Blood Biomarker Landscape in Patients with High-risk Nonmetastatic Castration-Resistant Prostate Cancer Treated with Apalutamide and Androgen-Deprivation Therapy as They Progress to Metastatic Disease
Bibliographic record
Abstract
Abstract Purpose: In the placebo-controlled SPARTAN study, apalutamide added to androgen-deprivation therapy (ADT) improved metastasis-free survival, second progression-free survival (PFS2), and overall survival (OS) in patients with nonmetastatic castration-resistant prostate cancer (nmCRPC). Mechanisms of resistance to apalutamide in nmCRPC require evaluation. Patients and Methods: In a subset of patients from SPARTAN, aberrations were assessed at baseline and end of study treatment (EOST) using targeted next-generation sequencing or qRT-PCR. Circulating-tumor DNA (ctDNA) levels were assessed qualitatively. Select aberrations in androgen receptor (AR) and other common PC-driving genes were detected and summarized by the treatment group; genomic aberrations were summarized in ctDNA-positive samples. Association between detection of aberrations in all patients and outcomes was assessed using Cox proportional-hazards models and multivariate analysis. Results: In 247 patients, the overall prevalence of ctDNA, AR aberrations, and TP53 inactivation increased from baseline (40.6%, 13.6%, and 22.2%) to EOST (57.1%, 25.4%, and 35.0%) and was comparable between treatment groups at EOST. In patients who received subsequent androgen signaling inhibition after study treatment, detectable biomarkers at EOST were significantly associated with poor outcomes: ctDNA with PFS2 or OS (HR, 2.01 or 2.17, respectively; P < 0.0001 for both), any AR aberration with PFS2 (1.74; P = 0.024), and TP53 or BRCA2 inactivation with OS (2.06; P = 0.003; or 3.1; P < 0.0001). Conclusions: Apalutamide plus ADT did not increase detectable AR/non-AR aberrations over ADT alone. Detectable ctDNA, AR aberrations, and TP53/BRCA2 inactivation at EOST were associated with poor outcomes in patients treated with first subsequent androgen signaling inhibitor.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".