Treatment of Atypical Nevi With Imiquimod 5% Cream
Bibliographic record
Abstract
BACKGROUND: 5% Imiquimod cream is a topical immune response modifier that has been used off-label to treat malignant melanocytic proliferations such as lentigo maligna. To our knowledge, imiquimod has not been previously used to treat atypical nevi (AN). OBSERVATIONS: Three patients each with 1 selected clinically AN were treated with imiquimod 5 nights per week for 12 weeks. The lesions were subsequently excised and sent for routine histologic and immunohistochemical analysis. None of the lesions cleared. Two were consistent with atypical compound nevus on excisional biopsy and demonstrated inflammation, while the third showed congenital features and demonstrated minimal inflammation. The AN were initially interpreted as displaying more severe histologic atypia on excisional biopsy than was present at baseline. Immunohistochemical studies revealed that the AN but not the congenital-like nevus exhibited increased staining for CD4(+) and CD8(+) cells and for a surrogate marker of interferon alpha expression. CONCLUSIONS: Twelve weeks of imiquimod treatment failed to cause lesional resolution. A differential inflammatory response was observed between the AN and the congenital-like nevus. The character of the inflammatory infiltrate was similar to that observed with halo nevi. Uncertainties remain concerning imiquimod use for chemoprevention of AN, and the posttreatment histologic features may be misinterpreted as severe melanocytic atypia or melanoma.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".