Clinical implications of idiopathic pulmonary arterial hypertension phenotypes defined by cluster analysis
Section snippets
Study population
Patients with prevalent IPAH (n = 252) from 2 referral centers, Policlinico Umberto I/Sapienza University of Rome and the University of Arizona, Tucson, Arizona, were enrolled in the study. The diagnosis of IPAH was confirmed according to the international guidelines1 (mean pulmonary artery pressure (mPAP) ≥ 25 mm Hg, pulmonary wedge pressure < 15 mm Hg, and pulmonary vascular resistance (PVR) ≥ 240 dynes•s/cm5).
Baseline clinical data included a medical history, physical examination, a
Results
The 30 clinical variables were available for all the subjects included in the cluster analysis (n = 252 patients), as routinely used in clinical practice by both centers. The overall cohort included a mixture of consecutive patients with IPAH with a range of hemodynamic severity, RV function, and exercise capacity. Patients from the 2 sites had similar demographic characteristics and WHO functional class, but U.S. patients had greater RV sizes and lower 6MWD and VO2 peak compared with the
Discussion
We applied a novel approach to a relatively large population of patients with IPAH, well representative of daily practice activity close to a European and a US referral center.
Within the umbrella category of IPAH, it was the combination of mPAP, RVEDA, and O2 pulse that further stratified patients into novel IPAH phenotypes that significantly associate with CW. These findings underscore the significant heterogeneity that exists within patients with IPAH and the need for novel multidimensional
Study limitations
First, this study was not meant to propose a phenotype classification for IPAH, as the clusters are likely to vary according to patient characteristics and available data. However, we decided to consider the simplest and commonly used parameters in clinical practice. These results serve to underscore the need for a novel multidimensional IPAH phenotyping approach and should be validated in multicenter studies with larger and different PAH populations. Second, the study population represented
Conclusions
This study shows that by using a clustering algorithm on clinically available data of patients with IPAH, we can identify 4 phenotypically distinct and clinically meaningful groups. We have also shown that patients in each cluster presented different outcomes on long-term follow-up. These findings highlight the significant heterogeneity that exists within patients with IPAH and the need for improved advanced phenotyping with exercise and imaging to enhance current risk assessment tools.
Disclosure statement
R. Badagliacca has received fees as speaker and scientific consultant for GSK, UT, Dompè, Ferrer, Bayer, MSD, and AOPOrphan Pharmaceuticals. CD Vizza has received fees as speaker and scientific consultant for GSK, UT, Dompè, Bayer, and MSD. The other authors have no conflicts of interest to disclose.
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