Inference in Spline‐Based Models for Multiple Time‐to‐Event Data, with Applications to a Breast Cancer Prevention Trial
- 11 December 2003
- journal article
- research article
- Published by Oxford University Press (OUP) in Biometrics
- Vol. 59 (4), 859-868
- https://doi.org/10.1111/j.0006-341x.2003.00100.x
Abstract
As part of the National Surgical Adjuvant Breast and Bowel Project, a controlled clinical trial known as the Breast Cancer Prevention Trial (BCPT) was conducted to assess the effectiveness of tamoxifen as a preventive agent for breast cancer. In addition to the incidence of breast cancer, data were collected on several other, possibly adverse, outcomes, such as invasive endometrial cancer, ischemic heart disease, transient ischemic attack, deep vein thrombosis and/or pulmonary embolism. In this article, we present results from an illustrative analysis of the BCPT data, based on a new modeling technique, to assess the effectiveness of the drug tamoxifen as a preventive agent for breast cancer. We extended the flexible model of Gray (1994, Spline-based test in survival analysis, Biometrics 50, 640-652) to allow inference on multiple time-to-event outcomes in the style of the marginal modeling setup of Wei, Lin, and Weissfeld (1989, Regression analysis of multivariate incomplete failure time data by modeling marginal distributions, Journal of the American Statistical Association 84, 1065-1073). This proposed model makes inference possible for multiple time-to-event data while allowing for greater flexibility in modeling the effects of prognostic factors with nonlinear exposure-response relationships. Results from simulation studies on the small-sample properties of the asymptotic tests will also be presented.Keywords
This publication has 18 references indexed in Scilit:
- Inference for smooth curves in longitudinal data with application to an aids clinical trialStatistics in Medicine, 1995
- Flexible Methods for Analyzing Survival Data Using Splines, With Applications to Breast Cancer PrognosisJournal of the American Statistical Association, 1992
- Flexible Methods for Analyzing Survival Data Using Splines, with Applications to Breast Cancer PrognosisJournal of the American Statistical Association, 1992
- Projecting Individualized Probabilities of Developing Breast Cancer for White Females Who Are Being Examined AnnuallyJNCI Journal of the National Cancer Institute, 1989
- Regression Analysis of Multivariate Incomplete Failure Time Data by Modeling Marginal DistributionsJournal of the American Statistical Association, 1989
- Analysing repeated measurements with possibly missing observations by modelling marginal distributionsStatistics in Medicine, 1988
- Cox's Regression Model for Counting Processes: A Large Sample StudyThe Annals of Statistics, 1982
- Bivariate Exponential DistributionsJournal of the American Statistical Association, 1960