Handling Time-dependent Variables: Antibiotics and Antibiotic Resistance
Author(s) -
L. Silvia MunozPrice,
Jos F. Frencken,
Sergey Tarima,
Marc J. M. Bonten
Publication year - 2016
Publication title -
clinical infectious diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.44
H-Index - 336
eISSN - 1537-6591
pISSN - 1058-4838
DOI - 10.1093/cid/ciw191
Subject(s) - antibiotics , medicine , guideline , observational study , antibiotic resistance , hazard ratio , hazard , intensive care medicine , confidence interval , microbiology and biotechnology , biology , pathology , ecology
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.
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