Comparative Survival Outcomes of Hyperthermic Intraperitoneal Chemotherapy, Intraperitoneal Chemotherapy and Intravenous Chemotherapy for Primary Advanced Ovarian Cancer: A Network Meta-Analysis
Bibliographic record
Abstract
Objective: We aimed to compare the survival outcomes and adverse events of hyperthermic intraperitoneal chemotherapy (HIPEC), intraperitoneal chemotherapy (IP)and intravenous chemotherapy (IP)for primary advanced ovarian cancer. Methods: PubMed, CENTRAL (Cochrane Central Registry of Controlled Trials), Embase, Web of Science and Scopus were searched using multiple terms for primary advanced ovarian cancer, including randomized controlled trials and comparative studies in both Chinese and English (up to date 15 August 2022). Outcomes include overall survival, progression-free survival and adverse events. The data were pooled and reported as hazard ratio (HRs) with 95% confidence intervals. The Newcastle–Ottawa Scales were used to assess the risk of bias in the included comparative study. The Cochrane Collaboration’s Risk of Bias Tool was used for randomized controlled trials. Results: In total, 32 studies, including 6347 patients and 8 different platinum-based chemotherapy regimens, were included in this network meta-analysis. Our analysis results showed that HIPEC2 (carboplatin with area under the curve 10) exhibited a statistically significant OS benefit compared to IV, weekly dose-dense chemotherapy and HIPEC1 (cisplatin with 75/100 mg/m2). Intraperitoneal plus intravenous chemotherapy was associated with a statistically significantly better likelihood of overall survival compared to IV. For progression-free survival, our statistical results only suggest a better progression-free survival in ovarian cancer patients treated with HIPEC1 compared with weekly dose-dense chemotherapy. No evidence of difference was observed between the other comparison groups. Compared with the non-HIPEC group, HIPEC may had a higher incidence of electrolyte disturbances (≥grade 3). Conclusion: Our statistical analysis suggests that the groups receiving HIPEC2 had a better OS than the groups receiving IV, weekly dose-dense chemotherapy and HIPEC1. For PFS, our analysis only showed HIPEC1 is better than IV. Moreover, HIPEC may lead to a higher incidence of electrolyte disturbances (≥grade 3). HIPEC therapy for advanced ovarian cancer is currently controversial.
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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 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.061 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".