Application of the Joint Latent Class Model in the Reversion of Mild Cognitive Impairment to Normal Cognition
10.11783/j.issn.1002-3674.2023.06.008
- VernacularTitle:联合潜在类别模型在轻度认知障碍向认知正常逆转研究中的应用
- Author:
Yao QIN
1
;
Hongjuan HAN
;
Long LIU
Author Information
1. 山西医科大学公共卫生学院卫生统计学教研室(030001)
- Keywords:
Joint latent class model;
Longitudinal data;
Survival data;
Mild cognitive impairment;
Reversion
- From:
Chinese Journal of Health Statistics
2023;40(6):836-840
- CountryChina
- Language:Chinese
-
Abstract:
Objective The joint latent class model(JLCM)was applied to study the reversion of mild cognitive impairment(MCI)to normal cognition(NC),providing a methodology reference for the longitudinal study of chronic diseases.Methods The JLCM model consisted of three sub-models:the latent class sub-model adopted multi-class logistic regression to estimate the latent classes;the longitudinal process sub-model adopted linear mixed model to describe the longitudinal cognitive measurement;and the survival process sub-model adopted proportional risk model to fit the cognitive process.Goodness of fit was based on information criterion,posterior classification,comparison between predicted value and observed value and conditional independence assumption.Results The MCI population was divided into two latent classes based on the JLCM model,including 783(92.88%)and 60(7.12%),respectively.The latent class sub-model showed that gender,marital status,APOE4 and FAQ had statistical significance for the determination of latent classes.The longitudinal process sub-model showed male(β=-0.685,95%CI:-1.144,-0.226),being single(β=0.743,95%CI:0.200,1.286),not carrying APOE4(β=-1.201,95%CI:-1.636,-0.766)and without functional impairment(β=-1.868,95%CI:-2.095,-1.641)had higher MMSE scores.The survival process sub-model showed that high education level(HR=1.264,95%CI:1.134,1.395),being single(HR=1.593,95%CI:1.286,1.899)and not carrying APOE4(HR=0.453,95%CI:0.043,0.862)were protective factors for reversion to NC in MCI patients.Conclusion JLCM model has good application value in the study of chronic diseases such as cognitive impairment.
