Leu Monica, Czene Kamila, Reilly Marie
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Am J Epidemiol. 2007 Dec 15;166(12):1461-7. doi: 10.1093/aje/kwm234. Epub 2007 Sep 17.
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.
由于截断和/或家族联系缺失,基于人群的疾病登记中家族史信息往往不完整。在本研究中,作者模拟了具有实际年龄、家族结构和发病率的相关个体的完整人群。在模拟基于登记数据的实际情况,如家族史的左截断和因死亡导致的家族联系缺失后,作者探索了从标准流行病学模型中恢复家族关联参数的方法。家族史的截断对于2倍的家族风险和50年的随访几乎没有偏差,但当家族风险为10时,它产生了巨大影响。疾病的年龄分布和背景发病率的大小也会影响家族史的丢失,从而影响偏差的大小。可以通过稍后开始随访来防止偏差,分析中要忽略的登记年数取决于家族风险的值。因死亡导致的家族联系缺失没有影响,除非有家族病史和无家族病史的病例存在差异死亡率。总之,截断以及在较小程度上的家族联系缺失会导致基于人群登记的家族风险估计产生偏差。