Phase II randomized study of dostarlimab alone or with bevacizumab versus non-platinum chemotherapy in recurrent gynecological clear cell carcinoma (DOVE/APGOT-OV7/ENGOT-ov80)
Bibliographic record
Abstract
BACKGROUND: Recurrent gynecological clear cell carcinoma (rGCCC) has a low objective response rate (ORR) to chemotherapy. Previous preclinical and clinical data suggest a potential synergy between immune checkpoint inhibitors and bevacizumab in rGCCC. Dostarlimab, a humanized monoclonal antibody targeting programmed cell death protein 1 (PD-1), combined with the anti-angiogenic bevacizumab, presents a novel therapeutic approach. This study will investigate the efficacy of dostarlimab +/- bevacizumab in rGCCC. METHODS: DOVE is a global, multicenter, international, open-label, randomized phase 2 study of dostarlimab +/- bevacizumab with standard chemotherapy in rGCCC. We will enroll 198 patients with rGCCC and assign them to one of three groups in a 1:1:1 ratio: arm A (dostarlimab monotherapy), B (dostarlimab + bevacizumab), and C (investigator's choice of chemotherapy [weekly paclitaxel, pegylated liposomal doxorubicin, doxorubicin, or gemcitabine]). Patients with disease progression in arm A or C will be allowed to cross over to arm B. Stratification factors include prior bevacizumab use, prior lines of therapy (1 vs. >1), and primary site (ovarian vs. non-ovarian). Key inclusion criteria are histologically proven recurrent or persistent clear cell carcinoma of the ovary, endometrium, cervix, vagina, or vulva; up to five prior lines of therapy; disease progression within 12 months after platinum-based chemotherapy; and measurable disease. Key exclusion criteria are prior treatment with an anti-PD-1, anti-programmed death-ligand 1, or anti-programmed death-ligand 2 agent. The primary endpoint is progression-free survival determined by investigators. Secondary endpoints are ORR, disease control rate, clinical benefit rate, progression-free survival 2, overall survival, and toxicity. Exploratory objectives include immune biomarkers. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT06023862.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".