Analysis of Statistical Biases in Studies Used to Formulate Guidelines: The Case of Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) The Case of ARVC

Abstract

To analyze the statistical biases in the studies used to derive cardiac magnetic resonance-based major and minor criteria for the diagnosis of arrhythmogenic right ventricular cardiomyopathy (ARVC). ARVC is a rare disorder of the heart that can lead to sudden death in young adults. Cardiac magnetic resonance imaging (CMR) plays a role in the diagnosis by contributing to the criteria set by experts. The original criteria emphasized qualitative analysis of CMR. The criteria were modified in 2010 to provide quantitative cutoffs. We apply the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for systematic review of diagnostic accuracy to the studies cited in the guidelines written in 1994 and revised in 2010. We use the signaling questions in QUADAS-2 to identify different types of statistical bias. The studies have understandable biases that affect the sensitivity and specificity of CMR in the diagnosis of ARVC, as well as the truth of the disease state. There is potential to overdiagnose ARVC particularly in low prevalence populations.