Identification and Characterization of Trajectories of Cardiac Allograft Vasculopathy After Heart Transplantation: A Population-Based Study. Issue 24 (16th June 2020)

• Record Type: Journal Article
• 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
• Is Part Of: Circulation. Volume 141:Issue 24(2020)
• Publication Date: 2020-06-16
• Subjects: allografts -- antibodies -- coronary artery disease -- graft rejection -- heart transplantation -- latent class analysis; Blood -- Circulation -- Periodicals; Cardiovascular system -- Periodicals; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; Blood Circulation; Cardiovascular System; Vascular Diseases; 616.1
• DOI: 10.1161/CIRCULATIONAHA.119.044924
• Languages: English
• ISSNs: 0009-7322

Abstract

Abstract : 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 ( P <0.001), donor male sex ( P <0.001), donor tobacco consumption ( P =0.001), recipient dyslipidemia ( P =0.009), class II anti–human leukocyte antigen donor-specific antibodies ( P =0.004), and acute cellular rejection ≥2R ( P =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 ( P <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. Abstract : Supplemental Digital Content is available in the text.