Ruth M Pfeiffer1, Bernd Mayer2, Ralph W Kuncl3, David P Check1, Elizabeth K Cahoon1, Donna R Rivera4, D Michal Freedman1. 1. National Cancer Institute, Division of Cancer Epidemiology and Genetics, NIH, DHHS, Bethesda, MD, USA. 2. Institute of Pharmaceutical Sciences, Department of Pharmacology and Toxicology, University of Graz, Graz, Austria. 3. Department of Biology, University of the Redlands, Redlands, CA, USA, and. 4. National Cancer Institute, Division of Cancer Control and Population Sciences, NIH, DHHS, Bethesda, MD, USA.
Abstract
Background: Few well-established factors are associated with risk of amyotrophic lateral sclerosis (ALS). We comprehensively evaluate prescription drugs use in administrative health claims from U.S. Medicare beneficiaries in relation to ALS risk to generate hypotheses for further research. Methods: This is a population-based case-control study of 10,450 U.S. Medicare participants (ages 66-89 years) diagnosed with ALS, based on Medicare Parts A and B fee-for-service claims, between 1 January 2008, and 31 December 2014, and 104,500 controls (1:10 ratio) frequency-matched on age, sex, and selection year. Odds ratios (ORs) for the ALS association with 685 prescription drugs were estimated using logistic regression models for both a one- and three-year lag period. Covariates included demographic characteristics and key comorbidities, among other factors. Prescription drug use was based on Medicare Part D claims. We adjusted for multiple comparisons using a Bonferroni correction. Additional a priori analyses of sex hormone drugs were also undertaken. Results: In the large drug screen, we found 10 drugs significantly associated with lower ALS risk after the multiple-testing correction in a one-year and three-year lag analysis. These included several drugs for hypertension, diabetes, and cardiovascular disease. In a separate a priori inquiry of sex hormone drugs, tamoxifen was related to lower ALS risk, and testosterone to a higher risk in women. Conclusions: These associations warrant replication in databases that include information on the severity and duration of medical conditions underlying drug use, and drug use over a longer portion of individuals' lifespans, to further help evaluate confounding by indication.
Background: Few well-established factors are associated with risk of amyotrophic lateral sclerosis (ALS). We comprehensively evaluate prescription drugs use in administrative health claims from U.S. Medicare beneficiaries in relation to ALS risk to generate hypotheses for further research. Methods: This is a population-based case-control study of 10,450 U.S. Medicare participants (ages 66-89 years) diagnosed with ALS, based on Medicare Parts A and B fee-for-service claims, between 1 January 2008, and 31 December 2014, and 104,500 controls (1:10 ratio) frequency-matched on age, sex, and selection year. Odds ratios (ORs) for the ALS association with 685 prescription drugs were estimated using logistic regression models for both a one- and three-year lag period. Covariates included demographic characteristics and key comorbidities, among other factors. Prescription drug use was based on Medicare Part D claims. We adjusted for multiple comparisons using a Bonferroni correction. Additional a priori analyses of sex hormone drugs were also undertaken. Results: In the large drug screen, we found 10 drugs significantly associated with lower ALS risk after the multiple-testing correction in a one-year and three-year lag analysis. These included several drugs for hypertension, diabetes, and cardiovascular disease. In a separate a priori inquiry of sex hormone drugs, tamoxifen was related to lower ALS risk, and testosterone to a higher risk in women. Conclusions: These associations warrant replication in databases that include information on the severity and duration of medical conditions underlying drug use, and drug use over a longer portion of individuals' lifespans, to further help evaluate confounding by indication.
Entities:
Keywords:
Amyotrophic lateral sclerosis; Medicare; drug screening; medications; population based; risk