Adverse events (AEs) with maintenance olaparib tablets in patients (pts) with <i>BRCA</i>-mutated (<i>BRCA</i>m) platinum-sensitive relapsed serous ovarian cancer (PSR SOC): Phase III SOLO2 trial.
Bibliographic record
Abstract
5518 Background: In the SOLO2 trial (ENGOT Ov-21; NCT01874353), maintenance therapy with the PARP inhibitor olaparib significantly improved PFS vs placebo (PBO) in BRCAm PSR SOC pts (HR 0.30, 95% CI 0.22–0.41, P<0.0001; median 19.1 vs 5.5 months) and was well tolerated (Pujade-Lauraine et al, SGO 2017). We analyzed AEs in SOLO2, the first study in PSR SOC to use the olaparib tablet formulation. Methods: Pts with BRCAm PSR SOC, who were in response to platinum chemotherapy, were treated with olaparib (300 mg bid; tablets; n=195) or PBO (n=99) until progression. AEs were graded by CTCAE v4.0. Results: The most common AEs with olaparib – nausea, fatigue/asthenia, anemia, and vomiting – were largely grade 1–2, though anemia was the most common grade ≥3 AE. AEs of fatigue/asthenia, vomiting and nausea generally improved as treatment continued, though fatigue/asthenia and anemia could last for several months (table). Most AEs were manageable by supportive treatment, dose interruptions (olaparib, 45%; PBO, 18%) and dose reductions (olaparib, 25%; PBO, 3%). Discontinuation of olaparib due to AEs was minimal (11%); anemia and neutropenia were the only AEs leading to discontinuation of olaparib in >one pt. Conclusions: Most AEs experienced by pts receiving olaparib tablets in SOLO2 were low grade and manageable. Initial nausea, vomiting and fatigue generally improved with ongoing treatment. The majority of AEs first occurred within the first three months of treatment. AEs causing treatment discontinuation were rare and mainly hematological. Clinical trial information: NCT01874353. [Table: see text]
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".