Identification of psychopathological course trajectories in schizophrenia

Abstract

Course trajectory analyses have been performed primarily for treatment response in acute episodes of schizophrenic disorders. As yet, corresponding data for the long-term course are lacking. Within a multicenter prospective observational study, 268 patients with schizophrenia were assessed at discharge from hospital and followed up after 6, 12, 18, and 24 months. A latent class growth analysis was performed on the scores from the Positive and Negative Syndrome Scale (PANSS). A two-class conditional latent class model showed the best data fit (Entropy: 0.924). The model divided the sample into a group with amelioration in all PANSS subscales (60%) and a group with stable positive/negative and deteriorating general psychopathology symptoms (40%). Global functioning (GAF score), gender, age, living situation and involuntary admission predicted course trajectory class membership. The model was predictive of significant differences between the two groups in health care service costs and quality of life. The results underline the heterogeneous course of the illness, which ranged from amelioration to deterioration over a 2-year period. Statistical models such as trajectory analysis could help to identify more homogenous subtypes in schizophrenia.