Distribution of prostate specific antigen (PSA) and percentage free PSA in a contemporary screening cohort with no evidence of prostate cancer
Bibliographic record
Abstract
OBJECTIVE: To explore the distribution of total prostate specific antigen (PSA) and percentage free/total PSA (%f/tPSA) in healthy volunteers with no clinical evidence of prostate cancer, who participated in prostate cancer screening. SUBJECTS AND METHODS: PSA and %f/tPSA values from 2323 men, who participated in one of three annual prostate cancer screening events between 2004 and 2006, were tabulated according to age strata of 40-49, 50-59, 60-69 and 70-79 years. Local regression smoothing plots provided a graphical display of the relation between age and PSA or %f/tPSA, respectively. All PSA and %f/tPSA analyses were repeated for each age category after excluding, respectively, the top and the bottom 10% of PSA and %f/tPSA values. RESULTS: Within the entire cohort, the median PSA level was 1.0 ng/mL and the median %f/tPSA was 25%. According to the age categories the PSA level and %f/tPSA medians within the entire cohort were, respectively, 0.7, 0.9, 1.3, 1.8 ng/mL and 28.0, 26.0, 24.0 and 25.0%. Of the 2323 men, 438 (18.9%) had a PSA level of >2.5 ng/mL and 1172 (50.5%) had a %f/tPSA of < or = 25%. When either a PSA level of >2.5 ng/mL or a %f/tPSA of < or = 25% were considered, 1235 (53.2%) had one or two abnormal values. Finally, if either a PSA level of >2.5 ng/mL or %f/tPSA of < or = 15% was used, 617 (26.6%) were considered abnormal. CONCLUSION: Half of men with no clinical evidence of prostate cancer should have PSA levels of <1.0 ng/mL and a %f/tPSA of >25%. A PSA level threshold of 2.5 ng/mL would require a biopsy in 20% of men and a %f/tPSA threshold of < or = 25% in half of the men. Alternatively, a %f/tPSA threshold of < or = 15% would decrease the probability to 15%.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".