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04 June 2018

Consider the following scenario: a subject with a specific illness presents to a physician who has a choice between two medicines she could prescribe. The physician will need to predict which intervention has a more favourable benefit-risk for the subject at hand. To achieve an informed decision,  she measures a series of additional data, or covariates, which have been shown to impact the benefit-risk profile of the medicines. In this talk we investigate the performance of a decision-rule for personalised benefit-risk assessment. Given a set of covariates, and a joint model for the efficacy and safety responses, results from a simulation study show that the decision-rule has good performance overall, giving high probability of proposing a specific treatment only to the subgroup of patients for which the treatment is known to have a positive benefit-risk profile.

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