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.
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.
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
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
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
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
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