Screening and predicting progression from high-risk mild cognitive impairment to Alzheimer’s disease

Abstract Individuals with mild cognitive impairment (MCI) are clinically heterogeneous, with different risks of progression to Alzheimer’s disease. Regular follow-up and examination may be time-consuming and costly, especially for MRI and PET. Therefore, it is necessary to identify a more precise MR...

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Autores principales:	Xiao-Yan Ge, Kai Cui, Long Liu, Yao Qin, Jing Cui, Hong-Juan Han, Yan-Hong Luo, Hong-Mei Yu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6058335ef7e5431b8d3c9d951ad243de
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spelling	oai:doaj.org-article:6058335ef7e5431b8d3c9d951ad243de2021-12-02T15:25:34ZScreening and predicting progression from high-risk mild cognitive impairment to Alzheimer’s disease10.1038/s41598-021-96914-32045-2322https://doaj.org/article/6058335ef7e5431b8d3c9d951ad243de2021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-96914-3https://doaj.org/toc/2045-2322Abstract Individuals with mild cognitive impairment (MCI) are clinically heterogeneous, with different risks of progression to Alzheimer’s disease. Regular follow-up and examination may be time-consuming and costly, especially for MRI and PET. Therefore, it is necessary to identify a more precise MRI population. In this study, a two-stage screening frame was proposed for evaluating the predictive utility of additional MRI measurements among high-risk MCI subjects. In the first stage, the K-means cluster was performed for trajectory-template based on two clinical assessments. In the second stage, high-risk individuals were filtered out and imputed into prognosis models with varying strategies. As a result, the ADAS-13 was more sensitive for filtering out high-risk individuals among patients with MCI. The optimal model included a change rate of clinical assessments and three neuroimaging measurements and was significantly associated with a net reclassification improvement (NRI) of 0.246 (95% CI 0.021, 0.848) and integrated discrimination improvement (IDI) of 0.090 (95% CI − 0.062, 0.170). The ADAS-13 longitudinal models had the best discrimination performance (Optimism-corrected concordance index = 0.830), as validated by the bootstrap method. Considering the limited medical and financial resources, our findings recommend follow-up MRI examination 1 year after identification for high-risk individuals, while regular clinical assessments for low-risk individuals.Xiao-Yan GeKai CuiLong LiuYao QinJing CuiHong-Juan HanYan-Hong LuoHong-Mei YuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiao-Yan Ge Kai Cui Long Liu Yao Qin Jing Cui Hong-Juan Han Yan-Hong Luo Hong-Mei Yu Screening and predicting progression from high-risk mild cognitive impairment to Alzheimer’s disease
description	Abstract Individuals with mild cognitive impairment (MCI) are clinically heterogeneous, with different risks of progression to Alzheimer’s disease. Regular follow-up and examination may be time-consuming and costly, especially for MRI and PET. Therefore, it is necessary to identify a more precise MRI population. In this study, a two-stage screening frame was proposed for evaluating the predictive utility of additional MRI measurements among high-risk MCI subjects. In the first stage, the K-means cluster was performed for trajectory-template based on two clinical assessments. In the second stage, high-risk individuals were filtered out and imputed into prognosis models with varying strategies. As a result, the ADAS-13 was more sensitive for filtering out high-risk individuals among patients with MCI. The optimal model included a change rate of clinical assessments and three neuroimaging measurements and was significantly associated with a net reclassification improvement (NRI) of 0.246 (95% CI 0.021, 0.848) and integrated discrimination improvement (IDI) of 0.090 (95% CI − 0.062, 0.170). The ADAS-13 longitudinal models had the best discrimination performance (Optimism-corrected concordance index = 0.830), as validated by the bootstrap method. Considering the limited medical and financial resources, our findings recommend follow-up MRI examination 1 year after identification for high-risk individuals, while regular clinical assessments for low-risk individuals.
format	article
author	Xiao-Yan Ge Kai Cui Long Liu Yao Qin Jing Cui Hong-Juan Han Yan-Hong Luo Hong-Mei Yu
author_facet	Xiao-Yan Ge Kai Cui Long Liu Yao Qin Jing Cui Hong-Juan Han Yan-Hong Luo Hong-Mei Yu
author_sort	Xiao-Yan Ge
title	Screening and predicting progression from high-risk mild cognitive impairment to Alzheimer’s disease
title_short	Screening and predicting progression from high-risk mild cognitive impairment to Alzheimer’s disease
title_full	Screening and predicting progression from high-risk mild cognitive impairment to Alzheimer’s disease
title_fullStr	Screening and predicting progression from high-risk mild cognitive impairment to Alzheimer’s disease
title_full_unstemmed	Screening and predicting progression from high-risk mild cognitive impairment to Alzheimer’s disease
title_sort	screening and predicting progression from high-risk mild cognitive impairment to alzheimer’s disease
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/6058335ef7e5431b8d3c9d951ad243de
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Screening and predicting progression from high-risk mild cognitive impairment to Alzheimer’s disease

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