AB0930 Quantitative Chest Ct in Ild-Ssc Patients with Divergent Risks of Mortality. (15th July 2016)

• Record Type: Journal Article
• Authors: Ariani, A.; Silva, M.; Seletti, V.; Bravi, E.; Saracco, M.; Parisi, S.; De Gennaro, F.; Lumetti, F.; Idolazzi, L.; Caramaschi, P.; Benini, C.; Bodini, F.C.; Scirè, C.A.; Alfieri, V.; Bonati, E.; Lucchini, G.; Aiello, M.; Santilli, D.; Mozzani, F.; Imberti, D.; Arrigoni, E.; Delsante, G.; Michieletti, E.; Pellerito, R.; Fusaro, E.; Chetta, A.A.; Sverzellati, N.
• Is Part Of: Annals of the rheumatic diseases. Volume 75(2016)Supplement 2
• Page Start: 1219
• Page End: 1219
• Publication Date: 2016-07-15
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2016-eular.2995
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: Quantitative analysis of chest CT (QCT) is increasingly applied to characterization of Interstitial Lung Disease (ILD) associated to Systemic Sclerosis (SSc). However, there is no prognostic evidence for QCT in predicting lung detrimental evolution or death. Many Authors proposed composite clinical indexes to predict 1-year mortality. Recently the ILD-GAP index and du Bois index were proven to stratify ILD-SSc patients in outcome-related subgroups. Objectives: The main aim of this study was to compare QCT assessment of SSc-ILD and composite clinical indexes in the selection of patients with high risk of mortality. Methods: Chest CT, anamnestic data and pulmonary function test of 146 patients with SSc were retrospectively collected and ILD-GAP and DuBois score were calculated. Each chest CT underwent a quantitative assessment. Correlation between clinical prediction models and QCT parameters was tested. p<0, 05 was considered statistically significant. Results: All QCT parameters had a statistically different distribution in patients with diverging mortality risk according to both clinical prediction models. The cut-off of QCT parameters were calculated by ROC curve analysis, with statistically significant value as compared to clinical prediction models (AUC >0.7, p<0.0001). Conclusions: QCT assessment of SSc-ILD can distinguish between different mortality risk categories, therefore it yields prognostic value. These findings, together with the operator-independence, strengthen the accuracy of QCT for assessment of SSc-ILD. Disclosure of Interest: None declared