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

Author

Listed:
  • Carole Siani

    (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD - Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale - IRD - Institut de Recherche pour le Développement - AMU - Aix Marseille Université - INSERM - Institut National de la Santé et de la Recherche Médicale)

  • Christian de Peretti

    (ECL - École Centrale de Lyon - Université de Lyon, LSAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)

  • Aurélie Millier

    (Creativ-Ceutical)

  • Laurent Boyer

    (Toxines bactériennes dans la relation hôtes-pathogènes - UNS - Université Nice Sophia Antipolis (1965 - 2019) - IFR50 - INSERM - Institut National de la Santé et de la Recherche Médicale - UniCA - Université Côte d'Azur, C3M - Centre méditerranéen de médecine moléculaire - UNS - Université Nice Sophia Antipolis (1965 - 2019) - INSERM - Institut National de la Santé et de la Recherche Médicale - UniCA - Université Côte d'Azur, UNS - Université Nice Sophia Antipolis (1965 - 2019))

  • Mondher Toumi

    (Laboratoire de Santé Publique - Université de la Méditerranée - Aix-Marseille 2)

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.

Suggested Citation

  • Carole Siani & Christian de Peretti & Aurélie Millier & Laurent Boyer & Mondher Toumi, 2015. "Predictive models to estimate utility from clinical questionnaires in schizophrenia: findings from EuroSC," Post-Print hal-04875595, HAL.
  • Handle: RePEc:hal:journl:hal-04875595
    DOI: 10.1007/s11136-015-1120-6
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