Risk stratification in Arrhythmogenic Right Ventricular Cardiomyopathy: the impact of genotype on the 2019 ARVC risk calculator
Authors: Protonotarios A , Barriales-Villa R , Antoniades L , Mogensen J , Garcia-Pavia P , Wahbi K , Biagini E , Anastasakis A , Tsatsopoulou A , Zorio E , Gimeno J R , Garcia-Pinilla J M , Sinagra G , Bauce B , Elliott P M 
Published: October 2022

Introduction

Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) is associated with sudden cardiac death (SCD). The 2019 ARVC risk model has been proposed as a method to quantify arrhythmic risk, but the impact of genotype its performance has not been addressed.

Purpose

To study arrhythmic outcomes in patients with ARVC and the performance of the 2019 ARVC risk model in predefined genetic subgroups.

Methods

This is an international, retrospective observational cohort study on consecutively evaluated patients with ARVC recruited from 17 centres in 7 countries. Inclusion criteria were: (i) a definite diagnosis of ARVC according to the 2010 Task Force Criteria; (ii) no history of sustained ventricular arrhythmia (VA) prior to first assessment at the participating centre; (iii) a follow up period of ≥1 month; (iv) age of diagnosis ≥14 years. Sustained ventricular arrhythmia (sustained ventricular tachycardia, appropriate implantable cardioverter defibrillator intervention, aborted SCD, or SCD) comprised the primary outcome (VA). Discriminative ability was assessed by Uno's concordance index (c-statistic) and calibration with the calibration plot slope. Fine-Gray regression was used to model the impact of clinical predictors on the arrhythmic outcome, in the context of competing risks (heart transplantation and non-arrhythmic death). The cumulative probability and 95% confidence intervals (95% CI) for the occurrence of an outcome were estimated using the Aalen-Johansen estimate in order to take into account competing risks.

Results

The study cohort comprised 554 ARVC patients. During a median follow-up of 6.0 [3.1,12.5] years, 100 patients (18%) experienced VA (Figure). Risk estimates for VA using the 2019 ARVC risk model showed good discriminative ability (c-statistic 0.75 (95% CI 0.70–0.81)) but with overestimation of risk (slope 0.46 (95% CI 0.33–0.63)). The ARVC risk model was compared in 4 gene groups: PKP2 (n=118, 21%); DSP (n=79, 14%); other desmosomal (n=59, 11%); and gene elusive (n=160, 29%). Discrimination and calibration were highest for PKP2 [c-statistic 0.83 (95% CI 0.75–0.91); calibration slope 0.67 (95% CI 0.40–1.04)] and lowest for the gene elusive group [c-statistic 0.65 (95% CI 0.57–0.74); calibration slope 0.26 (95% CI 0.06–0.49)]. Univariable analyses revealed variable performance of individual clinical risk markers in the different gene groups (see heatmap of hazard ratios and statistical significance in Figure). For example, RV dimensions and systolic function are significant risk markers in PKP2 but not in DSP patients and the opposite is true of LV systolic function (Figure).

Conclusion

The 2019 ARVC risk model performs reasonably well in gene positive ARVC, (particularly for PKP2) but is more limited in gene elusive patients. Genotype specific risk factors should be considered in ARVC patients.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): British Heart Foundation