Patient-Centered Outcomes in ARIEL3, a Phase III, Randomized, Placebo-Controlled Trial of Rucaparib Maintenance Treatment in Patients With Recurrent Ovarian Carcinoma
Bibliographic record
Abstract
PURPOSE To investigate quality-adjusted progression-free survival (QA-PFS) and quality-adjusted time without symptoms or toxicity (Q-TWiST) in a post hoc exploratory analysis of the phase III ARIEL3 study of rucaparib maintenance treatment versus placebo. PATIENTS AND METHODS Patients with platinum-sensitive, recurrent ovarian carcinoma were randomly assigned to rucaparib (600 mg twice per day) or placebo. QA-PFS was calculated as progression-free survival function × the 3-level version of the EQ-5D questionnaire (EQ-5D-3L) index score function. Q-TWiST analyses were performed defining TOX as the mean duration in which a patient experienced grade ≥ 3 treatment-emergent adverse events (TEAEs) or the mean duration in which a patient experienced grade ≥ 2 TEAEs of nausea, vomiting, fatigue, and asthenia. Q-TWiST was calculated as μTOX × TOX + TWiST, with μTOX calculated using EQ-5D-3L data. RESULTS The visit cutoff was Apr 15, 2017. Mean QA-PFS was significantly longer with rucaparib versus placebo in the intent-to-treat (ITT) population (375 randomly assigned to rucaparib v 189 randomly assigned to placebo; difference, 6.28 months [95% CI, 4.85 to 7.47 months]); BRCA-mutant cohort (130 rucaparib v 66 placebo; 9.37 months [95% CI, 6.65 to 11.85 months]); homologous recombination deficient (HRD) cohort (236 rucaparib v 118 placebo; 7.93 months [95% CI, 5.93 to 9.53 months]); and BRCA wild-type/loss of heterozygosity (LOH) low patient subgroup (107 rucaparib v 54 placebo; 2.71 months [95% CI, 0.31 to 4.44 months]). With TOX defined using grade ≥ 3 TEAEs, the difference in mean Q-TWiST (rucaparib v placebo) was 6.88 months (95% CI, 5.71 to 8.23 months), 9.73 months (95% CI, 7.10 to 11.94 months), 8.11 months (95% CI, 6.36 to 9.49 months), and 3.35 months (95% CI, 1.66 to 5.40 months) in the ITT population, BRCA-mutant cohort, HRD cohort, and BRCA wild-type/LOH low patient subgroup, respectively. Q-TWiST with TOX defined using select grade ≥ 2 TEAEs also consistently favored rucaparib. CONCLUSION The significant differences in QA-PFS and Q-TWiST confirm the benefit of rucaparib versus placebo in all predefined cohorts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".