Association of Endometrial Cancer Risk With Postmenopausal Bleeding in Women
Bibliographic record
Abstract
Importance: As the worldwide burden of endometrial cancer continues to rise, interest is growing in the evaluation of early detection and prevention strategies among women at increased risk. Focusing efforts on women with postmenopausal bleeding (PMB), a common symptom of endometrial cancer, may be a useful strategy; however, PMB is not specific for endometrial cancer and is often caused by benign conditions. Objective: To provide a reference of the prevalence of PMB in endometrial cancers and the risk of endometrial cancer in women with PMB. Data Sources: For this systematic review and meta-analysis, PubMed and Embase were searched for English-language studies published January 1, 1977, through January 31, 2017. Study Selection: Observational studies reporting the prevalence of PMB in women with endometrial cancer and the risk of endometrial cancer in women with PMB in unselected populations were selected. Data Extraction and Synthesis: Two independent reviewers evaluated study quality and risk of bias using items from the Newcastle-Ottawa Quality Assessment Scale and the Quality Assessment of Diagnostic Accuracy Studies tool. Studies that included highly selected populations, lacked detailed inclusion criteria, and/or included 25 or fewer women were excluded. Main Outcomes and Measures: The pooled prevalence of PMB in women with endometrial cancer and the risk of endometrial cancer in women with PMB. Results: A total of 129 unique studies, including 34 432 unique patients with PMB and 6358 with endometrial cancer (40 790 women), were analyzed. The pooled prevalence of PMB among women with endometrial cancer was 91% (95% CI, 87%-93%), irrespective of tumor stage. The pooled risk of endometrial cancer among women with PMB was 9% (95% CI, 8%-11%), with estimates varying by use of hormone therapy (range, 7% [95% CI, 6%-9%] to 12% [95% CI, 9%-15%]; P < .001 for heterogeneity) and geographic region (range, 5% [95% CI, 3%-11%] in North America to 13% [95% CI, 9%-19%] in Western Europe; P = .09 for heterogeneity). Conclusions and Relevance: Early detection strategies focused on women with PMB have the potential to capture as many as 90% of endometrial cancers; however, most women with PMB will not be diagnosed with endometrial cancer. These results can aid in the assessment of the potential clinical value of new early detection markers and clinical management strategies for endometrial cancer and will help to inform clinical and epidemiologic risk prediction models to support decision making.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".