Patch Test Results in Psoriasis Patients on Biologics
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to determine the prevalence of positive patch tests in patients with psoriasis receiving biologics and whether these results differ from those of patients with psoriasis not on biologics. METHODS: An institutional review board-approved retrospective chart review was conducted for patients with psoriasis patch tested January 2002-2012 at Tufts Medical Center. Patients had a history of psoriasis, psoriatic arthritis, and patch testing as identified by International Classification of Diseases, Ninth Revision codes 696.1, 696.0, and 95044, respectively, in their records. Patients were tested to a modified North American Contact Dermatitis Group standard and cosmetics series. Readings were performed at 48 hours and 72 to 96 hours. The North American Contact Dermatitis Group grading system was used to grade reactions. RESULTS: Fifteen patients with psoriasis on biologics (cases) and 16 patients with psoriasis not on biologics (control subjects) were studied. The biologics used were ustekinumab (n = 7), etanercept (n = 4), adalimumab (n = 3), and infliximab (n = 1). Eighty percent (12/15) of cases had at least 1 positive reaction compared with 81% (13/16) of the control subjects; 67% (10/15) of cases had 2+ reactions compared with 63% (10/16) of the control subjects, and 27% (4/15) of cases had 3+ reactions, compared with 38% (6/16) of control subjects. These differences were not statistically significant. CONCLUSIONS: Given the limitation of small numbers of patients, biologics do not appear to influence the abilities of patients with psoriasis to mount a positive patch test.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".