The primary objective of a randomized controlled screening trial is to evaluate the benefit of the screening program by comparing long-term survival between the study group and the control group. Although there has been considerable development in statistical inference for censored survival data, methods for the evaluation of survival benefit in the context of cancer prevention and screening trials are relatively limited. We describe and study the asymptotic distribution of a class of maximum weighted Kaplan-Meier test statistics where the weight functions are chosen from a family of smooth functions. The investigated test statistic is robust and sensitive to a variety of alternatives that are often observed in cancer prevention and screening trials. A simulation study is performed to compare the size and power properties between the proposed test statistics and some existing ones. We illustrate the procedure using data from a clinical trial of a breast cancer screening program.
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