title: Incidence of Exposure of Patients in the United States to Multiple Drugs for Which Pharmacogenomic Guidelines Are Available.
abstract: Pre-emptive pharmacogenomic (PGx) testing of a panel of genes may be easier to implement and more cost-effective than reactive pharmacogenomic testing if a sufficient number of medications are covered by a single test and future medication exposure can be anticipated. We analysed the incidence of exposure of individual patients in the United States to multiple drugs for which pharmacogenomic guidelines are available (PGx drugs) within a selected four-year period (2009-2012) in order to identify and quantify the incidence of pharmacotherapy in a nation-wide patient population that could be impacted by pre-emptive PGx testing based on currently available clinical guidelines. In total, 73 024 095 patient records from private insurance, Medicare Supplemental and Medicaid were included. Patients enrolled in Medicare Supplemental age > = 65 or Medicaid age 40-64 had the highest incidence of PGx drug use, with approximately half of the patients receiving at least one PGx drug during the 4 year period and one fourth to one third of patients receiving two or more PGx drugs. These data suggest that exposure to multiple PGx drugs is common and that it may be beneficial to implement wide-scale pre-emptive genomic testing. Future work should therefore concentrate on investigating the cost-effectiveness of multiplexed pre-emptive testing strategies.
authors.affiliation: Section for Artificial Intelligence and Decision Support; Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
authors.forename: Matthias
authors.identifier: http://orcid.org/0000-0002-4855-2571
authors.initials: M
authors.lastname: Samwald
authors.affiliation: Section for Artificial Intelligence and Decision Support; Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
authors.forename: Hong
authors.initials: H
authors.lastname: Xu
authors.affiliation: Section for Artificial Intelligence and Decision Support; Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
authors.forename: Kathrin
authors.initials: K
authors.lastname: Blagec
authors.affiliation: Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Philip E
authors.initials: PE
authors.lastname: Empey
authors.affiliation: College of Pharmacy, University of Arizona, Tucson, Arizona, United States of America.
authors.forename: Daniel C
authors.initials: DC
authors.lastname: Malone
authors.affiliation: Department of Pharmacy, College of public health and medical sciences, Jimma University, Jimma, Ethiopia.
authors.forename: Seid Mussa
authors.initials: SM
authors.lastname: Ahmed
authors.affiliation: Janssen Research and Development, Titusville, New Jersey, United States of America.|Observational Health Data Sciences and Informatics, New York, New York, United States of America.
authors.forename: Patrick
authors.initials: P
authors.lastname: Ryan
authors.affiliation: Section for Artificial Intelligence and Decision Support; Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Hofer
authors.affiliation: Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Richard D
authors.initials: RD
authors.lastname: Boyce
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D002648:Child; D002675:Child, Preschool; D003362:Cost-Benefit Analysis; D016208:Databases, Factual; D011307:Drug Prescriptions / Q000191:economics / Q000706:statistics & numerical data*; D064420:Drug-Related Side Effects and Adverse Reactions / Q000191:economics; D005260:Female; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D000071185:Pharmacogenomic Testing; D017410:Practice Guidelines as Topic; D012306:Risk; D014481:United States; D055815:Young Adult