Microinvasive cervical squamous cell carcinoma in Slovenia during the period 2001-2007
Bibliographic record
Abstract
BACKGROUND: Microinvasive squamous cell carcinoma (MISCC) comprises a significant portion of all cervical cancers in Slovenia. Criteria of carcinomatous invasion are well described in the literature, however histopathological assessment of MISCC is difficult, because morphological characteristics can overlap with cervical intraepithelial neoplasia grade 3 (CIN 3) and other pathological changes. The aim of our study was to evaluate the reliability of the histopathological diagnosis of MISCC in Slovenia during the period from 2001 to 2007. MATERIALS AND METHODS: Data on patients with a histopathological diagnosis of cervical MISCC (FIGO stage IA) in the period of 2001 to 2007 were obtained from the Cancer Registry of Slovenia. Histological slides were obtained from the majority of pathology laboratories in Slovenia. We received 250 cases (69% of all MISCC) for the review; 30 control cases with CIN 3 and invasive squamous cell carcinoma FIGO stage IB were intermixed. The slides were coded and reviewed. RESULTS: Among 250 cases originally diagnosed as MISCC, there was an agreement with MISCC diagnosis in 184 (73.6%) cases (of these 179/184 (97.3%) cases were FIGO stage IA1 and 5/184 (2.7%) cases were FIGO stage IA2). Among 179 FIGO stage IA1 cases 117 (65.4%) showed only early stromal invasion. CONCLUSIONS: The retrospective review of cases diagnosed as MISCC during the period 2001-2007 in Slovenia showed a considerable number of overdiagnosed cases. Amongst cases with MISCC confirmed on review, there was a significant proportion with early stromal invasion (depth of invasion less than 1 mm).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".