Predictive models to estimate utility from clinical questionnaires in schizophrenia: findings from EuroSC

Abstract

Objective: The clinical symptoms of schizophrenia are associated with serious social, quality of life and functioning alterations. Typically, data on health utilities are not available in clinical studies in schizophrenia. This makes the economic evaluation of schizophrenia treatments challenging. The purpose of this article was to provide a mapping function to predict unobserved utility values in patients with schizophrenia from the available clinical and socio-demographic information. Methods: The analysis was performed using data from EuroSC, a 2-year, multi-centre, cohort study conducted in France (N = 288), Germany (N = 618), and the UK (N = 302), totalling 1208 patients. Utility was calculated based on the EQ-5D questionnaire. The relationships between the utility values and the patients’ socio-demographic and clinical characteristics (Positive and Negative Syndrome Scale—PANSS, Calgary Depression Scale for Schizophrenia—CDSS, Global Assessment of Functioning—GAF, extra-pyramidal symptoms measured by Barnes Akathisia Scale—BAS, age, sex, country, antipsychotic type) were modelled using a random and a fixed individual effects panel linear model. Results: The analysis demonstrated the prediction ability of the used parameters for estimating utility measures in patients with schizophrenia. Although there are small variations between countries, the same variables appear to be the key predictors. From a clinical perspective, age, gender, psychopathology, and depression were the most important predictors associated with the EQ-5D. Conclusion: This paper proposed a reliable, robust and easy-to-apply mapping method to estimate EQ-5D utilities based on demographic and clinical measures in schizophrenia.