Safety and efficacy of mirvetuximab soravtansine, a folate receptor alpha (FRα)-targeting antibody-drug conjugate (ADC), in combination with bevacizumab in patients with platinum-resistant ovarian cancer
Bibliographic record
Abstract
PURPOSE: Evaluate the antitumor activity and safety profile of the combination of mirvetuximab soravtansine and bevacizumab in patients with platinum-resistant ovarian cancer. METHODS: Patients with recurrent epithelial ovarian, fallopian tube, or primary peritoneal cancer, whose most recent platinum-free interval was ≤6 months, were administered mirvetuximab soravtansine (6 mg/kg adjusted ideal body weight) and bevacizumab (15 mg/kg), intravenously, once every 3 weeks. Eligibility included FRα expression by immunohistochemistry (IHC; ≥25% of cells with ≥2+ intensity). Prior bevacizumab and/or PARP inhibitor (PARPi) treatment were permitted. The primary endpoint was confirmed objective response rate (ORR). Secondary endpoints included duration of response (DOR), progression-free survival (PFS), and safety. RESULTS: Ninety-four patients received combination treatment with mirvetuximab soravtansine and bevacizumab. Median age was 62 years (range, 39-81). Fifty-two percent had ≥3 prior therapies; 59% had prior bevacizumab; and 27% had prior PARPi. ORR was 44% (95% CI 33, 54) with 5 complete responses, median DOR 9.7 months (95% CI 6.9, 14.1), and median PFS 8.2 months (95% CI 6.8, 10.0). Treatment-related adverse events were consistent with the profiles of each agent, with the most common being blurred vision (all grades 57%; grade 3, 1%), diarrhea (54%; grade 3, 1%), and nausea (51%; grade 3, 1%). CONCLUSION: The mirvetuximab soravtansine plus bevacizumab doublet is an active and well-tolerated regimen in patients with FRα-expressing platinum-resistant ovarian cancer. Promising activity was observed for patients regardless of level of FRα expression or prior bevacizumab. These data underscore the potential for mirvetuximab soravtansine as the combination partner of choice for bevacizumab in this setting.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".