Latent class analysis in schizophrenia: a validity study with biomarkers

• Grant number: 15/04377-7
• Support type: Scholarships in Brazil - Doctorate
• Effective date (Start): August 01, 2015
• Effective date (End): March 02, 2019
• Field of knowledge: Health Sciences - Medicine - Psychiatry
• Cooperation agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
• Principal researcher: ARY GADELHA DE ALENCAR ARARIPE NETO
• Grantee: Cinthia Hiroko Higuchi
• Home Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil
• Associated scholarship(s): 16/22614-9 - LATENT CLASS ANALYSIS IN SCHIZOPHRENIA: A VALIDATION WITH PERIPHERAL BIOMARKERS, BE.EP.DR

Abstract

INTRODUCTION: The identification of statistical models to characterize the clinical heterogeneity observed in schizophrenia has been a great challenge. The most common factor model is represented by five factors and generated by the Positive and Negative Syndromes Scale (PANSS). However, this model is not confirmed by confirmatory factor analysis. No study has made a comparison of different methodologies to establish the model which best represents the nature of the data. Other limitation is the lack of external validity of the previous models. OBJECTIVE: To compare different statistical models to identify which best fits the data of PANSS. Validate the model generated by the analysis of latent classes with external variables (peripheral biomarkers). METHODS: We will analyze previously collected data from three different centers. The models will be generated by exploratory factor analysis and tested by confirmatory factor analysis. Alternative approaches will be applied: Bayesian confirmatory factor analysis and latent class analysis (LCA). The groups generated by LCA will be validated by peripheral biomarkers and other clinical and sociodemographic measures. All analysis will be performed in Mplus software - version 7. (AU)