Health state utility values in major depressive disorder treated with pharmacological interventions: a systematic literature review.

BACKGROUND: Major depressive disorder (MDD) is associated with decreased patient well-being and symptoms that can cause substantial impairments in patient functioning and even lead to suicide. Worldwide, MDD currently causes the second-most years lived with disability and is predicted to become the leading cause of disability by 2030. Utility values, capturing patient quality of life, are required in economic evaluations for new treatments undergoing reimbursement submissions. We aimed to identify health state utility values (HSUVs) and disutilities in MDD for use in future economic evaluations of pharmacological treatments. METHODS: Embase, PubMed, Econlit, and Cochrane databases, plus gray literature, were searched from January 1998 to December 21, 2018, with no language or geographical restrictions, for relevant studies that reported HSUVs and disutilities for patients with MDD receiving pharmacological interventions. RESULTS: 443 studies were identified; 79 met the inclusion criteria. We focused on a subgroup of 28 articles that reported primary utility data from 16 unique studies of MDD treated with pharmacological interventions. HSUVs were elicited using EQ-5D (13/16, 81%; EQ-5D-3L: 11/16, 69%; EQ-5D-3L or EQ-5D-5L not specified: 2/16), EQ-VAS (5/16, 31%), and standard gamble (1/16, 6%). Most studies reported baseline HSUVs defined by study entry criteria. HSUVs for a first or recurrent major depressive episode (MDE) ranged from 0.33 to 0.544 and expanded from 0.2 to 0.61 for patients with and without painful physical symptoms, respectively. HSUVs for an MDE with inadequate treatment response ranged from 0.337 to 0.449. Three studies reported HSUVs defined by MADRS or HAMD-17 clinical thresholds. There was a large amount of heterogeneity in patient characteristics between the studies. One study reported disutility estimates associated with treatment side effects. CONCLUSIONS: Published HSUVs in MDD, elicited using methods accepted by health technology assessment bodies, are available for future economic evaluations. However, the evidence base is limited, and it is important to select appropriate HSUVs for the intervention being evaluated and that align with clinical health state definitions used within an economic model. Future studies are recommended to elicit HSUVs for new treatments and their side effects and add to the existing evidence where data are lacking.

A modelling approach to estimate the prevalence of treatment-resistant schizophrenia in the United States.

INTRODUCTION: Schizophrenia is a condition that places a significant burden on individuals with the condition, their family, and society. A large proportion of those treated for schizophrenia do not experience treatment response and are referred to as having "treatment-resistant schizophrenia" (TRS). Expert opinion has long held that the prevalence of TRS among individuals with schizophrenia is 30%, but the basis of this estimate is unclear. This article presents a model developed for estimating the prevalence of TRS in the United States 2014. METHODS: An incidence-prevalence-mortality model was developed to estimate the prevalence of TRS in the United States. The model was populated with data from public health agencies and published literature. Prevalence in 2014 was modelled using a Markov cohort simulation for each birth cohort between 1930 to 2014. RESULTS: Using different scenarios for baseline incidence, relative risks of mortality, it was estimated that approximately 22% of individuals with schizophrenia would be considered treatment-resistant in 2014. DISCUSSION: The results suggests that prevalence of TRS may be somewhat lower than the 30% often reported, however this is highly dependent on the definition of treatment resistance. Methods such as this may help answer epidemiological and health policy questions as well as test the influence of key underlying assumptions.