Onset of Pyoderma Gangrenosum in Patients on Biologic Therapies: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To summarize clinical outcomes of paradoxical pyoderma gangrenosum (PG) onset in patients on biologic therapy. METHODS: The authors conducted MEDLINE and EMBASE searches using PRISMA guidelines to include 57 patients (23 reports). RESULTS: Of the included patients, 71.9% (n = 41/57) noted PG onset after initiating rituximab, 21.1% (n = 12/57) noted tumor necrosis factor α (TNF-α) inhibitors, 5.3% (n = 3/57) reported interleukin 17A inhibitors, and 1.8% (n = 1/57) reported cytotoxic T-lymphocyte-associated protein 4 antibodies. The majority of patients (94.3%) discontinued biologic use. The most common medications used to resolve rituximab-associated PG were intravenous immunoglobulins, oral corticosteroids, and antibiotics, with an average resolution time of 3.3 months. Complete resolution of PG in TNF-α-associated cases occurred within an average of 2.2 months after switching to another TNF-α inhibitor (n = 1), an interleukin 12/23 inhibitor (n = 2), or treatment with systemic corticosteroids and cyclosporine (n = 3), systemic corticosteroids alone (n = 1), or cyclosporine alone (n = 1). CONCLUSIONS: Further investigations are warranted to determine whether PG onset is associated with underlying comorbidities, the use of biologic agents, or a synergistic effect. Nevertheless, PG may develop in patients on rituximab or TNF-α inhibitors, suggesting the need to monitor and treat such adverse effects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".