Abstract
BACKGROUND: To fully assess the various dimensions affected by schizophrenia, clinical trials often include multiple scales measuring various symptom profiles, cognition, quality of life, subjective well-being, and functional impairment. In this exploratory study, we characterized the relationships among six clinical, functional, cognitive, and quality-of-life measures, identifying a parsimonious set of measurements. METHODS: We used baseline data from a randomized, multicenter study of patients diagnosed with schizophrenia, schizoaffective disorder, or schizophreniform disorder who were experiencing an acute symptom exacerbation (n = 628) to examine the relationship among several outcome measures. These measures included the Positive and Negative Syndrome Scale (PANSS), Montgomery-Asberg Depression Rating Scale (MADRS), Brief Assessment of Cognition in Schizophrenia Symbol Coding Test, Subjective Well-being Under Neuroleptics Scale Short Form (SWN-K), Schizophrenia Objective Functioning Instrument (SOFI), and Quality of Life Scale (QLS). Three analytic approaches were used: 1) path analysis; 2) factor analysis; and 3) categorical latent variable analysis. In the optimal path model, the SWN-K was selected as the final outcome, while the SOFI mediated the effect of the exogenous variables (PANSS, MADRS) on the QLS. RESULTS: The overall model explained 47% of variance in QLS and 17% of the variance in SOFI, but only 15% in SWN-K. Factor analysis suggested four factors: "Functioning," "Daily Living," "Depression," and "Psychopathology." A strong positive correlation was observed between the SOFI and QLS (r = 0.669), and both the QLS and SOFI loaded on the "Functioning" factor, suggesting redundancy between these scales. The measurement profiles from the categorical latent variable analysis showed significant variation in functioning and quality of life despite similar levels of psychopathology. CONCLUSIONS: Researchers should consider collecting PANSS, SOFI, and SWN-K in their trials. This would allow a broad spectrum of assessments that would have the ability to capture a wide range of treatment outcomes and allow for a rich characterization of the subgroups involved. Additional research is needed to identify the critical cognitive measures. CLINICAL TRIALS REGISTRATION: Predicting Response to Risperidone Treatment Through Identification of Early-onset of Antipsychotic Drug Action in SchizophreniaClinicalTrials.gov identifier: NCT00337662; http://www.clinicaltrials.gov/