Predictors of remission during acute treatment of first-episode schizophrenia patients involuntarily hospitalized and treated with algorithm-based pharmacotherapy: Secondary analysis of an observational study

Aim: Early clinical response predicts symptomatic remission and recovery in the maintenance treatment phase of first-episode schizophrenia (FES). However, little is known about predictors of symptomatic remission during acute treatment of severely ill patients with FES. Here, we conducted a secondary analysis of our retrospective observational study, which examined response, remission and treatment-resistance rates in seriously ill patients with FES spectrum disorders involuntarily hospitalized and treated with algorithm-based pharmacotherapy. Methods: We performed a retrospective chart review of 131 involuntarily admitted patients with schizophrenia or schizoaffective disorder. Our algorithm aimed to delay olanzapine treatment, standardize medications and suggest initiation of clozapine after failure of third-line antipsychotic treatment. The duration of each adequate antipsychotic treatment at an optimal dosage was 4 weeks or more. Remission was defined using the symptom-severity component of consensus remission criteria. A logistic regression model was applied to identify significant predictors of remission at discharge. Results: Overall, 74 patients (56%) were in remission at discharge. Non-remitters were hampered from becoming remitters mainly by the presence of negative symptoms. There were no differences in first-line antipsychotics, dosage of antipsychotics at time of response and adherence rates to algorithm-based pharmacotherapy between remitters and non-remitters. Shorter duration of untreated psychosis, favourable early response and less negative symptoms at baseline were identified as independent predictors of remission at discharge. Conclusions: The importance of early intervention and specific and adequate treatments of negative symptoms is highlighted.