Faculty Collaboration Database

Handling Time-dependent Variables: Antibiotics and Antibiotic Resistance. Clin Infect Dis 2016 Jun 15;62(12):1558-1563

Date

03/31/2016

Pubmed ID

27025824

DOI

10.1093/cid/ciw191

Scopus ID

2-s2.0-84973478477 (requires institutional sign-in at Scopus site)   44 Citations

Abstract

Elucidating quantitative associations between antibiotic exposure and antibiotic resistance development is important. In the absence of randomized trials, observational studies are the next best alternative to derive such estimates. Yet, as antibiotics are prescribed for varying time periods, antibiotics constitute time-dependent exposures. Cox regression models are suited for determining such associations. After explaining the concepts of hazard, hazard ratio, and proportional hazards, the effects of treating antibiotic exposure as fixed or time-dependent variables are illustrated and discussed. Wider acceptance of these techniques will improve quantification of the effects of antibiotics on antibiotic resistance development and provide better evidence for guideline recommendations.

Author List

Munoz-Price LS, Frencken JF, Tarima S, Bonten M

MESH terms used to index this publication - Major topics in bold

Anti-Bacterial Agents
Bacterial Infections
Drug Resistance, Microbial
Epidemiologic Research Design
Hospitalization
Hospitals
Humans
Proportional Hazards Models
Time Factors