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基于 ADNI 数据库中连续有界数据的功能评估问卷(FAQ)建模。

Modeling of Functional Assessment Questionnaire (FAQ) as continuous bounded data from the ADNI database.

机构信息

Pfizer Inc, Primary Care Business Unit, 445 Eastern Point Road, Groton, CT 06340, USA.

出版信息

J Pharmacokinet Pharmacodyn. 2012 Dec;39(6):601-18. doi: 10.1007/s10928-012-9271-3. Epub 2012 Sep 19.

Abstract

An assessment of abilities to function independently in daily life is an important clinical endpoint for all Alzheimer's disease (AD) patients and caregivers. A mathematical model was developed to describe the natural history of change of the Functional Assessment Questionnaire (FAQ) from data obtained in normal elderly, mild cognitive impairment, and mild AD in the AD neuroimaging initiative (ADNI) study. FAQ is a bounded outcome (ranging from 0 to 30), with 0 scored as "no impairment" and 30 as "severely impaired". Since many normal elderly patients had 0 scores and some AD patients had scores of 30 in the ADNI database, a censored approach for handling the boundary data was compared with a standard approach, which ignores the bounded nature of the data. Baseline severity, ApoE4 genotype, age, sex, and imaging biomarkers were tested as covariates. The censored approach greatly improved the predictability of the disease progression in FAQ scores. The basic method for handling boundary data used in this analysis is also applicable to handle boundary observations for numerous other endpoints.

摘要

日常生活中独立功能的评估是所有阿尔茨海默病(AD)患者及其照料者的一个重要临床终点。本研究构建了一个数学模型,以描述 AD 神经影像学倡议(ADNI)研究中正常老年人、轻度认知障碍和轻度 AD 患者的功能评估问卷(FAQ)变化的自然史。FAQ 是一个有界的结局(范围为 0 到 30),0 分为“无损伤”,30 分为“严重损伤”。由于 ADNI 数据库中有许多正常老年人的得分是 0,一些 AD 患者的得分是 30,因此,本研究比较了处理边界数据的删失方法与标准方法(忽略数据的有界性)。基线严重程度、ApoE4 基因型、年龄、性别和影像学生物标志物被作为协变量进行检验。删失方法极大地提高了 FAQ 评分中疾病进展的可预测性。该分析中使用的边界数据基本处理方法也适用于处理其他众多边界观测值的结局。

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