Increasing rates of NCCN high and very high‐risk prostate cancer versus number of prostate biopsy cores
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Recently, an increase in the rates of high-risk prostate cancer (PCa) was reported. We tested whether the rates of and low, intermediate, high and very high-risk PCa changed over time. We also tested whether the number of prostate biopsy cores contributed to changes rates over time. METHODS: Within the Surveillance, Epidemiology and End Results (SEER) database (2010-2015), annual rates of low, intermediate, high-risk according to traditional National Comprehensive Cancer Network (NCCN) and high versus very high-risk PCa according to Johns Hopkins classification were tabulated without and with adjustment for the number of prostate biopsy cores. RESULTS: In 119,574 eligible prostate cancer patients, the rates of NCCN low, intermediate, and high-risk PCa were, respectively, 29.7%, 47.8%, and 22.5%. Of high-risk patients, 39.6% and 60.4% fulfilled high and very high-risk criteria. Without adjustment for number of prostate biopsy cores, the estimated annual percentage changes (EAPC) for low, intermediate, high and very high-risk were respectively -5.5% (32.4%-24.9%, p < .01), +0.5% (47.6%-48.4%, p = .09), +4.1% (8.2%-9.9%, p < .01), and +8.9% (11.8%-16.9%, p < .01), between 2010 and 2015. After adjustment for number of prostate biopsy cores, differences in rates over time disappeared and ranged from 29.8%-29.7% for low risk, 47.9%-47.9% for intermediate risk, 8.9%-9.0% for high-risk, and 13.6%-13.6% for very high-risk PCa (all p > .05). CONCLUSIONS: The rates of high and very high-risk PCa are strongly associated with the number of prostate biopsy cores, that in turn may be driven by broader use magnetic resonance imaging (MRI).
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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) | 0.001 | 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 it