ArticleJournal of genetic counseling2007
Bayesian risk assessment in genetic testing for autosomal dominant disorders with age-dependent penetrance.
Article in Journal of genetic counseling, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed.
- Age-based risk estimates for C9orf72RE-related diseases: Theoretical developments and added value for genetic counseling.PLoS genetics · 2026Article
- Article
- Characterization of aryl hydrocarbon receptor interacting protein (AIP) mutations in familial isolated pituitary adenoma families.Human mutation · 2010Article
- The role of noise and positive feedback in the onset of autosomal dominant diseases.BMC systems biology · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Risk assessment is an essential component of genetic counseling and testing, and the accuracy of risk assessment is critical for decision making by consultands. However, it has been shown that genetic risk calculations may have high error rates in practice. Risk calculations for autosomal dominant disorders are frequently complicated by age-dependent penetrance and sensitivities of less than 100% in genetic testing. We provide methods of risk calculation for prototypical pedigrees of a family at risk for an autosomal dominant disorder with age-dependent penetrance. Our risk calculations include scenarios in which the sensitivity of genetic testing is less than 100%, and in which the sensitivity of genetic testing varies for different family members at risk. Our Bayesian methods permit autosomal dominant disease probabilities to be calculated accurately, taking into account all relevant information. Our methods are particularly useful for hereditary cancer syndromes, in which genetic testing can seldom achieve 100% sensitivity. Our methods can be applied to many different scenarios, including those where the sensitivity of genetic testing varies for different family members at risk.
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Registered trials
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