Familial risk of breast cancer by dynamic, accumulative, and static definitions of family history.

<bold>Background: </bold>Familial breast cancer risk studies usually overlook the dynamic nature of family history.<bold>Methods: </bold>The authors assessed the effect of incorporating the timing of cancer diagnosis events into the assessment of familial risks of breast cancer in first-degree and second-degree relatives in a nationwide cohort study of 5,099,172 women (follow-up was between 1958-2015). Family history was assessed using 3 approaches: 1) as a static variable (ever having a relative with breast cancer); 2) as accumulative history; and 3) as a dynamic variable (time-dependent variable).<bold>Results: </bold>For women aged <50 years, familial risk was mostly higher when family history was assessed as a dynamic variable compared with using a static or accumulative family history. For example, the cumulative risk of receiving a breast cancer diagnosis until age 50 years for women with a history of breast cancer in 1 first-degree relative was 2.6% (95% CI, 2.5%-2.7%) using the static method, 2.4% (95% CI, 2.3%-2.4%) using the accumulative method, and 3.1% (95% CI, 3.0%-3.2%) using the dynamic method. Relative risk in women aged <50 years with a breast cancer diagnosis in a sister was 1.40-fold (95% CI, 1.31-fold to 1.48-fold) using the static method, 1.66-fold (95% CI, 1.57-fold to 1.76-fold) using the accumulative method, and 2.28-fold (95% CI, 2.07-fold to 2.51-fold) using the dynamic method.<bold>Conclusions: </bold>The results of the current study demonstrated that assessing family history as static, accumulative, or dynamic results in different familial risk estimates. The answer as to which method to use for family history assessment depends on the implications of the study, with the dynamic method appearing to be better suited for risk stratification studies, the accumulative method being the most convenient in practice and the least favored for risk prediction, and the static method being suitable for etiological impact and risk attribution studies. [ABSTRACT FROM AUTHOR]