Invasive Stratified Mucinous Carcinoma (iSMC) of the Cervix Often Presents With High-risk Features That Are Determinants of Poor Outcome
Bibliographic record
Abstract
Invasive stratified mucinous carcinoma (iSMC) has been suggested to represent an aggressive subtype of endocervical adenocarcinoma. We sought to investigate the outcomes of iSMC and determine which clinical and pathologic parameters may influence the prognosis. Slides from 52 cases of iSMC were collected and classified as follows: pure iSMC (>90% of the entire tumor) and iSMC mixed with other human papillomavirus-associated adenocarcinoma components (miSMC) (>10%, but <90% of the entire tumor). Clinical and pathologic parameters were evaluated and compared with overall survival (OS) and recurrence-free survival (RFS). One third of patients with iSMC presented with lymph node metastases (LNM) and 25% developed local recurrences, whereas 4 (7.7%) developed distant recurrences. 29 cases (55.8%) were pure iSMC, whereas 23 cases (44.23%) were miSMC. OS was 74.7% in pure iSMC versus 85.2% in miSMC (P=0.287). RFS was 56.5% in pure iSMC and 72.9% in miSMC (P=0.185). At 5 years, OS in stage I was 88.9% versus stage II to IV 30% (P=0.004), whereas RFS in stage I was 73.9% versus stage II to IV 38.1% (P=0.02). OS was influenced by International Federation of Gynecology and Obstetrics (FIGO) stage (P=0.013), tumor size (P=0.02), LNM (P=0.015), and local recurrence (P=0.022), whereas RFS was influenced by FIGO stage (P=0.031), tumor size (P=0.001), local recurrence (P=0.009), LNM (P=0.008), and type of surgical treatment (P=0.044). iSMC is an aggressive cervical tumor biologically different from other human papillomavirus-associated adenocarcinomas due to the propensity for LNM, local/distant recurrence. FIGO stage, tumor size, LNM, and presence of local/pelvic recurrences are determinants of outcome in iSMCs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".