Vulvar malignancies: an interdisciplinary perspective
Bibliographic record
Abstract
Vulvar cancer represents the fourth most common gynecologic malignancy and is often encountered by the general Dermatologist or Gynecologist. Dermatooncologists and Gynecologic Oncologists share expertise in this field and the diagnosis and treatment should ideally be interdisciplinary. All subtypes are typically seen in the later decades of life, although all histologic subtypes have been described in women younger than 30 years. The diagnosis is often delayed. Exact mapping of biopsies is of high importance, as the location and distance from the midline guides the surgical approach depending on the underlying histology. Squamous cell carcinoma accounts for more than 76 % of vulvar cancer with vulvar intraepithelial neoplasia being an important precursor. Basal cell carcinoma is the second most common vulvar malignancy. Melanoma accounts for 5.7 % of vulvar cancer and has a worse prognosis compared to cutaneous melanoma. Most of the trials on checkpoint inhibitors and targeted therapy have not excluded patients with vulvar melanoma and the preliminary evidence is reviewed in the manuscript. Surgery remains the primary treatment modality of locally resectable vulvar cancer. In view of the rarity, the procedure should be performed in dedicated cancer centers to achieve optimal disease control and maintain continence and sexual function whenever possible.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".