A nomogram predicting metastatic progression after radical prostatectomy
Bibliographic record
Abstract
OBJECTIVES: To develop and internally validate a nomogram predicting the individual probability of metastatic progression after radical prostatectomy according to the length of disease-free interval. METHODS: Cox regression modeled the probability of metastatic progression of prostate cancer in 752 patients treated with radical prostatectomy with a mean follow up of 11.6 years (median 11.4; range 0.1-40.5). The significance of the predictors was confirmed in competing risks analysis, which accounts for other causes of mortality. The Cox regression model-based nomogram was internally validated with 200 bootstrap resamples. RESULTS: Eighty-five of 752 patients (11.3%) developed metastatic progression. The 5, 10, 15 and 20-year actuarial rates of metastatic progression-free survival were, respectively, 95.9, 90.5, 84.8 and 80.5%. Pathological stage T3, elevated radical prostatectomy Gleason sum and delivery of adjuvant radiotherapy represented independent predictors of metastatic progression in both Cox and competing risks regression models, and constituted the nomogram predictors along with a fourth variable describing the presence of co-morbidities. After 200 bootstrap resamples the nomogram achieved 80.2, 77.7, 77.6 and 76.0% accuracy in predicting metastatic progression at 5, 10, 15 and 20 years after radical prostatectomy. CONCLUSIONS: Metastatic progression is a sign of poor prognosis in men with prostate cancer. Our nomogram is able to accurately predict the conditional probability of metastatic progression up to 20 years after radical prostatectomy.
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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".