Source:http://linkedlifedata.com/resource/pubmed/id/11507721
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
2
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| pubmed:dateCreated |
2001-8-16
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| pubmed:abstractText |
When a rare inherited mutation in a disease gene, such as BRCA1, is found through extensive study of high-risk families, it is critical to estimate not only age-specific penetrance of the disease associated with the mutation, but also the residual effect of family history once the mutation is taken into account. The kin-cohort design, a cross-sectional survey of a suitable population that collects DNA and family history data, provides an efficient alternative to cohort or case-control designs for estimating age-specific penetrance in a population not selected because of high familial risk. In this report, we develop a method for analyzing kin-cohort data that simultaneously estimate the age-specific cumulative risk of the disease among the carriers and non-carriers of the mutations and the gene-adjusted residual familial aggregation or correlation of the disease. We employ a semiparametric modeling approach, where the marginal cumulative risks corresponding to the carriers and non-carriers are treated non-parametrically and the residual familial aggregation is described parametrically by a class of bivariate failure time models known as copula models. A simple and robust two-stage method is developed for estimation. We apply the method to data from the Washington Ashkenazi Study [Struewing et al., 1997, N Engl J Med 336:1401-1408] to study the residual effect of family history on the risk of breast cancer among non-carriers and carriers of specific BRCA1/BRCA2 germline mutations. We find that positive history of a single first-degree relative significantly increases risk of the non-carriers (RR = 2.0, 95% CI = 1.6-2.6) but has little or no effect on the carriers.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:citationSubset |
IM
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| pubmed:chemical | |
| pubmed:status |
MEDLINE
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| pubmed:month |
Sep
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| pubmed:issn |
0741-0395
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| pubmed:author | |
| pubmed:copyrightInfo |
Copyright 2001 Wiley-Liss, Inc.
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| pubmed:issnType |
Print
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| pubmed:volume |
21
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
123-38
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| pubmed:dateRevised |
2009-11-19
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| pubmed:meshHeading |
pubmed-meshheading:11507721-BRCA2 Protein,
pubmed-meshheading:11507721-Biometry,
pubmed-meshheading:11507721-Breast Neoplasms,
pubmed-meshheading:11507721-Cohort Studies,
pubmed-meshheading:11507721-District of Columbia,
pubmed-meshheading:11507721-Epidemiologic Methods,
pubmed-meshheading:11507721-Female,
pubmed-meshheading:11507721-Genes, BRCA1,
pubmed-meshheading:11507721-Genetic Testing,
pubmed-meshheading:11507721-Genotype,
pubmed-meshheading:11507721-Humans,
pubmed-meshheading:11507721-Jews,
pubmed-meshheading:11507721-Likelihood Functions,
pubmed-meshheading:11507721-Models, Statistical,
pubmed-meshheading:11507721-Mutation,
pubmed-meshheading:11507721-Neoplasm Proteins,
pubmed-meshheading:11507721-Risk Factors,
pubmed-meshheading:11507721-Transcription Factors
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| pubmed:year |
2001
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| pubmed:articleTitle |
Association and aggregation analysis using kin-cohort designs with applications to genotype and family history data from the Washington Ashkenazi Study.
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| pubmed:affiliation |
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland 20852, USA. chattern@mail.nih.gov
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| pubmed:publicationType |
Journal Article
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