European interdisciplinary guideline on invasive squamous cell carcinoma of the skin: Part 2. Treatment
Bibliographic record
Abstract
In order to update recommendations on treatment, supportive care, education and follow-up of patients with invasive cutaneous squamous cell carcinoma (cSCC), a multidisciplinary panel of experts from the European Dermatology Forum, the European Association of Dermato-Oncology and the European Organization of Research and Treatment of Cancer was formed. Recommendations were based on evidence-based literature review, guidelines and expert consensus. Treatment recommendations are presented for common primary cSCC (low risk, high risk), locally advanced cSCC, regional metastatic cSCC (operable or inoperable) and distant metastatic cSCC. For common primary cSCC (the most frequent cSCC type), first-line treatment is surgical excision with postoperative margin assessment or microscopically controlled sugery. Safety margins containing clinical normal-appearing tissue around the tumour during surgical excision and negative margins as reported in the pathology report are necessary to minimise the risk of local recurrence and metastasis. In case of positive margins, a re-excision shall be done, for operable cases. Lymph node dissection is recommended for cSCC with cytologically or histologically confirmed regional nodal involvement. Radiotherapy should be considered as curative treatment for inoperable cSCC, or for non-surgical candidates. Anti-PD-1 antibodies are the first-line systemic treatment for patients with metastatic or locally advanced cSCC who are not candidates for curative surgery or radiation, with cemiplimab being the first approved systemic agent for advanced cSCC by the Food and Drug Administration/European Medicines Agency. Second-line systemic treatments for advanced cSCC include epidermal growth factor receptor inhibitors (cetuximab) combined with chemotherapy or radiation therapy. Multidisciplinary board decisions are mandatory for all patients with advanced disease who require more than surgery. Patients should be engaged with informed decisions on management and be provided with best supportive care to optimise symptom management and improve quality of life. Frequency of follow-up visits and investigations for subsequent new cSCC depend on underlying risk characteristics.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.011 |
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".