Efficacy and toxicity of intraperitoneal chemotherapy as compared to intravenous chemotherapy in the treatment of patients with advanced ovarian cancer
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy and toxicity of intraperitoneal (IP) chemotherapy compared to intravenous (IV) chemotherapy. METHODS: Toxicity profiles, recurrence patterns, and long-term survival outcomes of 271 women with Stage IIIC or IV high-grade serous ovarian cancer (HGSC) treated with primary cytoreductive surgery followed by adjuvant IP or IV chemotherapy during 2001-2015 were reviewed. RESULTS: Women who received IP chemotherapy (n = 91) were more likely to have undergone aggressive and longer surgery with no residual disease compared to the IV arm (n = 180). Chemotherapy-related toxicities were comparable between the two groups. Extraperitoneal recurrences were more common in the IP arm compared to the IV arm. Five-year progression-free survival was 19% versus 18% (P = 0.63) and overall survival was 73% versus 44% (P < 0.01) in the IP versus IV arms, respectively. After adjustment for significant clinicopathologic factors in a multivariable model, use of IP was no longer a statistically significant predictor of overall survival. CONCLUSION: IP chemotherapy in advanced HGSC has not been widely adopted due to concerns about toxicity and inconvenience. Use of IP chemotherapy was associated with comparable safety profile and efficacy to IV chemotherapy in women with Stage IIIC/IV HGSC. Recurrences were more likely to be extraperitoneal with IP treatment.
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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 | 0.004 |
| 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".