Local Chemotherapy as an Adjuvant Treatment in Unresectable Squamous Cell Carcinoma: What Do We Know So Far?
Bibliographic record
Abstract
Background: Squamous cell carcinoma (SCC) is one of the most common cancers involving skin and oral mucosa. Although this condition’s gold-standard treatment is the surgical removal of the lesions, the physician must propose alternative treatments in some cases due to the patient’s ineligibility for surgery. Among the available alternative therapies, local chemotherapy may represent an initial treatment in combination with radiotherapy or systemic chemotherapy due to the low frequency of side-effects and the lack of necessity for expensive devices. Methods: In this paper, we review all available literature in various databases (PubMed, Scopus-Embase, Web of Science), proposing local chemotherapy as a treatment for cutaneous and oral SCC. Exclusion criteria included ocular lesions (where topical treatments are common), non-English language, and non-human studies. Results: We included 14 studies in this review. The majority were case reports and case series describing the treatment of non-resectable localized SCC with either imiquimod or 5-fluorouracil. We also analyzed small studies proposing combination treatments. Almost all studies reported an excellent clinical outcome, with a low risk of relapses in time. Conclusions: Resection of the lesion remains the gold-standard treatment for SCC. When this approach is not feasible, local chemotherapy may represent a treatment alternative, and it may also be associated with radiotherapy or systemic chemotherapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".