肺功能数据分析中的方法学问题

William M. Vollmer , Larry R. Johnson , Lynn E. McCamant , A.Sonia Buist
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引用次数: 41

摘要

一秒钟用力呼气量(FEV1)通常用于肺功能流行病学研究,以评估阻塞性气道疾病的存在和严重程度。使用健康、无症状个体的数据开发的规范性预测方程可用于临床环境,并根据已知的人口统计学差异调整风险亚组之间的比较。不幸的是,关于如何最好地模拟肺功能数据,尚未达成共识。本文以系统的方式解决了这一问题,使用了来自两个队列的数据,随访时间为9-11年。我们比较了FEV1的各种横截面和纵向模型,展示了它们如何被表示为一类更大的一般线性模型的成员,并讨论了比较它们的拟合优度程序。我们发现很少有客观证据来区分这些模型;只有那些适合FEV1/ht3的表现不佳。我们在使用基于FEV1的模型的主观理由上进行了争论,FEV1是年龄、身高及其相互作用的函数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methodologic issues in the analysis of lung function data

The forced expiratory volume in one second (FEV1) is routinely used in epidemiologic studies of lung function to assess the presence and severity of obstructive airways disease. Normative prediction equations developed using data from healthy, asymptomatic individuals may then be used both in a clinical setting and to adjust comparisons among risk subgroups for known demographic differences. Unfortunately no concensus has yet developed as to how best to model lung function data. This paper addresses this issue in a systematic manner using data derived from two cohorts followed over a period of 9–11 years. We compare a variety of cross-sectional and longitudinal models for FEV1, show how they may be expressed as members of a larger class of general linear models, and discuss goodness-of-fit procedures for comparing them. We found little objective evidence for discriminating among these models; only those fit to FEV1/ht3 performed poorly. We argue on subjective grounds for the use of models based on FEV1, as a function of age, height and their interactions.

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