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Enregistrement W4411429311 · doi:10.1016/j.ard.2025.05.321

OP0319 LUNG TRANSPLANT OUTCOMES IN PATIENTS WITH MYOSITIS- AND SYSTEMIC SCLEROSIS-ASSOCIATED INTERSTITIAL LUNG DISEASE COMPARED TO IDIOPATHIC PULMONARY FIBROSIS: A MULTICENTRIC RETROSPECTIVE ANALYSIS

2025· article· en· W4411429311 sur OpenAlexaffabout
Naveed Saleh, Anna Marie Chang, Aibing Yu, D. Seyed-Jalaledin, S. Hoa, Robert D. Levy, Jennifer M. Wilson, C. Poirier, John Yee, James J. Choi, Océane Landon‐Cardinal, Hyungjin Kim, Kun Huang

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueMedical Imaging and Pathology Studies
Établissements canadiensResearch CanadaCentre Hospitalier de l’Université de MontréalUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésMedicineInterstitial lung diseaseIdiopathic pulmonary fibrosisMyositisPulmonary fibrosisLung fibrosisLungScleroderma (fungus)FibrosisRetrospective cohort studyPathologyInternal medicineLung diseaseConnective tissue diseaseDiseaseAutoimmune disease

Résumé

récupéré en direct d'OpenAlex

Background: Interstitial lung disease (ILD) is a frequent complication of idiopathic inflammatory myositis (IIM) and systemic sclerosis (SSc), associated with significant morbidity and mortality. Pulmonary manifestations range from subclinical ILD to rapidly progressive respiratory failure. ILD affects 40–50% of myositis patients, often presenting as part of antisynthetase syndrome (ASyS) or anti-melanoma differentiation-associated protein 5 (MDA5) dermatomyositis, and up to 60% of SSc patients, particularly those with anti-Scl70 antibodies. Despite advances in immunosuppressive and antifibrotic agents, many progress to end-stage respiratory failure and may require lung transplantation. Unlike idiopathic pulmonary fibrosis (IPF), data on lung transplant outcomes in patients with IIM and SSc remain limited. Informing on the outcomes and challenges of lung transplantation in this specific patient population is critical for tailoring strategies and ultimately improve patients' survival and quality of life. Objectives: The aim of this study was to compare the clinical characteristics and post-lung transplant outcomes in patients with IIM and SSc to those with IPF. Methods: We retrospectively analyzed clinical data collected in patients with ILD who underwent lung transplant between January 1, 2014 and April 30, 2024 at the British Columbia (BC) lung transplant center and since January 1, 2012 at the Centre hospitalier de l'Université de Montréal ILD clinic. Patients with IIM and SSc according to the 2017 and 2013 ACR/EULAR classification criteria were included. Additionally, IPF controls from the BC cohort meeting the 2022 Official ATS/ERS/JRS/ALAT Clinical Practice Guideline were also included. Univariant analyses were performed for continuous and categorical data. Continuous variables were analyzed using the Kruskal-Wallis test, followed by post-hoc pairwise comparisons with Dunn's test for significant results. Categorical variables were assessed using the Chi-squared test, with pairwise comparisons conducted using Fisher's Exact test and Bonferroni correction for multiple comparisons. Statistical significance was defined as p < 0.05. Results: A total of 18 patients with IIM, 23 with SSc, and 64 with IPF were included. Characteristics of patients at baseline before lung transplant, and short- and long-term outcomes following the procedure are presented in Table 1 and 2 respectively. Median post-lung transplantation follow-up durations were 3.5 years (IQR 1.8-5.8) for IIM, 2.1 years (IQR 1.0-5.1) for SSc, and 3.5 years (IQR 2.1-6.2) for IPF. In the 18 IIM patients, 50% was identified as anti-MDA5 dermatomyositis, 39% as anti-synthetase syndrome; 50% had anti-Ro52. In the 23 SSc patients, anti-Scl-70 was found in 35%, and anti-centromere in 12%. Patients with IIM and SSc were younger at the time of ILD diagnosis and lung transplantation, more likely to be female, less likely to have a smoking history, and had fewer comorbidities compared to those with IPF. Patients with SSc had significantly lower diffusing capacity for carbon monoxide (DLCO) and a longer ILD disease duration before lung transplant compared to IIM and IPF patients. IIM and SSc patients were more exposed to immunosuppressants, whereas IPF patients received more antifibrotics. Additionally, IIM patients more frequently required intensive care unit (ICU) and emergency transplantation. In almost all IPF cases, usual interstitial pneumonia (UIP) was the dominant pathology identified on explant. Nonspecific interstitial pneumonia (NSIP) was more frequently observed in SSc and IIM, with organizing pneumonia (OP) and mixed NSIP/OP only seen in IIM cases. Post-transplant, there was no significant difference in 1-year survival or cumulative survival at the last follow-up among the three groups. However, IIM patients required significantly longer post-transplant ICU and hospital care compared to those with SSc and IPF. At the 1-year follow-up, forced vital capacity (FVC) was significantly lower in SSc and IIM patients compared to IPF. However, no significant differences were observed in DLCO, rates of acute rejection, or hospitalizations due to infections. At the last follow-up, the rates of chronic lung allograft dysfunction (CLAD) or post-transplant malignancies were comparable between the groups. Conclusion: This study highlights key differences in baseline characteristics, explant pathology, and post-transplant outcomes in myositis and SSc in comparison to IPF. While survival, risk of acute and chronic rejection, infections, and post-transplant malignancies were comparable across the three groups, distinctive differences were observed. Patients with myositis were more likely to have rapidly progressive ILD, leading to increased ICU care before transplantation, a higher likelihood of emergency transplantation, and prolonged ICU and hospital stays post-transplant. Furthermore, myositis and SSc were associated with unique explant pathology and lower FVC at 1-year follow-up compared to IPF. These findings emphasize the need for tailored management strategies to optimize outcomes in these distinct patient populations. This study is the first to report short-term and long-term lung transplant outcomes in patients with myositis and SSc, compared to the more commonly studied IPF. REFERENCES: NIL . Acknowledgements: Drs. Chang, Saleh and Yu contributed equally to this manuscript. Drs. Kim and Huang contributed equally to this manuscript. We thank the support from Fresenius Kabi and Pfizer in this investigator initiated clinical research project. Disclosure of Interests: Navid Saleh: None declared, Angela Chang: None declared, Alec Yu: None declared, Darya Seyed-Jalaledin: None declared, Sabrina Hoa: None declared, Robert Levy: None declared, Jennifer Wilson: None declared, Charles Poirier: None declared, John Yee: None declared, James Choi: None declared, Océane Landon-Cardinal: None declared, Hyein Kim: None declared, Kun Huang Fresenius Kabi, Novartis, Abbvie, I received $10,000 canadian dollars from Fresenius Kabi and Pfizer each for investigator initiated research projects. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,022
Score d'incertitude au seuil0,581

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,278
Écart entre enseignants0,263 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission2
Résumé présentoui

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