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Provedor de dados:  Genet. Mol. Biol.
País:  Brazil
Título:  Performance of the Gail and Tyrer-Cuzick breast cancer risk assessment models in women screened in a primary care setting with the FHS-7 questionnaire
Autores:  Vianna,Fernanda Sales Luiz
Giacomazzi,Juliana
Oliveira Netto,Cristina Brinckmann
Nunes,Luciana Neves
Caleffi,Maira
Ashton-Prolla,Patricia
Camey,Suzi Alves
Data:  2019-01-01
Ano:  2019
Palavras-chave:  Breast neoplasms
Risk assessments
Family medical history
Hereditary breast and ovarian cancer
Resumo:  Abstract Breast cancer (BC) risk assessment models base their estimations on different aspects of a woman’s personal and familial history. The Gail and Tyrer–Cuzick models are the most commonly used, and BC risks assigned by them vary considerably especially concerning familial history. In this study, our aim was to compare the Gail and Tyrer-Cuzick models after initial screening for familial history of cancer in primary care using the FHS-7 questionnaire. We compared 846 unrelated women with at least one positive answer to any of the seven FHS-7 questions (positive group) and 892 unrelated women that answered negatively (negative group). Concordance between BC risk estimates was compared by Bland-Altman graphics. Mean BC risk estimates were higher using the Tyrer-Cuzick Model in women from the positive group, while women from the negative group had higher BC risk estimates using the Gail model. With increasing estimates, discordance also increased, mainly in the FHS-7 positive group. Our results show that in women with a familial history of cancer, the Gail model underestimates risk and the Tyrer-Cuzick seems to be more appropriate. FHS-7 can be a useful tool for the identification of women with higher breast cancer risks in the primary care setting.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572019000200232
Editor:  Sociedade Brasileira de Genética
Relação:  10.1590/1678-4685-gmb-2018-0110
Formato:  text/html
Fonte:  Genetics and Molecular Biology v.42 n.1 suppl.1 2019
Direitos:  info:eu-repo/semantics/openAccess
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