Survival in women with ovarian cancer with and without microsatellite instability.
Bibliographic record
Abstract
PURPOSE OF INVESTIGATION: Microsatellite instability (MSI) is a hallmark of defective mismatch repair and is present in approximately 20% of ovarian cancers. It is not known if the presence of MSI predicts survival in women with epithelial ovarian cancer. MATERIALS AND METHODS: Cases of epithelial ovarian cancer were ascertained from a population-based study in Ontario and tumour samples were tested for MSI, using five MSI markers. Patients were divided into MSI-high and MSI-low/normal, according to National Cancer Institute criteria. The authors compared the prevalence of specific prognostic factors in the two subgroups, including age, grade, stage, and histology. They estimated the hazard ratio for death from ovarian cancer associated with MSI-high and with other prognostic factors using a multi-variate analysis. RESULTS: A total of 418 ovarian cancer patients were included. One hundred and twenty-seven (19.7%) cancers were MSI- high. Subgroup analyses did not reveal any statistically significant differences for pathologic features associated with MSI status. No survival difference was seen according to MSI status. CONCLUSIONS: The presence of MSI in ovarian cancer is not associated with survival.
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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 | 0.000 | 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".