A Serial NT-proBNP Model to Improve Prognostication in Patients with Pulmonary Arterial Hypertension

Abstract

Background: Baseline elevation in N-terminal pro-brain natriuretic peptide (NT-proBNP) in pulmonary arterial hypertension (PAH) patients is associated with worse outcomes. Serial measurement of commonly available biomarkers could improve the precision of prognostic estimates and our understanding of PAH pathophysiology. Methods: Included were 103 PAH patients with baseline elevated NT-proBNP prior to the initiation or escalation of therapy with at least two subsequent NT-proBNP measurements. Using patients’ serial measurements, a linear mixed-effects model extrapolated a baseline NT-proBNP (intercept) and evolution (slope). These model-determined values were then used in Cox proportional hazards analysis to determine predictors of survival. Time-dependent area under the curve (AUC) analysis compared survival discrimination of serial versus single measurements of NTproBNP. Results: Subjects were 50 ± 14 years; most had idiopathic PAH, congenital heart disease, or connective tissue disease. Survivors were younger than non-survivors 47 ± 14 versus 55 ± 12 years (p=0.002). A multivariable survival model using invasive and non-invasive covariates found NT-proBNP significantly predicted mortality. Timedependent AUC was significantly greater for modeled (intercept) versus measured NT-proBNP. Conclusions: Prognostic modeling utilizing serial NT-proBNP measurements better predict survival than a single baseline value. This evidence supports the conduct of future studies of serial measurement of NT-proBNP to further clarify its role in the clinical care of PAH patients.