In phase III oncology studies, delayed treatment effects have often been observed. These delayed treatment effects require a long-term approach to evaluate treatment effects. In addition, these phenomena bring more challenges to the interim analysis using survival endpoints. An improper interim analysis may falsely stop a promising compound due to the late separation of survival curves. In this scenario, short-term surrogate endpoints which are believed to be predictive of the primary long-term outcome can be extremely useful. For trials with delayed treatment effect, using surrogate endpoints in the interim analysis can help make more informative Go/No Go decision based on the interim analysis results and re-estimate sample sizes during the interim analysis to maintain a high probability of success. We propose using a surrogate endpoint (e.g ORR) in the interim analysis to improve conditional power in designing adaptive sample size re-estimation trial with time-to-event endpoint (e.g PFS). Through theoretic modeling and extensive simulations, our work will demonstrate the practical feasibility and benefits of using surrogate endpoints in trials with delayed treatment effects.