Canadian Consensus-based and Evidence-based Guidelines for Benign Endometrial Pathology Reporting in Biopsy Material
Bibliographic record
Abstract
Standardized terminology has proven benefits in cancer reporting; in contrast, reporting of benign diagnoses in endometrial biopsy currently lacks such standardization. Unification and update on the lexicon can provide the structure and consistency needed for optimal patient care and quality assurance purposes. The Special Interest Group in Gynecologic Pathology of the Canadian Association of Pathologists-Association Canadienne des Pathologistes (CAP-ACP) embarked in an initiative to address the current need for consensus terminology in benign endometrial biopsy pathology reporting. Nine members of the Special Interest Group developed a guideline for structured diagnosis of benign endometrial pathology through critical appraisal of the available peer-reviewed literature and joint discussions. The first version of the document was circulated for feedback to a group of professionals in akin fields, the CAP-ACP Executive Committee and the CAP-ACP general membership. The final 1-page document included 17 diagnostic terms comprising the most common benign endometrial entities, as well as explanatory notes for pathologists. The proposed terminology was implemented in the practice of 5 pathologists from the group, who applied the guideline to all benign endometrial biopsies over a 2-wk period. A total of 212 benign endometrial biopsies were evaluated in this implementation step; the recommended terminology adequately covered the diagnosis in 203 cases (95.8%). A list of terminology for benign endometrial biopsy reporting, based on expert consensus and critical appraisal of the available literature, is presented. On the basis of our results of implementation at multiple centers, the proposed guideline can successfully cover the large majority of diagnostic scenarios. The document has the potential to positively impact patient care, promote quality assurance, and facilitate research initiatives aimed at improving histopathologic assessment of benign endometrium.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".