Handling Time-dependent Variables: Antibiotics and Antibiotic Resistance

Luisa Munoz-Price, Jos F. Frencken, Sergey Tarima, Marc Bonten

Research output: Contribution to journalArticle

15 Scopus 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.

Original languageEnglish (US)
Pages (from-to)1558-1563
Number of pages6
JournalClinical Infectious Diseases
Volume62
Issue number12
DOIs
StatePublished - Jun 15 2016
Externally publishedYes

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Keywords

  • antibiotics
  • Cox proportional hazards
  • hazard ratio
  • time-dependent variables

ASJC Scopus subject areas

  • Infectious Diseases
  • Microbiology (medical)

Cite this

Munoz-Price, L., Frencken, J. F., Tarima, S., & Bonten, M. (2016). Handling Time-dependent Variables: Antibiotics and Antibiotic Resistance. Clinical Infectious Diseases, 62(12), 1558-1563. https://doi.org/10.1093/cid/ciw191