Personalized Medicine in Arrhythmogenic Right Ventricular Cardiomyopathy

Abstract

Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) is a hereditary heart muscle disease, characterized by fibrofatty replacement of predominantly the right ventricle (RV). ARVC is one of the major causes of sudden cardiac death (SCD) in young (<40 years), often athletic people. The disease presentation and the risk of SCD can vary highly among individual patients. SCD can only be prevented by an implantable cardioverter-defibrillator (ICD), but this requires timely diagnosis and accurate ventricular arrhythmia (VA) assessment. The research in this thesis focused on this clinical challenge, aiming to prevent SCD in ARVC patients while simultaneously avoid burdening patients with a low risk with unnecessary ICD placements. For the purpose of this and future research, a large database was designed containing clinical data of ARVC patients, in collaboration with multiple centers across Europe and North-America. Clinical characteristics that can potentially be used to identify patients at risk of life-threatening arrhythmias or SCD were identified by a systematically reviewing prior literature. Based on this selection of potential risk factors, statistical computer models were used to derive two multivariable models for predicting the risk of life-threatening arrhythmias or SCD in individual patients within five years. These models were made available publicly online to provide clinicians and their patients the data that is essential for informed shared decision making for the placement of an ICD. As ARVC patients are disproportionally athletic, it has been postulated that exercise may promote disease expression and the risk of arrhythmias in those with a genetic predisposition to develop ARVC. Indeed, the research in this thesis supports this theory by showing that athletic patients are at higher risk of incident life-threatening VA. However, the data showed a potential threshold below which exercise can be practiced safely without increasing this risk. Furthermore, as exercise also promoted expression of disease characteristics that are included in the newly developed risk prediction models, the predictions of these models remained accurate regardless of exercise. The last study in this thesis investigates the diagnostic accuracy of the current criteria for diagnosing ARVC, i.e. the 2010 Task Force Criteria (TFC), as these are predominantly expert opinion based and have never before been clinically validated. This study showed that while the TFC performed well overall, some of the criteria in the TFC can be considered redundant and might cause false positive diagnosis. By removing these, the TFC can be simplified. Furthermore, the results identified a selection of criteria with particularly high sensitivity that suggest the potential for a simple screening test based on these criteria alone to be used in at-risk relatives and pathogenic mutation carriers who need to be evaluated for signs of ARVC at regular intervals.