Endometrial cancer after endometrial ablation: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To investigate whether a previously performed endometrial ablation is associated with the development and diagnosis of endometrial cancer. METHODS: First, a systematic review was performed of the articles reporting the incidence of endometrial cancer in patients treated with endometrial ablation. Second, a systematic review was performed to identify all individual cases of endometrial cancer after ablation to evaluate presenting symptoms, diagnostic work-up, potential risk factors, and the type and stage of the endometrial cancer. A systematic search was performed, using Medline, EMBASE, and the Cochrane Library databases, from inception through February 24, 2022. RESULTS: Based on 11 included studies, the incidence of endometrial cancer in a population of 29 102 patients with a prior endometrial ablation ranged from 0.0% to 1.6%.A total of 38 cases of endometrial cancer after ablation were identified. In 71% of cases (17 of 24 cases), vaginal bleeding was the first presenting symptom. With transvaginal ultrasound it was possible to identify and measure the endometrial thickness in eight cases. Endometrium sampling was successful in 16 of 18 described cases (89%). In 18 of 20 cases (90%) pathologic examination showed early-stage endometrioid adenocarcinoma (International Federation of Gynecology and Obstetrics stage I). CONCLUSION: Previous endometrial ablation is not associated with the development of endometrial cancer. Diagnostic work-up is not impeded by previous endometrial ablation. In addition, endometrial cancers after endometrial ablation are not detected at an advanced stage.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".