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Inclusion of Synovial Tissue–Derived Characteristics in a Nomogram for the Prediction of Treatment Response in Treatment‐Naive Rheumatoid Arthritis Patients
OBJECTIVE: This study applied a synovitis score obtained during routine care from ultrasound (US)–guided biopsies of synovial tissue (ST) in patients with rheumatoid arthritis (RA) and patients with other inflammatory and noninflammatory joint diseases to identify pretreatment synovial biomarkers as...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8457106/ https://www.ncbi.nlm.nih.gov/pubmed/33750008 http://dx.doi.org/10.1002/art.41726 |
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author | Alivernini, Stefano Tolusso, Barbara Gessi, Marco Gigante, Maria Rita Mannocci, Alice Petricca, Luca Perniola, Simone Di Mario, Clara Bui, Laura Fedele, Anna Laura Capacci, Annunziata Bruno, Dario Peluso, Giusy La Torre, Giuseppe Federico, Francesco Ferraccioli, Gianfranco Gremese, Elisa |
author_facet | Alivernini, Stefano Tolusso, Barbara Gessi, Marco Gigante, Maria Rita Mannocci, Alice Petricca, Luca Perniola, Simone Di Mario, Clara Bui, Laura Fedele, Anna Laura Capacci, Annunziata Bruno, Dario Peluso, Giusy La Torre, Giuseppe Federico, Francesco Ferraccioli, Gianfranco Gremese, Elisa |
author_sort | Alivernini, Stefano |
collection | PubMed |
description | OBJECTIVE: This study applied a synovitis score obtained during routine care from ultrasound (US)–guided biopsies of synovial tissue (ST) in patients with rheumatoid arthritis (RA) and patients with other inflammatory and noninflammatory joint diseases to identify pretreatment synovial biomarkers associated with disease characteristics, and to integrate the findings into a multiparameter nomogram for use in baseline prediction of diagnosis and treatment response in treatment‐naive rheumatoid arthritis (RA) patients. METHODS: The study enrolled a total of 1,015 patients with various autoimmune diseases (545 patients with RA, 167 patients with psoriatic arthritis [PsA], 199 patients with undifferentiated peripheral inflammatory arthritis [UPIA], 18 patients with crystal‐induced arthritis, 26 patients with connective tissue diseases, and 60 patients with osteoarthritis [OA] [as part of the SYNGem cohort]). All patients underwent a US‐guided ST biopsy at baseline, and patients were then stratified according to disease phase. The KSS, along with disease characteristics and clinical outcomes, were incorporated into a nomogram for prediction of achievement of clinical remission in RA patients who were previously naive to treatment. In patients in whom a treat‐to‐target strategy was applied, remission was defined as change in the Disease Activity Score in 28 joints (DAS28) at 6 months after treatment initiation. RESULTS: The KSS significantly differed among RA patients, as well as PsA patients and UPIA patients, when compared to OA patients. In RA, the KSS directly correlated with the DAS28 and was related to autoantibody positivity in treatment‐naive RA patients. Moreover, at baseline, treatment‐naive RA patients achieving 6‐month remission according to DAS28 had a lower KSS, shorter duration of symptoms (very early RA [VERA]), and lower disease activity than treatment‐naive RA patients not achieving remission according to DAS28. Results of logistic regression analysis identified the following synergistic predictive factors of achievement of DAS28‐based disease remission at 6 months: having a short disease duration (VERA), not having high disease activity, and having a KSS of <5 at baseline. A nomogram integrating these baseline clinical and histologic characteristics in treatment‐naive RA patients yielded an up to 81.7% probability of achieving 6‐month remission according to the DAS28. CONCLUSION: The KSS is a reliable tool for synovitis assessment on US‐guided ST biopsy, contingent on the phase of the disease and the autoimmune profile of each patient. This tool could be integrated within a therapeutic response–predictive nomogram for the prediction of treatment response in RA patients who were previously naive to treatment. |
format | Online Article Text |
id | pubmed-8457106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84571062021-09-27 Inclusion of Synovial Tissue–Derived Characteristics in a Nomogram for the Prediction of Treatment Response in Treatment‐Naive Rheumatoid Arthritis Patients Alivernini, Stefano Tolusso, Barbara Gessi, Marco Gigante, Maria Rita Mannocci, Alice Petricca, Luca Perniola, Simone Di Mario, Clara Bui, Laura Fedele, Anna Laura Capacci, Annunziata Bruno, Dario Peluso, Giusy La Torre, Giuseppe Federico, Francesco Ferraccioli, Gianfranco Gremese, Elisa Arthritis Rheumatol Rheumatoid Arthritis OBJECTIVE: This study applied a synovitis score obtained during routine care from ultrasound (US)–guided biopsies of synovial tissue (ST) in patients with rheumatoid arthritis (RA) and patients with other inflammatory and noninflammatory joint diseases to identify pretreatment synovial biomarkers associated with disease characteristics, and to integrate the findings into a multiparameter nomogram for use in baseline prediction of diagnosis and treatment response in treatment‐naive rheumatoid arthritis (RA) patients. METHODS: The study enrolled a total of 1,015 patients with various autoimmune diseases (545 patients with RA, 167 patients with psoriatic arthritis [PsA], 199 patients with undifferentiated peripheral inflammatory arthritis [UPIA], 18 patients with crystal‐induced arthritis, 26 patients with connective tissue diseases, and 60 patients with osteoarthritis [OA] [as part of the SYNGem cohort]). All patients underwent a US‐guided ST biopsy at baseline, and patients were then stratified according to disease phase. The KSS, along with disease characteristics and clinical outcomes, were incorporated into a nomogram for prediction of achievement of clinical remission in RA patients who were previously naive to treatment. In patients in whom a treat‐to‐target strategy was applied, remission was defined as change in the Disease Activity Score in 28 joints (DAS28) at 6 months after treatment initiation. RESULTS: The KSS significantly differed among RA patients, as well as PsA patients and UPIA patients, when compared to OA patients. In RA, the KSS directly correlated with the DAS28 and was related to autoantibody positivity in treatment‐naive RA patients. Moreover, at baseline, treatment‐naive RA patients achieving 6‐month remission according to DAS28 had a lower KSS, shorter duration of symptoms (very early RA [VERA]), and lower disease activity than treatment‐naive RA patients not achieving remission according to DAS28. Results of logistic regression analysis identified the following synergistic predictive factors of achievement of DAS28‐based disease remission at 6 months: having a short disease duration (VERA), not having high disease activity, and having a KSS of <5 at baseline. A nomogram integrating these baseline clinical and histologic characteristics in treatment‐naive RA patients yielded an up to 81.7% probability of achieving 6‐month remission according to the DAS28. CONCLUSION: The KSS is a reliable tool for synovitis assessment on US‐guided ST biopsy, contingent on the phase of the disease and the autoimmune profile of each patient. This tool could be integrated within a therapeutic response–predictive nomogram for the prediction of treatment response in RA patients who were previously naive to treatment. John Wiley and Sons Inc. 2021-08-09 2021-09 /pmc/articles/PMC8457106/ /pubmed/33750008 http://dx.doi.org/10.1002/art.41726 Text en © 2021 The Authors. Arthritis & Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Rheumatoid Arthritis Alivernini, Stefano Tolusso, Barbara Gessi, Marco Gigante, Maria Rita Mannocci, Alice Petricca, Luca Perniola, Simone Di Mario, Clara Bui, Laura Fedele, Anna Laura Capacci, Annunziata Bruno, Dario Peluso, Giusy La Torre, Giuseppe Federico, Francesco Ferraccioli, Gianfranco Gremese, Elisa Inclusion of Synovial Tissue–Derived Characteristics in a Nomogram for the Prediction of Treatment Response in Treatment‐Naive Rheumatoid Arthritis Patients |
title | Inclusion of Synovial Tissue–Derived Characteristics in a Nomogram for the Prediction of Treatment Response in Treatment‐Naive Rheumatoid Arthritis Patients |
title_full | Inclusion of Synovial Tissue–Derived Characteristics in a Nomogram for the Prediction of Treatment Response in Treatment‐Naive Rheumatoid Arthritis Patients |
title_fullStr | Inclusion of Synovial Tissue–Derived Characteristics in a Nomogram for the Prediction of Treatment Response in Treatment‐Naive Rheumatoid Arthritis Patients |
title_full_unstemmed | Inclusion of Synovial Tissue–Derived Characteristics in a Nomogram for the Prediction of Treatment Response in Treatment‐Naive Rheumatoid Arthritis Patients |
title_short | Inclusion of Synovial Tissue–Derived Characteristics in a Nomogram for the Prediction of Treatment Response in Treatment‐Naive Rheumatoid Arthritis Patients |
title_sort | inclusion of synovial tissue–derived characteristics in a nomogram for the prediction of treatment response in treatment‐naive rheumatoid arthritis patients |
topic | Rheumatoid Arthritis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8457106/ https://www.ncbi.nlm.nih.gov/pubmed/33750008 http://dx.doi.org/10.1002/art.41726 |
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