Scarring Alopecia in Tumor Necrosis Factor-α Antagonists-Induced Scalp Psoriasis
Bibliographic record
Abstract
Background: A broad spectrum of adverse reactions associated with the use of tumor necrosis factor alpha (TNFα) antagonists has been recognized over the past years. Induction of scalp psoriasis is a less known undesirable consequence of the use of these drugs and is not well characterized. Objective: To characterize TNFα inhibitors-induced psoriatic alopecia. Methods: We studied 6 patients with TNF-inhibitor induced psoriatic alopecia and reviewed 28 patients with this condition reported in the literature to date. Results: In addition to severe scalp psoriasis, we report hair follicle pathologies ranging from alopecia areata to scarring alopecia. Prognosis was good, but discontinuation of TNFα inhibitors was required in more than half of the cases in order to achieve a favourable outcome. Conclusion: TNFα inhibitors-associated psoriatic alopecia is rarely reported but requires a high index of suspicion and prompt diagnosis, as timely intervention may prevent irreversible damage.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".