Association of black race with improved outcomes following definitive radiotherapy with androgen deprivation therapy for high-risk prostate cancer: A meta-analysis of eight randomized trials.
Bibliographic record
Abstract
327 Background: Though Black men with prostate cancer are more likely to have aggressive disease features than White men, race-specific differences in initial treatment responses in localized disease remains unknown. Methods: Individual patient data were obtained for 9259 patients (including 1674 [18.1%] Black men and 7585 [81.9%] White men) enrolled on eight randomized controlled trials evaluating definitive radiotherapy (RT) ± short-term or long-term androgen deprivation therapy (STADT and LTADT). The primary endpoints were biochemical recurrence (BCR), distant metastasis (DM), and prostate cancer-specific mortality (PCSM). Fine-Gray subdistribution HR (sHR) models were developed to evaluate the cumulative incidences of all endpoints after stratification by National Comprehensive Cancer Network risk grouping. A meta-analysis was done to estimate pair-wise comparisons of treatments within and between Black and White men, after adjusting for age, Gleason score, clinical T stage, and initial PSA. Results: Black men were more likely to have NCCN high-risk disease at enrollment (656/1674 [39.2%] vs 2506/7585 [33%], p<0.001). However, within the high-risk stratum Black men had lower 10-year rates of BCR (46.1% vs. 50.4%, p=0.02), DM (14% vs. 21.6%, p<0.001), and PCSM (4.9% vs. 9.8%, p<0.001). After adjusting for age and disease characteristics, Black men with high-risk prostate receiving RT+STADT had lower rates of BCR (sHR 0.73, 95% CI 0.62-0.86, p<0.001), DM (sHR 0.64, 95% CI 0.49-0.84, p=0.001) and PCSM (sHR 0.49, 95% CI 0.25-0.95, p=0.04). There were no differences in BCR, DM, or PCSM among men receiving RT+LTADT. The interaction between race and the impact of adding STADT to RT alone on BCR was statistically significant (p=0.003). Conclusions: Black men enrolled on randomized trials with long-term follow-up have higher risk disease at enrollment, but have better BCR, DM, and PCSM outcomes with RT-based therapy compared with White men, particularly with the addition of STADT.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.034 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".