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.