Metastatic disease of screen‐detected prostate cancer
Bibliographic record
Abstract
BACKGROUND: Screening for prostate cancer has not only led to a stage migration, but also to a higher incidence of the disease. A decrease in mortality has occurred in several countries during the same time period. Risk stratification of screen-detected cancers at diagnosis has become more important for the anticipation and interpretation of changing incidence/mortality ratios. METHODS: From 1993 to 1998, 633 men were diagnosed with nonmetastatic prostate cancer in the prevalence screen of the Rotterdam section of the European Randomized study of Screening for Prostate Cancer (ERSPC). The characteristics at diagnosis of men who developed metastatic disease were compared with men without evidence of metastases during follow-up. RESULTS: During the median follow-up of 7.5 years, 41 men developed metastatic disease. After 10 years the metastasis-free survival rate was 89.6%, the overall survival 64.7%. In a Cox-model 2logPSA (prostate-specific antigen), biopsy Gleason score and the number of biopsy cores with prostate cancer were independent predictors for the development of metastases; the latter only predicted metastases that presented within 60 months of follow-up. CONCLUSIONS: The metastasis-free survival of men with prostate cancer detected in a prevalence screening was very high. Whether this was related to the beneficial effects of screening or to overdiagnosis due to screening (or both) remains unclear. The prognostic factors known for clinically diagnosed disease also hold for screen-detected disease.
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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 | 0.000 | 0.002 |
| 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) | 0.003 | 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".