ENGOT-OV44/FIRST study: A randomized, double-blind, adaptive, phase III study of platinum-based therapy with dostarlimab (TSR-042) + niraparib versus standard-of-care (SOC) platinum-based therapy as first-line treatment of stage 3/4 non-mucinous epithelial ovarian cancer (OC).
Bibliographic record
Abstract
TPS5600 Background: Despite surgery and SOC therapy (paclitaxel and carboplatin ± bevacizumab[bev]), 5-year survival rates remain low for patients (pts) with FIGO stage 3/4 OC. Niraparib (ZEJULA) is the first selective poly(ADP-ribose) polymerase inhibitor (PARPi) approved in the US and Europe for maintenance treatment in pts with recurrent OC regardless of BRCAmut status. Preclinical data suggest synergy with PARPi + anti-PD-1 blockade. Niraparib + pembrolizumab has shown clinical efficacy in pts with platinum-resistant or secondary refractory OC regardless of biomarker status. Dostarlimab is an anti–PD-1 humanized monoclonal with clinical activity as monotherapy in early phase trials. The primary objective of the currently enrolling FIRST trial is to compare PFS (per RECIST v1.1) in pts treated with SOC + dostarlimab + niraparib to SOC. Methods: Eligible pts (up to 912) are FIGO stage 3 (with residual disease, CC0 high risk, or planned neoadjuvant therapy) or stage 4, non-mucinous epithelial OC and ECOG score < 2. After 1 cycle of SOC, pts are stratified by concurrent bev use, BRCAmut/HRR status, and disease burden then randomized as 1:1:2 to 1 of 3 arms (Table). An innovative feature of ENGOT-OV44/FIRST (NCT03602859; EUDRACT 2018-000413-20) is the pre-planned adaptive study design to adapt the control arm to the evolving SOCs in OC, allowing pts in the control arm to receive up to date SOC. These adaptations will occur when practice-changing data are released. Following publication of SOLO1 results, BRCAmut pts will only be randomized to arm 2 or 3 to ensure they receive niraparib. Further adaptations may be incorporated as new data become available, leading to stop randomization in arm 1 or 2 of pts based on their biomarker status. Clinical trial information: NCT03602859. [Table: see text]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".