Power of logrank test and Cox regression model in clinical trials with heterogeneous samples.
This paper evaluates the loss of power of the simple and stratified logrank tests due to heterogeneity of patients in clinical trials and proposes a flexible and efficient method of estimating treatment effects adjusting for prognostic factors. The results of the paper are based on the analyses of survival data from a large clinical trial which includes more than 6000 cancer patients. Major findings from the simulation study on power are: (i) for a heterogeneous sample, such as advanced cancer patients, a simple logrank test can yield misleading results and should not be used; (ii) the stratified logrank test may suffer some power loss when many prognostic factors need to be considered and the number of patients within stratum is small. To address the problems due to heterogeneity, the Cox regression method with a special hazard model is recommended. We illustrate the method using data from a gastric cancer clinical trial.
Akazawa
K
K
Department of Medical Informatics, Faculty of Medicine, Kyushu University, Fukuoka, Japan.
Nakamura
T
T
Palesch
Y
Y
D015982:Bias; D002986:Clinical Trials as Topic; D015987:Effect Modifier, Epidemiologic; D006801:Humans; D011379:Prognosis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D013274:Stomach Neoplasms / Q000628:therapy; D016019:Survival Analysis; D016896:Treatment Outcome