Nonsurgical Treatment of Lentigo Maligna with Imiquimod and Cryotherapy: A Case Report
Bibliographic record
Abstract
Introduction: Lentigo maligna (LM) is a melanoma in situ caused by prolonged ultraviolet radiation exposure, most commonly affecting the head and neck of older adults. Although often indolent, LM progresses to invasive lentigo maligna melanoma in approximately 5% of cases. Surgical excision remains the gold standard, but alternatives are required for patients who are poor surgical candidates. Case Presentation: A 92-year-old female with a history of nonmelanoma skin cancer presented with a 7.0 × 7.0 cm pigmented lesion on the left zygomatic region. Dermoscopy revealed features consistent with LM, and biopsy confirmed an early evolving lesion. Given her age and preference to avoid surgery, topical imiquimod 5% cream was prescribed. Treatment consisted of once-daily application, 5 days per week, for 16 weeks. Residual pigmentation was subsequently treated with cryotherapy. After 16 weeks of imiquimod therapy, the lesion showed significant regression in size and pigmentation. Cryotherapy further reduced residual areas, and at 6-month follow-up, complete clinical and histopathologic resolution was observed. The patient tolerated treatment well, with no significant adverse effects. Conclusion: This case highlights the efficacy of imiquimod in combination with cryotherapy as a nonsurgical treatment option for LM, particularly in elderly patients or those unfit for surgery. Our approach offers a safe, viable alternative to excision, with minimal side effects, while underscoring the need for vigilant follow-up to monitor for recurrence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| 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".