Long‐term overall survival of radical prostatectomy patients is often superior to the general population: A comparison using life‐table data
Bibliographic record
Abstract
BACKGROUND: To examine overall survival rates within a large cohort of German prostate cancer (PCa) patients and to compare these with life-expectancy (LE) predictions derived from German life tables. We hypothesized that the advantage of good general health in radical prostatectomy (RP) patients combined with favorable cancer outcomes might lead to even higher overall survival rates over 10 years compared to the LE of a general population. METHODS: A total of 6483 patients were treated with RP between 1992 and 2007 at the Martini-Klinik Prostate Cancer Center. Preoperative risk classification was performed according to D'Amico. Postoperative risk classification was performed according to the Cancer of the Prostate Risk Assessment score (CAPRA-S). A simulated cohort was created that resembled the exact age distribution of the RP population using Monte Carlo simulation which was based on data derived from official male German life tables (1992-2017). Markov chain was used to represent natural age progression of the simulated cohort. Kaplan-Meier plots were created to display the differences between 10-year observed overall survival (OS) and the simulated, predicted LE. RESULTS: For D'Amico low risk and intermediate risk, 10-year OS was 12.0% and 9.2% above predicted LE in the simulated cohort, respectively. For D'Amico high risk, OS was virtually the same as predicted LE (0.8% difference in favor of RP treated patients). For CAPRA-S low and intermediate risk, OS was 11.8% and 9.7% above predicted LE. For CAPRA-S high risk, OS was virtually the same as predicted LE (0.3% difference in favor of the simulated cohort). CONCLUSIONS: Low- and intermediate risk PCa patients treated with RP can expect a very favorable overall survival, that even exceeds LE predictions. High risk patients' overall survival perfectly aligns with LE predictions.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".