Screening for prostate cancer without digital rectal examination and transrectal ultrasound: Results after four years in the European Randomized Study of Screening for Prostate Cancer (ERSPC), Rotterdam
Bibliographic record
Abstract
BACKGROUND: Omission of DRE/TRUS as biopsy indication results in fewer unnecessary biopsies, but may increase the risk of missing potentially aggressive prostate cancers (PCs). In 1997, the biopsy indication within the ERSPC was changed from a PSA cut-off of 4.0 ng/ml and/or abnormal DRE/TRUS (group-1) to solely a PSA cut-off of 3.0 ng/ml (group-2). We estimated the effect of omitting DRE/TRUS by comparing the results of a re-screening 4 years after initial screening to the original policy. METHODS: We compared rate and characteristics of detected PCs in the second round in men initially screened in group-1 (N=5,957) or group-2 (N=8,044). Additionally, we compared the rate of interval cancers (ICs) after screening with and without DRE/TRUS. RESULTS: There was no significant difference in second round cancer-detection-rates (group-1, 3.0%; group-2, 2.7%), positive-predictive-values (group-1, 23.9%; group-2, 26.3%), and number of poorly-differentiated tumors (group-1, 2.6%; group-2, 3.8%). Most PCs were clinically confined to the prostate. Eleven ICs were detected in each group (0.18 and 0.14%). CONCLUSIONS: Omitting DRE/TRUS did not result in an increased IC- or PC-detection. However, considering the natural history of PC, the 4-year follow-up may be too short to draw a definitive conclusion.
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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 | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".