• Eur. J. Intern. Med. · Jun 2020

    Computed tomography assessment of evolution of interstitial lung disease in systemic sclerosis: Comparison of two scoring systems.

    • Fausto Salaffi, Marina Carotti, Marika Tardella, Marco Di Carlo, Paolo Fraticelli, Colomba Fischetti, Andrea Giovagnoni, and Armando Gabrielli.
    • Rheumatological Clinic, Ospedale Carlo Urbani Jesi, Università Politecnica delle Marche, Ancona, Italy. Electronic address: fausto.salaffi@gmail.com.
    • Eur. J. Intern. Med. 2020 Jun 1; 76: 71-75.

    BackgroundThe aim of this study was to evaluate and compare the internal and external responsiveness of a computed-aided method (CaM) with a conventional visual reader-based score (CoVR) to measure interstitial lung disease (ILD) in patients with systemic sclerosis (SSc) on high resolution computed tomography (HRCT).MethodsForty-five patients were evaluated in this retrospective cohort. HRCTs were collected at baseline and after 1 year. HRCT abnormalities were evaluated according to a CoVR (Warrick's method) and a quantitative CaM. Internal 1-year responsiveness was tested with a standardized mean response (SRM). Analyses of the receiver operating characteristic curves (ROCs) evaluated the sensitivity and specificity of the two methods to discriminate between clinically relevant progression and no relevant progression, using expert judgment as the gold standard (external responsiveness).ResultsIn one year, lung involvement was stable/improved in 17 of the 45 patients (37.8%) and worsened in 28 patients (62.2%). HRCT scores changed moderately over the follow-up period. Using SFM, CaM was significantly more responsive in detecting changes due to treatment than the CoVR method. Likewise, in the analysis of the ROC curve, CaM scores showed the highest performance (AUC ROC CaM vs. CoVR, 0.951 vs. 0.807; p = 0.0065).ConclusionQuantitative analysis of CaM was more responsive than the CoVR method to accurately evaluate and monitor SSc-ILD progression or response to therapy.Copyright © 2020. Published by Elsevier B.V.

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