Heterogeneity of treatment effect (HTE) refers to the nonrandom variation in the magnitude or direction of a treatment effect across levels of a covariate, as measured on a selected scale, against a clinical outcome. In randomized controlled trials (RCTs), HTE is typically examined through a subgroup analysis that contrasts effects in groups of patients defined "1 variable at a time" (for example, male vs. female or old vs. young). The authors of this statement present guidance on an alternative approach to HTE analysis, "predictive HTE analysis." The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risks with versus without the intervention, taking into account all relevant patient attributes simultaneous...
Do the effects of interventions vary across patient and community subgroups based on health needs, v...
Objectives: To contrast the interpretations of treatment effect esti-mates using risk adjustment and...
Treatment effects vary across different patients, and estimation of this variability is essential fo...
The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed to promot...
Background: Recent evidence suggests that there is often substantial variation in the benefits and h...
Background: Recent evidence suggests that there is often substantial variation in the benefits and h...
Mounting evidence suggests that there is frequently considerable variation in the risk of the outcom...
Mounting evidence suggests that there is frequently considerable variation in the risk of the outcom...
BackgroundSome patients will experience more or less benefit from treatment than the averages report...
Background: Risk of the outcome is a mathematical determinant of the absolute treatment benefit of a...
A relevant problem in meta-analysis concerns the possible heterogeneity between trial results. If a ...
Heterogeneity in meta-analysis describes differences in treatment effects between trials that exceed...
UnrestrictedThe foundation of this dissertation is built upon the belief that treatment effects are ...
textabstractRandomized clinical trials (RCTs) are essential to evaluate the usefulness of treatment...
Heterogeneity of treatment effect in randomized clinical trials is referred to the problem of high v...
Do the effects of interventions vary across patient and community subgroups based on health needs, v...
Objectives: To contrast the interpretations of treatment effect esti-mates using risk adjustment and...
Treatment effects vary across different patients, and estimation of this variability is essential fo...
The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed to promot...
Background: Recent evidence suggests that there is often substantial variation in the benefits and h...
Background: Recent evidence suggests that there is often substantial variation in the benefits and h...
Mounting evidence suggests that there is frequently considerable variation in the risk of the outcom...
Mounting evidence suggests that there is frequently considerable variation in the risk of the outcom...
BackgroundSome patients will experience more or less benefit from treatment than the averages report...
Background: Risk of the outcome is a mathematical determinant of the absolute treatment benefit of a...
A relevant problem in meta-analysis concerns the possible heterogeneity between trial results. If a ...
Heterogeneity in meta-analysis describes differences in treatment effects between trials that exceed...
UnrestrictedThe foundation of this dissertation is built upon the belief that treatment effects are ...
textabstractRandomized clinical trials (RCTs) are essential to evaluate the usefulness of treatment...
Heterogeneity of treatment effect in randomized clinical trials is referred to the problem of high v...
Do the effects of interventions vary across patient and community subgroups based on health needs, v...
Objectives: To contrast the interpretations of treatment effect esti-mates using risk adjustment and...
Treatment effects vary across different patients, and estimation of this variability is essential fo...