eCite Digital Repository

A comparison of the predictive accuracy of three screening models for pulmonary arterial hypertension in systemic sclerosis

Citation

Hao, Y and Thakkar, V and Stevens, W and Morrisroe, K and Prior, D and Rabusa, C and Youssef, P and Gabbay, E and Roddy, J and Walker, J and Zochling, J and Sahhar, J and Nash, P and Lester, S and Rischmueller, M and Proudman, SM and Nikpour, M, A comparison of the predictive accuracy of three screening models for pulmonary arterial hypertension in systemic sclerosis, Arthritis Research & Therapy, 17, (1) Article 7. ISSN 1478-6362 (2015) [Refereed Article]


Preview
PDF
300Kb
  

Copyright Statement

Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/

DOI: doi:10.1186/s13075-015-0517-5

Abstract

Introduction: There is evidence that early screening for pulmonary arterial hypertension (PAH) in systemic sclerosis (SSc) improves outcomes. We compared the predictive accuracy of two recently published screening algorithms (DETECT 2013 and Australian Scleroderma Interest Group (ASIG) 2012) for SSc-associated PAH (SSc-PAH) with the commonly used European Society of Cardiology/European Respiratory Society (ESC/ERS 2009) guidelines.

Methods: We included 73 consecutive SSc patients with suspected PAH undergoing right heart catheterization (RHC). The three screening models were applied to each patient. For each model, contingency table analysis was used to determine sensitivity, specificity, and positive (PPV) and negative (NPV) predictive values for PAH. These properties were also evaluated in an 'alternate scenario analysis' in which the prevalence of PAH was set at 10%.

Results: RHC revealed PAH in 27 (36.9%) patients. DETECT and ASIG algorithms performed equally in predicting PAH with sensitivity and NPV of 100%. The ESC/ERS guidelines had sensitivity of 96.3% and NPV of only 91%, missing one case of PAH. these guidelines could not be applied to three patients who had absent tricuspid regurgitant (TR) jet. The ASIG algorithm had the highest specificity (54.5%). With PAH prevalence set at 10%, the NPV of the models was unchanged, but the PPV dropped to less than 20%.

Conclusions: In this cohort, the DETECT and ASIG algorithms out-perform the ESC/ERS guidelines, detecting all patients with PAH. The ESC/ERS guidelines have limitations in the absence of a TR jet. Ultimately, the choice of SSc-PAH screening algorithm will also depend on cost and ease of application.

Item Details

Item Type:Refereed Article
Keywords:scleroderma, pulmonary hypertension, prediction model
Research Division:Medical and Health Sciences
Research Group:Clinical Sciences
Research Field:Rheumatology and Arthritis
Objective Division:Health
Objective Group:Clinical Health (Organs, Diseases and Abnormal Conditions)
Objective Field:Skeletal System and Disorders (incl. Arthritis)
Author:Zochling, J (Dr Jane Zochling)
ID Code:98078
Year Published:2015
Web of Science® Times Cited:15
Deposited By:Menzies Institute for Medical Research
Deposited On:2015-01-31
Last Modified:2017-11-03
Downloads:58 View Download Statistics

Repository Staff Only: item control page