title: The impact of truncation and missing family links in population-based registers on familial risk estimates.
abstract: Family history information is often incomplete in population-based disease registers because of truncation and/or missing family links. In this study, the authors simulated complete populations of related individuals with realistic age, family structure, and incidence rates. After mimicking the realities of register-based data, such as left truncation of family history and missing family links due to death, the authors explored recovery of familial association parameters from standard epidemiologic models. Truncation of family history produced almost no bias for a familial risk of 2 and 50 years of follow-up, but it had a dramatic impact when the familial risk was 10. The age distribution of disease and the magnitude of background incidence rates also affected family history loss and thus the magnitude of bias. One can safeguard against bias by starting follow-up later, with the number of registration years to be ignored in the analysis depending on the value of familial risk. The missing familial links due to death had no effect, except when there was differential mortality for cases with and without a family history of disease. In summary, truncation, and to a lesser extent missing family links, induces bias in familial risk estimates from population-based registers.
authors: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
authors: Monica
authors: M
authors: Leu
authors: Kamila
authors: K
authors: Czene
authors: Marie
authors: M
authors: Reilly
mesh_terms: D001943:Breast Neoplasms / Q000453:epidemiology / Q000235:genetics; D003198:Computer Simulation; D003710:Demography; D016021:Epidemiologic Studies; D005260:Female; D020022:Genetic Predisposition to Disease / Q000453:epidemiology*; D006801:Humans; D012042:Registries; D018570:Risk Assessment; D012984:Software; D013548:Sweden