Prostate‐specific antigen kinetics in Asian patients with metastatic castration‐sensitive prostate cancer treated with apalutamide in the <scp>TITAN</scp> trial: A post hoc analysis
Bibliographic record
Abstract
OBJECTIVE: In the TITAN trial of patients with metastatic castration-sensitive prostate cancer (mCSPC), deep and rapid prostate-specific antigen (PSA) decline with apalutamide plus androgen deprivation therapy (ADT) was associated with longer overall survival (OS), radiographic progression-free survival (rPFS), time to PSA progression (TTPP), and time to castration resistance (TTCR) compared with no decline (all p < 0.0001). This post hoc analysis evaluated PSA kinetics in the Asian subpopulation. METHODS: Data were analyzed for patients enrolled in China, Japan, and Korea and treated with apalutamide (n = 111) or placebo (n = 110) plus ADT. Examined were depth of PSA response, rates of PSA decline, and associations between a deep PSA response and clinical outcomes in apalutamide-treated patients. RESULTS: Confirmed PSA response rates were higher with apalutamide than placebo: 73.9% versus 33.6% for PSA ≤0.2 ng/mL, 90.1% versus 58.2% for PSA reduction ≥50% [PSA50], and 74.8% versus 25.5% for PSA reduction ≥90% [PSA90]. Median (Q1; Q3) time to PSA ≤0.2 ng/mL, PSA50 and PSA90 response in the apalutamide group was 1.9 (1.0; 3.7), 1.0 (1.0; 1.0), and 1.8 (1.0; 1.9) months, respectively. PSA responses with apalutamide or placebo were consistent irrespective of high- or low-volume disease. Achievement of confirmed PSA ≤0.2 ng/mL or PSA90 response with apalutamide at landmark 3 months was associated with significantly (nominal p-values) longer OS (hazard ratio: 0.23; p = 0.0009), TTPP (0.16; p = 0.0001), TTCR (0.20; p < 0.0001), and time to progression on first subsequent therapy or death (0.19; p < 0.0001) compared with no decline. CONCLUSION: PSA kinetics have applications for early prognostic evaluation in Asian patients with mCSPC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".