Handling Time-dependent Variables: Antibiotics and Antibiotic Resistance

Clin Infect Dis. 2016 Jun 15;62(12):1558-1563. doi: 10.1093/cid/ciw191. Epub 2016 Mar 29.


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.

Keywords: Cox proportional hazards; antibiotics; hazard ratio; time-dependent variables.

Publication types

  • Review

MeSH terms

  • Anti-Bacterial Agents / therapeutic use*
  • Bacterial Infections / drug therapy
  • Bacterial Infections / epidemiology
  • Drug Resistance, Microbial*
  • Epidemiologic Research Design*
  • Hospitalization
  • Hospitals
  • Humans
  • Proportional Hazards Models
  • Time Factors


  • Anti-Bacterial Agents