Infiltrative pattern of invasion is independently associated with shorter survival and desmoplastic stroma markers <scp>FAP</scp> and <scp>THBS2</scp> in mucinous ovarian carcinoma
Bibliographic record
Abstract
AIMS: Mucinous ovarian carcinoma (MOC) is a rare ovarian cancer histotype with generally good prognosis when diagnosed at an early stage. However, MOC with the infiltrative pattern of invasion has a worse prognosis, although to date studies have not been large enough to control for covariables. Data on reproducibility of classifying the invasion pattern are limited, as are molecular correlates for infiltrative invasion. We hypothesized that the invasion pattern would be associated with an aberrant tumour microenvironment. METHODS AND RESULTS: Four subspecialty pathologists assessed interobserver reproducibility of the pattern of invasion in 134 MOC. Immunohistochemistry on fibroblast activation protein (FAP) and THBS2 was performed on 98 cases. Association with survival was tested using Cox regression. The average interobserver agreement for the infiltrative pattern was moderate (kappa 0.60, agreement 86.3%). After reproducibility review, 24/134 MOC (18%) were determined to have the infiltrative pattern and this was associated with a higher risk of death, independent of FIGO stage, grade, and patient age in a time-dependent manner (hazard ratio [HR] = 10.2, 95% confidence interval [CI] 3.0-34.5). High stromal expression of FAP and THBS2 was more common in infiltrative MOC (FAP: 60%, THBS2: 58%, both P < 0.001) and associated with survival (multivariate HR for FAP: 1.5 [95% CI 1.1-2.1] and THBS2: 1.91 [95% CI 1.1-3.2]). CONCLUSIONS: The pattern of invasion should be included in reporting for MOC due to the strong prognostic implications. We highlight the histological features that should be considered to improve reproducibility. FAP and THBS2 are associated with infiltrative invasion in MOC.
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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 | 0.003 |
| 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".