The newly proposed International Endocervical Adenocarcinoma Criteria and Classification and its relevance to cervical cytology screening assessed in a prospective 2‐year study of 118 cases
Bibliographic record
Abstract
BACKGROUND: It is generally acknowledged that interobserver variability for the histological diagnosis of endocervical adenocarcinoma (EA) subtypes is suboptimal. The recently proposed International Endocervical Adenocarcinoma Criteria and Classification (IECC) system is based on the presence of associated human papilloma virus (HPV) infection. It recognises HPV-associated EAs and non-HPV-associated EAs. METHODS: This prospective cytology-histology and molecular genetics-based study investigated the potential effect of IECC being applied to Papanicolaou (Pap) test with regard to the diagnostic accuracy of severe glandular lesions reported at least as adenocarcinoma in situ (AIS). RESULTS: Out of 118 liquid-based cytology Pap tests with AIS+ lesion, complete information on follow-up biopsy and HPV status was available in 51 cases. AIS and EA category correlated with histologically confirmed AIS/EA in 88.5% (23/26) and 70.5% (12/17) of cases, respectively. Interestingly, 93% (40/43) of cases diagnosed as AIS/EA were HPV positive and 7% (3/43) were HPV negative (originating in the cervix, endometrium and adnexa). CONCLUSIONS: Our findings suggest that this approach could possibly divide Pap tests containing severe glandular lesion into two groups: (a) robust diagnosis of HPV-associated EA and (b) non-HPV associated glandular lesions of heterogeneous origin, requiring further clinical preoperative diagnostic workup.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".