In prognosis studies to evaluate association between a continuous biomarker and a survival outcome, investigators often classify subjects into two subclasses of the high‐ and low‐expression groups and apply simple survival analysis techniques of the Kaplan‐Meier method and the logrank test. The high‐ and low‐expressions are defined according to whether or not the observation of the biomarker is higher than the cut‐off value, which is heterogeneous across studies. The heterogeneous definitions of the cut‐off value make it difficult to apply the standard meta‐analysis techniques. We propose a method to estimate the concordance index for a survival outcome synthesizing published prognosis studies, in which the Kaplan‐Meier estimates for the high‐ and low‐expression groups are reported. We illustrate our proposed method with a real dataset for meta‐analysis of prognosis studies evaluating Ki‐67 in early breast cancer and evaluate its performance with a simulation study.