Using Bayesian Evidence Synthesis Methods to Incorporate Real-World Evidence in Surrogate Endpoint Evaluation.

Regulatory agencies increasingly rely on surrogate endpoints when making licensing decisions, and for the decisions to be robust, surrogate endpoints need to be validated. In the era of precision medicine, when surrogacy patterns may depend on the drug's mechanism of action and trials of targeted therapies may be small, data from randomized controlled trials may be limited.Real-world evidence (RWE) is increasingly used at different stages of the drug development process. When used to enhance the evidence base for surrogate endpoint evaluation, RWE can improve inferences about the strength of surrogate relationships and the precision of predicted treatment effect on the final clinical outcome based on the observed effect on the surrogate endpoint in a new trial.Careful selection of RWE is needed to reduce risk of bias.