Phase 3 clinical trials evaluating poly(ADP-ribose) polymerase inhibition plus immunotherapy for first-line treatment of advanced ovarian cancer
Bibliographic record
Abstract
BACKGROUND: Ovarian cancer is the second deadliest gynecologic malignancy globally. The current standard of care first-line therapy for newly diagnosed advanced epithelial ovarian cancer is surgery and platinum-based chemotherapy (±bevacizumab), followed by maintenance therapy with a poly(ADP-ribose) polymerase (PARP) inhibitor, bevacizumab, or a combination of the two. Although anti-programmed cell death (PD) protein 1 and anti-PD ligand 1 antibodies (PD-[L]1 inhibitors) have shown benefit in several solid tumors, their effect in ovarian cancer remains uncertain. Several trials are evaluating PD-(L)1 inhibitors in combination with first-line platinum-based chemotherapy and PARP inhibitor maintenance treatment. Here, we review trial designs to understand key similarities and differences for future assessments of the results. MATERIALS AND METHODS: The clinical trials registry "ClinicalTrials.gov" was searched using keywords, including ovarian cancer and niraparib, olaparib, or rucaparib. Search results were then filtered for phase 3 and manually reviewed to identify trials evaluating combinations of PARP inhibitors and PD-(L)1 inhibitors in the first-line setting. RESULTS: Four trials, ENGOT-OV44/FIRST (NCT03602859), ENGOT-OV46/AGO-OVAR 23/GOG-3025/DUO-O (NCT03737643), ENGOT-OV43/GOG-3036/KEYLYNK-001 (NCT03740165), and ENGOT-OV45/GOG-3020/ATHENA (NCT03522246), were identified. Of these, FIRST, DUO-O, and KEYLYNK-001 are evaluating both first-line use in combination with chemotherapy and maintenance, whereas ATHENA focuses on maintenance after a response to chemotherapy; however, DUO-O and KEYLYNK-001 do not include a PARP inhibitor in the comparator arm, limiting the ability to compare the added benefit of immunotherapy over the current standard of care. CONCLUSIONS: Results of these trials will determine whether PARP inhibitor and PD-(L)1 inhibitor combination with or without bevacizumab can improve patient outcomes.
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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 | 0.004 | 0.001 |
| 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 | 0.001 |
| 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".