Early radiotherapy after radical prostatectomy improves cancer‐specific survival only in patients with highly aggressive prostate cancer: Validation of recently released criteria
Bibliographic record
Abstract
OBJECTIVES: To test the effect of radiotherapy administered within 6 months after radical prostatectomy on cancer-specific mortality in prostate cancer patients after stratification according to a risk score. METHODS: Overall, 7616 patients with pT3/4 N0/1 prostate cancer treated with radical prostatectomy between 1995 and 2009 within the Surveillance Epidemiology and End Results Medicare-linked database were included in the study. Competing-risks regression models were carried out to test the effect of early radiotherapy on cancer-specific mortality in the entire cohort, and after stratifying patients according to the risk score based on the number and nature of adverse pathological characteristics (Gleason score 8-10; pT3b/4, lymph node invasion). RESULTS: The risk score was associated with increasing 5- and 10-year cancer-specific mortality rates (P < 0.001). When considering only patients with a risk score ≥ 2, 5- and 10-year cancer-specific mortality rates were significantly lower for individuals undergoing early radiotherapy compared with their counterparts not receiving early radiotherapy (2.9 and 6.9 vs 5.7 and 16.2%, respectively; P = 0.002). The corresponding number required to treat to prevent one death from prostate cancer at 10-year follow up was 10. Early radiotherapy was not associated with lower cancer-specific mortality rates overall and in patients with a risk score <2. This was confirmed in multivariable analyses, where early radiotherapy decreased the risk of cancer-specific mortality only in patients with a risk score ≥ 2 (P ≤ 0.02). CONCLUSIONS: The presence of two or more of the following pathological features might be used to identify patients who benefit from early radiotherapy: Gleason score 8-10, pT3b/4 and lymph node invasion.
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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) | 0.000 | 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".