Wallace Chris, Clayton David
London School of Hygiene and Tropical Medicine, IDEU, London, UK.
Genet Epidemiol. 2003 Dec;25(4):293-302. doi: 10.1002/gepi.10270.
The relative recurrence risk ratio lambdaR (and particularly the sibling recurrence risk ratio, lambdaS) is often of interest to those wanting to quantify the genetic contribution towards risk of disease or to discriminate between different genetic models. However, estimating lambdaR for complex diseases for which genetic and environmental risk factors are both involved is not straightforward. Ignoring environmental factors may lead to inflated estimates of lambdaR. We present a marginal model which uses a copula function to model the association in cumulative incidence rates between pairs of relatives. This model is applicable to present-state data and allows estimation of risk of disease in a pair of relatives (and hence lambdaR), given measured environmental covariates. We apply the model to leprosy among sibling pairs from the Karonga district, Malawi. If risk factors are ignored, the apparent lambdaS in this population is over 3. Accounting for known nongenetic risk factors reduces it to just under 2.
相对复发风险比λR（尤其是同胞复发风险比λS）对于那些想要量化疾病风险的遗传贡献或区分不同遗传模型的人来说常常是令人感兴趣的。然而，对于涉及遗传和环境风险因素的复杂疾病，估计λR并非易事。忽略环境因素可能导致λR的估计值虚高。我们提出了一种边际模型，该模型使用copula函数对亲属对之间累积发病率的关联进行建模。该模型适用于现况数据，并允许在给定测量的环境协变量的情况下估计一对亲属的疾病风险（从而估计λR）。我们将该模型应用于马拉维卡龙加地区同胞对中的麻风病。如果忽略风险因素，该人群中明显的λS超过3。考虑已知非遗传风险因素后，该值降至略低于2。
