ArticleEuropean journal of epidemiology2025
Choosing a sensible contrast makes "prevalence bias" irrelevant in screening colonoscopy trials.
Article in European journal of epidemiology, 2025. 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.
- Overcoming prevalence bias in colorectal cancer screening studies by sensible analyses rather than ignoring it or giving up relevant effect measures.European journal of epidemiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Screening colonoscopy has been shown to reduce colorectal cancer incidence. However, the magnitude of this effect is debated. There is concern that some trial participants already had colorectal cancer at baseline. The screening procedure could not prevent disease occurrence in these participants, leading to "prevalence bias". Some authors have argued that the effect of interest is confined to participants without disease at baseline, and failing to exclude prevalent cases supposedly leads to effect underestimation. Yet, the issue is debated, with other authors arguing that conventional randomized trials provide the effects that are most relevant to public health. Here we present new, formal arguments that clarify misconceptions in this debate. We show that, under mild assumptions, the so-called "prevalence bias" is not a concern when researchers are interested in estimating risk differences, rather than risk ratios. This is because of a statistical property of the causal risk difference when outcomes are rare, called "doomed-selection stability".
Indexed as
Identifiers
What OpenQuestion holds
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.