BACKGROUND: In 2002, the National Institute for Health and Clinical Excellence (NICE), recommended atypical antipsychotics over conventional ones for first-line schizophrenia treatment, based on their lower risk of extrapyramidal symptoms. OBJECTIVE: To estimate the incremental cost-effectiveness of atypical relative to conventional antipsychotics for the treatment of schizophrenia in the UK. METHODS: A discrete event simulation (DES) model was adopted to reflect the treatment of schizophrenia in the UK. The model estimates symptoms (using the Positive and Negative Symptom Score [PANSS]), psychiatrist visits, pharmacological treatment and treatment location, number and duration of psychotic relapses, level of compliance, quality-adjusted life-years (QALYs), and side effects over a 5-year time period. Probabilistic sensitivity analyses were carried out. Following NICE's "atypical" recommendation, the cost-effectiveness of atypical versus conventional antipsychotics was estimated in a scenario analysis, assuming both groups differ only in side-effect profile. RESULTS: When comparing conventional and atypical antipsychotics, the model predicts that the latter would decrease 5-year costs by 1633 Pound per patient and result in a QALY gain of 0.101. The probabilistic sensitivity analysis suggests these results are robust. The sensitivity analyses indicate that incremental costs and effects are most sensitive to the differential efficacy of atypicals and conventionals, as measured by PANSS. When it is assumed that the only differences between atypicals and conventionals are found in side-effect profiles, the incremental cost-effectiveness ratio of the atypicals is 45,000 Pound per QALY gained. CONCLUSION: According to this DES model for schizophrenia, atypical antipsychotics are cost-effective compared to the conventional antipsychotics. The assumptions used in the model need further validation through large naturalistic based studies with reasonable follow-up to determine the real-life differences between atypicals and conventional antipsychotics.
BACKGROUND: In 2002, the National Institute for Health and Clinical Excellence (NICE), recommended atypical antipsychotics over conventional ones for first-line schizophrenia treatment, based on their lower risk of extrapyramidal symptoms. OBJECTIVE: To estimate the incremental cost-effectiveness of atypical relative to conventional antipsychotics for the treatment of schizophrenia in the UK. METHODS: A discrete event simulation (DES) model was adopted to reflect the treatment of schizophrenia in the UK. The model estimates symptoms (using the Positive and Negative Symptom Score [PANSS]), psychiatrist visits, pharmacological treatment and treatment location, number and duration of psychotic relapses, level of compliance, quality-adjusted life-years (QALYs), and side effects over a 5-year time period. Probabilistic sensitivity analyses were carried out. Following NICE's "atypical" recommendation, the cost-effectiveness of atypical versus conventional antipsychotics was estimated in a scenario analysis, assuming both groups differ only in side-effect profile. RESULTS: When comparing conventional and atypical antipsychotics, the model predicts that the latter would decrease 5-year costs by 1633 Pound per patient and result in a QALY gain of 0.101. The probabilistic sensitivity analysis suggests these results are robust. The sensitivity analyses indicate that incremental costs and effects are most sensitive to the differential efficacy of atypicals and conventionals, as measured by PANSS. When it is assumed that the only differences between atypicals and conventionals are found in side-effect profiles, the incremental cost-effectiveness ratio of the atypicals is 45,000 Pound per QALY gained. CONCLUSION: According to this DES model for schizophrenia, atypical antipsychotics are cost-effective compared to the conventional antipsychotics. The assumptions used in the model need further validation through large naturalistic based studies with reasonable follow-up to determine the real-life differences between atypicals and conventional antipsychotics.
Authors: Sean M Murphy; Michael G McDonell; Sterling McPherson; Debra Srebnik; Frank Angelo; John M Roll; Richard K Ries Journal: Drug Alcohol Depend Date: 2015-05-14 Impact factor: 4.492
Authors: Tatiana Dilla; Jörgen Möller; Paul O'Donohoe; María Álvarez; José A Sacristán; Michael Happich; Antje Tockhorn Journal: BMC Psychiatry Date: 2014-12-02 Impact factor: 3.630