Abstract 10390: Using a Trial Modelling Framework to Emulate a Target Trial Evaluating Revascularisation Strategies in Patients With Heart Failure

Abstract

Introduction: We developed a novel trial modelling framework which utilises real world data to emulate a target trial and estimate key parameters to support trial planning. We applied this framework using the UK Hospital Episode Statistics (HES), which captures all admissions at NHS hospitals in England, and reported the findings of an emulated target trial evaluating revascularisation strategies in heart failure (HF) patients with coronary artery disease. Methods: Phenotyping algorithms derived from the target trial protocol were applied to HES, to identify HF patients who had coronary artery bypass grafting (CABG) or percutaneous transluminal coronary angioplasty (PTCA). Trial participants are often different from the target trial population due to voluntary basis of participation. The HES-derived cohort was matched on baseline features (age, gender, comorbidities) to an existing trial (STICH) which targeted the same high-risk population, so that the matched cohort mimics a likely trial population. Treatment effects were estimated using instrumental variable analysis (IVA) and meta-learning models to adjust for confounding. Results: A total of 13,519 HF patients undergoing revascularisation during April 2009 and March 2015 met the eligibility criteria. This HF patient cohort was matched with the STICH cohort, resulting in 2046 patients in the study cohort. The 5-year composite outcome of all-cause mortality or cardiovascular hospitalisation was observed in 51.1% of HF patients who had CABG and 70.0% in those who had PTCA. IVA showed that CABG was associated with a lower risk of the composite outcome (risk difference -16.2%, 95%CI: -20.6% to -11.8%). This was consistent with the treatment effects derived from other machine learning models. Our analyses also identified a trend in greater treatment effects being observed in the matched cohort than unmatched cohort. This suggests that a clinical trial may over-estimate treatment effects when compared to the actual treatment benefit observed in clinical practice. Conclusions: The framework provides a structured process to emulate a trial and anticipate findings of the trial. Our analyses showed that CABG is associated with a greater long-term benefit in HF patients requiring revascularisation.