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Enregistrement W4411401415 · doi:10.1016/j.ard.2025.05.499

POS0111 THE LACK OF ASSOCIATION BETWEEN CUMULATIVE METHOTREXATE DOSE AND LIVER FIBROSIS IN PSORIATIC ARTHRITIS: A COHORT STUDY

2025· article· en· W4411401415 sur OpenAlexaff
F. Kharouf, Parag Mehta, V. Carrizo Abarza, Sheng Gao, D. Periera, Dafna Gladman, D. Poddubnyy, V. Chandran

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueSpondyloarthritis Studies and Treatments
Établissements canadiensKrembil Foundation
Organismes subventionnairesnon disponible
Mots-clésMedicinePsoriatic arthritisMethotrexateCohortLiver fibrosisInternal medicineAntirheumatic AgentsArthritisOncologyFibrosisDermatology

Résumé

récupéré en direct d'OpenAlex

Background: Several studies have suggested an association between the cumulative methotrexate dose and liver fibrosis in patients with psoriatic disease. However, these studies are primarily derived from the psoriasis literature and many did not account for potential confounding factors. Additionally, some analyses have challenged this association, raising questions about its validity. Objectives: This study aimed to explore the proportion of patients with psoriatic arthritis (PsA) who have liver fibrosis and identify the factors associated with its occurrence, with a particular focus on the cumulative methotrexate dose and metabolic factors. Methods: We analyzed data from a prospective observational cohort of PsA patients. We identified cases of liver fibrosis based on the Aspartate Aminotransferase to Platelet Ratio Index (APRI), a non-invasive marker used to assess liver fibrosis in hepatitis C virus-infected patients and other liver diseases [1–3]. A cutoff of >0.7 was used to denote the presence of liver fibrosis [1]. We performed univariable and multivariable generalized estimating equations (GEE) analysis to model the impact of cumulative methotrexate dose on liver fibrosis. The analysis was adjusted for multiple confounders, including age, sex, PsA duration, calendar time, alcohol consumption (none, socially, and daily), hepatitis (viral, alcohol-induced, drug-induced, and autoimmune), presence of inflammatory bowel disease, human immunodeficiency virus infection, or celiac disease, use of non-steroidal anti-inflammatory drugs, and use of leflunomide or sulfasalazine. Importantly, the analysis also included factors reflective of metabolic-associated steatotic liver disease (MASLD), namely body mass index (BMI), diabetes mellitus, and hyperlipidemia, as well as disease activity and therapy-related variables, including Disease Activity Index for Psoriatic Arthritis (DAPSA) and use of biologic or targeted synthetic disease-modifying anti-rheumatic drugs (DMARDs). Results: A total of 1,314 patients were included in the study, with a mean age of 44.4 (SD 13.1) years and a median disease duration of 2.5 [IQR: 0.7, 8.1] years at baseline (clinic entry) (Table 1). Of these, 375 (28.5%) patients were receiving methotrexate at clinic entry, while 763 (58.1%) had ever received the medication. The median cumulative methotrexate dose of the overall cohort at baseline was 0.0 [IQR: 0.0, 115.0] mg, and for those who had ever taken methotrexate, the median cumulative dose at the last visit was 4696.1 [IQR: 1304.5, 13849.9] mg. Forty (3.3%) of the patients had an abnormal APRI at baseline, indicating liver fibrosis, while 154 (11.7%) developed liver fibrosis during follow-up at a median of 5.6 [IQR: 2.0, 11.1] years from baseline. In the multivariable GEE analysis (Table 2), adjusted for the confounders mentioned above, cumulative methotrexate dose was not independently associated with the occurrence of liver fibrosis (OR 0.99, 95% CI 0.98–1.01). However, higher BMI (OR 1.03, 95% CI 1.00–1.05) and diabetes mellitus (OR 5.03, 95% CI 2.19–11.56) showed a significant association. Conclusion: Liver fibrosis may occur in patients with PsA. Metabolic factors, such as high BMI and diabetes mellitus, rather than the cumulative methotrexate dose, are associated with its occurrence, highlighting the importance of MASLD in PsA. Further studies incorporating imaging are required to confirm our findings. REFERENCES: [1] Lin ZH, Xin YN, Dong QJ, et al. Performance of the aspartate aminotransferase-to-platelet ratio index for the staging of hepatitis C-related fibrosis: an updated meta-analysis. Hepatology. 2011 Mar;53(3):726–36. [2] Loaeza-del-Castillo A, Paz-Pineda F, Oviedo-Cárdenas E, et al. AST to platelet ratio index (APRI) for the noninvasive evaluation of liver fibrosis. Ann Hepatol. 2008;7(4):350–7. [3] Rigor J, Diegues A, Presa J, et al. Noninvasive fibrosis tools in NAFLD: validation of APRI, BARD, FIB-4, NAFLD fibrosis score, and Hepamet fibrosis score in a Portuguese population. Postgrad Med. 2022 May;134(4):435–40. Table 1Patient characteristics at the time of clinic entryVariableOverall(n=1314)Never had liver fibrosis*(n=1116)Ever had liver fibrosis(n=198)Age in years, mean (SD)44.4 (13.1)44.4 (13.3)44.5 (12.4)Sex (male), n (%)742 (56.5)610 (54.7)132 (66.7)Duration of PsA in years, median [IQR]2.5 [0.7, 8.1]2.54 [0.7, 8.2]2.4 [0.8, 8.0]BMI in kg/m2, mean (SD)28.8 (6.3)28.8 (6.4)28.9 (6.1)Alcohol consumption, n (%)None468 (41.0)392 (41.1)76 (40.4)Socially570 (49.9)485 (50.8)85 (45.2)Daily104 (9.1)77 (8.1)27 (14.4)Diabetes mellitus, n (%)83 (6.6)63 (5.9)20 (10.2)Hypertension, n (%)191 (14.6)154 (13.8)37 (18.7)Hyperlipidemia, n (%)98 (8.0)81 (7.9)17 (8.8)Hepatitis~, n (%)31 (2.9)19 (2.2)12 (6.7)DAPSA, median [IQR]16.6 [9.0, 29.2]16.6 [9.0, 30.8]16.0 [9.0, 27.0]Modified Steinbrocker score, median [IQR]2.0 [0.0, 8.0]2.0 [0.0, 8.0]2.0 [0.0, 9.0]Sacroiliitis, n (%)267 (21.7)230 (22.1)37 (19.5)APRI, median [IQR]0.22 [0.16, 0.30]0.21 [0.15, 0.28]0.31 [0.21, 0.60]NSAIDs, n (%)860 (65.4)723 (64.8)137 (69.2)Leflunomide or Sulfasalazine, n (%)100 (7.6)85 (7.6)15 (7.6)Methotrexate, n (%)375 (28.5)324 (29.0)51 (25.8)Cumulative methotrexate dose in mg, median [IQR]0.0 [0.0, 115.0]0.0 [0.0, 133.1]0.0 [0.0, 57.1]Biologic or targeted synthetic DMARDs, n (%)88 (6.7)80 (7.2)8 (4.0)SD, standard deviation; PsA, psoriatic arthritis; IQR, interquartile range; BMI, body mass index; DAPSA, Disease Activity Index for Psoriatic Arthritis; APRI, Aspartate Aminotransferase to Platelet Ratio Index; NSAIDs: Non-steroidal anti-inflammatory drug; DMARDs: disease-modifying anti-rheumatic drugs*Liver fibrosis was defined as an APRI value greater than 0.7~Viral, alcohol-induced, drug-induced, or autoimmune Acknowledgements: NIL . Disclosure of Interests: Fadi Kharouf: None declared, Pankti Mehta: None declared, Virginia Carrizo Abarza: None declared, Shangyi Gao: None declared, Daniel Periera: None declared, Dafna D. Gladman AstraZeneca, Abbvie, Amgen, BMS, Eli Lilly, GSK, Janssen, Novartis, Pfizer, UCB, Abbvie, Amgen, Eli Lilly, Janssen, Novartis, Pfizzer, UCB, Denis Poddubnyy AbbVie, Canon, DKSH, Eli Lilly, Janssen, MSD, Medscape, Novartis, Peervoice, Pfizer, and UCB, AbbVie, Biocad, Bristol-Myers Squibb, Eli Lilly, Janssen, Moonlake, Novartis, Pfizer, and UCB, AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, UCB, Vinod Chandran AbbVie, BMS, Eli Lilly, Fresenius Kabi, Johnson and Johnson, Novartis, UCB, AbbVie, Eli Lilly. © 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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,006
Score d'incertitude au seuil0,020

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,008
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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 Opus0,051
Tête enseignante GPT0,359
Écart entre enseignants0,308 · 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 source (Gemma direct ou Codex distillé), 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'admission1
Résumé présentoui

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