Update on Intraperitoneal Chemotherapy for the Treatment of Epithelial Ovarian Cancer
Bibliographic record
Abstract
Surgical treatment and chemotherapy administration in women with epithelial ovarian cancer is more controversial today than at any point in the last 3 decades. The use of chemotherapy administered intraperitoneally has been particularly contentious. Three large randomized phase III studies, multiple meta-analyses, and now real-world data have demonstrated substantial outcome benefit for the use of chemotherapy administered intraperitoneally versus intravenously for first-line postoperative treatment of optimally debulked advanced ovarian cancer. Unfortunately, for each of these randomized studies, there was scope to either criticize the design or otherwise refute adoption of this route of administration. As a result, the uptake has been variable in North America, although in Europe it has been practically nonexistent. Reasons for this include unquestionable additional toxicity, more inconvenience, and extra cost. However, 10-year follow up of these studies demonstrates unprecedented survival in the intraperitoneal arm (median survival 110 months in patients with completely debulked stage III), raising the possibility that by combining maximal debulking surgery with postoperative intraperitoneal chemotherapy it may be possible to bring about a step change in the outcomes for these patients. In this review, we discuss the rationale for administering chemotherapy intraperitoneally, the merits of the main randomized clinical trials, the evidence regarding optimal regimes, issues of toxicity, port considerations, and reasons for lack of universal adoption. We also explore potential clinical and biologic factors that may be useful for patient selection in the future.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".