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Regression splines for threshold selection in survival data analysis

✍ Scribed by Nicolas Molinari; Jean-Pierre Daurès; Jean-François Durand

Publisher: John Wiley and Sons
Year: 2001
Tongue: English
Weight: 111 KB
Volume: 20
Category: Article
ISSN: 0277-6715
DOI: 10.1002/1097-0258(20010130)20:2<237::aid-sim654>3.0.co;2-i

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✦ Synopsis

The Cox proportional hazards model restricts the hazard ratio to be linear in the covariates. A survival model based on data from a clinical trial is developed using spline functions with variable knots to estimate the log hazard function. Moreover, the main point of the method is that a knot, seen as free parameters for a piecewise linear spline, represents a break point in the log hazard function which may be interpreted as a threshold value. The likelihood ratio test is used to select the final model and to determine the threshold number for a covariate. Confidence intervals for these threshold values are computed by bootstrapping the data. Two examples illustrate the method.

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