Exploratory outcome analyses according to stage and/or residual disease in the ICON7 trial of carboplatin and paclitaxel with or without bevacizumab for newly diagnosed ovarian cancer
Bibliographic record
Abstract
OBJECTIVE: In the randomized phase 3 ICON7 trial (ISRCTN91273375), adding bevacizumab to chemotherapy for newly diagnosed ovarian cancer significantly improved progression-free survival (PFS; primary endpoint) but not overall survival (OS; secondary endpoint) in the intent-to-treat (ITT) population. We explored treatment effect according to stage and extent of residual disease. METHODS: Patients with stage IIB-IV or high-risk (grade 3/clear-cell) stage I-IIA ovarian cancer were randomized to receive six cycles of carboplatin and paclitaxel either alone or with bevacizumab 7.5 mg/kg every 3 weeks followed by single-agent bevacizumab for 12 further cycles (total duration 12 months). Post hoc exploratory analyses of subgroups defined by stage and extent of residual disease at diagnosis within the stage IIIB-IV population (European indication) was performed. RESULTS: The PFS benefit from bevacizumab was seen consistently in all subgroups explored. The PFS hazard ratio was 0.77 (95% confidence interval [CI], 0.59-0.99) in 411 patients with stage IIIB-IV ovarian cancer with no visible residuum and 0.81 (95% CI, 0.69-0.95) in 749 patients with stage IIIB-IV disease and visible residuum. As in the ITT population, no OS difference was detected in any subgroup except the previously described 'high-risk' subgroup. Safety results in analyzed subgroups were consistent with the overall population. CONCLUSIONS: Adding bevacizumab to front-line chemotherapy improves PFS irrespective of stage/residual disease. In patients with stage III with >1 cm residuum, stage IV or inoperable disease, this translates into an OS benefit. No OS benefit or detriment was seen in other subgroups explored.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".