Occupation as a predictor of prostate cancer screening behaviour in Canada
Bibliographic record
Abstract
ObjectivesIf prostate cancer screening practices relate to occupation, this would have important implications when studying the aetiological role of workplace exposures on prostate cancer. We identified variations in screening by occupation among men in Montreal, Canada (2005–2012).MethodsProstate specific antigen testing and digital rectal examination (ever-screened and frequency of screening, previous five years) were examined among population controls from the Prostate Cancer & Environment Study. Face-to-face interviews elicited lifestyle and occupational histories. Multivariable logistic regression was used to estimate the odds of ever-screening for the longest-held occupation, adjusting for potential confounders. Negative binomial models were used to examine relationships with screening frequency.ResultsAmong 1989 controls, 81% reported ever having had a prostate specific antigen test, and 77% a digital rectal examination. Approximately 40% of men reported having a prostate specific antigen test once a year, on average. Compared with those in management or administrative jobs, men in primary industry (odds ratio 0.26, 95% confidence interval 0.10–0.65), construction (0.44, 0.25–0.79), machining (0.45, 0.21–0.97), and teaching (0.37, 0.20–0.70) were less likely to have undergone prostate specific antigen screening. Results were similar when considering the most recent job.ConclusionsOur findings highlight substantial variations in prostate cancer screening by occupation. Men in occupations where carcinogen exposures are more common are less likely to participate in prostate screening activities. This could be an important source of bias, and occupational studies of prostate cancer should account for screening practices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".