Prognostic significance of heterologous component in carcinosarcoma of the gynecologic organs: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: The aim of this study is to determine the histologic presence of heterologous component as a prognostic factor in gynecologic carcinosarcoma through a systematic review and meta-analysis. METHODS: PubMed, Web of Science, and Embase were searched for publications. Studies that evaluated survival effect of sarcomatous component based on histology in human ovarian or uterine carcinosarcoma were included. Two authors independently reviewed the references based on eligibility criteria and extracted the data including primary tumor site, survival outcome, type of survival outcome, and proportion of each sarcomatous differentiation. The quality of each eligible study was assessed with Newcastle-Ottawa scale. Meta-analysis was conducted using a random-effects model to estimate hazard ratio (HR) and 95% confidence intervals (CIs) of survival outcome for carcinosarcoma with or without heterologous component. RESULTS: Eight studies including 1,594 patients were identified. Overall proportion of carcinosarcoma with heterologous component was 43.3%. Presence of heterologous component was associated with worse overall survival (HR=1.81; 95% CI=1.15-2.85) but not with pooled recurrence-free survival and disease-free survival (HR=1.79; 95% CI=0.85-3.77). Removing multivariate analysis studies, early-stage studies, ovarian tumor study, or studies with large number of patient samples did not affect the significance between heterologous component and overall survival. CONCLUSION: Gynecologic carcinosarcoma is histologically a biphasic tumor which comprise of epithelial and mesenchymal components. Our study emphasizes pathologic evaluation of heterologous component as a prognostic factor in gynecologic carcinosarcoma when all stages were considered. TRIAL REGISTRATION: PROSPERO Identifier: CRD42022298871.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.019 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".