Dataset Information


Co-prescription trends in a large cohort of subjects predict substantial drug-drug interactions.

ABSTRACT: Pharmaceutical prescribing and drug-drug interaction data underlie recommendations on drug combinations that should be avoided or closely monitored by prescribers. Because the number of patients taking multiple medications is increasing, a comprehensive view of prescribing patterns in patients is important to better assess real world pharmaceutical response and evaluate the potential for multi-drug interactions. We obtained self-reported prescription data from NHANES surveys between 1999 and 2010, and confirm the previously reported finding of increasing drug use in the elderly. We studied co-prescription drug trends by focusing on the 2009-2010 survey, which contains prescription data on 690 drugs used by 10,537 subjects. We found that medication profiles were unique for individuals aged 65 years or more, with ?98 unique drug regimens encountered per 100 subjects taking 3 or more medications. When drugs were viewed by therapeutic class, it was found that the most commonly prescribed drugs were not the most commonly co-prescribed drugs for any of the 16 drug classes investigated. We cross-referenced these medication lists with drug interaction data from Drugs.com to evaluate the potential for drug interactions. The number of drug alerts rose proportionally with the number of co-prescribed medications, rising from 3.3 alerts for individuals prescribed 5 medications to 11.7 alerts for individuals prescribed 10 medications. We found 22% of elderly subjects taking both a substrate and inhibitor of a given cytochrome P450 enzyme, and 4% taking multiple inhibitors of the same enzyme simultaneously. By examining drug pairs prescribed in 0.1% of the population or more, we found low agreement between co-prescription rate and co-discussion in the literature. These data show that prescribing trends in treatment could drive a large extent of individual variability in drug response, and that current pairwise approaches to assessing drug-drug interactions may be inadequate for predicting real world outcomes.

SUBMITTER: Sutherland JJ 

PROVIDER: S-EPMC4349653 | BioStudies | 2015-01-01

REPOSITORIES: biostudies

Similar Datasets

2017-01-01 | S-EPMC5636653 | BioStudies
2009-01-01 | S-EPMC2710467 | BioStudies
1000-01-01 | S-EPMC4175643 | BioStudies
2008-01-01 | S-EPMC2359504 | BioStudies
2017-01-01 | S-EPMC5543562 | BioStudies
1000-01-01 | S-EPMC5781016 | BioStudies
2020-01-01 | S-EPMC7060873 | BioStudies
1000-01-01 | S-EPMC4933607 | BioStudies
1000-01-01 | S-EPMC3957400 | BioStudies
2016-01-01 | S-EPMC5130196 | BioStudies