ArticleEuropean journal of epidemiology2011
Residual confounding after adjustment for age: a minor issue in breast cancer screening effectiveness.
Article in European journal of epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Negative controls to detect uncontrolled confounding in observational studies of mammographic screening comparing participants and non-participants.International journal of epidemiology · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Residual confounding, after adjustment for age, is the major criticism of observational studies on breast cancer screening effectiveness. We developed realistic scenarios for the prevalence and strength of risk factors on screened and not screened groups, and explored the impact of residual confounding bias. Our results demonstrate that residual confounding bias is a minor issue in screening programme evaluations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.