Efficacy and safety of niraparib in patients aged 65 years and older with advanced ovarian cancer: Results from the PRIMA/ENGOT-OV26/GOG-3012 trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate the impact of age on the efficacy and safety of niraparib first-line maintenance therapy in patients with newly diagnosed advanced ovarian cancer with a complete/partial response to first-line platinum-based chemotherapy. METHODS: Post hoc analysis of the phase 3 PRIMA/ENGOT-OV26/GOG-3012 study (NCT02655016). Patients in the intent-to-treat population were categorized according to age at baseline (<65 years vs ≥65 years), and progression-free survival (PFS), safety, and health-related quality of life (HRQOL) were evaluated for each age subgroup (clinical cutoff date, May 17, 2019). Safety findings were also evaluated according to a fixed starting dose (FSD) or an individualized starting dose (ISD). RESULTS: Of 733 randomized patients, 289 (39.4%) were ≥65 years (190 niraparib, 99 placebo) at baseline. Median PFS (niraparib vs placebo) and hazard ratios (95% CI) were similar in patients aged <65 years (13.9 vs 8.2 months; HR, 0.61 [0.47-0.81]) and ≥65 years (13.7 vs 8.1 months; HR, 0.53 [0.39-0.74]). The incidences of any-grade and grade ≥3 treatment-emergent adverse events (TEAEs) were similar across age subgroups; in the niraparib arm, TEAEs leading to dose discontinuation occurred in 7.8% of patients <65 years and 18.4% of patients ≥65 years. ISD use lowered the incidence of grade ≥3 thrombocytopenia events in niraparib-treated patients compared with the FSD (<65 years: 42.8% vs 18.0%; ≥65 years 57.0% vs 26.1%). HRQOL was comparable across age subgroups. CONCLUSION: Niraparib efficacy, safety, and HRQOL were generally comparable across age subgroups, although patients ≥65 years had a higher rate of discontinuations due to TEAEs. ISD use reduced grade ≥3 thrombocytopenia events regardless of age.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".