Refinement of prespecified cutoff for genomic loss of heterozygosity (LOH) in ARIEL2 part 1: A phase II study of rucaparib in patients (pts) with high grade ovarian carcinoma (HGOC).
Bibliographic record
Abstract
5540 Background: ARIEL2 (NCT01891344) prospectively evaluated a tumor-based next-generation sequencing (NGS) LOH assay and novel algorithm to predict sensitivity to rucaparib based on BRCAmutstatus and degree of genomic LOH. Methods: Pts with measurable, platinum-sensitive HGOC were classified as BRCAmut, BRCAwt/LOHhigh (BRCA-like), or BRCAwt/LOHlow by NGS analysis of tumor tissue DNA. The primary objective of this analysis was to compare progression-free survival (PFS) of BRCAmut vs LOHhigh and LOHlow tumors. A planned post hoc analysis identified a refined genomic LOH cutoff to differentiate PFS of pts with LOHhigh vs LOHlowtumors. Results: ARIEL2 part 1 completed enrollment in December 2014; the data cutoff date was January 18, 2016. In 204 treated pts, median age was 65 years; median number of prior regimens was 1. Efficacy data are shown in the Table. The confirmed radiologic objective response rate (rORR) for germline (n=20) and somatic (n=20) BRCAmut pts was 85% and 75%, respectively. Refinement of the LOH cutoff improved median PFS and PFS HR in the LOHhigh vs LOHlowgroup. Common treatment-related AEs included nausea (71%; grade ≥3: 3%), fatigue (59%; grade ≥3: 6%), ALT/AST increased (41%; grade ≥3: 11%), and anemia (30%; grade ≥3: 19%). Three pts died due to disease progression. Conclusions: Refinement of the genomic LOH cutoff improves selection of BRCAwt/LOHhigh pts more likely to benefit from rucaparib. Clinical trial information: NCT01891344. BRCAmut Prespecified LOH Cutoff BRCAwt/LOHhigh BRCAwt/LOHlow n* 40 82 70 rORR, % 80.0 35.4† 12.9† DOR‡ 11.2 (7.4–13.7) 10.8 (5.5–12.0) 5.9 (4.6–8.5) PFS‡ 12.8 (9.0–14.7) 5.7 (5.3–7.6) 5.2 (3.6–5.5) PFS HR§ 0.27 (0.16–0.44); P<0.001 0.62 (0.42–0.90); P=0.011 − BRCAmut Refined LOH Cutoff BRCAwt/LOHhigh BRCAwt/LOHlow n* 40 69 83 rORR, % 80.0 39.1† 13.3† DOR‡ 11.2 (7.4–13.7) 10.8 (7.6–20.6) 5.7 (1.9–7.4) PFS‡ 12.8 (9.0–14.7) 7.2 (5.5–9.6) 5.0 (3.6–5.4) PFS HR§ 0.25 (0.15–0.42); P<0.001 0.51 (0.34–0.74); P<0.001 − DOR, duration of response; HR, hazard ratio. *LOH not determined for 12 pts. †Both confirmed and unconfirmed responses (RECIST v1.1). ‡Median months (95% confidence interval [CI]). §HR (95% CI) vs BRCAwt/LOHlow.
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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 | 0.003 | 0.002 |
| 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 | 0.001 | 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".