Compliance-adjusted intervention effects in survival data
Time-to-event endpoints are a common outcome of interest in randomised clinical trials. The primary analysis should usually be by intention-to-treat, giving an indication of the effectiveness of the intervention in a population as a whole. However, the benefit specifically for an individual receiving the intervention is becoming increasingly important as patient decisions become more evidence-based. Effectiveness is defined as the benefit of intervention as actually applied, and may be estimated from simple all-or-nothing compliance data. Efficacy, on the other hand, is the benefit of intervention under ideal circumstances, and requires more complex compliance data. Intervention effectiveness and efficacy after accounting for non-compliance can be estimated in various ways, some of which have already been implemented in Stata (e.g. Author-Email: strbee). Recently, Loeys and Goetghebeur (2003) provided new methodology using proportional-hazards techniques in survival data where compliance is all-or-nothing in the intervention arm and perfect in the control arm. Here, their method is implemented in Stata. The output is a hazard ratio for the effectiveness of intervention, adjusted for observed adherence to intervention in the treated group. An example application is discussed for a subset of a large, randomised trial of screening where the average benefit of 26% risk reduction becomes a 34% risk reduction for individuals attending screening.
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