Monte-Carlo simulation of clinical and economic effectiveness of drugs (on example of antibiotics therapy of acute bronchitis with bronchospasm in children)

Abstract

Introduction: The study objective was to determine which antibiotics are optimal in the treatment of children with complicated acute bronchitis with bronchospasm. For that, a Monte-Carlo simulation was conducted.

Materials and methods: The retrospective study was performed on the antibiotic therapy data from 1604 medical records of inpatients from Nizhny Novgorod (Russian Federation) medical centers admitted with acute bronchitis with bronchospasm. The treatment programs involved cephalosporins, inhibitor-protected penicillins, and macrolides. The starter drug was selected empirically considering the possible etiology and sensitivity of the presumed pathogen to the antimicrobial agents. The input data for the model (Monte-Carlo simulation) were the costs of antibiotic therapy and the probability of the clinical outcome (recovery, or the absence of effect). The probabilities of the clinical outcome were described with β-distribution, while the costs distribution was described using gamma-distribution.

Results and discussion: Most positive clinical outcomes were observed with the use of macrolides, which also provided the lowest CER (cost-efficiency ratio), and are, therefore, optimal pharmacoeconomically. During the trial, the confidence intervals were evaluated for the clinical efficiency (95% CI of the β-distribution curve). The least interval of probable clinical efficiency for the investigated nosology was found for macrolides, which indicates their high clinical efficiency.

Conclusion: Monte-Carlo method visualizes the results of clinical-economical evaluation of any medical technology in one disease compared to another. That is of value for the clinical pharmacologists and health professionals selecting the drugs for healthcare facilities.