Assessment of endometrial sampling as a predictor of final surgical pathology in endometrial cancer
Bibliographic record
Abstract
BACKGROUND: The histology and grade of endometrial cancer are important predictors of disease outcome and of the likelihood of nodal involvement. In most centres, however, surgical staging decisions are based on a preoperative biopsy. The objective of this study was to assess the concordance between the preoperative histology and that of the hysterectomy specimen in endometrial cancer. METHODS: Patients treated for endometrial cancer during a 10-year period at a tertiary cancer centre were identified from a prospectively collected pathological database. All pathology reports were reviewed to confirm centralised reporting of the original sampling or biopsy specimens; patients whose biopsies were not reviewed by a dedicated gynaecological pathologist at the treating centre were excluded. Surgical pathology data including histology, grade, depth of myometrial invasion, cervical stromal involvement and lymphovascular space invasion (LVSI) as well as preoperative histology and grade were collected. Preoperative and final tumour cell type and grade were compared and the distribution of other high-risk features was analysed. RESULTS: A total of 1329 consecutive patients were identified; 653 patients had a centrally reviewed epithelial endometrial cancer on their original biopsy, and are included in this study. Of 255 patients whose biopsies were read as grade 1 (G1) adenocarcinoma, 45 (18%) were upgraded to grade 2 (G2) on final pathology, 6 (2%) were upgraded to grade 3 (G3) and 5 (2%) were read as a non-endometrioid high-grade histology. Overall, of 255 tumours classified as G1 endometrioid cancers on biopsy, 74 (29%) were either found to be low-grade (G1-2) tumours with deep myometrial invasion, or were reclassified as high-grade cancers (G3 or non-endometrioid histologies) on final surgical pathology. Despite these shifts, we calculate that omitting surgical staging in preoperatively diagnosed G1 endometrioid cancers without deep myometrial invasion would result in missing nodal involvement in only 1% of cases. CONCLUSIONS: Preoperative endometrial sampling is only a modest predictor of surgical pathology features in endometrial cancer and may underestimate the risk of disease spread and recurrence. In spite of frequent shifts in postoperative vs preoperative histological assessment, the predicted rate of missed nodal metastases with a selective staging policy remains low.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".