When Is a Pathology Review Indicated in Endometrial Cancer?
Bibliographic record
Abstract
OBJECTIVE: Discrepancies may exist between an original pathology report and formal pathology review, with subsequent implications for treatment. We conducted a study of pathology review in endometrial cancer from a population-based study to identify areas of discrepancy and effect on treatment. METHODS: This was a retrospective cohort study in Ontario, Canada from 1996 to 2000. We identified hysterectomy cases from patients with endometrial cancer that were subject to formal pathology review by a gynecologic pathologist at one of six tertiary care centers. Sarcomas and other rare histologic subtypes with fewer than five cases were excluded. We evaluated discrepancy between original pathology and review by demographics, stage, grade, and risk group. Four risk groups were defined: 1) low (stage I), 2) intermediate (stage I and II), 3) high-risk (stage I and II), and 4) advanced stage (all stage III and IV). Reclassification from one risk group to another upon pathology review represented a potential change in treatment. Factors associated with significant discrepancy were identified by a multivariable logistic regression model. RESULTS: Formal pathology review was available on 450 cases. There were no differences by age, year, or hospital type. The overall discrepancy rate was 42.7% (95% confidence interval 38.2-47.3%). The intermediate-risk group had the highest rate of reclassification into another group (33.1%). The most significant rates of discrepancy were associated with endometrioid grades 2 and 3 tumors and stage IIA disease (39.8%, 50.9%, and 79.6%, respectively). CONCLUSION: There was significant discrepancy between original pathology and formal review in endometrial cancer, with implications for guidelines on pathology review at a population level. LEVEL OF EVIDENCE: III
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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 | 0.009 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".