A comparative analysis of risk stratification tools in SSc-associated pulmonary arterial hypertension: a EUSTAR analysis

Abstract

Objectives: The 2022 European Society of Cardiology and European Respiratory Society (ESC/ERS) guidelines for pulmonary arterial hypertension (PAH) recommend risk stratification to optimize management. However, the performance of generic PAH risk stratification tools in patients with SSc-associated PAH remains unclear. Our objective was to identify the most accurate approach for risk stratification at SSc-PAH diagnosis.

Methods: In this multicentre, international cohort study from the European Scleroderma Trials and Research (EUSTAR) group database, we screened 11 risk stratification tools upon SSc-PAH diagnosis. We compared the performance of the three top-ranked tools to predict mortality with the ESC/ERS three-strata model, the currently recommended tool for baseline risk assessment. We also assessed the impact of incorporating SSc-specific characteristics into the tools. Kaplan-Meier analyses and Cox regression with area under the ROC curve (AUC) were conducted.

Results: The ESC/ERS three-strata model had a lower ability to predict mortality than the ESC/ERS four-strata model, 'SPAHR updated' and 'REVEAL Lite 2'. The ESC/ERS four-strata model divided 'intermediate-risk' patients into two groups with significantly different long-term survival rates and is the easiest applicable tool. Incorporating SSc-specific characteristics did not significantly improve the predictive ability of any model, but a low diffusing capacity of the lung for carbon monoxide (DLCO) was an independent predictor of mortality.

Conclusion: Considering its ability to predict mortality, risk segregation capabilities and clinical applicability, this study provides a rationale for using the simplified ESC/ERS four-strata model at SSc-PAH diagnosis as an alternative to the comprehensive ESC/ERS three-strata model. We propose considering DLCO as an individual prognostic marker in SSc-PAH.

Keywords: observational study; pulmonary arterial hypertension; risk stratification; systemic sclerosis.

Graphical abstract

Figure 1.

Description of the risk stratification tools and calculation of risk scores. ESC/ERS: European Society of Cardiology and European Respiratory Society; SPAHR: Swedish Pulmonary Arterial Hypertension Registry; REVEAL: Registry to Evaluate Early and Long-Term PAH Disease Management; WHO-FC: World Health Organization functional class; 6MWD: 6-min walk distance; NT-proBNP: N-terminal brain natriuretic peptide; SvO₂: mixed-venous oxygen saturation; VO₂: oxygen uptake; VE/VCO₂: ventilatory equivalents for carbon dioxide; TAPSE/sPAP: tricuspid annular plane systolic excursion/systolic pulmonary artery pressure; cMRI: cardiac magnetic resonance imaging; RVEF: right ventricular ejection fraction; SVI: stroke volume index; RVESVI: right ventricular end-systolic volume index; eGFR: estimated glomerular filtration rate. The figure was created using BioRender.com

Figure 2.

(A) Proportion of patients and (B) observed 1-year mortality across risk categories in the four risk stratification tools. ESC/ERS: European Society of Cardiology and European Respiratory Society; SPAHR: Swedish Pulmonary Arterial Hypertension Registry; REVEAL: Registry to Evaluate Early and Long-Term PAH Disease Management. The 1-year mortality rate was determined for patients who were either deceased or had at least a one-year observation period

Figure 3.

Transplant-free survival by risk groups in the four risk stratification tools. (A) ESC/ERS three-strata model, (B) ESC/ERS four-strata model, (C) ‘SPAHR updated’ and (D) ‘REVEAL Lite 2’. P-values for pairwise comparison of the risk groups using the log-rank test. ESC/ERS: European Society of Cardiology and European Respiratory Society; SPAHR: Swedish Pulmonary Arterial Hypertension Registry; REVEAL: Registry to Evaluate Early and Long-Term PAH Disease Management

Figure 4.

Performance of the risk stratification tools in predicting all-cause mortality compared with the ESC/ERS three-strata model (reference) in unadjusted analysis. (A) ESC/ERS four-strata model compared to the reference, (B) ‘SPAHR updated’ compared to the reference and (C) ‘REVEAL Lite 2’ compared to the reference. Predictive abilities were evaluated using area under the ROC curve (AUC) based on univariable Cox regression analysis, and performance was compared to the ESC/ERS three-strata model (reference). P-values represent the statistical significance of differences in predictive performance between the risk stratification tools. The graphs were generated using STATA and assembled in BioRender.com. ESC/ERS: European Society of Cardiology and European Respiratory Society; SPAHR: Swedish Pulmonary Arterial Hypertension Registry; REVEAL: Registry to Evaluate Early and Long-Term PAH Disease Management; AUC: area under the ROC curve

Figure 5.

Impact of risk stratification tools on predicting all-cause mortality in multivariable analysis. (A) ESC/ERS three-strata model (reference), (B) ESC/ERS four-strata model, (C) ‘SPAHR updated’ and (D) ‘REVEAL Lite 2’. The multivariable models are adjusted for age, male sex, pre-existing vascular-targeted therapy, DLCO% predicted, ILD of limited extent and anti-centromere antibodies. Hazard ratios (HRs) and 95% CIs are shown for all variables. HRs for risk groups are referenced to the low-risk group. P-values represent the significance of the HRs obtained from multivariable Cox regression analyses. ESC/ERS: European Society of Cardiology and European Respiratory Society; SPAHR: Swedish Pulmonary Arterial Hypertension Registry; REVEAL: Registry to Evaluate Early and Long-Term PAH Disease Management; DLCO: diffusing capacity of the lung for carbon monoxide; ILD: interstitial lung disease, limited extent; Ab: antibodies; HR: hazard ratio