The American College of Cardiology Foundation (ACCF) and the American Heart Association (AHA) have jointly engaged in the production of guideline in the area of cardiovascular disease since 1980. The developed guidelines are intended to assist health care providers in clinical decision making by describing a range of generally acceptable approaches for the diagnosis, management, or prevention of specific diseases or conditions. This talk describes some of our work under a contract with ACCF/AHA for applying Bayesian methods to guideline recommendation development. In a demonstration example, we use Bayesian meta-analysis strategies to summarize evidence on the comparative effectiveness betweenPercutaneous coronary intervention and Coronary artery bypass grafting for patients with unprotected left main coronary artery disease. We show the usefulness and flexibility of Bayesian methods in handling data arisen from studies with different designs (e.g. RCTs and observational studies), performing indirect comparison among treatments when studies with direct comparisons are unavailable, and accounting for historical data.
Group for Research in Decision Analysis