Eruptive papules during efalizumab (anti-CD11a) therapy of psoriasis vulgaris: a case series
Bibliographic record
Abstract
BACKGROUND: Newer biological therapies for moderate-to-severe psoriasis are being used more frequently, but unexpected effects may occur. CASE PRESENTATIONS: We present a group of 15 patients who developed inflammatory papules while on efalizumab therapy (Raptiva, Genentech Inc, anti-CD11a). Immunohistochemistry showed that there were increased CD11b+, CD11c+ and iNOS+ cells (myeloid leukocytes) in the papules, with relatively few CD3+ T cells. While efalizumab caused a decreased expression of CD11a on T cells, other circulating leukocytes from patients receiving this therapy often showed increased CD11b and CD11c. In the setting of an additional stimulus such as skin trauma, this may predispose to increased trafficking into the skin using these alternative beta2 integrins. In addition, there may be impaired immune synapse formation, limiting the development of these lesions to small papules. There is little evidence for these papular lesions being "allergic" in nature as there are few eosinophils on biopsy, and they respond to minimal or no therapy even if efalizumab is continued. CONCLUSION: We hypothesize that these papules may represent a unique type of "mechanistic" inflammatory reaction, seen only in the context of drug-induced CD11a blockade, and not during the natural disease process.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".