Cancer screening outside of age recommendations: a population-based study
Bibliographic record
Abstract
BACKGROUND: Cancer screening outside of evidence-based recommendations can be considered a form of low-value care. We aimed to describe the frequency of colorectal, breast, cervical, and prostate cancer screening outside of recommended age guidelines in Switzerland. METHODS: We analysed data from the 2022 Swiss Health Survey. Of 21,930 participants aged 15 or more, 20,515 (9,555 men and 10,960 women) were included in this study. We calculated age at last screening and classified individuals as having been not screened, screened within age-specific A, B, and C recommendations from the United States Preventive Services Taskforce (USPSTF), screened within age-specific A and B recommendations, or screened outside of recommendations. RESULTS: Among adults aged 75 years and above (75+), 40.2% (men: 35.1%; women: 44.5%) had undergone cancer screening outside of USPSTF A, B, and C recommendations. This proportion was 26.0% for adults aged 85+ (men: 27.8%; women: 24.6%). Cervical cancer screening was the most frequently undertaken outside of recommended ages by older adults (women aged 75+: 37.1%), followed by prostate (men aged 75+: 34.0%), breast (women aged 75+: 17.8%), and colorectal cancer screening (adults aged 75+: 1.3%). Screening outside of recommendations was also observed among middle-aged adults 40-59 at 12.3% (men: 20.8%; women 4.0%), and younger-aged women 20-39 at 9.9%. Proportions for screening outside of USPSTF A and B recommendations were high (adults 75+: 50.4%; adults 85+: 40.6%; adults 40-59: 20.9%). CONCLUSIONS: Cancer screening outside of recommendations is highly prevalent, particularly among older adults. Further research is needed to better understand drivers of this form of low-value care.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".