The attributive value of comprehensive surgical staging in clinically early-stage epithelial ovarian carcinoma: a systematic review and meta-analysis.
Bibliographic record
Abstract
Background: Tumor positivity and upstaging rates from various surgical staging components performed in clinically early-stage epithelial ovarian carcinoma (EOC) vary widely in literature. Objectives: To quantify tumor positivity and upstaging rates for all staging surgery components in EOC patients. Differences between subgroups based on their clinical and histological characteristics are explored. Search strategy: A systematic search using synonyms of ‘ovarian cancer’, ‘neoplasm staging’, and ’neoplasm metastasis’ was conducted in PubMed, Embase, and the Cochrane Library. Selection criteria: Meta-analysis was performed on 23 included studies, comprising 5194 clinical stage I or II EOC patients who underwent comprehensive surgical staging. Data Collection and Analysis: Studies were assessed using the Newcastle-Ottawa Scale risk-of-bias tool. Pooled proportions and 95% confidence intervals were calculated using an inverse variance weighted random-effects model. Main Results: Overall upstaging rate of clinically early-stage EOC patients was 18.7% (95%CI: 14.1-23.4%). Serous histology or high grade EOC showed the highest upstaging rate at 35.3% (95%CI: 21.8-48.7%) and 40.9% (95%CI: 35.6-46.2%). Lymph node involvement resulted in an upstaging rate of 8.7% (95%CI: 6.2-11.3%). Tumor was identified in uterus, cytology, peritoneal biopsies, omentum and appendix in 6.2% (95%CI: 1.8-10.7%), 18.4% (95%CI: 13.8-22.9%), 9.7% (95%CI: 3.8-15.6%), 5.2% (95%CI: 1.7-8.8%) and 3.6% (95%CI: 0.0-7.5%) of EOC patients. The corresponding upstaging rates were 5.9% (95%CI: 1.4-10.4%), 8.5% (95%CI: 1.8-15.2%), 3.5% (95%CI: 1.0-6.0%), 3.9% (95%CI: 1.4-6.3%) and 1.6% (95%CI: 0.0-3.4%), respectively. Conclusion: The attributive value of comprehensive surgical staging in clinically early-stage EOC patients remains substantial, particularly in serous and high grade tumors.
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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 | 0.022 | 0.052 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.042 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".