Translating clinical trial results into personalized recommendations by considering multiple outcomes and subjective views.

ABSTRACT: Currently, clinicians rely mostly on population-level treatment effects from RCTs, usually considering the treatment's benefits. This study proposes a process, focused on practical usability, for translating RCT data into personalized treatment recommendations that weighs benefits against harms and integrates subjective perceptions of relative severity. Intensive blood pressure treatment (IBPT) was selected as the test case to demonstrate the suggested process, which was divided into three phases: (1) Prediction models were developed using the Systolic Blood-Pressure Intervention Trial (SPRINT) data for benefits and adverse events of IBPT. The models were externally validated using retrospective Clalit Health Services (CHS) data; (2) Predicted risk reductions and increases from these model

SUBMITTER: Dagan N 

PROVIDER: S-EPMC6704144 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature