Stratification in systemic sclerosis according to autoantibody status versus skin involvement : a study of the prospective EUSTAR cohort
Copyright © 2022 Elsevier Ltd. All rights reserved..
BACKGROUND: The current subclassification of systemic sclerosis into cutaneous subtypes does not fully capture the heterogeneity of the disease. We aimed to compare the performances of stratification into LeRoy's cutaneous subtypes versus stratification by autoantibody status in systemic sclerosis.
METHODS: For this cohort study, we assessed people with systemic sclerosis in the multicentre international European Scleroderma Trials and Research (EUSTAR) database. Individuals positive for systemic-sclerosis autoantibodies of two specificities were excluded, and remaining individuals were classified by cutaneous subtype, according to their systemic sclerosis-specific autoantibodies, or both. We assessed the performance of each model to predict overall survival, progression-free survival, disease progression, and different organ involvement. The three models were compared by use of the area under the curve (AUC) of the receiver operating characteristic and the net reclassification improvement (NRI). Missing data were imputed.
FINDINGS: We assessed the database on July 26, 2019. Of 16 939 patients assessed for eligibility, 10 711 patients were included: 1647 (15·4%) of 10 709 were male, 9062 (84·6%) were female, mean age was 54·4 (SD 13·8) years, and mean disease duration was 7·9 (SD 8·2) years. Information regarding cutaneous subtype was available for 10 176 participants and antibody data were available for 9643 participants. In the prognostic analysis, there was no difference in AUC for overall survival (0·82, 95% CI 0·81-0·84 for cutaneous only vs 0·84, 0·82-0·85 for antibody only vs 0·84, 0·83-0·86 for combined) or for progression-free survival (0·70, 0·69-0·71 vs 0·71, 0·70-0·72 vs 0·71, 0·70-0·72). However, at 4 years the NRI showed substantial improvement for the antibody-only model compared with the cutaneous-only model in prediction of overall survival (0·57, 0·46-0·71 for antibody only vs 0·29, 0·19-0·39 for cutaneous only) and disease progression (0·36, 0·29-0·46 vs 0·21, 0·14-0·28). The antibody-only model did better than the cutaneous-only model in predicting renal crisis (AUC 0·72, 0·70-0·74 for antibody only vs 0·66, 0·64-0·69 for cutaneous only) and lung fibrosis leading to restrictive lung function (AUC 0·76, 0·75-0·77 vs 0·71, 0·70-0·72). The combined model improved the prediction of digital ulcers and elevated systolic pulmonary artery pressure, but did poorly for cardiac involvement.
INTERPRETATION: The autoantibody-only model outperforms cutaneous-only subsetting for risk stratifying people with systemic sclerosis in the EUSTAR cohort. Physicians should be aware of these findings at the time of decision making for patient management.
FUNDING: World Scleroderma Foundation.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2022 |
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Erschienen: |
2022 |
Enthalten in: |
Zur Gesamtaufnahme - volume:4 |
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Enthalten in: |
The Lancet. Rheumatology - 4(2022), 11 vom: 01. Nov., Seite e785-e794 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Elhai, Muriel [VerfasserIn] |
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Anmerkungen: |
Date Completed 26.01.2024 Date Revised 26.01.2024 published: Print Citation Status MEDLINE |
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doi: |
10.1016/S2665-9913(22)00217-X |
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funding: |
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PPN (Katalog-ID): |
NLM36756372X |
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520 | |a Copyright © 2022 Elsevier Ltd. All rights reserved. | ||
520 | |a BACKGROUND: The current subclassification of systemic sclerosis into cutaneous subtypes does not fully capture the heterogeneity of the disease. We aimed to compare the performances of stratification into LeRoy's cutaneous subtypes versus stratification by autoantibody status in systemic sclerosis | ||
520 | |a METHODS: For this cohort study, we assessed people with systemic sclerosis in the multicentre international European Scleroderma Trials and Research (EUSTAR) database. Individuals positive for systemic-sclerosis autoantibodies of two specificities were excluded, and remaining individuals were classified by cutaneous subtype, according to their systemic sclerosis-specific autoantibodies, or both. We assessed the performance of each model to predict overall survival, progression-free survival, disease progression, and different organ involvement. The three models were compared by use of the area under the curve (AUC) of the receiver operating characteristic and the net reclassification improvement (NRI). Missing data were imputed | ||
520 | |a FINDINGS: We assessed the database on July 26, 2019. Of 16 939 patients assessed for eligibility, 10 711 patients were included: 1647 (15·4%) of 10 709 were male, 9062 (84·6%) were female, mean age was 54·4 (SD 13·8) years, and mean disease duration was 7·9 (SD 8·2) years. Information regarding cutaneous subtype was available for 10 176 participants and antibody data were available for 9643 participants. In the prognostic analysis, there was no difference in AUC for overall survival (0·82, 95% CI 0·81-0·84 for cutaneous only vs 0·84, 0·82-0·85 for antibody only vs 0·84, 0·83-0·86 for combined) or for progression-free survival (0·70, 0·69-0·71 vs 0·71, 0·70-0·72 vs 0·71, 0·70-0·72). However, at 4 years the NRI showed substantial improvement for the antibody-only model compared with the cutaneous-only model in prediction of overall survival (0·57, 0·46-0·71 for antibody only vs 0·29, 0·19-0·39 for cutaneous only) and disease progression (0·36, 0·29-0·46 vs 0·21, 0·14-0·28). The antibody-only model did better than the cutaneous-only model in predicting renal crisis (AUC 0·72, 0·70-0·74 for antibody only vs 0·66, 0·64-0·69 for cutaneous only) and lung fibrosis leading to restrictive lung function (AUC 0·76, 0·75-0·77 vs 0·71, 0·70-0·72). The combined model improved the prediction of digital ulcers and elevated systolic pulmonary artery pressure, but did poorly for cardiac involvement | ||
520 | |a INTERPRETATION: The autoantibody-only model outperforms cutaneous-only subsetting for risk stratifying people with systemic sclerosis in the EUSTAR cohort. Physicians should be aware of these findings at the time of decision making for patient management | ||
520 | |a FUNDING: World Scleroderma Foundation | ||
650 | 4 | |a Journal Article | |
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700 | 1 | |a de Vries-Bouwstra, Jeska |e verfasserin |4 aut | |
700 | 1 | |a Riemekasten, Gabriela |e verfasserin |4 aut | |
700 | 1 | |a Distler, Jörg H W |e verfasserin |4 aut | |
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700 | 1 | |a Del Galdo, Francesco |e verfasserin |4 aut | |
700 | 1 | |a Mendoza, Fabian A |e verfasserin |4 aut | |
700 | 1 | |a Furst, Daniel E |e verfasserin |4 aut | |
700 | 1 | |a de la Puente, Carlos |e verfasserin |4 aut | |
700 | 1 | |a Hoffmann-Vold, Anna-Maria |e verfasserin |4 aut | |
700 | 1 | |a Gabrielli, Armando |e verfasserin |4 aut | |
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700 | 1 | |a Bloch-Queyrat, Coralie |e verfasserin |4 aut | |
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700 | 1 | |a Matucci Cerinic, Marco |e investigator |4 oth | |
700 | 1 | |a Walker, Ulrich |e investigator |4 oth | |
700 | 1 | |a Iannone, Florenzo |e investigator |4 oth | |
700 | 1 | |a Jordan, Suzana |e investigator |4 oth | |
700 | 1 | |a Becvar, Radim |e investigator |4 oth | |
700 | 1 | |a Kowal Bielecka, Otylia |e investigator |4 oth | |
700 | 1 | |a Cutolo, Maurizio |e investigator |4 oth | |
700 | 1 | |a Cuomo, Giovanna |e investigator |4 oth | |
700 | 1 | |a Kedor, Claudia |e investigator |4 oth | |
700 | 1 | |a Rednic, Simona |e investigator |4 oth | |
700 | 1 | |a Avouac, Jérome |e investigator |4 oth | |
700 | 1 | |a Vlachoyiannopoulos, P |e investigator |4 oth | |
700 | 1 | |a Montecucco, C |e investigator |4 oth | |
700 | 1 | |a Stork, Jiri |e investigator |4 oth | |
700 | 1 | |a Inanc, Murat |e investigator |4 oth | |
700 | 1 | |a Carreira, Patricia E |e investigator |4 oth | |
700 | 1 | |a Novak, Srdan |e investigator |4 oth | |
700 | 1 | |a Czirják, László |e investigator |4 oth | |
700 | 1 | |a Iudici, Michele |e investigator |4 oth | |
700 | 1 | |a Kucharz, Eugene J |e investigator |4 oth | |
700 | 1 | |a Zanatta, Elisabetta |e investigator |4 oth | |
700 | 1 | |a Perdan-Pirkmajer, Katja |e investigator |4 oth | |
700 | 1 | |a Coleiro, Bernard |e investigator |4 oth | |
700 | 1 | |a Moroncini, Gianluca |e investigator |4 oth | |
700 | 1 | |a Farge Bancel, Dominique |e investigator |4 oth | |
700 | 1 | |a Airò, Paolo |e investigator |4 oth | |
700 | 1 | |a Hesselstrand, Roger |e investigator |4 oth | |
700 | 1 | |a Radic, Mislav |e investigator |4 oth | |
700 | 1 | |a Braun-Moscovici, Yolanda |e investigator |4 oth | |
700 | 1 | |a Lo Monaco, Andrea |e investigator |4 oth | |
700 | 1 | |a Hunzelmann, Nicolas |e investigator |4 oth | |
700 | 1 | |a Pellerito, Raffaele |e investigator |4 oth | |
700 | 1 | |a Giollo, Alessandro |e investigator |4 oth | |
700 | 1 | |a Morovic-Vergles, Jadranka |e investigator |4 oth | |
700 | 1 | |a Denton, Christopher |e investigator |4 oth | |
700 | 1 | |a Vonk, Madelon |e investigator |4 oth | |
700 | 1 | |a Damjanov, Nemanja |e investigator |4 oth | |
700 | 1 | |a Henes, Jörg |e investigator |4 oth | |
700 | 1 | |a Ortiz Santamaria, Vera |e investigator |4 oth | |
700 | 1 | |a Heitmann, Stefan |e investigator |4 oth | |
700 | 1 | |a Krasowska, Dorota |e investigator |4 oth | |
700 | 1 | |a Hasler, Paul |e investigator |4 oth | |
700 | 1 | |a Kohm, Michaela |e investigator |4 oth | |
700 | 1 | |a Foeldvari, Ivan |e investigator |4 oth | |
700 | 1 | |a Bajocchi, Gianluigi |e investigator |4 oth | |
700 | 1 | |a Salvador, Maria João |e investigator |4 oth | |
700 | 1 | |a Stamenkovic, Bojana |e investigator |4 oth | |
700 | 1 | |a Selmi, Carlo Francesco |e investigator |4 oth | |
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700 | 1 | |a Sobrino Grande, Cristina |e investigator |4 oth | |
700 | 1 | |a Midtvedt, Øyvind |e investigator |4 oth | |
700 | 1 | |a Launay, David |e investigator |4 oth | |
700 | 1 | |a Riccieri, Valeria |e investigator |4 oth | |
700 | 1 | |a Ionescu, Ruxandra Maria |e investigator |4 oth | |
700 | 1 | |a Sha, Ami |e investigator |4 oth | |
700 | 1 | |a Gheorghiu, Ana Maria |e investigator |4 oth | |
700 | 1 | |a Sunderkötter, Cord |e investigator |4 oth | |
700 | 1 | |a Ingegnoli, Francesca |e investigator |4 oth | |
700 | 1 | |a Mouthon, Luc |e investigator |4 oth | |
700 | 1 | |a Smith, Vanessa |e investigator |4 oth | |
700 | 1 | |a Cantatore, Francesco Paolo |e investigator |4 oth | |
700 | 1 | |a Ullman, Susanne |e investigator |4 oth | |
700 | 1 | |a Alberto von Mühlen, Carlos |e investigator |4 oth | |
700 | 1 | |a Pozzi, Maria Rosa |e investigator |4 oth | |
700 | 1 | |a Eyerich, Kilian |e investigator |4 oth | |
700 | 1 | |a Wiland, Piotr |e investigator |4 oth | |
700 | 1 | |a Vanthuyne, Marie |e investigator |4 oth | |
700 | 1 | |a Alegre-Sancho, Juan Jose |e investigator |4 oth | |
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