Cancer‐specific survival after radical prostatectomy versus external beam radiotherapy in high‐risk and very high‐risk African American prostate cancer patients
Bibliographic record
Abstract
BACKGROUND: To test for differences in cancer-specific mortality (CSM) rates between radical prostatectomy (RP) vs external beam radiotherapy (EBRT) in National Comprehensive Cancer Network (NCCN) high-risk African American patients, as well as Johns Hopkins University (JHU) high-risk and very high-risk patients. MATERIALS AND METHODS: Within the Surveillance, Epidemiology, and End Results database (2010-2016), we identified 4165 NCCN high-risk patients, of whom 1944 (46.7%) and 2221 (53.3%) patients qualified for JHU high-risk or very high-risk definitions. Of all 4165 patients, 1390 (33.5%) were treated with RP versus 2775 (66.6%) with EBRT. Cumulative incidence plots and competing risks regression models addressed CSM before and after 1:1 propensity score matching between RP and EBRT NCCN high-risk patients. Subsequently, analyses were repeated separately in JHU high-risk and very high-risk subgroups. Finally, all analyses were repeated after landmark analyses were applied. RESULTS: In the NCCN high-risk cohort, 5-year CSM rates for RP versus EBRT were 2.4 versus 5.2%, yielding a multivariable hazard ratio of 0.50 (95% confidence interval [CI] 0.30-0.84, p = 0.009) favoring RP. In JHU very high-risk patients 5-year CSM rates for RP versus EBRT were 3.7 versus 8.4%, respectively, yielding a multivariable hazard ratio of 0.51 (95% CI: 0.28-0.95, p = 0.03) favoring RP. Conversely, in JHU high-risk patients, no significant CSM difference was recorded between RP vs EBRT (5-year CSM rates: 1.3 vs 1.3%; multivariable hazard ratio: 0.55, 95% CI: 0.16-1.90, p = 0.3). Observations were confirmed in propensity score-matched and landmark analyses adjusted cohorts. CONCLUSIONS: In JHU very high-risk African American patients, RP may hold a CSM advantage over EBRT, but not in JHU high-risk African American patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".