Mental Health-Related Disability Days and Costs Among Patients with Treatment-Resistant Depression Initiated on Esketamine Nasal Spray and Conventional Therapies in the USA.
Manish K Jha, Maryia Zhdanava, Aditi Shah, Arthur Voegel, Anabelle Tardif-Samson, Dominic Pilon, Kruti Joshi
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引用次数: 0
Abstract
Introduction: Treatment-resistant depression (TRD) is related to disproportionate unemployment and productivity burden in the USA. The current study describes real-world mental health (MH)-related disability days and costs of patients with TRD initiated on esketamine nasal spray or conventional therapies in the USA.
Methods: Adults with TRD were selected from Merative™ MarketScan® Commercial database (from January 2016 to January 2023) and classified into four cohorts (esketamine, ECT [electroconvulsive therapy], TMS [transcranial magnetic stimulation], and SGA [second-generation antipsychotics] augmentation) based on therapy initiated (index date) on/after 5 March 2019 (esketamine approval date for TRD). Patients had ≥ 12 months of health plan eligibility pre-index date and disability information available pre- and post-index in the Merative™ MarketScan® Health and Productivity Management database (from January 2016 to December 2021). MH-related disability days (i.e., short- or long-term) and associated costs (US dollars [USD] 2022) were reported per-patient-per-month for the 6 months pre- and post-index.
Results: The study comprised four cohorts: esketamine (n = 107; mean age: 45.5 years, female: 54.2%), ECT (n = 55; mean age: 47.6 years, female: 41.8%), TMS (n = 443; mean age: 46.1 years, female: 57.3%), and SGA (n = 4374; mean age: 44.8 years, female: 59.1%). In month 6 pre-index, mean number of MH-related disability days was 1.7 in the esketamine cohort, 1.2 in the TMS cohort, 1.3 in the ECT cohort, and 0.8 in the SGA augmentation cohort; mean MH-related disability costs were US $443 in the esketamine cohort, US $339 in the TMS cohort, US $178 in the ECT cohort, and US $143 in the SGA augmentation cohort. In all cohorts, a peak in mean MH-related disability days and costs was observed 1 month after therapy initiation followed by a decreasing trend. In month 6 post-index versus month 6 pre-index, the mean number of MH-related disability days trended lower in the esketamine cohort (- 0.4 days), remained the same in the TMS cohort and largely the same in the SGA augmentation cohort (+ 0.1 days), and trended higher (+ 1.6 days) in the ECT cohort. In the same timeframe, MH-related disability costs trended lower in the esketamine and TMS cohorts, with observed reductions of US $312 and US $123, respectively. Costs remained largely the same in the SGA augmentation cohort (+ US $26), and trended higher (+ US $353) in the ECT cohort.
Conclusions: In this descriptive study, initiation of esketamine was associated with trends toward lower MH-related disability days and costs. Conventional therapies demonstrated varied patterns, with no consistent trend toward reductions in disability days across all therapies and no observed cost-savings trends for SGA augmentation and ECT. These trends suggest potential economic and societal gains of esketamine treatment for TRD but warrant further investigation with larger samples and robust statistical comparisons.
期刊介绍:
Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.