Bibliographic record
Abstract
Paradoxical psoriasis (PP) represents an uncommon but well-documented adverse effect that occurs following exposure to tumour necrosis factor-alpha (TNF-α) inhibitors. There is growing evidence that this reaction may not be class-specific, as the indications for biologic interventions (interleukin [IL]12/23, IL23, IL17, IL4/13) broaden in chronic inflammatory diseases. However, cumulative evidence amongst other classes remains limited to case reports. The pathogenesis of this reaction to TNF inhibitors has been postulated and experimentally supported as a switch toward interferon (IFN) production by antigen-presenting cells, however, the mechanism with other biologics remains elusive. The baseline association of classical psoriasis (non-drug induced) with the seronegative rheumatic and gastrointestinal inflammatory diseases treated by TNF inhibitors, initially made this reaction a challenge to define and study. As evidence has grown, PP has been defined as psoriatic lesions that arise de novo or as morphologically atypical exacerbations of pre-existing known psoriasis during TNF-α therapy. These lesions may persist and worsen unless treated, commonly requiring systemic therapeutic adjustments. This review explores the epidemiology, pathogenesis, clinical manifestations, and management of PP, with an emphasis on patient outcomes and recommendations based on primary data, systematic reviews, and contributions from key researchers in the field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".