Feasibility and safety of front-line bevacizumab (BEV)-containing therapy after neoadjuvant (NA) chemotherapy (CT) for ovarian cancer (OC): The ROSiA experience.
Bibliographic record
Abstract
5541 Background: BEV significantly improved the efficacy of front-line CT for OC in the GOG-0218 and ICON7 phase III trials. The ongoing single-arm ROSiA study, which has completed recruitment of 1039 patients (pts), is assessing BEV + CT in routine oncology practice. Unlike GOG-0218 and ICON7, prior NACT is permitted. We assessed the surgical safety of BEV + CT in the subgroup of pts with prior NACT. Methods: Inclusion criteria include: FIGO stage IIb–IV or grade 3 stage I–IIa epithelial ovarian, fallopian tube, or primary peritoneal carcinoma; no prior post-surgical therapy for OC; and ECOG PS 0–2. Pts with uncontrolled hypertension or clinical signs/symptoms of GI obstruction or history of abdominal fistula, GI perforation, or intra-abdominal abscess in the preceding 6 mo are excluded. Pts in the NA subgroup were enrolled into the study after up to 4 cycles of NACT without BEV. After interval debulking, pts received BEV 15 mg/kg q3w (or 7.5 mg/kg at the investigator’s discretion) in combination with CT (paclitaxel [175 mg/m2 d1 q3w or 80 mg/m2 qw] + q3w carboplatin [AUC 5 or 6]), to a maximum total of 8 cycles including the pre-study NA cycles. Single-agent BEV was continued until progression, unacceptable toxicity, or for up to 36 cycles in total. The primary objective is evaluation of safety (CTCAE v4.03). Additional endpoints include efficacy (including PFS, response rate, OS) and exploratory translational research. Results: Of the 1039 pts enrolled in ROSiA, 150 (14%) had received NACT. Of these, most had stage IIIc (60%) or IV (29%) disease; 65% had residual disease ≤1 cm; and 19% underwent bowel resection. At the data cut-off 22 mo after enrollment began, median follow-up from post-surgery study entry was 12.6 mo; 69 patients (46%) remained on BEV therapy. At cut-off, pts had received a median of 13 cycles of BEV (range 1–31), including 4 cycles (range 1–6) of BEV in combination with CT after surgery. To date, no pts have had grade ≥3 wound-healing complications during study therapy; 1 pt experienced grade 4 GI perforation 10 weeks after surgery (3 weeks after the first BEV dose), which resolved within 4 weeks. Conclusions: NACT followed by BEV + CT was feasible and tolerable. Clinical trial information: NCT01239732.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".