Re-evaluating Endometrial Thickness in Symptomatic Postmenopausal Patients for Excluding Cancer: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
PURPOSE: The current ACR and American College of Obstetricians and Gynecologists guidelines recommend a ≤4-mm endometrial thickness threshold for excluding endometrial cancer in symptomatic postmenopausal patients. This systematic review and meta-analysis aims to re-evaluate the optimal endometrial thickness threshold on imaging for excluding cancer in symptomatic postmenopausal patients. MATERIALS AND METHODS: A systematic search of MEDLINE, EMBASE, Cochrane Library, and Scopus from inception to October 2023 was performed in addition to a gray literature search. Studies were included if they evaluated the diagnostic imaging accuracy of endometrial thickness thresholds for detecting endometrial cancer in symptomatic postmenopausal patients. The reference standard was histopathology. Full-text review and data extraction were performed independently by two reviewers. Risk of bias and applicability were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Meta-analysis was performed using a bivariate mixed-effects regression model. RESULTS: Thirty-five studies with 6,302 patients met inclusion criteria. Mean age range was 51 to 68 years. The sensitivities and specificities with 95% confidence intervals for the 2- to 7-mm thresholds are 95% (84%-98%) and 22% (8%-49%) for ≤2 mm, 94% (82%-98%) and 35% (24%-47%) for ≤3 mm, 95% (86%-98%) and 45% (34%-56%) for ≤4 mm, 88% (75%-95%) and 56% (42%-68%) for ≤5 mm, 84% (63%-94%) and 60% (43%-74%) for ≤6 mm, and 85% (56%-96%) and 62% (49%-73%) for ≤7 mm. Studies were deemed predominantly low risk for bias across domains. CONCLUSION: This comprehensive meta-analysis supports the ≤4-mm endometrial thickness threshold for excluding endometrial cancer in symptomatic postmenopausal patients.
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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 | 0.023 | 0.057 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.046 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".