Validation of a Multivariate Prediction Model of the Clinical Progression of Alzheimer's Disease in a Community-Dwelling Multiethnic Cohort

E. Stallard, A. Kociolek, Zhezhen Jin, Hyunnam Ryu, Seonjoo Lee, Stephanie Cosentino, C. Zhu, Yian Gu, K. Fernández, Michelle Hernandez, B. Kinosian, Y. Stern
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引用次数: 1

Abstract

BackgroundThe major aims of the three Predictors Studies have been to further our understanding of Alzheimers disease (AD) progression sufficient to predict the length of time from disease onset to major disease outcomes in individual patients with AD. ObjectivesTo validate a longitudinal Grade of Membership (L-GoM) prediction algorithm developed using clinic-based, mainly white patients from the Predictors 2 Study in a statistically representative community-based sample of Hispanic (N=211) and non-Hispanic (N=62) older adults (with 60 males and 213 females) from the Predictors 3 Study and extend the algorithm to mild cognitive impairment (MCI). MethodsThe L-GoM model was applied to data collected at the initial Predictors 3 visit for 150 subjects with AD and 123 with MCI. Participants were followed annually for up to seven years. Observed rates of survival and need for full-time care (FTC) were compared to those predicted by the algorithm. ResultsInitial MCI/AD severity in Predictors 3 was substantially higher than among clinic-based AD patients enrolled at the specialized Alzheimers centers in Predictors 2. The observed survival and need for FTC followed the L-GoM model trajectories in individuals with MCI or AD, except for N=32 subjects who were initially diagnosed with AD but reverted to a non-AD diagnosis on follow-up. ConclusionsThese findings indicate that the L-GoM model is applicable to community-dwelling, multiethnic older adults with AD. They extend the use of the model to the prediction of outcomes for MCI. They also justify release of our L-GoM calculator at this time.
在社区居住的多民族队列中,阿尔茨海默病临床进展的多变量预测模型的验证
背景:这三项预测因子研究的主要目的是进一步加深我们对阿尔茨海默病(AD)进展的理解,足以预测AD患者从发病到主要疾病结局的时间长度。目的验证基于临床的纵向成员等级(L-GoM)预测算法,主要是来自Predictors 2研究的白人患者,在具有统计学代表性的社区样本中,来自Predictors 3研究的西班牙裔(N=211)和非西班牙裔(N=62)老年人(60名男性和213名女性),并将该算法扩展到轻度认知障碍(MCI)。方法采用L-GoM模型对150例AD患者和123例MCI患者在Predictors 3初访时收集的数据进行分析。研究人员每年对参与者进行为期7年的随访。观察到的生存率和需要全职护理(FTC)与算法预测的结果进行比较。结果预测因子3中初始MCI/AD严重程度显著高于预测因子2中专门阿尔茨海默病中心登记的临床AD患者。在MCI或AD患者中,观察到的生存和FTC需求遵循L-GoM模型轨迹,除了N=32名最初被诊断为AD但在随访中恢复为非AD诊断的受试者。结论L-GoM模型适用于社区居住的多民族老年AD患者。他们将该模型的应用扩展到MCI的预后预测。他们也证明了在这个时候发布我们的L-GoM计算器是合理的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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