Use of two-segmented logistic regression to estimate change-points in epidemiologic studies
Use of two-segmented logistic regression to estimate change-points in epidemiologic studies
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DOI：
10.1093/aje/148.7.631
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发表时间：
1998-10-01
影响因子：
5
通讯作者：
Guallar, E
中科院分区：
文献类型：
--
作者：
Pastor, R;Guallar, E
在许多流行病学数据中，当暴露变量达到一个未知的阈值水平（所谓的变点）时，连续暴露与疾病风险之间的剂量-反应关系会突然发生变化。虽然有几种方法可用于剂量反应评估与二分的结果，他们都没有提供推理程序来估计变点。本文描述了一个两段Logistic回归模型，其中标准Logistic回归中与连续暴露相关的线性项被替换为一个具有未知变点的两段多项式函数，并对变点进行了估计。提出了一种改进的迭代加权最小二乘算法来获得参数估计和置信区间，并通过仿真研究了该模型的性能。最后，一个两段逻辑回归模型应用于病例对照研究的酒精摄入量与心肌梗死的风险，并与其他分析比较。两段逻辑回归的能力，估计和提供推论的变化点的位置和其他参数的影响的大小将使该模型的流行病学研究中的剂量反应分析的其他方法的一个有用的补充。
In many epidemiologic data, the dose-response relation between a continuous exposure and the risk of disease abruptly changes when the exposure variable reaches an unknown threshold level, the so-called change-point. Although several methods are available for dose-response assessment with dichotomous outcomes, none of them provide inferential procedures to estimate change-points. In this paper, we describe a two-segmented logistic regression model, in which the linear term associated with a continuous exposure in standard logistic regression is replaced by a two-segmented polynomial function with unknown change-point, which is also estimated. A modified, iteratively reweighted least squares algorithm is presented to obtain parameter estimates and confidence intervals, and the performance of this model is explored through simulation. Finally, a two-segmented logistic regression model is applied to a case-control study of the association of alcohol intake with the risk of myocardial infarction and compared with alternative analyses. The ability of two-segmented logistic regression to estimate and provide inferences for the location of change-points and for the magnitude of other parameters of effect will make this model a useful complement to other methods of dose-response analysis in epidemiologic studies.