Macrolide Treatment Failure due to Drug-Drug Interactions: Real-World Evidence to Evaluate a Pharmacological Hypothesis

• Main Authors: Brian Cicali (Author), Stephan Schmidt (Author), Markus Zeitlinger (Author), Joshua D. Brown (Author)
• Format: Book
• Published: MDPI AG, 2022-03-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.3390/pharmaceutics14040704; 1999-4923
• Keywords: macrolide antibiotics; treatment failure; drug-drug interactions; pharmacoepidemiology; Pharmacy and materia medica; RS1-441
• Source: Pharmaceutics, Vol 14, Iss 4, p 704 (2022)

Macrolide antibiotics have received criticism concerning their use and risk of treatment failure. Nevertheless, they are an important class of antibiotics and are frequently used in clinical practice for treating a variety of infections. This study sought to utilize pharmacoepidemiology methods and pharmacology principles to estimate the risk of macrolide treatment failure and quantify the influence of their pharmacokinetics on the risk of treatment failure, using clinically reported drug-drug interaction data. Using a large, commercial claims database (2006-2015), inclusion and exclusion criteria were applied to create a cohort of patients who received a macrolide for three common acute infections. Furthermore, an additional analysis examining only bacterial pneumonia events treated with macrolides was conducted. These criteria were formulated specifically to ensure treatment failure would not be expected nor influenced by intrinsic or extrinsic factors. Treatment failure rates were 6% within the common acute infections and 8% in the bacterial pneumonia populations. Regression results indicated that macrolide AUC changes greater than 50% had a significant effect on treatment failure risk, particularly for azithromycin. In fact, our results show that decreased or increased exposure change can influence failure risk, by 35% or 12%, respectively, for the acute infection scenarios. The bacterial pneumonia results were less significant with respect to the regression analyses. This integration of pharmacoepidemiology and clinical pharmacology provides a framework for utilizing real-world data to provide insight into pharmacokinetic mechanisms and support future study development related to antibiotic treatments.