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ABSTRACT: Background
Risk of the outcome is a mathematical determinant of the absolute treatment benefit of an intervention, yet this can vary substantially within a trial population, complicating the interpretation of trial results.Methods
We developed risk models using Cox or logistic regression on a set of large publicly available randomized controlled trials (RCTs). We evaluated risk heterogeneity using the extreme quartile risk ratio (EQRR, the ratio of outcome rates in the lowest risk quartile to that in the highest) and skewness using the median to mean risk ratio (MMRR, the ratio of risk in the median risk patient to the average). We also examined heterogeneity of treatment effects (HTE) across risk strata.Results
We describe 39 analyses using data from 32 large trial
SUBMITTER: Kent DM
PROVIDER: S-EPMC5841614 | biostudies-literature | 2016 Dec
REPOSITORIES: biostudies-literature