Prostate specific antigen (PSA) screening rates and factors associated with screening in Eastern Canadian men: Findings from cross-sectional survey data
Bibliographic record
Abstract
INTRODUCTION: The prostate-specific antigen (PSA) test is used in Canada to detect prostate cancer (PCa) despite mixed recommendations. Complications arising from false-positives are common, posing as a cancer-screening concern. This work estimates some Canadian rates of PSA screening and identifies men at increased odds for PSA screening. METHODS: The Canadian Community Health Survey (CCHS) from 2009/10 (Atlantic Canada; ATL), 2011/2012 (Ontario; ON), and 2013/2014 (Quebec; QC) were used. Lifetime and recent PSA screening with confidence intervals were constructed to estimate PSA screening in ATL, ON, and QC. Two logistic regression models (for men <50 and ≥50 years of age) were used to determine associations between factors and lifetime PSA screening. RESULTS: PSA screening rates have increased in most age groups for ATL, ON, and QC since 2000/2001. Factors positively associated with lifetime PSA screening in men of all ages were: having a digital rectal exam, having a regular doctor, and having a colorectal exam. Fruit and vegetables consumption and non-smoking status were positively associated with lifetime PSA screening in men <50 years of age. High income and the presence of chronic health conditions were positively associated with lifetime PSA screening in men ≥50 years of age. CONCLUSIONS: PSA screening rates have generally increased since 2000/2001 in Canada. Physician-related factors play a role in men at all ages, while different factors are associated in men <50 years of age and men ≥50 years of age. Limitations include the generalizability to all of Canada and the potential for recall bias.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".