Taking First Steps Toward Modeling Risk of Rejection in Children.

SEE PAGE 670 P ediatric cardiologists envy our colleagues who treat adults with respect to their feasibility of performing clinical trials, gathering data that results in evidence-based clinical guidelines with class I recommendations, and generating validated risk prediction models, such as the Framingham Risk Score, the Seattle Heart Failure Model, and the CHARM (Candesartan in Heart failure Assessment of Reduction in Mortality and morbidity) risk score (1,2). Pediatric heart transplantation practitioners are used to relying on data generated from multicenter registries and databases, and on data from single-center studies to help guide management decisions. Our patients do not present in great enough numbers to allow us to easily conduct multicenter, randomized, blinded, placebo-controlled trials. Fortunately, the pioneers in our field had the foresight to create registries and databases, such as the Pediatric Cardiomyopathy Registry and the Pediatric Heart Transplant Study (PHTS) database (3,4). These registries, in addition to the Organ Procurement and Transplantation Network (OPTN) database and the International Society for Heart and Lung Transplantation (ISHLT) registry, have been essential in developing an understanding of the risk and outcomes in pediatric heart failure and transplantation. Although data generated from these registries have helped us to better understand risk factors for adverse outcomes, very few analyses have provided us with a risk score. Until now, pediatric heart transplantation risk prediction models have been limited