Jean-Luc Taupin, Jon Kobashigawa, Xavier Jouven, Jigneh K Patel, Maarten Naesens, Ryan Levine, Jean-Philippe Empana, Romain Guillemain, Pascal Leprince, Shaida Varnous, Carmen Lefaucheur, Alexandre Loupy, Patrick Bruneval, Jean-Paul Duong Van Huyen, Daniel Yoo, Maud Racapé, Marie-Cécile Bories, Olivier Aubert, Marc Raynaud, Jan Van Keer, Guillaume Bonnet, Guillaume Coutance
Journal: Circulation 2021;141(24):1954-1967
PMID: 32363949
BACKGROUND
Cardiac allograft vasculopathy (CAV) is a major contributor of heart transplant 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 nonimmune factors in CAV development.
METHODS
Heart transplant recipients were from 4 academic centers (Pitié-Salpêtrière and Georges Pompidou Hospital, Paris, Katholieke Universiteit Leuven, and Cedars-Sinai, Los Angeles; 2004-2016). Patients underwent prospective, protocol-based monitoring consisting of repeated coronary angiographies together with systematic assessments of clinical, histological, and immunologic parameters. The main outcome was a prediction for CAV trajectory. We identified CAV trajectories by 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 cohorts, respectively). The median follow-up after transplantation was 6.6 (interquartile range, 4-9.1) years with 4710 coronary angiographies analyzed. We identified 4 distinct profiles of CAV trajectories over 10 years. The 4 trajectories were characterized by (1) patients without CAV at 1 year and nonprogression over time (56.3%), (2) patients without CAV at 1 year and late-onset slow CAV progression (7.6%), (3) patients with mild CAV at 1 year and mild progression over time (23.1%), and (4) patients with mild CAV at 1 year and accelerated progression (13.0%). This model showed good discrimination (0.92). Among candidate predictors assessed, 6 early independent predictors of these trajectories were identified: donor age (<0.001), donor male sex (<0.001), donor tobacco consumption (=0.001), recipient dyslipidemia (=0.009), class II anti-human leukocyte antigen donor-specific antibodies (=0.004), and acute cellular rejection ≥2R (=0.028). The 4 CAV trajectories manifested consistently in the US independent cohort with similar discrimination (0.97) and in different clinical scenarios, and showed gradients for overall-cause mortality (<0.001).
CONCLUSIONS
In a large multicenter and highly phenotyped prospective cohort of heart transplant recipients, we identified 4 CAV trajectories and their respective independent predictive variables. Our results provide the basis for a trajectory-based assessment of patients undergoing heart transplantation for early risk stratification, patient monitoring, and clinical trials. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04117152.
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