The optimal time for surgery in women with serous ovarian cancer
Bibliographic record
Abstract
BACKGROUND: Advanced high-grade serous ovarian carcinoma (HGSC) is commonly treated with surgery and chemotherapy. We investigated the survival of patients treated with primary or interval surgery at different times following neoadjuvant chemotherapy. Their survival was compared with that of patients treated with primary cytoreductive surgery and adjuvant chemotherapy. METHODS: Patients with stage III or IV HGSC were included in this retrospective cohort study. Clinical data were obtained from patient records. Patients were divided into 2 groups based on treatment with neoadjuvant chemotherapy and interval cytoreductive surgery (NAC) or with primary cytoreductive surgery and adjuvant chemotherapy (PCS). Study groups were stratified by several clinical variables. RESULTS: We included 334 patients in our study: 156 in the NAC and 178 in the PCS groups. Survival of patients in the NAC group was independent of when they underwent interval cytoreductive surgery following initiation of neoadjuvant chemotherapy (p < 0.001). Optimal surgical cytoreduction had no impact on overall survival in the NAC group (p < 0.001). Optimal cytoreduction (p < 0.001) and platinum sensitivity (p < 0.001) were independent predictors of improved survival in the PCS but not in the NAC group. Patients in the NAC group had significantly worse overall survival than those in the PCS group (31.6 v. 61.3 mo, p < 0.001). CONCLUSION: Women with advanced HGSC who underwent PCS had better survival than those who underwent interval NAC, regardless of the number of cycles of neoadjuvant therapy. Optimal cytoreduction did not provide a survival advantage in the NAC group.
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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 | 0.002 |
| 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) | 0.001 | 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".