Olaparib Efficacy in Patients with Metastatic Castration-resistant Prostate Cancer and <i>BRCA1, BRCA2</i> , or <i>ATM</i> Alterations Identified by Testing Circulating Tumor DNA
Bibliographic record
Abstract
PURPOSE: The phase III PROfound study (NCT02987543) evaluated olaparib versus abiraterone or enzalutamide (control) in metastatic castration-resistant prostate cancer (mCRPC) with tumor homologous recombination repair (HRR) gene alterations. We present exploratory analyses on the use of circulating tumor DNA (ctDNA) testing as an additional method to identify patients with mCRPC with HRR gene alterations who may be eligible for olaparib treatment. PATIENTS AND METHODS: Plasma samples collected during screening in PROfound were retrospectively sequenced using the FoundationOne®Liquid CDx test for BRCA1, BRCA2 (BRCA), and ATM alterations in ctDNA. Only patients from Cohort A (BRCA/ATM alteration positive by tissue testing) were evaluated. We compared clinical outcomes, including radiographic progression-free survival (rPFS) between the ctDNA subgroup and Cohort A. RESULTS: Of the 181 (73.9%) Cohort A patients who gave consent for plasma sample ctDNA testing, 139 (76.8%) yielded a result and BRCA/ATM alterations were identified in 111 (79.9%). Of these, 73 patients received olaparib and 38 received control. Patients' baseline demographics and characteristics, and the prevalence of HRR alterations were comparable with the Cohort A intention-to-treat (ITT) population. rPFS was longer in the olaparib group versus control [median 7.4 vs. 3.5 months; hazard ratio (HR), 0.33; 95% confidence interval (CI), 0.21-0.53; nominal P < 0.0001], which is consistent with Cohort A ITT population (HR, 0.34; 95% CI, 0.25-0.47). CONCLUSIONS: When tumor tissue testing is not feasible or has failed, ctDNA testing may be a suitable alternative to identify patients with mCRPC carrying BRCA/ATM alterations who may benefit from olaparib treatment.
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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) | 0.001 | 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".