Psoriasis and Pustular Dermatitis Triggered by TNF-α Inhibitors in Patients With Rheumatologic Conditions
Bibliographic record
Abstract
BACKGROUND: New onset or worsening of psoriasis has been reported in patients treated with tumor necrosis factor alpha (TNF-alpha) inhibitors for a variety of rheumatologic conditions. There is mounting evidence that a key innate immune pathway for triggering common human autoimmune disease, including psoriasis, involves plasmacytoid dendritic cell precursors (PDCs) and type 1 interferon (IFN) production. We present herein a case series with clinical and histopathologic evidence of psoriasis in patients with rheumatologic disease treated with TNF-alpha inhibitors. We propose that the cross regulation between TNF-alpha and IFN may have a role in the pathogenesis of this reaction. OBSERVATIONS: We observed new-onset psoriasis (n = 13) or severe exacerbation of psoriasis (n = 2) in 15 patients with a variety of rheumatologic conditions-rheumatoid arthritis (n = 13), psoriatic arthritis (n = 1), and seronegative arthritis (n = 1)-during treatment with etanercept (n = 6), infliximab (n = 5), and adalimumab (n = 4). Immunohistochemical staining of skin biopsy specimens for myxovirus-resistance protein A (MxA, a surrogate marker for lesional type 1 IFN activity) showed increased staining in TNF-alpha inhibitor-induced psoriasis compared with psoriasis vulgaris. CONCLUSIONS: New onset or severe exacerbation of psoriasis is a rare complication of TNF-alpha inhibitor therapy. The finding of increased production of IFN-alpha in TNF-alpha inhibitor-induced psoriasis is a possible pathophysiologic explanation for this reaction.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".