Literature DB >> 10854492

Design and analysis issues in a population-based, case-control-family study of the genetic epidemiology of breast cancer and the Co-operative Family Registry for Breast Cancer Studies (CFRBCS).

J L Hopper1, G Chenevix-Trench, D J Jolley, G S Dite, M A Jenkins, D J Venter, M R McCredie, G G Giles.   

Abstract

BACKGROUND: Historically, studies of the "genetic epidemiology" of cancer have used nonsystematically sampled kindreds with numerous cases of cancer across multiple generations. From the epidemiologic viewpoint, it is difficult to extrapolate findings to the population because of the ad hoc ascertainment of these atypical, ill-defined families. Since 1992, we have been conducting a population-based, case-control-family study of breast cancer.
METHODS: Families are identified through a single, population-sampled proband, who is either affected or unaffected, making adjustment for ascertainment straightforward. Administered questionnaires and blood samples are sought from cases, controls, and specified sets of relatives. From 1996 through 1999, a further 1200 case families have been recruited as part of the Co-operative Family Registry for Breast Cancer Studies (CFRBCS). Issues relevant to the study design and analysis are discussed.
RESULTS: Epidemiologic and genetic findings published to date are summarized. In particular, this population-based study has shown that the so-called "high-risk" families containing multiple cases of breast cancer are not typical of families in the general population in which BRCA1 or BRCA2 mutations are segregating. Most "hereditary" cancers are "sporadic."
CONCLUSION: The collection of DNA, as well as data on disease status and risk factors, from population-sampled sets of relatives provides a powerful resource for addressing genetic and environmental determinants of cancer. A population-based multicenter, multidisciplinary enterprise, such as has been developed by the CFRBCS, may become a model for future research in cancer epidemiology, allowing genetic and environmental risk factors to be put into a proper population perspective.

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Year:  1999        PMID: 10854492     DOI: 10.1093/oxfordjournals.jncimonographs.a024232

Source DB:  PubMed          Journal:  J Natl Cancer Inst Monogr        ISSN: 1052-6773


  36 in total

1.  After BRCA1 and BRCA2-what next? Multifactorial segregation analyses of three-generation, population-based Australian families affected by female breast cancer.

Authors:  J Cui; A C Antoniou; G S Dite; M C Southey; D J Venter; D F Easton; G G Giles; M R McCredie; J L Hopper
Journal:  Am J Hum Genet       Date:  2000-12-27       Impact factor: 11.025

2.  Genomewide scans of complex human diseases: true linkage is hard to find.

Authors:  J Altmüller; L J Palmer; G Fischer; H Scherb; M Wjst
Journal:  Am J Hum Genet       Date:  2001-09-14       Impact factor: 11.025

3.  Spouses and unrelated friends of probands as controls for stroke genetics studies.

Authors:  Bradford Burke Worrall; Devin L Brown; Thomas G Brott; Robert D Brown; Scott L Silliman; James F Meschia
Journal:  Neuroepidemiology       Date:  2003 Jul-Aug       Impact factor: 3.282

4.  CHEK2*1100delC and susceptibility to breast cancer: a collaborative analysis involving 10,860 breast cancer cases and 9,065 controls from 10 studies.

Authors: 
Journal:  Am J Hum Genet       Date:  2004-04-30       Impact factor: 11.025

5.  Unconditional analyses can increase efficiency in assessing gene-environment interaction of the case-combined-control design.

Authors:  Alisa M Goldstein; Marie-Gabrielle Dondon; Nadine Andrieu
Journal:  Int J Epidemiol       Date:  2006-03-23       Impact factor: 7.196

6.  Identification of a de novo BRCA1 mutation in a woman with early onset bilateral breast cancer.

Authors:  Emma Edwards; Catharina Yearwood; Julie Sillibourne; Diana Baralle; Diana Eccles
Journal:  Fam Cancer       Date:  2009-07-21       Impact factor: 2.375

7.  Prevalence of Inherited Mutations in Breast Cancer Predisposition Genes among Women in Uganda and Cameroon.

Authors:  Babatunde Adedokun; Yonglan Zheng; Paul Ndom; Antony Gakwaya; Timothy Makumbi; Alicia Y Zhou; Toshio F Yoshimatsu; Alex Rodriguez; Ravi K Madduri; Ian T Foster; Aminah Sallam; Olufunmilayo I Olopade; Dezheng Huo
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-12-23       Impact factor: 4.254

8.  Population-based, case-control-family design to investigate genetic and environmental influences on melanoma risk: Australian Melanoma Family Study.

Authors:  Anne E Cust; Helen Schmid; Judith A Maskiell; Jodie Jetann; Megan Ferguson; Elizabeth A Holland; Chantelle Agha-Hamilton; Mark A Jenkins; John Kelly; Richard F Kefford; Graham G Giles; Bruce K Armstrong; Joanne F Aitken; John L Hopper; Graham J Mann
Journal:  Am J Epidemiol       Date:  2009-11-03       Impact factor: 4.897

Review 9.  Advances in breast cancer: pathways to personalized medicine.

Authors:  Olufunmilayo I Olopade; Tatyana A Grushko; Rita Nanda; Dezheng Huo
Journal:  Clin Cancer Res       Date:  2008-12-15       Impact factor: 12.531

10.  Using SNP genotypes to improve the discrimination of a simple breast cancer risk prediction model.

Authors:  Gillian S Dite; Maryam Mahmoodi; Adrian Bickerstaffe; Fleur Hammet; Robert J Macinnis; Helen Tsimiklis; James G Dowty; Carmel Apicella; Kelly-Anne Phillips; Graham G Giles; Melissa C Southey; John L Hopper
Journal:  Breast Cancer Res Treat       Date:  2013-06-18       Impact factor: 4.872

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