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Estimates of clinically useful measures in competing risks survival analysis
Author(s) -
Ambrogi Federico,
Biganzoli Elia,
Boracchi Patrizia
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3455
Subject(s) - survival analysis , statistics , econometrics , computer science , mathematics
Competing risks occur frequently in follow‐up clinical studies. To assess treatment or covariate effects, measures of clinical impact based on crude cumulative incidence should be considered, such as relative risks or the absolute risk reduction. In this work, transformation models through suitable link functions provide a straightforward approach to obtain point and interval estimates of such measures. An extension of the Klein and Andersen proposal, based on pseudo‐values, is considered. Non‐additive effects were tested by interactions between baseline (spline function on time) and covariates. The methods are applied to the evaluation of the impact of axillary lymph node nanometastases on metastatic relapse of breast cancer patients. Further, a literature data set on prostate cancer was used for illustration. Copyright © 2008 John Wiley & Sons, Ltd.