Adjuvant radiotherapy for early-stage endometrial cancer based on randomized controlled trials: a narrative review
Bibliographic record
Abstract
Endometrial carcinoma (EC) is the most common gynecologic malignancy in the USA, with surgical staging as the cornerstone of treatment. Although most patients are diagnosed at an early stage, adjuvant therapies, including external beam radiation therapy (EBRT), vaginal brachytherapy (VBT), and systemic treatments, are employed in select cases to reduce recurrence risk. This review highlights data from randomized controlled trials assessing the efficacy of adjuvant radiotherapy in early-stage EC. For low-risk EC, studies suggest that postoperative brachytherapy has minimal impact on locoregional recurrence and is not recommended without significant uterine risk factors. In intermediate-risk EC, trials such as GOG 99 and PORTEC-1 demonstrated reduced recurrence with pelvic RT, particularly in high-intermediate risk subsets, though overall survival benefits were not observed. For high-intermediate risk EC, PORTEC-2 showed that VBT effectively controls vaginal recurrence with less morbidity compared to EBRT, recommending VBT as the preferred modality. Medium-risk cases benefit similarly from VBT alone, as shown in Swedish trials. In high-risk EC, RCTs such as GOG 249 and PORTEC-3 examined the addition of chemotherapy to radiotherapy, finding comparable recurrence and survival outcomes between VBT with chemotherapy and EBRT, though acute toxicity was higher with combined therapy. Across these trials, the degree of lymphovascular space invasion (LVSI), patient age, tumor grade, and histology were key prognostic factors influencing treatment recommendations. Despite advancements in molecular classification and modern radiotherapy techniques, most data derive from earlier studies, emphasizing the need for updated research to refine treatment paradigms.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.004 | 0.159 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| 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) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".