title: A systematic selection method for the development of cancer staging systems.
abstract: The tumor-node-metastasis (TNM) staging system has been the anchor of cancer diagnosis, treatment, and prognosis for many years. For meaningful clinical use, an orderly, progressive condensation of the T and N categories into an overall staging system needs to be defined, usually with respect to a time-to-event outcome. This can be considered as a cutpoint selection problem for a censored response partitioned with respect to two ordered categorical covariates and their interaction. The aim is to select the best grouping of the TN categories. A novel bootstrap cutpoint/model selection method is proposed for this task by maximizing bootstrap estimates of the chosen statistical criteria. The criteria are based on prognostic ability including a landmark measure of the explained variation, the area under the receiver operating characteristic (ROC) curve, and a concordance probability generalized from Harrell's c-index. We illustrate the utility of our method by applying it to the staging of colorectal cancer.
authors.affiliation: Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA yunzhi@stat.wisc.edu.
authors.forename: Yunzhi
authors.initials: Y
authors.lastname: Lin
authors.affiliation: Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA.
authors.forename: Richard
authors.initials: R
authors.lastname: Chappell
authors.affiliation: Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.
authors.forename: Mithat
authors.initials: M
authors.lastname: Gönen
mesh_terms: D015179:Colorectal Neoplasms / Q000175:diagnosis*; D006801:Humans; D009367:Neoplasm Staging / Q000379:methods*; D011336:Probability; D011379:Prognosis; D012372:ROC Curve; D016019:Survival Analysis
keywords: TNM system; bootstrap; cancer staging; model selection; survival analysis