An adjustment for a post-randomization variable in the comparison of two treatments for survival.

Abstract:

:A method is proposed to infer the randomized treatment effect on survival after an adjustment for a post-randomization variable. The post-randomization variable is made independent of the treatment assignment and is considered a surrogate for baseline prognostic factors. The relationship between the post-randomization surrogate and baseline prognostic factors for survival is considered smooth, but otherwise unknown. The effect of these factors on survival is modelled using the Cox proportional hazards model with a semi-parametric relative risk function. Likelihood based estimates and tests for the treatment effect are demonstrated. An example from a randomized clinical trial in cancer illustrates the methodology.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Heller G

doi

10.1002/sim.968

subject

Has Abstract

pub_date

2001-11-30 00:00:00

pages

3475-85

issue

22

eissn

0277-6715

issn

1097-0258

pii

10.1002/sim.968

journal_volume

20

pub_type

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