Red cell distribution width outperforms other potential circulating biomarkers in predicting survival in idiopathic pulmonary arterial hypertension

Abstract

Background: In addition to N-terminal pro-brain natriuretic peptide (NT-proBNP), red cell distribution width (RDW), growth differentiation factor (GDF)-15, interleukin (IL)-6 and creatinine are all potential circulating prognostic biomarkers in pulmonary arterial hypertension (PAH).

Objective: To establish the relative prognostic utility of these biomarkers in patients with idiopathic PAH (IPAH) and to identify independent prognostic markers in this disease.

Main outcome measures: Circulating RDW, GDF-15, IL-6, creatinine and NT-proBNP levels were determined in 139 patients with IPAH (mean follow-up 4.0±2.4 years) and 40 age- and sex-matched healthy volunteers. Coincident clinical data and baseline haemodynamic measurements were also analysed.

Results: All the biomarkers except creatinine correlated with a 6 min walk distance (6MWD; p<0.05), and all but NT-proBNP correlated with WHO functional class (p<0.01). GDF-15, creatinine and NT-proBNP correlated with mean right atrial pressures and cardiac index. RDW outperformed other biomarkers in receiver operating characteristic (ROC) analysis (area under the curve 0.820). Sensitive (>80%) ROC-derived cut-off points of RDW (15.7%, p=0.001), GDF-15 (779 pg/ml, p<0.001), IL-6 (2.5 pg/ml, p=0.019), creatinine (80.5 μmol/l, p=0.010) and NT-proBNP (491 fmol/ml, p<0.001), all predicted survival in patients with IPAH over time. All the plasma biomarkers analysed predicted survival in Cox regression analysis, as did clinical and haemodynamic parameters. However, only RDW predicted survival independently of NT-proBNP and 6MWD.

Conclusions: Circulating RDW, GDF-15, IL-6, creatinine and NT-proBNP levels are all related to disease severity and may be used to predict survival in patients with IPAH. RDW added significant prognostic value to measurements of NT-proBNP and exercise capacity and may prove valuable in a multiple biomarker approach to disease stratification.