TBD: An innovative easy to use tool to enhance robustness and precision of safety analysis with historical controls
Senior patient safety physician
Boehringer Ingelheim International Gmbh Germany
Discuss the pitfalls associated with the use of historic controls for safety analysis. Explain how Bayesian Borrowing differs from “simple” pooling of current and historical safety data. Detect how the tool can support safety analysis.
Small treatment groups present a challenge for safety analysis, especially in early development and for rare diseases. It is the known dilemma of finding the right equipoise with regards to sample size in order to get treatments to patients faster and at the same to have an adequate safety data package for a proper benefit-risk assessment and risk minimization planning. To address this challenge a new tool was developed. It integrates current safety data and historical safety data using Bayesian borrowing. The historical data is used to construct a robust meta-analytic predictive (MAP) prior which is then combined with the data from the new study to generate the posterior evidence. In contrast to simple pooling of safety data the robust MAP prior accounts for heterogeneity between different data sources and will automatically down-weight the historical information in case of prior data conflicts.
At the same time, B-Safe is an easy-to-use tool that does not need much training. The tool interactively guides the user through the analysis. The user can choose between two safety data estimands: incidence proportions and incidence rates per treatment year to account for differences in treatment duration. Point estimates and credibility intervals are provided per treatment and for risk difference and risk ratio between treatments.
In the session we will present the new analysis tool. Results of a retrospective analysis of a clinical trial will demonstrate its innovative and valuable use in safety analysis that supports informative decision making. Additional features are planned for the tool to extend its future use, e.g. in-time monitoring of safety data.
With digital innovation we are increasing the precision of our judgements, shortening the time from observations to insights to action, which ultimately leads to offering better treatments to patients without undue delay.