Long-Term Responders on Olaparib Maintenance in High-Grade Serous Ovarian Cancer: Clinical and Molecular Characterization
Bibliographic record
Abstract
Abstract Purpose: Maintenance therapy with olaparib has improved progression-free survival in women with high-grade serous ovarian cancer (HGSOC), particularly those harboring BRCA1/2 mutations. The objective of this study was to characterize long-term (LT) versus short-term (ST) responders to olaparib. Experimental Design: A comparative molecular analysis of Study 19 (NCT00753545), a randomized phase II trial assessing olaparib maintenance after response to platinum-based chemotherapy in HGSOC, was conducted. LT response was defined as response to olaparib/placebo >2 years, ST as <3 months. Molecular analyses included germline BRCA1/2 status, three-biomarker homologous recombination deficiency (HRD) score, BRCA1 methylation, and mutational profiling. Another olaparib maintenance study (Study 41; NCT01081951) was used as an additional cohort. Results: Thirty-seven LT (32 olaparib) and 61 ST (21 olaparib) patients were identified. Treatment was significantly associated with outcome (P < 0.0001), with more LT patients on olaparib (60.4%) than placebo (11.1%). LT sensitivity to olaparib correlated with complete response to chemotherapy (P < 0.05). In the olaparib LT group, 244 genetic alterations were detected, with TP53, BRCA1, and BRCA2 mutations being most common (90%, 25%, and 35%, respectively). BRCA2 mutations were enriched among the LT responders. BRCA methylation was not associated with response duration. High myriad HRD score (>42) and/or BRCA1/2 mutation was associated with LT response to olaparib. Study 41 confirmed the correlation of LT response with olaparib and BRCA1/2 mutation. Conclusions: Findings show that LT response to olaparib may be multifactorial and related to homologous recombination repair deficiency, particularly BRCA1/2 defects. The type of BRCA1/2 mutation warrants further investigation. Clin Cancer Res; 23(15); 4086–94. ©2017 AACR.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".