Novel Use of Patient-Specific Covariates From Oncology Studies in the Era of Biomedical Data Science: A Review of Latest Methodologies. Issue 30 (20th October 2022)

• Record Type: Journal Article
• Authors: Xu, Ronghui; Chen, Guanhua; Connor, Michael; Murphy, James
• Is Part Of: Journal of clinical oncology. Volume 40:Issue 30(2022)
• Page Start: 3546
• Page End: 3553
• Publication Date: 2022-10-20
• Subjects: Oncology -- Periodicals; Cancer -- Periodicals; Oncology; Medical Oncology; Cancérologie -- Périodiques; Cancer -- Périodiques; Cancérologie; Cancer; Oncology; Oncologia; Càncer; Periodicals; 616.994
• DOI: 10.1200/JCO.21.01957
• Languages: English
• ISSNs: 0732-183X

Abstract

Abstract : In this article, we review different applications of how to incorporate individual patient variables into clinical research within oncology. These methodologies range from the more traditional use of baseline covariates from randomized clinical trials, as well as observational studies, to using covariates to generalize the results of randomized clinical trials to other populations. Individual patient variables also allow for the consideration of heterogeneity in treatment effects and individualized treatment rules. We primarily consider two treatment groups and mostly focus on time-to-event outcomes where such methodologies have been well established and widely applied. We also discuss more conceptually newer statistical research that has not been widely applied in clinical oncology, but is likely to make an impact in future oncology research. With the increasing amount of biomedical data available for analysis, it is inevitable that more methods are developed to make best use of information, to advance oncology research.