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Background: Risk assessment in pulmonary arterial hypertension (PAH) is fundamental to guiding treatment and improved outcomes. Clinical models are excellent at identifying high-risk patients, but leave uncertainty amongst moderate-risk patients., Research Question: Can a multiple blood biomarker model of PAH, using previously described biomarkers, improve risk discrimination over current models?, Study Design and Methods: Using a multiplex enzyme-linked immunosorbent assay, we measured N-terminal fragment of the prohormone brain natriuretic peptide (NT-proBNP), soluble suppressor of tumorigenicity, IL-6, endostatin, galectin 3, HDGF, and insulin-like growth factor binding proteins (IGFBP1-7) in training (n = 1,623), test (n = 696), and validation (n = 237) cohorts. Clinical variables and biomarkers were evaluated by principal component analysis. NT-proBNP was not included to develop a model independent of NT-proBNP. Unsupervised k-means clustering classified participants into clusters. Transplant-free survival by cluster was examined using Kaplan-Meier and Cox proportional hazard regressions. Hazard by cluster was compared with NT-proBNP, Registry to Evaluate Early and Long-Term PAH Disease Management (REVEAL), and European Society of Cardiology (ESC) and European Respiratory Society (ERS) risk models alone and combined clinical and biomarker models., Results: The algorithm generated 5 clusters with good risk discrimination using 6 biomarkers, weight, height, and age at PAH diagnosis. In the test and validation cohorts, the biomarker model alone performed equivalent to REVEAL (area under the receiver operating characteristic curve, 0.74). Adding the biomarker model to the ESC and ERS score and REVEAL score improved the ESC and ERS score and REVEAL score. The best overall model was the biomarker model adjusted for NT-proBNP with the best C statistic, Akaike information criterion, and calibration for the adjusted model compared with either the biomarker or NT-proBNP model alone., Interpretation: A multibiomarker model alone was equivalent to current PAH clinical mortality risk prediction models and improved performance when combined and added to NT-proBNP. Clinical risk scores offer excellent predictive models, but require multiple tests; adding blood biomarkers to models can improve prediction or can enable more frequent, noninvasive monitoring of risk in PAH to support therapeutic decision-making., Competing Interests: Financial/Nonfinancial Disclosures None declared., (Copyright © 2024 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Background: Three biomarkers, soluble suppression of tumorigenicity 2 (ST2), galectin 3 (Gal3), and N-terminal brain natriuretic peptide prohormone (NT-proBNP), are approved for noninvasive risk assessment in left-sided heart failure, and small observational studies have shown their prognostic usefulness in heterogeneous pulmonary hypertension cohorts. We examined associations between these biomarkers and disease severity and survival in a large cohort of patients with pulmonary arterial hypertension (PAH) (ie, group 1 pulmonary hypertension). We hypothesized that additive use of biomarkers in combination would improve the prognostic value of survival models., Methods: Biomarker measurements and clinical data were obtained from 2,017 adults with group 1 PAH. Associations among biomarker levels and clinical variables, including survival times, were examined with multivariable regression models. Likelihood ratio tests and the Akaike information criterion were used to compare survival models., Results: Higher ST2 and NT-proBNP were associated with higher pulmonary pressures and vascular resistance and lower 6-min walk distance. Higher ST2 and NT-proBNP levels were associated with increased risk of death (hazard ratios: 2.79; 95% CI, 2.21-3.53; P < .001 and 1.84; 95% CI, 1.62-2.10; P < .001, respectively). The addition of ST2 to survival models composed of other predictors of survival, including NT-proBNP, significantly improved model fit and predictive capacity., Conclusions: ST2 and NT-proBNP are strong, noninvasive prognostic biomarkers in PAH. Despite its prognostic value in left-sided heart failure, Gal3 was not predictive in PAH. Adding ST2 to survival models significantly improves model predictive capacity. Future studies are needed to develop multimarker assays that improve noninvasive risk stratification in PAH., (Copyright © 2020 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)