Combined Interval Cytoreductive Surgery and Carboplatin-Based Hyperthermic Intraperitoneal Chemotherapy in Advanced Primary High-Grade Serous Ovarian Cancer
Bibliographic record
Abstract
Combining interval cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) improves survival in advanced epithelial ovarian carcinoma (EOC). Although limited, growing evidence regarding carboplatin-based HIPEC highlights its potential. This retrospective study included all patients with advanced primary high-grade serous ovarian cancer who underwent interval CRS combined with carboplatin-based HIPEC at our Canadian tertiary care center between 2014 and 2020. We identified 40 patients with a median age of 61 years. The median peritoneal cancer index was 13 and complete cytoreduction was achieved in 38 patients (95%). Median hospital stay was 13 days and there were four admissions to the intensive care unit (10%) and six readmissions (15%). Severe adverse events occurred in eight patients (20%) and there was no perioperative death. Recurrence was seen in 33 patients (82%) with a median DFS of 18.0 months and a median overall survival of 36.4 months. Multivariate analyses showed that age, peritoneal cancer index, completeness of cytoreduction, occurrence of severe complications, and bowel resection did not significantly impact DFS or OS in our cohort. Interval CRS combined with carboplatin-based HIPEC for advanced primary EOC is associated with acceptable morbidity and oncological outcomes. Larger studies are required to determine the long-term outcomes.
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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 | 0.000 |
| 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) | 0.000 | 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 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".