Radiation therapy after radical prostatectomy is associated with higher other-cause mortality
Bibliographic record
Abstract
PURPOSE: To test the association between external beam radiotherapy (EBRT) after radical prostatectomy (RP) vs RP only on rates of other-cause mortality (OCM) in men with prostate cancer (PCa). PATIENTS AND METHODS: Within the 2004-2016 Surveillance, Epidemiology, and End Results database, we identified 181,849 localized PCa patients, of whom 168,041 received RP only vs 13,808 who received RP + EBRT. Cumulative incidence plots displayed OCM between RP vs RP + EBRT after propensity score matching for age, PSA, clinical T- and N-stages, and biopsy Gleason scores. Multivariable competing risks regression models addressed OCM, accounting prostate cancer-specific mortality (CSM) as a competing event. Stratifications were made according to low- vs intermediate- vs high-risk groups and additionally according to age groups of ≤ 60, 61-70, and ≥ 71 years, within each risk group. RESULTS: In low-, intermediate-, and high-risk patients, RP + EBRT rates were 2.7, 5.4 and 17.0%, respectively. After matching, 10-year OCM rates between RP and RP + EBRT were 7.7 vs 16.2% in low-, 9.4 vs 13.6% in intermediate-, and 11.4 vs 13.5% in high-risk patients (all p < 0.001), which, respectively, resulted in multivariable HR of 2.1, 1.3, and 1.2 (all p < 0.001). In subgroup analyses, excess OCM was recorded in low-risk RP + EBRT patients of all age groups (all p ≤ 0.03), but only in the older age group in intermediate-risk patients (61-70 years, p = 0.03) and finally, only in the oldest age group in high-risk patients (≥ 71 years, p = 0.02). CONCLUSION: Excess OCM was recorded in patients exposed to RT after RP. Its extent was most pronounced in low-risk patients, decreased in intermediate-risk patients, and was lowest in high-risk patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".