MRI-guided brachytherapy for vaginal recurrence of endometrial cancer
Bibliographic record
Abstract
PURPOSE: Vaginal recurrence of endometrial cancer can be salvaged by external beam radiotherapy and vaginal brachytherapy, but data on MRI-guided brachytherapy is limited. This study evaluated disease and toxicity outcomes of patients treated with MRI-guided brachytherapy for vaginal recurrence of endometrial cancer. METHODS: Patients who received salvage MRI-guided interstitial/intracavitary brachytherapy for vaginal recurrence of endometrial cancer between 2015 and 2023 were retrospectively reviewed. Local failure (LF) was estimated using the cumulative incidence function. Disease-free (DFS) and overall survival (OS) were estimated using the Kaplan-Meier method. Toxicities were assessed using the Common Terminology Criteria for Adverse Events (version 5). RESULTS: was 82 Gy. With a median follow up of 39.5 months, 11 patients (20%) developed recurrence: four local failures (LFs), three regional failures, and seven distant failures (simultaneous failures at different sites included). The 2-year LF was 5.9% (95% confidence interval [CI] 1.5%-15.9%); 2-year DFS was 83% (95% CI 73%-94%); and 2-year OS was 94% (95% CI 87%-100%). There were few late toxicities, with the highest toxicity grade being grade 2: 0 gastrointestinal, one genitourinary and six vaginal. CONCLUSION: Patients with vaginal recurrence of endometrial cancer treated with MRI-guided interstitial/intracavitary brachytherapy had favorable local control, DFS, OS and toxicity rates.
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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 | 0.001 |
| 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) | 0.003 | 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".