Niraparib in patients (pts) with metastatic castration-resistant prostate cancer (mCRPC) and biallelic DNA-repair gene defects (DRD): Correlative measures of tumor response in phase II GALAHAD study.
Bibliographic record
Abstract
118 Background: Niraparib, a highly potent and selective poly (ADP-ribose) polymerase inhibitor (PARPi) received breakthrough designation by US FDA for treatment of pts with BRCA1,2 mutant mCRPC who progressed on taxane and androgen receptor-targeted therapy. Circulating tumor cells (CTC) detection associates with poor outcomes, with declining counts consistent with improved survival [1,2]. Methods: GALAHAD study assessed niraparib (300 mg daily) in pts with mCRPC+DRD (NCT02854436). Patients with non-measurable soft tissue disease by RECIST 1.1 were required to have a baseline CTC count ≥1 cell/7.5 mL blood. CTC response was defined as CTC conversion to <5 for pts with baseline CTC≥5 and CTC drop to 0 post-baseline for pts with ≥1 baseline CTC. Alkaline phosphatase (ALP) was collected at each monthly cycle. Results: For primary efficacy population of pts with BRCA1/2 mutations, the objective response rate (ORR) by RECIST 1.1 criteria was 41.4%. CTC response rates for this population were as high as ORR regardless of measurability (Table). Time to CTC response for each CTC responder will be shown. Radiographic progression-free survival (rPFS) durations were similar for patients with a measurable disease response and patients with CTC conversion. Median duration of treatment for responders of any type was 6.7mo (range: 2–27). DRD status, both BRCA and non- BRCA, for each responder will also be discussed. Trends in disease burden and markers of bone metabolism will also be quantitatively explored including 24% pts who were on treatment for at least one cycle who had ≥25% decreased unfractionated ALP from baseline. Conclusions: Niraparib showed clinical activity with CTC response and decline in ALP levels in mCRPC pts having biallelic BRCA mutations, which further supports its recent breakthrough designation. Clinical trial information: NCT02854436. [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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".