The development of methods to identify, validate and use surrogate biomarkers to test for a treatment effect has been an area of intense research interest given the potential for valid surrogate biomarkers to reduce the required costs and follow-up times of future studies. Several quantities and procedures have been proposed to assess the utility of a surrogate biomarker. However, few methods have been proposed to address how one might use the surrogate biomarker information to test for a treatment effect at an earlier time point or use biomarker information to plan a future clinical trial, especially in settings where the primary outcome and the biomarker are subject to censoring. We propose a novel nonparametric test statistic to test for a treatment effect using surrogate biomarker information measured prior to the end of the study in a time-to-event outcome setting. In addition, we propose a procedure to use surrogate biomarker information from an earlier trial to plan a future clinical trial and evaluate expected power and needed sample size. We illustrate the proposed procedures using simulation studies and clinical trial data.