Rationale and design of the CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) Registry.

BACKGROUND: Coronary computed tomographic angiography (CCTA) of 64-detector rows or greater represents a novel noninvasive anatomic method for evaluation of patients with suspected coronary artery disease (CAD). Early studies suggest a potential for prognostic risk assessment by CCTA findings but were limited by small patient cohorts or single centers. The CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) registry is a large, prospective, multinational dynamic observational study of patients undergoing CCTA. The primary aim of CONFIRM is to determine the prognostic value of CCTA findings for the prediction of future adverse CAD events. METHODS: The CONFIRM registry currently represents 27,125 consecutive patients at 12 cluster sites in 6 countries in North America, Europe, and Asia. CONFIRM sites were chosen on the basis of adequate CCTA volume, site CCTA proficiency, and local demographic characteristics and medical facilities to ensure a broad-based sample of patients. Patients comprising the present CONFIRM cohort include those with suspected but without known CAD, with known CAD, or asymptomatic persons undergoing CAD evaluation. A data dictionary comprising a wide array of demographic, clinical, and CCTA findings was developed by the CONFIRM investigators and is uniformly used for all patients. Patients are followed up after CCTA performance to identify adverse CAD events, including death, myocardial infarction, unstable angina, target vessel revascularization, and CAD-related hospitalization. CONCLUSIONS: From a number of countries worldwide, the information collected from the CONFIRM registry will add incremental and important insights into CCTA findings that confer prognostic value beyond demographic and clinical characteristics. The results of the CONFIRM registry will provide valuable information about the optimal methods for using CCTA findings.

Duke Scholars

Author Michael J Pencina Biostatistics & Bioinformatics, Division of Biostatistics