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根据监测数据估算发病的年龄条件概率。

Estimating age conditional probability of developing disease from surveillance data.

作者信息

Fay Michael P

机构信息

National Cancer Institute 6116 Executive Blvd, Suite 504 Bethesda, MD 20892-8317, USA.

出版信息

Popul Health Metr. 2004 Jul 27;2(1):6. doi: 10.1186/1478-7954-2-6.

Abstract

Fay, Pfeiffer, Cronin, Le, and Feuer (Statistics in Medicine 2003; 22; 1837-1848) developed a formula to calculate the age-conditional probability of developing a disease for the first time (ACPDvD) for a hypothetical cohort. The novelty of the formula of Fay et al (2003) is that one need not know the rates of first incidence of disease per person-years alive and disease-free, but may input the rates of first incidence per person-years alive only. Similarly the formula uses rates of death from disease and death from other causes per person-years alive. The rates per person-years alive are much easier to estimate than per person-years alive and disease-free. Fay et al (2003) used simple piecewise constant models for all three rate functions which have constant rates within each age group. In this paper, we detail a method for estimating rate functions which does not have jumps at the beginning of age groupings, and need not be constant within age groupings. We call this method the mid-age group joinpoint (MAJ) model for the rates. The drawback of the MAJ model is that numerical integration must be used to estimate the resulting ACPDvD. To increase computational speed, we offer a piecewise approximation to the MAJ model, which we call the piecewise mid-age group joinpoint (PMAJ) model. The PMAJ model for the rates input into the formula for ACPDvD described in Fay et al (2003) is the current method used in the freely available DevCan software made available by the National Cancer Institute.

摘要

费伊、 Pfeiffer、克罗宁、勒和费尔(《医学统计学》,2003年;22卷;1837 - 1848页)为一个假设队列开发了一个公式,用于计算首次患某种疾病的年龄条件概率(ACPDvD)。费伊等人(2003年)公式的新颖之处在于,不必知道每人年存活且无病时的疾病首次发病率,而只需输入每人年存活时的首次发病率。同样,该公式使用每人年存活时的疾病死亡率和其他原因死亡率。每人年存活时的发病率比每人年存活且无病时的发病率更容易估计。费伊等人(2003年)对所有三个发病率函数都使用了简单的分段常数模型,这些模型在每个年龄组内具有恒定的发病率。在本文中,我们详细介绍了一种估计发病率函数的方法,该方法在年龄分组开始时没有跳跃,并且在年龄分组内不必是恒定的。我们将这种方法称为发病率的中年组连接点(MAJ)模型。MAJ模型的缺点是必须使用数值积分来估计由此产生的ACPDvD。为了提高计算速度,我们提供了MAJ模型的分段近似,我们称之为分段中年组连接点(PMAJ)模型。输入到费伊等人(2003年)描述的ACPDvD公式中的发病率的PMAJ模型是美国国家癌症研究所免费提供的DevCan软件中使用的当前方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e21/517510/e6f28731a05b/1478-7954-2-6-1.jpg

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