Treatment Strategy and Residual Disease as Determinants of Survival in Stage IVB High‐Grade Serous Ovarian Cancer: A Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Stage IVB high-grade serous ovarian cancer (HGSOC) carries a poor prognosis. We aimed to: (1) describe the characteristics and survival of patients treated with primary cytoreductive surgery (PCS), interval cytoreductive surgery (ICS) or chemotherapy alone, (2) investigate the correlation between disease distribution and treatment type, and (3) evaluate the impact of cytoreductive surgery (CS) "aggressiveness" and outcome on survival. METHODS: A single-center retrospective cohort study of Stage IVB HGSOC patients. Demographics, tumor characteristics, treatment including "aggressive" CS (upper abdominal and extraperitoneal procedures), and outcomes were analyzed using descriptive statistics and survival analysis, with nonparametric tests and Cox-proportional hazard models. RESULTS: Of 110 patients, 24 (22%) underwent PCS, 73 (66%) ICS, and 13 (12%) chemotherapy alone. Median overall survival (OS) was 76.2 (PCS), 36.9 (ICS), and 20.1 months (chemotherapy alone) (p = 0.014). Supradiaphragmatic lymph-node metastasis differed across groups (p = 0.042). "Aggressive" CS was performed in 53.6% of the surgical cohort, with 54.86% no-gross-residual (NGR), 34% optimal ≤ 1 cm ≤ and 11.3% suboptimal/aborted surgical outcome. Median OS post CS for NGR, optimal ≤ 1 cm, and suboptimal was 67.55, 35.26, and 20.97 months, respectively (p = 0.006). CONCLUSIONS: OS for Stage IVB HGSOC follows a hierarchical pattern: PCS, ICS, and chemotherapy. Disease distribution guides treatment and residual tumor after CS correlates 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 | 0.001 | 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 | 0.001 | 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".