Supplements New Perspectives on Overactive Bladder and Its Treatment
The Total Economic Burden of Overactive Bladder in the United States: A Disease-Specific Approach
The sex-stratified weighted prevalence rates of OAB at least "often" in the current analysis were 26.1% among adult women and 10.7% among adult men. Sex-stratified weighted prevalence estimates from NOBLE were 16.9% in adult women and 16% in adult men.19 Prevalence estimates used in the current COI study are higher than previous estimates reported from the NOBLE study and used in the study by Hu et al.5 Variation in prevalence estimates was shown in the sensitivity analyses to have the largest impact on the current COI estimate. Thus, the different prevalence estimates between the NOBLE and EpiLUTS surveys may be largely responsible for the difference in COI estimates between the study by Hu et al5 and the current study. The cost estimates between the 2 studies also will differ due to the differences in the COI method. The current study utilizes a disease-specific total-cost approach, while Hu et al5 utilize an incremental cost approach.
Results indicate that the estimated cost is impacted by the definition of OAB utilized. Estimated total costs differed across the 2 classifications of OAB. The economic burden of OAB differed across age subgroups and may reflect differences in the epidemiology and management of OAB.7,20 In addition, the relative economic burden of illness does not differ according to the OAB definition employed. The percentage increase in costs between the group younger than 65 years of age and the group 65 years of age or older was comparable for the 2 classifications of OAB and among women but was less comparable among men. In all cases, the relative economic burden was lower for OAB at least "often" compared with OAB at least "sometimes." Compared with the alternative, the base-case definition of OAB may include cases that are more severe in their symptom severity. If this is true, then defining OAB using the base case would lead to a narrowing of the differential cost burden across subgroups compared with the results using the alternative-case definition.
A few limitations are worth mentioning. The use of self-reported disease-specific measures in a total cost approach may provide a less accurate measure of disease-attributable economic burden compared with an incremental cost approach in the presence of unobserved differences between groups. The use of disease-specific health services utilization is preferred to adding up costs in a population of patients with OAB and then attributing the total costs to the treatment of OAB.10 However, other differences between cases and noncases, including underlying health status, smoking behavior, and mental health status, that also may contribute to higher healthcare expenditures are not specifically accounted for in a total cost approach.
We calculated the total economic burden of disease among community-dwelling adults using the current ICS definition of OAB. The total cost of disease is estimated at $24.9 billion, with a significantly higher burden among adults younger than 65 years of age. If institutional costs were included, this figure would be even higher. Future research is needed to determine whether any differential cost burden across age groups is robust to alternative COI analysis methods and using current ICS definitions of OAB. Information on the differential economic burden across demographic groups can be used to guide the development of treatment and program interventions designed to improve the management of OAB symptoms.
Editorial assistance was provided by the University of Maryland and funded by Pfizer Inc. The authors would like to acknowledge Jim Gardner of the University of Maryland, School of Pharmacy's Pharmaceutical Research Computing Center for providing timely and reliable data analysis support and the EpiLUTS Working Group. Coordination support and management of this supplement were provided by Complete Healthcare Communications, Inc.
Author Affiliations: From the Pharmaceutical Health Services Research Department (EO, IHZ, CDM), Pharmaceutical Research Computing Department (DM), School of Pharmacy, University of Maryland, Baltimore; United BioSource Corporation Center for Health Outcomes Research, Bethesda, MD (KSC); Pfizer Inc, New York, NY (VV).
Funding Source: Financial support for this work was provided by Pfizer Inc.
Author Disclosures: The authors report being consultants (EO, KSC, CDM) for, an employee (VV) of, and receiving grants and honoraria (EO, CDM) from Pfizer Inc; consultant (CDM) for Novartis. The authors (IHZ, DM) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design (EO, IHZ, DM, KSC, VV, CDM); acquisition of data (KSC, VV, CDM); analysis and interpretation of data (EO, IHZ, DM, KSC, VV); drafting of the manuscript (EO, KSC, VV); critical revision of the manuscript for important intellectual content (EO, IHZ, VV, CDM); statistical analysis (EO, KSC, VV); provision of study materials or patients (VV); obtaining funding (KSC, VV, CDM); administrative, technical, or logistic support (DM, VV); and supervision (KSC, VV).
Address correspondence to: Ebere Onukwugha, PhD, Department of Pharmaceutical Health Services Research, School of Pharmacy, University of Maryland, 220 Arch St, Baltimore, MD 21201. E-mail: firstname.lastname@example.org.
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