ArticleFrontiers in genetics2013
A population-based analysis of clustering identifies a strong genetic contribution to lethal prostate cancer.
Article in Frontiers in genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed, 14 citations in OpenAlex.
- High-Risk Pedigree Study IdentifiesCancers · 2023Article
- Population genealogy resource shows evidence of familial clustering for Alzheimer disease.Neurology. Genetics · 2018Article
- Simulating pedigrees ascertained for multiple disease-affected relatives.Source code for biology and medicine · 2018Article
- Novel approaches to the analysis of family data in genetic epidemiology.Frontiers in genetics · 2015Article
- Significant evidence of linkage for a gene predisposing to colorectal cancer and multiple primary cancers on 22q11.Clinical and translational gastroenterology · 2014Article
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Authors and funding
4 authors at 1 institution in 1 country.
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Abstract
backgroundProstate cancer is a common and often deadly cancer. Decades of study have yet to identify genes that explain much familial prostate cancer. Traditional linkage analysis of pedigrees has yielded results that are rarely validated. We hypothesize that there are rare segregating variants responsible for high-risk prostate cancer pedigrees, but recognize that within-pedigree heterogeneity is responsible for significant noise that overwhelms signal. Here we introduce a method to identify homogeneous subsets of prostate cancer, based on cancer characteristics, which show the best evidence for an inherited contribution.
methodsWe have modified an existing method, the Genealogical Index of Familiality (GIF) used to show evidence for significant familial clustering. The modification allows a test for excess familial clustering of a subset of prostate cancer cases when compared to all prostate cancer cases.
resultsConsideration of the familial clustering of eight clinical subsets of prostate cancer cases compared to the expected familial clustering of all prostate cancer cases identified three subsets of prostate cancer cases with evidence for familial clustering significantly in excess of expected. These subsets include prostate cancer cases diagnosed before age 50 years, prostate cancer cases with body mass index (BMI) greater than or equal to 30, and prostate cancer cases for whom prostate cancer contributed to death.
conclusionsThis analysis identified several subsets of prostate cancer cases that cluster significantly more than expected when compared to all prostate cancer familial clustering. A focus on high-risk prostate cancer cases or pedigrees with these characteristics will reduce noise and could allow identification of the rare predisposition genes or variants responsible.
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