The effect of age on efficacy, safety and patient-centered outcomes with rucaparib: A post hoc exploratory analysis of ARIEL3, a phase 3, randomized, maintenance study in patients with recurrent ovarian carcinoma
Bibliographic record
Abstract
BACKGROUND: In the phase 3 trial ARIEL3, maintenance treatment with the poly(ADP-ribose) polymerase (PARP) inhibitor rucaparib provided clinical benefit versus placebo for patients with recurrent, platinum-sensitive ovarian cancer. Here, we evaluate the impact of age on the clinical utility of rucaparib in ARIEL3. METHODS: Patients with platinum-sensitive, recurrent ovarian carcinoma with ≥2 prior platinum-based chemotherapies who responded to their last platinum-based therapy were enrolled in ARIEL3 and randomized 2:1 to rucaparib 600 mg twice daily or placebo. Exploratory, post hoc analyses of progression-free survival (PFS), patient-centered outcomes (quality-adjusted PFS [QA-PFS] and quality-adjusted time without symptoms or toxicity [Q-TWiST]), and safety were conducted in three age subgroups (<65 years, 65-74 years, and ≥75 years). RESULTS: Investigator-assessed PFS was significantly longer with rucaparib than placebo in patients aged <65 years (rucaparib n = 237 vs placebo n = 117; median, 11.1 vs 5.4 months; hazard ratio [HR]: 0.33 [95% confidence interval (95% CI) 0.25-0.43]; P < 0.0001) and 65-74 years (n = 113 vs n = 64; median, 8.3 vs 5.3 months; HR 0.43 [95% CI 0.29-0.63]; P < 0.0001) and numerically longer in patients aged ≥75 years (n = 25 vs n = 8; median, 9.2 vs 5.5 months; HR 0.47 [95% CI 0.16-1.35]; P = 0.1593). QA-PFS and Q-TWiST were significantly longer with rucaparib than placebo across all age subgroups. Safety of rucaparib was generally similar across the age subgroups. CONCLUSIONS: Efficacy, patient-centered outcomes, and safety of rucaparib were similar between age subgroups, indicating that all eligible women with recurrent ovarian cancer should be offered this therapeutic option, irrespective of age. https://clinicaltrials.gov/ct2/show/NCT01968213.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".