Prognostic Impact of Prostate-Specific Antigen at 6 Months After Radiotherapy in Localized Prostate Cancer: An Individual Patient Data Analysis of Randomized Trials
Bibliographic record
Abstract
PURPOSE: We sought to evaluate the prognostic impact of prostate-specific antigen (PSA) at 6 months after completion of radiotherapy (RT) in patients treated with RT alone, RT plus short-term (st; 3-6 months), and RT plus long-term (lt; 24-36 months) androgen-deprivation therapy (ADT). PATIENTS AND METHODS: Individual patient data were obtained from 16 randomized trials evaluating RT ± ADT for localized prostate cancer (PCa) between 1987 and 2011. The lowest PSA recorded within 6 months after RT completion was identified and categorized as < or ≥0.1 ng/mL. The primary outcomes were metastasis-free survival (MFS), PCa-specific mortality (PCSM), and overall survival (OS), from 12 months after random assignment. RESULTS: Ninety-eight percent (n = 2,339/2,376) of patients allocated to RT alone, 84% (n = 4,756/5,658) allocated to RT + stADT, and 77% (n = 1,258/1,626) allocated to RT + ltADT had PSA ≥0.1 ng/mL within 6 months after completing RT. PSA ≥0.1 ng/mL was associated with lower MFS and OS and higher PCSM among patients allocated to RT ± ADT (RT - MFS: hazard ratio [HR], 2.24 [95% CI, 1.21 to 4.16]; PCSM: subdistribution hazard ratio [sHR], 1.82 [0.51 to 6.49]; OS: HR, 1.72 [0.97 to 3.05]; RT + stADT - MFS: HR, 1.27 [1.12 to 1.44]; PCSM: sHR, 2.10 [1.52 to 2.92]; OS: HR, 1.26 [1.11 to 1.44]; RT + ltADT - MFS: HR, 1.58 [1.27 to 1.96]; PCSM: sHR, 1.97 [1.11 to 3.49]; OS: HR, 1.59 [1.27 to 1.99]). Five-year MFS rates among patients allocated to RT, RT + stADT, and RT + ltADT were 91% versus 79%, 83% versus 76%, and 87% versus 74%, respectively, based on PSA < or ≥0.1 ng/mL. CONCLUSION: PSA ≥0.1 ng/mL within 6 months after RT completion was prognostic for lt outcomes in patients treated with RT ± ADT for localized PCa. This can be used to counsel patients treated with RT ± ADT and in guiding clinical trial design evaluating novel systemic therapies with RT + ADT as well as (de)intensification strategies.
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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 | 0.048 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.015 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".