All Times EDT
Keywords: Real-world data, Propensity scores, Augmenting prospective study, Regulatory decision-making
In medical product development, there has been a growing interest in utilizing real-world data which have become abundant owing to advances in biomedical science, information technology and engineering. High-quality real-world data may be utilized to generate real-world evidence for regulatory or healthcare decision-making. This presentation will focus on propensity score-based methods for leveraging patients from a real-world data source to augment a single-arm or two-arm prospective investigational clinical study, to reduce the required number of prospectively enrolled patients, thereby saving time and cost. The proposed propensity score-based methods leverage real-world patients that are similar to those prospectively enrolled into the investigational study in terms of baseline characteristics. Either frequentist or Bayesian inference can then be applied for outcome data analysis, with the option of down-weighting information from real-world data source. Examples based on pre-market regulatory review experience are provided to illustrate the implementation of the proposed methods.