Emilie Bruzelius1,2, Joseph Scarpa1, Yiyi Zhao1,2, Sanjay Basu3, James H Faghmous3, Aaron Baum1. 1. Icahn School of Medicine at Mount Sinai, New York, New York, USA. 2. Mailman School of Public Health, Columbia University, New York, New York, USA. 3. Stanford University School of Medicine, New York, New York, USA.
Abstract
BACKGROUND: Despite extensive research regarding the etiology of Huntington's disease, relatively little is known about the epidemiology of this rare disorder, particularly in the United States where there are no national-scale estimates of the disease. OBJECTIVES: To provide national-scale estimates of Huntington's disease in a U.S. population and to test whether disease rates are increasing, and whether frequency varies by race, ethnicity, or other factors. METHODS: Using an insurance database of over 67 million enrollees, we retrospectively identified a cohort of 3,707 individuals diagnosed with Huntington's disease between 2003 and 2016. We estimated annual incidence, annual diagnostic frequency, and tested for trends over time and differences in diagnostic frequency by sociodemographic characteristics. RESULTS: During the observation period, the age-adjusted cumulative incidence rate was1.22 per 100,000 persons (95% confidence interval: 1.53, 1.65), and age-adjusted diagnostic frequency was 6.52 per 100,000 persons (95% confidence interval: 5.31, 5.66); both rates remained relatively stable over the 14-year period. We identified several previously unreported differences in Huntington's disease frequency by self-reported sex, income, and race/ethnicity. However, racial/ethnic differences were of lower magnitude than have previously been reported in other country-level studies. CONCLUSIONS: In these large-scale estimates of U.S. Huntington's disease epidemiology, we found stable disease frequency rates that varied by several sociodemographic factors. These findings suggest that disease patterns may be more driven by social or environmental factors than has previously been appreciated. Results further demonstrate the potential utility of administrative Big Data in rare disease epidemiology when other data sources are unavailable.
BACKGROUND: Despite extensive research regarding the etiology of Huntington's disease, relatively little is known about the epidemiology of this rare disorder, particularly in the United States where there are no national-scale estimates of the disease. OBJECTIVES: To provide national-scale estimates of Huntington's disease in a U.S. population and to test whether disease rates are increasing, and whether frequency varies by race, ethnicity, or other factors. METHODS: Using an insurance database of over 67 million enrollees, we retrospectively identified a cohort of 3,707 individuals diagnosed with Huntington's disease between 2003 and 2016. We estimated annual incidence, annual diagnostic frequency, and tested for trends over time and differences in diagnostic frequency by sociodemographic characteristics. RESULTS: During the observation period, the age-adjusted cumulative incidence rate was1.22 per 100,000 persons (95% confidence interval: 1.53, 1.65), and age-adjusted diagnostic frequency was 6.52 per 100,000 persons (95% confidence interval: 5.31, 5.66); both rates remained relatively stable over the 14-year period. We identified several previously unreported differences in Huntington's disease frequency by self-reported sex, income, and race/ethnicity. However, racial/ethnic differences were of lower magnitude than have previously been reported in other country-level studies. CONCLUSIONS: In these large-scale estimates of U.S. Huntington's disease epidemiology, we found stable disease frequency rates that varied by several sociodemographic factors. These findings suggest that disease patterns may be more driven by social or environmental factors than has previously been appreciated. Results further demonstrate the potential utility of administrative Big Data in rare disease epidemiology when other data sources are unavailable.
Authors: Kevin Michael Biglan; Ira Shoulson; Karl Kieburtz; David Oakes; Elise Kayson; M Aileen Shinaman; Hongwei Zhao; Megan Romer; Anne Young; Steven Hersch; Jack Penney; Karen Marder; Jane Paulsen; Kimberly Quaid; Eric Siemers; Caroline Tanner; William Mallonee; Greg Suter; Richard Dubinsky; Carolyn Gray; Martha Nance; Scott Bundlie; Dawn Radtke; Sandra Kostyk; Corrine Baic; James Caress; Francis Walker; Victoria Hunt; Christine O'Neill; Sylvain Chouinard; Stewart Factor; Timothy Greenamyre; Cathy Wood-Siverio; Jody Corey-Bloom; David Song; Guerry Peavy; Carol Moskowitz; Melissa Wesson; Ali Samii; Thomas Bird; Hillary Lipe; Karen Blindauer; Frederick Marshall; Carol Zimmerman; Jody Goldstein; Diana Rosas; Peter Novak; John Caviness; Charles Adler; Amy Duffy; Vicki Wheelock; Teresa Tempkin; David Richman; Lauren Seeberger; Roger Albin; Kelvin L Chou; Brad Racette; Joel S Perlmutter; Susan Perlman; Yvette Bordelon; Wayne Martin; Marguerite Wieler; Blair Leavitt; Lynn Raymond; Joji Decolongon; Lorne Clarke; Joseph Jankovic; Christine Hunter; Robert A Hauser; Juan Sanchez-Ramos; Sarah Furtado; Oksana Suchowersky; Mary Lou Klimek; Mark Guttman; Rustom Sethna; Andrew Feigin; Marie Cox; Barbara Shannon; Alan Percy; Leon Dure; Madaline Harrison; William Johnson; Donald Higgins; Eric Molho; Constance Nickerson; Sharon Evans; Douglas Hobson; Carlos Singer; Nestor Galvez-Jimenez; Kathleen Shannon; Cynthia Comella; Christopher Ross; Marie H Saint-Hilaire; Claudia Testa; Adam Rosenblatt; Penelope Hogarth; William Weiner; Peter Como; Rajeev Kumar; Candace Cotto; Julie Stout; Alicia Brocht; Arthur Watts; Shirley Eberly; Christine Weaver; Tatiana Foroud; James Gusella; Marcy MacDonald; Richard Myers; Stanley Fahn; Clifford Shults Journal: JAMA Neurol Date: 2016-01 Impact factor: 18.302