Phase II/III Study of Intraperitoneal Chemotherapy after Neoadjuvant Chemotherapy for Ovarian Cancer: NCIC CTG OV.21
Bibliographic record
Abstract
Three large randomized clinical trials have shown a survival benefit in women with stage iii epithelial ovarian cancer (eoc) who receive intraperitoneal (IP) chemotherapy after optimal primary debulking surgery. The most recent Gynecologic Oncology Group study, gog 172, showed an improvement in median overall survival of approximately 17 months. That result led to a U.S. National Cancer Institute (nci) clinical announcement recommending that IP chemotherapy be considered for this group of women with eoc. However, IP chemotherapy is associated with increased toxicity, and rates for completion of treatment are low (42% in gog 172). The optimal IP regimen and duration of treatment has yet to be defined. Women undergoing chemotherapy before optimal debulking surgery were not included in the studies or in the nci clinical announcement. The National Cancer Institute of Canada Clinical Trials Group has developed a protocol for a randomized phase ii/iii study which will examine whether IP platinum-taxane-based chemotherapy benefits women who have received neoadjuvant chemotherapy before optimal surgical debulking. To address whether the less systemically toxic carboplatin can be substituted for cisplatin IP, the first phase of the study will have 3 arms: 1 intravenous-only, and 2 IP-containing regimens. At the end of the first stage, and provided that IP therapy is feasible to administer in this patient population, one of the IP regimens, either IP carboplatin or IP cisplatin, will proceed into a phase iii comparison with the intravenous arm. This exciting new study has gathered international support.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".