discuss specific examples in various medical contexts with oncology as an emphasis. We also point the reader to statistical software for implementation of the methods when available.
authors.affiliation: Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Unit 1411, 1400 Pressler Street, Houston, TX 77030, USA.
authors.forename: Junsheng
authors.initials: J
authors.lastname: Ma
authors.affiliation: Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Unit 1411, 1400 Pressler Street, Houston, TX 77030, USA.
authors.forename: Brian P
authors.initials: BP
authors.lastname: Hobbs
authors.affiliation: Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Unit 1411, 1400 Pressler Street, Houston, TX 77030, USA.
authors.forename: Francesco C
authors.initials: FC
authors.lastname: Stingo
mesh_terms: D006801:Humans; D008495:Medical Oncology / Q000706:statistics & numerical data*; D009369:Neoplasms / Q000188:drug therapy / Q000453:epidemiology / Q000235:genetics; D010597:Pharmacogenetics / Q000706:statistics & numerical data*; D057285:Precision Medicine / Q000706:statistics & numerical data*