Background: There is inadequate power to perform a valid clinical trial in pediatric heart transplantation (HT) using a conventional end-point, because the disease is rare and hard end-points, such as death or graft loss, are infrequent. We sought to develop and validate a surrogate end-point involving the cumulative burden of post-transplant complications to predict death/graft loss to power a randomized clinical trial of maintenance immunosuppression in pediatric HT.
Methods: Pediatric Heart Transplant Study (PHTS) data were used to identify all children who underwent an isolated orthotopic HT between 2005 and 2014 who survived to 6 months post-HT. A time-varying Cox model was used to develop and evaluate a surrogate end-point comprised of 6 major adverse transplant events (MATEs) (acute cellular rejection [ACR], antibody-mediated rejection [AMR], infection, cardiac allograft vasculopathy [CAV], post-transplant lymphoproliferative disease [PTLD] and chronic kidney disease [CKD]) occurring between 6 and 36 months, where individual events were defined according to international guidelines. Two thirds of the study cohort was used for score development, and one third of the cohort was used to test the score.
Results: Among 2,118 children, 6.4% underwent graft loss between 6 and 36 months post-HT, whereas 39% developed CKD, 34% ACR, 34% infection, 9% AMR, 4% CAV and 2% PTLD. The best predictive score involved a simple MATE score sum, yielding a concordance probability estimate (CPE) statistic of 0.74. Whereas the power to detect non-inferiority (NI), assuming the NI hazard ratio of 1.45 in graft survival was 10% (assuming 200 subjects and 6% graft loss rate), the power to detect NI assuming a 2-point non-inferiority margin was >85% using the MATE score.
Conclusion: The MATE score reflects the cumulative burden of MATEs and has acceptable prediction characteristics for death/graft loss post-HT. The MATE score may be useful as a surrogate end-point to power a clinical trial in pediatric HT.
Keywords: congenital heart disease; heart failure; heart transplantation; pediatrics; risk-prediction model; study design; surrogate end-point.
Copyright © 2018. Published by Elsevier Inc.