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利用动态微观模拟技术预测老年人群的认知功能。

Using dynamic microsimulation to project cognitive function in the elderly population.

机构信息

Leonard D. Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, California, United States of America.

出版信息

PLoS One. 2022 Sep 15;17(9):e0274417. doi: 10.1371/journal.pone.0274417. eCollection 2022.

Abstract

BACKGROUND

A long-term projection model based on nationally representative data and tracking disease progression across Alzheimer's disease continuum is important for economics evaluation of Alzheimer's disease and other dementias (ADOD) therapy.

METHODS

The Health and Retirement Study (HRS) includes an adapted version of the Telephone Interview for Cognitive Status (TICS27) to evaluate respondents' cognitive function. We developed an ordered probit transition model to predict future TICS27 score. This transition model is utilized in the Future Elderly Model (FEM), a dynamic microsimulation model of health and health-related economic outcomes for the US population. We validated the FEM TICS27 model using a five-fold cross validation approach, by comparing 10-year (2006-2016) simulated outcomes against observed HRS data.

RESULTS

In aggregate, the distribution of TICS27 scores after ten years of FEM simulation matches the HRS. FEM's assignment of cognitive/mortality status also matches those observed in HRS on the population level. At the individual level, the area under the receiver operating characteristic (AUROC) curve is 0.904 for prediction of dementia or dead with dementia in 10 years, the AUROC for predicting significant cognitive decline in two years for mild cognitive impairment patients is 0.722.

CONCLUSIONS

The FEM TICS27 model demonstrates its predictive accuracy for both two- and ten-year cognitive outcomes. Our cognition projection model is unique in its validation with an unbiased approach, resulting in a high-quality platform for assessing the burden of cognitive decline and translating the benefit of innovative therapies into long-term value to society.

摘要

背景

基于具有全国代表性的数据并跟踪阿尔茨海默病连续体中的疾病进展,建立长期预测模型对于评估阿尔茨海默病和其他痴呆症(ADOD)治疗的经济学意义非常重要。

方法

健康与退休研究(HRS)包括电话认知状态测试(TICS27)的改编版本,用于评估受访者的认知功能。我们开发了一个有序概率转移模型来预测未来的 TICS27 分数。该转移模型用于未来老年人模型(FEM),这是一种针对美国人口的健康和与健康相关的经济结果的动态微观模拟模型。我们通过使用五折交叉验证方法来验证 FEM 的 TICS27 模型,即将 10 年(2006-2016 年)的模拟结果与 HRS 观察数据进行比较。

结果

总体而言,FEM 模拟十年后的 TICS27 分数分布与 HRS 匹配。FEM 的认知/死亡率状态分配也与 HRS 中观察到的人口水平相匹配。在个体水平上,预测 10 年内痴呆或死于痴呆的接收器工作特征(AUROC)曲线下面积为 0.904,预测轻度认知障碍患者两年内显著认知下降的 AUROC 为 0.722。

结论

FEM TICS27 模型在两年和十年的认知结果方面都表现出其预测准确性。我们的认知预测模型具有独特的优势,其验证方法是无偏的,因此为评估认知能力下降的负担以及将创新疗法的收益转化为对社会的长期价值提供了一个高质量的平台。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/45f9/9477290/70d64017a657/pone.0274417.g001.jpg

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