Objectives: In this interactive workshop participants will be introduced to quantitative benefit-harm assessments. With the help of two examples from real-life studies, about primary prevention of cardiovascular diseases and second line treatment in diabetes type-2, participants will learn how evidence for benefit harm analysis is selected and how the benefit harm balance can be individualised.
Description: Quantitative benefit-harm assessments (BHA) rely on evidence synthesised in systematic reviews. They can inform patients and clinicians about treatment decisions. BHA is influenced by three key determinants: The baseline risk, treatment effect and importance of outcomes. Evidence for these key determinants should be carefully selected. While the first BHA were based on population levels, methods have been developed to individualise the benefit-harm balance.
For personalised benefit-harm balance to be determined from aggregated data, baseline risks that best reflect the characteristics of the person can be selected. Moreover, effect modification can be considered and treatment effect estimates thus adjusted. Finally, the individual preferences for health outcomes can be incorporated.
In this workshop we will introduce individualised BHA. With real-world examples and discussions, we will reflect on the use of aggregated evidence in BHA.