Immunotherapy for treatment of female genital tract melanoma: National Cancer Database analysis
Why this work is in the frame
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Bibliographic record
Abstract
Goal of this study was to examine the impact of immunotherapy on overall survival (OS) in patients with female genital tract melanoma (GTM). This retrospective cohort study utilized the National Cancer Database to identify individuals with invasive vulvar or vaginal melanoma diagnosed between 2004 and 2019. Kaplan-Meier plots and multivariate Cox regression were used to describe the impact of immunotherapy on OS and to examine predictors of OS among those who received immunotherapy for those with vulvar or vaginal melanoma. Of the 870 patients with vaginal melanoma, 23.6% received immunotherapy. Receiving immunotherapy for treatment of vaginal melanoma was associated with improved OS (median: 21.8 versus 18.9 months; P = 0.01); this association remained after adjustment for other prognostic factors [hazard ratio (HR), 0.77; 95% confidence interval (CI), 0.62-0.95; P = 0.01]. The survival advantage was more pronounced among those who did not receive primary surgical resection (median: 18.6 versus 12.2 months; P = 0.0009). Among 3123 patients with vulvar melanoma, 15.3% received immunotherapy. Receiving immunotherapy for treatment of vulvar melanoma was associated with an improvement in OS (median: 43.6 versus 57.7 months; P = 0.06; HR, 0.86; 95% CI, 0.74-1.00; P = 0.04). Survival benefit was more pronounced when restricted to patients with advanced or unknown stage disease (median OS, 31.6 versus 24.2 months; P = 0.002; adjusted HR, 0.74; 95% CI, 0.61-0.89; P = 0.002) and among the small subset who did not receive primary surgical resection (median: 19.8 versus 9.6 months; P = 0.0005). Immunotherapy was associated with improved OS in patients with female GTM, with some subsets particularly benefitting.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it