A parametric model for long-term follow-up data from phase III breast cancer clinical trials.
We propose a parametric version of a univariate gamma frailty model. The proposed model is shown to be flexible enough to model long-term follow-up survival data from breast cancer clinical trials when the treatment effect diminishes as time progresses, a case for which neither the proportional hazards nor proportional odds assumptions are satisfied. The observed information matrix is computed to evaluate the variances of parameter estimates. A simple parametric test statistic to test proportional odds assumption is also constructed. The model is applied to a data set from a phase III clinical trial on breast cancer.
Jeong
Jong-Hyeon
JH
Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA. jeong@nsabp.pitt.edu
Jung
Sin-Ho
SH
Wieand
Samuel
S
D018931:Antineoplastic Agents, Hormonal / Q000627:therapeutic use; D001943:Breast Neoplasms / Q000188:drug therapy*; D017326:Clinical Trials, Phase III as Topic / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D018572:Disease-Free Survival; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D015233:Models, Statistical; D013629:Tamoxifen / Q000627:therapeutic use
D018931:Antineoplastic Agents, Hormonal; D013629:Tamoxifen