E-Synthesis: A Bayesian Framework for Causal Assessment in Pharmacosurveillance.

ABSTRACT: Background: Evidence suggesting adverse drug reactions often emerges unsystematically and unpredictably in form of anecdotal reports, case series and survey data. Safety trials and observational studies also provide crucial information regarding the (un-)safety of drugs. Hence, integrating multiple types of pharmacovigilance evidence is key to minimising the risks of harm. Methods: In previous work, we began the development of a Bayesian framework for aggregating multiple types of evidence to assess the probability of a putative causal link between drugs and side effects. This framework arose out of a philosophical analysis of the Bradford Hill Guidelines. In this article, we expand the Bayesian framework and add "evidential modulators," which bear on the assessment of the reliability of i

SUBMITTER: De Pretis F 

PROVIDER: S-EPMC6929659 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature