First and recurrent events after percutaneous coronary intervention: implications for survival analyses.

Objectives. Using composite endpoints and/or only first events in clinical research result in information loss and alternative statistical methods which incorporate recurrent event data exist. We compared information-loss under traditional analyses to alternative models. Design. We conducted a retrospective analysis of patients who underwent percutaneous coronary intervention (Jan2010-Dec2014) and constructed Cox models for a composite endpoint (readmission/death), a shared frailty model for recurrent events, and a joint frailty (JF) model to simultaneously account for recurrent and terminal events and evaluated the impact of heart failure (HF) on the outcome. Results. Among 4901 patients, 2047(41.8%) experienced a readmission or death within 1 year. Of those with recurrent events, 60% had ≥1 readmission and 6% had >4; a total of 121(2.5%) patients died during follow-up. The presence of HF conferred an adjusted Hazard ratio (HR) of 1.32 (95% CI: 1.18-1.47, p < .001) for the risk of composite endpoint (Cox model), 1.44 (95% CI: 1.36-1.52, p < .001) in the frailty model, and 1.34 (95% CI:1.22-1.46, p < .001) in the JF model. However, HF was not associated with death (HR 0.87, 95% CI: 0.52-1.48, p = .61) in the JF model. Conclusions. Using a composite endpoint and/or only the first event yields substantial loss of information, as many individuals endure >1 event. JF models reduce bias by simultaneously providing event-specific HRs for recurrent and terminal events.