Latent class analysis in schizophrenia: a validation with peripheral biomarkers

• Grant number: 16/22614-9
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: April 03, 2017
• End date: October 02, 2017
• Field of knowledge: Health Sciences - Medicine - Psychiatry
• Principal Investigator: Ary Gadelha de Alencar Araripe Neto
• Grantee: Cinthia Hiroko Higuchi
• Supervisor: Bethany Cara Bray
• Host Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil
• Institution abroad: Pennsylvania State University, United States
• Associated to the scholarship: 15/04377-7 - Latent class analysis in schizophrenia: a validity study with biomarkers, BP.DR

Abstract

Schizophrenia is marked by extensive clinical heterogeneity that causes several challenges for stablishing accurate diagnosis. The Positive and Negative Syndrome Scale (PANSS) is widely used as an instrument to assess dimensional symptomatology. The PANSS is frequently represented by a five factor model. However, there is no dimensional model with good fit. A categorical approach by latent class analysis could be an alternative. OBJECTIVE: To find and validate a categorical model of PANSS by performing a latent class analysis (LCA) and LCA with auxiliary variables. METHODS: The sample was collected in four different centers. First we will perform a LCA analysis with maximum likelihood estimator. The number of classes will be defined: a) Comparison of the values of AIC, BIC and Log likelihood: lower values indicate better fit; b) Analysis of entropy measures (values close to 1 indicate good fit); c) Theoretical framework: how much the model is useful and representative to in practice. The final model will be validated by LCA with auxiliary variables (Sociodemographic and clinical data and peripheral biomarkers). EXPECTED RESULTS: The categorical model will be a good alternative to dimensional models of PANSS. The groups generated by LCA may be useful to reduce the heterogeneity of symptoms by identifying different profiles of patient by PANSS. POTENTIALS CONTRIBUTIONS OF THE INTERNSHIP: It will allow the student to learn the newest approaches in the LCA field. This knowledge would be useful to the development of new lines of research and methodological improvement on the existing ones. Besides, it could start a contribution between our group and The Methodology Center. (AU)