Burden of multiple sclerosis on direct, indirect costs and quality of life: National US estimates
Introduction
MS, a chronic and debilitating inflammatory autoimmune disorder of the central nervous system, afflicts approximately 400,000 people in the United States (Zwibel and Smrtka, 2011, Goldberg et al., 2009) and 2.1 million people worldwide (Zwibel and Smrtka, 2011). MS is among the most common contributors to neurologic disability in young and middle-aged adults (Phillips, 2004) with detrimental effects on patients' productivity and health-related quality of life (HRQoL). Peak age of onset is approximately 30 years (Olofsson et al., 2011). Because patients with MS typically have a long life span and increased healthcare utilization (Prescott et al., 2007), MS imposes a significant burden on patients and their families/caregivers, employers, and the healthcare system.
Average total (direct and indirect) costs in a study of 1909 patients identified from the North American Committee on Multiple Sclerosis Patient Registry (NARCOMS) were estimated at $47,215 per patient per year, 63% for direct medical and nonmedical costs ($29,634) and 37% for total indirect costs including early retirement and informal care ($17,581) (Kobelt et al., 2006b). Ivanova et al. (2012) reported annual average total (direct and indirect) costs, excluding costs of disease modifying treatments (DMTs), ranging from $14,095 for DMT-adherent patients to $16,638 for those with poor adherence to DMTs. In a retrospective claims-based analysis of privately insured US employees with MS, total indirect costs (2006 US dollars) were more than 4 times higher for MS patients than for matched controls (P<0.0001) (Ivanova et al., 2009).
A less widely reported component of the costs of MS is the additional burden on HRQoL (Orlewska, 2006), commonly referred to as “intangible costs”. Many studies assessing MS burden do not include HRQoL in their estimates due in part to challenges in monetizing HRQoL measures (Orlewska, 2006). One HRQoL-informed measure that has been monetized is quality-adjusted life years (QALYs), a common metric used in cost-effectiveness research (Neumann and Greenberg, 2009). QALYs include two components: an HRQoL-informed utility weight (quality-adjusted component) and survival (life years component). Utility values are anchored at 0 for death and 1 for perfect health. For each time interval of survival, the utility weight is multiplied by the survival time and summed overall survival times thus producing QALYs. The QALY therefore allows for the translation of disparate risks and benefits into one common outcome measure that can be compared within and across diseases.
As the incidence of MS is projected to grow 5% by 2013 (National Multiple Sclerosis Society, 2011), and as new DMTs are expected to be introduced to the market that could influence treatment choice and cost, further examination of the economic and intangible burden of MS would add to the platform for evidence-based decisions.
The primary objective of the present study was to conduct a comprehensive evaluation of the current burden of MS in the United States using nationally representative data from the Medical Expenditure Panel Survey (MEPS), a public-access, large-scale database that links direct cost information with information on productivity and HRQoL. MEPS also makes adjustments for socioeconomic and demographic characteristics. This is the first time this unique dataset has been utilized to evaluate the comprehensive burden of MS including direct costs, indirect costs, and HRQoL.
Section snippets
Data source
MEPS tracks individual and household demographic, socioeconomic, and health-related characteristics (Agency for Healthcare Research and Quality, 2013), providing a nationally representative sample of the US civilian non-institutionalized population (the study population of inference). The Household Component of the Medical Expenditure Panel Survey (MEPS-HC) is a nationally representative survey of the US civilian noninstitutionalized population. The sampling frame is drawn from respondents to
Results
There were 526 respondents (0.21% survey sample weight-adjusted) with a verified MS diagnosis in the 12-year cohort, (1998–2009), with an estimated annual prevalence of 572,312 (95% confidence interval [CI] 397,004, 747,619) in the United States. MS and non-MS cohorts were similar on the demographic dimensions of race and education (Table 1). Compared with the non-MS population, the MS population was more likely to be female (77% vs. 52%), older by about 4 years on average, non-Hispanic (97%
Discussion
We observed a higher annual prevalence of N=572,312 (0.21%) of MS in our MEPS-identified study population than the commonly cited national estimate of 400,000 persons (0.13% of an estimated US population of 300 million) (Zwibel and Smrtka, 2011; Goldberg et al., 2009; National Multiple Sclerosis Society, 2011; Noonan et al., 2002; Loma and Heyman, 2011; Asche et al., 2010; Vlahiotis et al., 2010). Past primary data studies on the prevalence for MS vary from 58 to 177 per 100,000 population
Limitations
Certain limitations must be considered when interpreting these study results, such as the fact that the MEPS dataset does not include information on disease severity, which could affect the estimates. As DMT utilization was rarely captured in the MEPS dataset, we excluded the costs of DMTs from our prescription expenditures but included a literature-based estimate of annual DMT costs for completeness. This study's estimates of MS burden are likely conservative for at least two reasons: (1) our
Conclusions
Based on our findings, MS prevalence is likely higher than previous conservative US estimates, especially among women. MS patients have higher healthcare costs and utilization than their non-MS counterparts, and are at higher risk for not being employed and having lower HRQoL. Further, MS direct costs, indirect costs, and intangible burden in the MS population are higher across most domains as compared with other debilitating chronic conditions.
Study funding
This project was supported by an unrestricted grant from Biogen Idec. The content is solely the responsibility of the authors.
Author contributions
Study concept and design—all authors. Acquisition of the data—Dr. Ghushchyan. Statistical analysis and data interpretation—primarily conducted by Dr. Ghushchyan with support from Dr. Campbell, Mr. McQueen, and Dr. Nair. Critical revision of the manuscript for important intellectual content—all authors. Study supervision—Dr. Campbell and Dr. Nair.
Conflict of interest
Dr. Campbell is a consultant for Amgen Inc., AstraZeneca Inc., Biogen Idec, and for VeriTech Inc., and has received grant support from the Centers for Disease Control and Prevention and the Agency for Health Care Research and Quality.
Dr. Ghushchyan is a consultant for Janssen Services and Biogen Idec. and has received grant support from Amgen Inc, Janssen Services and Biogen Idec.
Mr. McQueen is a consultant for Biogen Idec and VeriTech Inc. and has received grant support from PhRMA Foundation.
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