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Медицинская библиотека · Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2003

Modeling familial clustered breast cancer using published data.

Jonker M A, Jacobi C E, Hoogendoorn W E, Nagelkerke N J D, de Bock Geertruida H, van Houwelingen Johannes C

Сравнительное исследованиеСтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

The purpose of this research was to model the familial clustering of breast cancer and to provide an accurate risk estimate for individuals from the general population, based on their family history of breast and ovarian cancer. We constructed a genetic model as an extension of a model by Claus et al. (E. B. Claus et al., Am. J. Hum. Genet., 48: 232-242, 1991), with three breast cancer genes, BRCA1, BRCA2, and a hypothetical BRCAu, in two variants, one in which BRCAu was dominant and one in which BRCAu was recessive. The model parameters were estimated using published estimates of population incidence and relative risks. Risk estimation was performed for a set of 196 counselees and for a set of simulated counselees with both the dominant BRCAu and the recessive BRCAu model, and compared relating to medical management. Estimates of the model parameters were found. Relative risks among family members were comparable between the model of Claus et al. (E. B. Claus et al., Am. J. Hum. Genet., 48: 232-242, 1991) and our model. The dominant and the recessive model provided approximately similar lifetime risks for breast cancer. Our model is suitable for breast cancer risk estimation in a health care setting.

Для цитирования: Jonker M A, Jacobi C E, Hoogendoorn W E, Nagelkerke N J D, de Bock Geertruida H, van Houwelingen Johannes C. Modeling familial clustered breast cancer using published data.. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. 2003.

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