Schizophrenia | Treatment Algorithms | Claims Data Analysis | US | 2015

Schizophrenia is a chronic, severe mental illness characterized by a range of symptoms that include positive symptoms (e.g., delusions, hallucinations), negative symptoms (e.g., affective flattening, avolition), and cognitive deficits. The primary goals of medical treatment for schizophrenia are to reduce positive and negative symptoms, maintain the reduction of these symptoms over the long term, and improve patients’ functional capacity—thereby improving the quality of life for patients and their caregivers. Atypical antipsychotics are the cornerstone of schizophrenia treatment with ten molecules available in the United States, in various oral, intramuscular, and depot formulations. The continued genericization of the schizophrenia market will be an obstacle to emerging therapies targeting the disease’s positive symptoms; in particular, the generic availability of therapies with more-favorable tolerability profiles (e.g., aripiprazole), will likely relegate emerging therapies to later lines of therapy. Using national patient-level claims data, Treatment Algorithms in Schizophrenia explores the use of key therapies and drug classes among newly diagnosed and recently treated schizophrenia patient populations. Among the newly diagnosed patients, this report provides a quantitative analysis of treatment patterns and share by line of therapy, as well as progression between lines, duration of treatment on each line, and use of concomitant treatment. Among recently treated patients, this report quantifies a therapy’s overall drug share, use in combination with other therapies, and source of business compared with its competitors, detailing which drugs precede others through an analysis of add-versus-switch patterns. Additional analyses explore persistency and compliance by therapy.