Identifying and characterizing treatment-resistant schizophrenia in observational database studies.

Objectives: Treatment-resistant schizophrenia (TRS) is clinically defined as failure to respond to two antipsychotics of adequate dose and duration. An algorithm (registry TRS) was developed, for identifying patients with TRS in claim datasets from Sweden and the United States.

Methods: Schizophrenia (SZ) patients aged ≥13 years were identified in both datasets and matched to controls. Patients were identified as having TRS by use of the registry TRS or ≥1 prescription for clozapine or use of other published criteria. The algorithm was compared for sensitivity, and patients with and without TRS were compared for psychiatric and hospital burden and Global Assessment of Functioning (GAF) scores. TRS prevalence was not assessed due to lack of clinically validated data to test the specificity of the algorithm.

Results: Swedish registry TRS patients ≤45 years at first SZ diagnosis had significantly lower GAF scores and earlier disease onset than non-TRS patients. SZ patients with higher psychiatric comorbidity and hospital burden were more likely identified as TRS by all algorithms. The registry algorithm was significantly more sensitive to multiple inpatient stays and all psychiatric comorbidities at identifying TRS.

Conclusion: The registry algorithm appeared more sensitive at identifying patients with TRS, who had greater psychiatric and hospital burden.