一种慢性病患病率与发病率的新关系

Ralph Brinks;Sandra Landwehr
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引用次数: 44

摘要

1991年,Keiding发表了慢性病的年龄特异性发病率和发病率之间的关系(《年龄特异性患病率和患病率:统计视角》,J.Roy.Stat.Soc.a,154371–412)。对于特殊情况,Brinks等人(2013年,用常微分方程从患病率推导年龄特异性发病率。Statist.Med.,32070–2078)和Brinks&Landwehr(2014,德国非传染性疾病患病率的年龄和时间依赖性模型及其在痴呆症中的应用,Theor.Popul.Biol.,92,62–68)。从这些工作中,我们概括了公式,并讨论了新方法的优点。因此,我们从患病率数据中获得了一种估计慢性病发病率的新方法。这使我们能够在需要昂贵和漫长的后续研究的情况下采用横断面研究。本文在德国痴呆症的模拟研究中说明并验证了这种新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A new relation between prevalence and incidence of a chronic disease

A new relation between prevalence and incidence of a chronic disease

A new relation between prevalence and incidence of a chronic disease
In 1991 Keiding published a relation between the age-specific prevalence and incidence of a chronic disease (in Age-specific incidence and prevalence: a statistical perspective. J. Roy. Stat. Soc. A, 154, 371–412). For special cases alternative formulations by differential equations were given recently in Brinks et al. (2013, Deriving age-specific incidence from prevalence with an ordinary differential equation. Statist. Med., 32, 2070–2078) and in Brinks & Landwehr (2014, Age- and time-dependent model of the prevalence of non-communicable diseases and application to dementia in Germany, Theor. Popul. Biol., 92, 62–68). From these works, we generalize formulations and discuss the advantages of the novel approach. As an implication, we obtain a new way of estimating the incidence rate of a chronic disease from prevalence data. This enables us to employ cross-sectional studies where otherwise expensive and lengthy follow-up studies are needed. This article illustrates and validates the novel method in a simulation study about dementia in Germany.
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