Drug-drug interactions (DDIs) are an important public health problem, especially in the elderly, who are the largest consumers of medications. Nearly all existing knowledge about the clinical importance of potential DDIs comes from pharmacokinetic studies or case reports, both of which have limited utility for identifying clinically important DDIs. As a result, there is a great deal of disagreement among standard DDI reference texts regarding the clinical importance of most potential DDIs. Systematic efforts such as drug utilization review programs and computerized physician order entry that seek to improve medication use depend entirely upon a valid set of clinical rules, and are thus severely hampered by this knowledge gap. To address these critical gaps in existing knowledge of the clinical importance of DDIs, the investigators will perform controlled epidemiologic studies of high-priority potential DDIs that have been selected based on a formal process involving consultation with an Expert Panel of clinicians and clinical pharmacologists. We will use and expand upon an existing, very large pharmacoepidemiologic database consisting of Medicaid data from five large programs, supplemented by Medicare data to ensure complete capture of outcomes in the elderly, together with the General Practice Research Database from the UK. We will examine the validity of our outcome measures using medical record review. Our research strategy will include nested case-control and case-crossover designs, and will yield relative risks, risk differences, and number needed to harm (NNH). Patient and treatment factors associated with developing the adverse outcome of interest will be studied. The results of this study will have important implications for public health, clinical care, and the elucidation of the pharmacology of DDIs, and will serve as a basis for future studies examining factors not recorded in administrative and medical records data.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG025152-04
Application #
7657356
Study Section
Special Emphasis Panel (ZRG1-HOP-C (90))
Program Officer
Nayfield, Susan G
Project Start
2006-09-15
Project End
2011-08-31
Budget Start
2009-09-01
Budget End
2010-08-31
Support Year
4
Fiscal Year
2009
Total Cost
$471,517
Indirect Cost
Name
University of Pennsylvania
Department
Biostatistics & Other Math Sci
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Leonard, Charles E; Brensinger, Colleen M; Aquilante, Christina L et al. (2018) Comparative Safety of Sulfonylureas and the Risk of Sudden Cardiac Arrest and Ventricular Arrhythmia. Diabetes Care 41:713-722
Leonard, Charles E; Han, Xu; Brensinger, Colleen M et al. (2018) Comparative risk of serious hypoglycemia with oral antidiabetic monotherapy: A retrospective cohort study. Pharmacoepidemiol Drug Saf 27:9-18
Ertefaie, Ashkan; Small, Dylan S; Ji, Xinyao et al. (2018) Statistical Power for Trend-in-trend Design. Epidemiology 29:e21-e23
Leonard, Charles E; Hennessy, Sean; Han, Xu et al. (2017) Pro- and Antiarrhythmic Actions of Sulfonylureas: Mechanistic and Clinical Evidence. Trends Endocrinol Metab 28:561-586
Leonard, Charles E; Brensinger, Colleen M; Bilker, Warren B et al. (2017) Gastrointestinal bleeding and intracranial hemorrhage in concomitant users of warfarin and antihyperlipidemics. Int J Cardiol 228:761-770
Ji, Xinyao; Small, Dylan S; Leonard, Charles E et al. (2017) The Trend-in-trend Research Design for Causal Inference. Epidemiology 28:529-536
Leonard, Charles E; Brensinger, Colleen M; Bilker, Warren B et al. (2017) Thromboembolic and neurologic sequelae of discontinuation of an antihyperlipidemic drug during ongoing warfarin therapy. Sci Rep 7:18037
Han, Xu; Chiang, ChienWei; Leonard, Charles E et al. (2017) Biomedical Informatics Approaches to Identifying Drug-Drug Interactions: Application to Insulin Secretagogues. Epidemiology 28:459-468
Leonard, Charles E; Brensinger, Colleen M; Nam, Young Hee et al. (2017) The quality of Medicaid and Medicare data obtained from CMS and its contractors: implications for pharmacoepidemiology. BMC Health Serv Res 17:304
Li, L (2017) Precision Medicine in Pharmacometrics and Systems Pharmacology. CPT Pharmacometrics Syst Pharmacol 6:151-152

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