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Handling Time-dependent Variables: Antibiotics and Antibiotic Resistance. Clin Infect Dis 2016 06 15;62(12):1558-1563



Pubmed ID




Scopus ID

2-s2.0-84973478477   21 Citations


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


L Silvia Munoz-Price MD, PhD Professor in the Medicine department at Medical College of Wisconsin
Sergey S. Tarima PhD Associate Professor in the Institute for Health and Equity department at Medical College of Wisconsin

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

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