Title: Survival analysis in multi-site studies using summary-level risk set tables
Authors: Di Shu - University of Pennsylvania and Children's Hospital of Philadelphia (United States) [presenting]
Abstract: Medical research often analyzes data from multiple sources to increase statistical power and generalizability. A growing number of studies are now conducted within multi-site distributed data networks. For example, the Sentinel System, funded by the U.S. Food and Drug Administration, monitors the safety of approved medical products using data from multiple data partners. Within these networks like the Sentinel System, each data partner maintains physical control of their data and may not always be able or willing to share individual-level data for analysis. We will introduce a one-step method that allows data partners to share only summary-level risk set tables to estimate overall and site-specific hazard ratios. We will also discuss how to apply risk set tables to other important measures such as Kaplan-Meier curves, as well as some future topics. We will justify the method theoretically, illustrate its use, and demonstrate its statistical performance using both real-world and simulated data.