Identification and Characterization of Trajectories of Cardiac Allograft Vasculopathy After Heart Transplantation: A Population-Based Study

• Published in: Circulation (New York, N.Y.) N.Y.), 2020-06, Vol.141 (24), p.1954-1967
• Main Authors: Loupy, Alexandre, Coutance, Guillaume, Bonnet, Guillaume, Van Keer, Jan, Raynaud, Marc, Aubert, Olivier, Bories, Marie-Cécile, Racapé, Maud, Yoo, Daniel, Duong Van Huyen, Jean-Paul, Bruneval, Patrick, Taupin, Jean-Luc, Lefaucheur, Carmen, Varnous, Shaida, Leprince, Pascal, Guillemain, Romain, Empana, Jean-Philippe, Levine, Ryan, Naesens, Maarten, Patel, Jigneh K., Jouven, Xavier, Kobashigawa, Jon
• Format: Article
• Language: English
• ISSN: 0009-7322; 1524-4539
• DOI: 10.1161/CIRCULATIONAHA.119.044924

BACKGROUND:Cardiac allograft vasculopathy (CAV) is a major contributor of heart transplant (HTx) recipient mortality. Little is known about the prototypes of CAV trajectories at the population level. We aimed to identify the different evolutionary profiles of CAV and to determine the respective contribution of immune and non-immune factors in CAV development. METHODS:HTx recipients from four academic centers (Pitié-Salpêtrière & Georges Pompidou Hospital, Paris, Katholieke Universiteit Leuven, Cedars-Sinai, Los Angeles; 2004 to 2016) Patients underwent prospective, protocol-based monitoring consisting of repeated coronary angiographies together with systematic assessments of clinical, histological and immunological parameters. The main outcome was a prediction for CAV trajectory. We identified CAV trajectories using unsupervised latent class mixed models. We then identified the independent predictive variables of the CAV trajectories and their association with mortality. RESULTS:A total of 1301 patients were included (815 and 486 in the European and US cohort, respectively). The median follow-up post-transplant was 6.6 (IQR = 4-9.1) years with 4710 coronary angiographies analyzed. We identified four distinct profiles of CAV trajectories over 10 years. The four trajectories were characterized by i) patients without CAV at one year and non-progression over time (56.3%), ii) patients without CAV at one year and late onset slow CAV progression (7.6%), iii) patients with mild CAV at one year and mild progression over time (23.1%) and iv) patients with mild CAV at one year and accelerated progression (13.0%). This model showed good discrimination (0.92). Among candidate predictors assessed, six early independent predictors of these trajectories were identifieddonor age (p