The Impact of High-Dose-Rate Brachytherapy: Measuring Clinical Outcomes in the Primary Treatment of Cervical Cancer
Bibliographic record
Abstract
Purpose Radical concurrent chemoradiotherapy with combined external beam radiotherapy (EBRT) and brachytherapy is used to treat locally advanced cervical cancer. Our institution has transitioned to high-dose-rate (HDR) intracavitary brachytherapy (ICBT) from low-dose-rate (LDR) brachytherapy in 2008, and a review was conducted on the effect of this change on patient outcomes. Methods and Materials A single-arm retrospective chart review was performed on locally advanced (Fédération Internationale de Gynécologie et d'Obstétrique stage IB-IVA) patients with cervical cancer treated with combined external beam radiation therapy and HDR-ICBT with curative intent between 2008 and 2014. Clinical outcomes were evaluated, and multivariate analysis was performed to identify prognostic factors. Results Of the 76 patients selected, median age was 47.9 years and median follow-up was 5.2 years. Thirteen patients (17.1%) developed locoregional recurrence and 23 patients (30.3%) patients developed distant recurrence. Five-year progression-free survival and overall survival were 63.7% and 69.3%, respectively. A significant survival difference was found between stages ( P < .001). Multivariate analysis found nodal involvement was strongly associated with poorer survival ( P = .007). Conclusions Our experience with the transition to HDR-ICBT as part of concurrent chemoradiotherapy in treatment of locally advanced cervical cancer resulted in acceptable long-term outcomes and toxicity to that of LDR brachytherapy. Potential further improvement of treatment outcomes for patients may be possible with image guided brachytherapy and the addition of effective systemic therapy.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".