009 Frequency of low-value cancer screening: a nationwide population-based study
Bibliographic record
Abstract
Objectives Cancer screening is only recommended when the benefits of a screening test outweigh its harms at a reasonable cost. Evidence-based guideline recommendations produced by independent expert bodies are an important decision-making tool that should guide cancer screening practices. Screening outside of these recommendations is a form of low-value care that can lead to unnecessary harm including overdiagnosis. Our goal was to estimate the frequency of colorectal, breast, cervical, and prostate cancer screening outside of the recommended age guidelines in Switzerland. Method We undertook a secondary data analysis of the 2022 Swiss Health Survey, a random-sampled nationwide population-based cross-sectional survey of 21,930 (36.2% participation rate) Swiss residents aged 15 years and above. Survey participants underwent telephone interviews where they self-reported cancer screening use for breast, cervical, colorectal, and prostate cancer. Participants indicated whether they had undergone specified screening tests and, if they had, the reason (preventive or other) and timing of their most recent corresponding test. We calculated participants’ age at screening and classified participants as either having not undergone screening, undergone screening within United States Preventive Service Taskforce (USPSTF) A, B, and C grade and A and B grade recommendations, or undergone screening outside these recommendations, respectively. Results Cancer screening outside of USPSTF A, B, and C recommendations was observed among 40.2% of older adults 75 years old or more (75+), with a higher proportion among women (44.5%) than men (35.1%) within this age group. The proportion of adults aged 75+ who have been screened outside of A and B recommendations was 50.4% (women: 50.2%; men: 50.5%). Among adults aged 40–59, the proportions screened outside of A, B, and C recommendations were 12.3% and 20.9% for A and B recommendations. Among women aged 20–39 years, screening outside of recommendations was observed at 9.9% for both A, B, and C and A and B recommendations. Cervical and prostate cancer screening were the most frequently used outside of A, B, and C recommendations among adults aged 75+ (37.1% of women; 34.0% of men). Conclusions Cancer screening outside of evidence-based recommendations is highly common, especially among older adults. These low-value screening practices likely contribute to high rates of overdiagnosis and overtreatment of inconsequential cancers. Interventions aimed at de-implementing and deterring this form of low-value care urgently need to be developed to prevent overdiagnosis.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".