The spectrum of oestrogen receptor expression in endometrial carcinomas of no specific molecular profile
Bibliographic record
Abstract
AIMS: Decreased oestrogen receptor (ER) expression is a marker of poor prognosis in endometrial carcinomas (EC) of no specific molecular profile (NSMP), but the optimal cut-off to separate high-risk 'low ER' versus low-risk 'high ER' expression has not been defined. Here we characterised the distribution of ER staining in a cohort of ECs. METHODS AND RESULTS: Biopsy specimens from 120 cases of NSMP EC were stained for ER and assigned an Allred score. In 66 additional cases ER staining of matched biopsy and hysterectomy were compared. Twelve of 120 tumours had an Allred score of 0-3, including three endometrioid carcinomas (EEA) (one G1, two G3), four clear cell carcinomas (CCC), two mesonephric-like adenocarcinoma (MLA) and one each of: gastric-type adenocarcinoma, carcinosarcoma and endometrial carcinoma NOS. Three had Allred scores of 4-5: two MLA and one high-grade carcinoma with yolk sac differentiation. Five had Allred scores of 6: four EEA (one G1, one G2, two G3) and one mixed clear cell and endometrioid carcinoma. The remaining 100 tumours with Allred scores ≥ 7 were all EEA (66 G1, 28 G2, five G3 and one grade unknown). Comparing the biopsy versus hysterectomy ER staining (n = 66), the results were within a single Allred score point, except two cases with strong diffuse expression in the biopsy (Allred 8) and moderate expression in the hysterectomy (Allred 5). CONCLUSIONS: Most NSMP ECs (> 80%) show high ER expression (Allred score ≥ 7). All non-endometrioid carcinomas and a few endometrioid carcinomas had lower ER expression (Allred score ≤ 6) or were completely negative.
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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 | 0.000 | 0.001 |
| 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".