Efficacy and safety of niraparib as maintenance treatment in older patients (≥ 70 years) with recurrent ovarian cancer: Results from the ENGOT-OV16/NOVA trial
Bibliographic record
Abstract
OBJECTIVE: To analyze the safety and efficacy of niraparib in patients aged ≥70 years with recurrent ovarian cancer in the ENGOT-OV16/NOVA trial. METHODS: The trial enrolled 2 independent cohorts with histologically diagnosed recurrent ovarian, fallopian tube, or peritoneal cancer who responded to platinum rechallenge, on the basis of germline breast cancer susceptibility gene mutation (gBRCAmut) status. Patients were randomized 2:1 to receive niraparib (300 mg) or placebo once daily until disease progression. The primary endpoint was progression-free survival (PFS) by blinded independent central review. Adverse events (AEs) of special interest were based on the known safety profile of poly(ADP-ribose) polymerase inhibitors. RESULTS: Patients aged ≥70 years in the gBRCAmut cohort receiving niraparib (n = 14) had not yet reached a median PFS compared with a median PFS of 3.7 months for the same age group in the placebo arm (hazard ratio [HR], 0.09 [95% confidence interval (CI), 0.01 to 0.73]). Non-gBRCAmut patients aged ≥70 years receiving niraparib (n = 47) had a median PFS of 11.3 months compared with 3.8 months in the placebo arm (HR, 0.35 [95% CI, 0.18 to 0.71]). Median duration of follow-up in the niraparib arm was 17.3 months in patients ≥70 years and 17.2 months in patients <70 years. Frequency, severity of AEs, and dose reductions in the niraparib arm were similar in patients aged <70 and ≥ 70 years population. The most common grade ≥ 3 AEs in patients ≥70 years were hematologic: thrombocytopenia event (34.4%), anemia event (13.1%), and neutropenia event (16.4%). CONCLUSIONS: For patients ≥70 years of age receiving niraparib as maintenance treatment in the ENGOT-OV16/NOVA trial, PFS benefits and incidence of any grade or serious treatment-emergent AEs were comparable to results in the younger population. Use of niraparib should be considered in this population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".