Contrasting methods of measurement of antibiotic exposure in clinical research: a real-world application predicting hospital-associated Clostridioides difficile infection

The goal of this article is to summarize common methods of antibiotic measurement used in clinical research and demonstrate analytic methods for selection of exposure variables. Variable selection was demonstrated using three methods for modeling exposure, using data from a case-control study on Clostridioides difficile infection in hospitalized patients: 1) factor analysis of mixed data, 2) multiple logistic regression models, and 3) Least Absolute Shrinkage and Selection Operator (LASSO) regression. The factor analysis identified 9 variables contributing the most variation in the dataset: any antibiotic treatment; number of classes; number of treatments; dose; and classes monobactam, 𝛽-lactam 𝛽-lactamase inhibitors, rifamycin, carbapenem, and cephalosporin. The regression models resulting in the best model fit used predictors any antibiotic exposure and proportion of hospitalization on antibiotics. The LASSO model selected 22 variables for inclusion in the predictive model, exposure variables including: any antibiotic treatment; classes 𝛽-lactam 𝛽-lactamase inhibitors, carbapenem, cephalosporin, fluoroquinolone, monobactam, rifamycin, sulfonamides, and miscellaneous; and proportion of hospitalization on antibiotics. Investigators studying antibiotic exposure should consider multiple aspects of treatment informed by their research question and the theory on how antibiotics may impact the distribution of the outcome in their target population. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Institutional review board approval (no. 1403002707) for this project was granted by Drexel University Human Research Protections Office. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data not available - participant consent.