Adaptive risk group refinement.
We construct interpretable prognostic rules based on a sequence of "box-shaped" regions in the predictor space indexed by the fraction of patients in the prognostic group. In addition, the method can be used as a building block to construct more general prognostic rules based on unions of boxes, or even as a tool to find multiple prognostic groups. Simulations are used to study the properties of the new method and compare it to constructing prognostic groups based on regression trees and linear proportional hazards (PH) models. We consider an example based on data from several completed clinical trials for patients with multiple myeloma.
LeBlanc
Michael
M
Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, M3-C102, Seattle, Washington 98109, USA. mleblanc@fhcrc.org
Moon
James
J
Crowley
John
J
D000465:Algorithms; D001699:Biometry; D002986:Clinical Trials as Topic; D003198:Computer Simulation; D006801:Humans; D016014:Linear Models; D015233:Models, Statistical; D008962:Models, Theoretical; D009101:Multiple Myeloma / Q000097:blood / Q000401:mortality / Q000628:therapy*; D015999:Multivariate Analysis; D011379:Prognosis; D016016:Proportional Hazards Models; D012044:Regression Analysis; D012306:Risk; D016019:Survival Analysis; D016896:Treatment Outcome