The prevalence of multiple sclerosis in the United States has steadily grown over the past 5 years to nearly 1 million people.
By applying a validated algorithm to multiple sets of administrative health data (AHC), researchers have shown that there has been a steady rise in the prevalence of multiple sclerosis (MS) in the US over the past 5 years to nearly 1 million people.
This number is nearly double that of previously reported estimates from prior studies, which had estimated that this population in the US numbered approximately 572,312 (95% CI, 397,004-747,619, and 403,630 individual cases (95% CI 387,445-419,833). Establishing an accurate estimate of MS prevalence in the US is essential for evaluating changes in disease frequency in relation to changing population demographics.
“We must understand the reasons behind the growing MS prevalence estimates in the US,” Mitchell Wallin, MD, MPH, Director for The Multiple Sclerosis Centers of Excellence (MSCoE) East at the US Department of Veterans Affairs (VA), told MD Magazine®. “For example, how are the demographic changes in the US influencing the incidence and mortality experience of MS?”
Wallin said more neurologists and health care providers experienced in MS will be needed to care for the rising rate of older patients with MS.
“Using large population-based MS cohorts and datasets that are well characterized is critical to a better understanding of the disease,” he said.
In a new study, researchers describe how this novel algorithm-based approach responds to the need for estimating the true prevalence of MS in the US, using analyses of AHCs from government and private health claims databases as the most reliable and cost-effective method. Previously, the primary method used to estimate national MS prevalence has been probability health surveys that relied on patient or family member reports of physician-diagnosed MS.
The data are less reliable due to the risk of the inclusion of false-positive MS cases or provisional cases that would not meet formal case definition criteria, and insufficient numbers of people with MS to enable precise estimation of MS prevalence, much less prevalence within demographic or regional subgroups. What’s more, the national survey no longer includes questions about MS.
While AHC databases present a tremendous resource for analyzing neurologic disease incidence using the international disease coding (ICD) system, there are potential limitations when used for epidemiological purposes. The algorithm developed is optimal in terms of sensitivity, specificity, and simplicity, requiring ≥3 MS-related hospitalizations, outpatient visits, or prescription release encounters for an MS disease-modifying therapy within a 1-year period that was approved by the US Food and Drug Administration (FDA) for MS by 2010. Depending on the dataset, the sensitivity of the MS algorithm was 86% to 92% and the specificity was 66% to 83%, when tested among individuals with at least 1 MS claim.
“The planned US Neurological Disease Surveillance System, if properly launched and funded, could be very helpful in this regard and should be supported,” continued Wallin. “Additionally, we must understand how the aging process itself impacts with morbidity and mortality of MS.”
Though the MS Prevalence Workgroup intends to analyze how race impacts MS prevalence to the extent possible in national healthcare datasets, more work must be done to confirm new variables, because of known risk factors for MS onset and progression, Wallin concluded.
The study, “The prevalence of MS in the United States,” was published online in Neurology.
This article was originally published by MD Magazine.