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评估疾病家族聚集性的回归方法。

Regression methods for assessing familial aggregation of disease.

作者信息

Laird Nan M, Cuenco Karen T

机构信息

Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.

出版信息

Stat Med. 2003 May 15;22(9):1447-55. doi: 10.1002/sim.1504.

Abstract

This paper reviews methods for assessing familial aggregation of disease based on simple logistic regression models. Studies are based on a case-control sampling design, where the disease status of the first degree relatives of both cases and controls are obtained. Both 'proband predictive' and 'family predictive' models are discussed, and an example is given using a case-control sample from a lung cancer study in non-smokers. The methods are extended to characterize co-aggregation of two disorders, that is, presence of one disorder in the proband increases the risk of a second disorder in the relative. An example involving eating disorders and depression is given.

摘要

本文回顾了基于简单逻辑回归模型评估疾病家族聚集性的方法。研究基于病例对照抽样设计,获取病例组和对照组一级亲属的疾病状态。文中讨论了“先证者预测”模型和“家族预测”模型,并给出了一个来自非吸烟者肺癌研究的病例对照样本实例。这些方法被扩展用于描述两种疾病的共同聚集性,即先证者中一种疾病的存在增加了亲属中另一种疾病的风险。文中给出了一个涉及饮食失调和抑郁症的实例。

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