Association between pyoderma gangrenosum and autoimmune connective tissue disorders: A systematic review
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Notice bibliographique
Résumé
Pyoderma gangrenosum (PG) is a neutrophilic dermatosis that may result in painful cutaneous ulcers and can be challenging to manage.1 PG is frequently associated with underlying systemic disorders, particularly hematologic dyscrasias and inflammatory bowel disease (IBD).1, 2 PG has also been associated with autoimmune connective tissue disorders (AI-CTD), but its characteristics are not well documented. Hence, we sought to perform a systematic literature review to characterize the epidemiology, clinical characteristics, and management of patients with concomitant PG and AI-CTD. Following PRISMA guidelines, EMBASE, MEDLINE, and CENTRAL were searched from inception to July 23, 2023. AI-CTDs of interest include systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), antiphospholipid syndrome (APS), Sjögren syndrome (SS), scleroderma (Scl), and overlap syndrome (OS). Primary studies with original data for patients 18 years or older with an established diagnosis of AI-CTD were included. Non-English studies were excluded. Study quality and bias assessments were performed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) scale. Of the initial 702 articles identified in the search, 78 met the inclusion criteria and comprised 48 case reports, 21 case series, 6 cohort studies, and 3 case–control studies. A total of 234 patients were included, with a mean age of 57.3 years (range: 18–92). A majority occurred in females (76%) (Table 1). Lower legs (52.2%) were the most common site of PG involvement, followed by thigh/hips (18.7%), arms (11.0%), torso (9.9%), head/neck (3.3%), and mucous membranes (4.9%). The most prevalent AI-CTD associated with PG was RA (85.9%, n = 201), followed by SLE (12.0%, n = 28), Scl (1.3%, n = 3), APS (0.4%, n = 1), and SS (0.4%, n = 1). Six patients (2.6%) had OS. The mean treatment duration for PG was 39 weeks and included systemic corticosteroids (n = 65), calcineurin inhibitors (n = 21), tumor necrosis factor (TNF)-alpha inhibitors (n = 14), antibiotics (n = 19), purine antagonists (n = 18), interleukin (IL)-1 receptor antagonists (n = 3), dapsone (n = 7), cyclophosphamide (n = 7) and Janus kinase (JAK) inhibitors (n = 2) (Table 1). Treatment type did not vary significantly with AI-CTD. There were 88 patients (37.6%) with complete resolution and 12 patients (5.1%) with recurrences. Two deaths (0.9%) were reported prior to PG resolution due to other comorbidities, one of which was sepsis. This review is limited by study heterogeneity, reporting bias, and low-quality studies, as the majority were case reports. The pathogenesis of PG and AI-CTD both result from autoreactive T-cells and aberrant proinflammatory cytokine production, including IL-1, IL-17, IL-36, and TNF-alpha, among others.2, 3 Hence, both conditions often require long courses of immunosuppressants that come with inherent risks, yet evidence-based guidelines remain sparse. IL-36 is the key cytokine responsible for perpetuating neutrophilic inflammation in PG.4, 5 Spesolimab, a novel IL-36 receptor antagonist, may be a promising and safer off-label option given its targeted mechanism of action, but further studies are necessary. In conclusion, our review found that RA is the predominant AI-CTD associated with PG, the lower extremities are the most common sites of PG involvement, and females with concomitant AI-CTD represented a majority of PG cases in a 3:1 ratio. We propose an algorithm for working up patients with a new diagnosis of PG for suspected AI-CTD (Figure 1). Clinicians managing patients with a new onset of PG on the lower extremities should acknowledge this association and consider further workup for underlying AI-CTD, especially for RA in females when hematologic disorders or IBD have been ruled out. We would like to thank Ms. Risa Shorr, MLIS, Librarian at The Ottawa Hospital, for assisting with the literature search query. Data is available on request from the authors.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,004 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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