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Revised European Scleroderma Trials and Research Group Activity Index is the best predictor of short-term severity accrual.
Fasano, Serena; Riccardi, Antonella; Messiniti, Valentina; Caramaschi, Paola; Rosato, Edoardo; Maurer, Britta; Smith, Vanessa; Siegert, Elise; De Langhe, Ellen; Riccieri, Valeria; Airó, Paolo; Mihai, Carina; Avouac, Jerome; Zanatta, Elisabetta; Walker, Ulrich A; Iannone, Florenzo; García De la Peña Lefebvre, Paloma; Distler, Jörg H W; Vacca, Alessandra; Distler, Oliver; Kowal-Bielecka, Otylia; Allanore, Yannick; Valentini, Gabriele.
Afiliação
  • Fasano S; Department of Precision Medicine, Section of Rheumatology, University of Campania Luigi Vanvitelli, Naples, Italy serena.fasano@unicampania.it.
  • Riccardi A; Department of Precision Medicine, Section of Rheumatology, University of Campania Luigi Vanvitelli, Naples, Italy.
  • Messiniti V; Department of Precision Medicine, Section of Rheumatology, University of Campania Luigi Vanvitelli, Naples, Italy.
  • Caramaschi P; Department of Rheumatology, University of Verona, Verona, Italy.
  • Rosato E; Dipartimento di Medicina Traslazionale e di Precisione, Sapienza University of Rome, Roma, Italy.
  • Maurer B; Department of Rheumatology, University Hospital Zurich, Zurich, Switzerland.
  • Smith V; Department of Rheumatology, University Hospital Ghent, Gent, Belgium.
  • Siegert E; Department of Rheumatology, Charit University Hospital, Berlin, Germany.
  • De Langhe E; Department of Development and Regeneration, Laboratory of Tissue Homeostasis and Disease, Skeletal Biology and Engineering Research Center, KU Leuven, Leuven, Belgium.
  • Riccieri V; Clinical Medicine and Therapy, Sapienza University of Rome, Rome, Italy.
  • Airó P; Rheumatology and Clinical Immunology Department, Spedali Civili di Brescia, Brescia, Italy.
  • Mihai C; Department of Rheumatology, Carol Davila University of Medicine and Pharmacy, Bucarest, Romania.
  • Avouac J; Department of Rheumatology, Paris Descartes University, Rheumatology A and INSER U1016, Cochin Hospital, Paris, France.
  • Zanatta E; Dipartimento di Medicina, DIMED, Universita degli Studi di Padova, Padova, Italy.
  • Walker UA; Department of Rheumatology, Basel University, Basel, Switzerland.
  • Iannone F; Department of Rheumatology, University of Bari, Bari, Italy.
  • García De la Peña Lefebvre P; Department of Rheumatology, Ramon y Cajal University Hospital, Madrid, Spain.
  • Distler JHW; Department of Internal Medicine III, University of Erlangen, Erlangen, Germany.
  • Vacca A; Chair and Rheumatology Unit, University Clinic AOU Cagliari, Monserrato, Italy.
  • Distler O; Department of Rheumatology, University Hospital Zurich, Zurich, Switzerland.
  • Kowal-Bielecka O; Department of Rheumatology and Internal Medicine, Medical University of Bialystok, Bialystok, Poland.
  • Allanore Y; Department of Rheumatology, Paris Descartes University, Rheumatology A and INSER U1016, Cochin Hospital, Paris, France.
  • Valentini G; Department of Precision Medicine, Section of Rheumatology, University of Campania Luigi Vanvitelli, Naples, Italy.
Ann Rheum Dis ; 78(12): 1681-1685, 2019 12.
Article em En | MEDLINE | ID: mdl-31422354
ABSTRACT

BACKGROUND:

The European Scleroderma Trials and Research Group (EUSTAR) recently developed a preliminarily revised activity index (AI) that performed better than the European Scleroderma Study Group Activity Index (EScSG-AI) in systemic sclerosis (SSc).

OBJECTIVE:

To assess the predictive value for short-term disease severity accrual of the EUSTAR-AI, as compared with those of the EScSG-AI and of known adverse prognostic factors.

METHODS:

Patients with SSc from the EUSTAR database with a disease duration from the onset of the first non-Raynaud sign/symptom ≤5 years and a baseline visit between 2003 and 2014 were first extracted. To capture the disease activity variations over time, EUSTAR-AI and EScSG-AI adjusted means were calculated. The primary outcome was disease progression defined as a Δ≥1 in the Medsger's severity score and in distinct items at the 2-year follow-up visit. Logistic regression analysis was carried out to identify predictive factors.

RESULTS:

549 patients were enrolled. At multivariate analysis, the EUSTAR-AI adjusted mean was the only predictor of any severity accrual and of that of lung and heart, skin and peripheral vascular disease over 2 years.

CONCLUSION:

The adjusted mean EUSTAR-AI has the best predictive value for disease progression and development of severe organ involvement over time in SSc.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Escleroderma Sistêmico / Ensaios Clínicos como Assunto Tipo de estudo: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male / Middle aged País/Região como assunto: Europa Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Escleroderma Sistêmico / Ensaios Clínicos como Assunto Tipo de estudo: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male / Middle aged País/Região como assunto: Europa Idioma: En Ano de publicação: 2019 Tipo de documento: Article