Endometrial Evaluation with Transvaginal US and Hysterosonography in Asymptomatic Postmenopausal Women with Breast Cancer Receiving Tamoxifen
Bibliographic record
Abstract
PURPOSE: To determine performance characteristics of transvaginal ultrasonography (US) and hysterosonography for diagnosing endometrial abnormality in asymptomatic postmenopausal women with breast cancer receiving tamoxifen. MATERIALS AND METHODS: The authors prospectively examined 138 women receiving tamoxifen by using transvaginal US, hysterosonography, and office hysteroscopy. The combined hysteroscopic-histopathologic diagnosis was the reference standard. Sensitivity, specificity, positive and negative predictive values, and likelihood ratios of transvaginal US and hysterosonography were calculated. RESULTS: All 138 women underwent transvaginal US; 104, successful hysterosonography; and 117, successful hysteroscopy. Uterine abnormality was present in 47 (40.2%) of 117 women: 45 with polyps and two with submucosal fibroids. Receiver operating characteristic curve analysis revealed 6 mm to be the optimal endometrial thickness cutoff for diagnosing endometrial abnormalities. When a thickness greater than 6 mm or a focal endometrial finding was considered abnormal, transvaginal US had a sensitivity of 85.1% and a specificity of 55.7%. In 92 women who completed transvaginal US, hysterosonography, and hysteroscopy, hysterosonography was more specific (79.2%; P =.008) but not significantly more sensitive (89.7%; P =.508) than transvaginal US. When women with abnormal transvaginal US findings were further examined with hysterosonography, the sequential combination of transvaginal US and hysterosonography was more specific (77.1%) than transvaginal US alone (P <.001), without a significant decrease in sensitivity (78.7%; P =.25). CONCLUSION: In asymptomatic postmenopausal women receiving tamoxifen, 6 mm is the optimal endometrial thickness cutoff for diagnosing endometrial abnormalities with transvaginal US. Further examination with hysterosonography can improve specificity by reducing the high false-positive rate of transvaginal US.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".