Some design issues of strata-matched non-randomized studies with survival outcomes

Non-randomized studies for the evaluation of a medical intervention are useful for quantitative hypothesis generation before the initiation of a randomized trial and also when randomized clinical trials are difficult to conduct. A strata-matched non-randomized design is often utilized where subjects treated by a test intervention are matched to a fixed number of subjects treated by a standard intervention within covariate based strata. In this paper, we consider the issue of sample size calculation for this design. Based on the asymptotic formula for the power of a stratified log-rank test, we derive a formula to calculate the minimum number of subjects in the test intervention group that is required to detect a given relative risk between the test and standard interventions. When this minimum number of subjects in the test intervention group is available, an equation is also derived to find the multiple that determines the number of subjects in the standard intervention group within each stratum. The methodology developed is applied to two illustrative examples in gastric cancer and sarcoma.