Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study.
Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study.
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DOI：
10.1186/s12911-021-01590-y
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发表时间：
2021-08-11
影响因子：
3.5
通讯作者：
GBD 2019 Dementia Collaborators
中科院分区：
文献类型：
--
作者：
GBD 2019 Dementia Collaborators
数据稀疏性是估计国家和全球痴呆症负担的主要限制。在许多情况下，对痴呆症患病率进行全面诊断评估的调查资源密集得令人望而却步。然而，来自全国代表性调查的验证样本允许开发用于预测全国痴呆症患病率的算法。使用亚当斯研究的A波(2001年至2003年)和2000年的 = 研究的A波(n = 744)的认知测试数据和关于功能限制的数据，我们估计了一个二维项目反应理论模型来计算所有70岁以上个体的认知和功能分数。基于ADAMS正式临床裁决的诊断信息，我们用认知和功能评分建立了痴呆状态分类的Logistic回归模型，并将该算法应用于全部HRS样本，计算按年龄和性别划分的痴呆症患病率。我们的算法在ADAMS中的交叉验证预测准确率为88%(86-90)，曲线下面积为0.97(0.97-0.98)。女性的患病率高于男性，并随着年龄的增长而增加，70-79岁的人患病率为4%(3-4)，80-89岁的人为11%(9-12)，90岁及以上的人为28%(22-35)。我们的模型与之前回顾的预测HRS痴呆症患病率的算法相比，具有类似或更好的准确性，同时使用了更灵活的方法。这些方法可以更容易地推广，并在其他国家调查中用于估计痴呆症患病率。网上版载有补充材料，可在10.1186/s12911-021-01590-y查阅。
Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Using cognitive testing data and data on functional limitations from Wave A (2001–2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Our algorithm had a cross-validated predictive accuracy of 88% (86–90), and an area under the curve of 0.97 (0.97–0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3–4) in individuals 70–79, 11% (9–12) in individuals 80–89 years old, and 28% (22–35) in those 90 and older. Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys. The online version contains supplementary material available at 10.1186/s12911-021-01590-y.
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影响因子：
5.7
作者：
Langa, KM;Plassman, BL;Willis, RJ
通讯作者：
Willis, RJ
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Gianattasio, Kan Z.;Wu, Qiong;Power, Melinda C.
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Power, Melinda C.
影响因子：
5.7
作者：
Lopez, Oscar L;Kuller, Lewis H
通讯作者：
Kuller, Lewis H
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影响因子：
6.9
作者：
JORM, AF
通讯作者：
JORM, AF