Survival analysis with time-varying relative risks: a tree-based approach.
A tree-based method for estimating time-varying effects of baseline patient characteristics on survival is introduced. A Cox-type model for censored survival data is used in which the time-varying relative risks are modelled as piecewise constants. The tree method consists of three steps: 1. Growing the tree, in which a fast algorithm using maximized score statistics is utilized to determine the optimal change points; 2. A pruning algorithm is applied to obtain more parsimonious models; 3. Selection of a final tree, which may be either via bootstrap resampling or based on a measure of explained variation. The piecewise constant model is more suitable for clinical interpretation of the regression parameters than the more continuously time-varying models (spline, loess, etc.) that have been proposed previously.
Xu
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Department of Biostatistics, Harvard School of Public Health, and Dana-Farber Cancer Institute, Boston, MA, USA. rxu@jimmy.harvard.edu
Adak
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D000465:Algorithms; D001943:Breast Neoplasms / Q000401:mortality*; D005260:Female; D005602:France; D006801:Humans; D011379:Prognosis; D016016:Proportional Hazards Models; D012044:Regression Analysis; D012306:Risk; D016019:Survival Analysis