Topical Treatment of Skin Squamous Cell Carcinoma with Potassium Dobesilate Cream
Bibliographic record
Abstract
Skin squamous cell carcinoma, the second most common skin cancer arises from the malignant proliferation of keratinocytes in the epidermis. Although it is locally invasive, surgical excision or topical therapy is usually curative. However, surgical management of skin squamous cell carcinoma located in certain regions of the body may require reconstructive procedures. This can result in significant scarring and increased morbidity and dysfunction. Topical therapy may be preferable to surgery depending on anatomic localizations, and in instances where patients reject it or are poor surgical candidates. Fibroblast growth factors are variously implicated in skin tumorigenesis where they may be involved in the enhancement of tumor cell proliferation and viability, induction of angiogenesis and stimulation of tumor invasiveness. We investigated the efficacy and safety of the fibroblast growth factor inhibitor, dobesilate, administered as a 5% potassium cream, for the treatment of skin squamous cell carcinoma. Two months application of dobesilate cleared squamous cell carcinoma probably due to inhibition of cell proliferation and angiogenesis, and induction of tumor cell apoptosis. No local side effects were observed in relation with treatment. This report highlights the need for efficient and safe topical therapies in the management of skin neoplasms and supports the use of potassium dobesilate in non-melanoma skin cancers treatment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".