Analysis Group Researchers Develop a Novel Framework to Help Clinicians Predict the Likelihood of Antibiotic-Resistant Bacteria in Patients with Uncomplicated Urinary Tract Infections

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May 22, 2024, 09:00 ET

BOSTON, May 22, 2024 /PRNewswire/ -- Researchers from Analysis Group, a global leader in health economics and outcomes research (HEOR), have coauthored a study detailing a novel framework that clinicians can use to inform antibiotic prescribing for patients with E. coli-caused uncomplicated urinary tract infections (uUTIs), the most common outpatient infection in the US. The study, published in the journal Clinical Infectious Diseases, is the first to use predictive modeling to categorize patient risk profiles for antimicrobial resistance (AMR) as low, moderate, and high risk across four commonly prescribed antibiotic classes for uUTI.

Despite guideline recommendations from the Infectious Diseases Society of America (IDSA) on appropriate first-line antibiotic agents for the treatment of uUTI, 86% of patients are prescribed antibiotic agents that are not considered first-line therapies. These inappropriate prescribing practices contribute to the growth of AMR, treatment failure, persistent uUTI symptoms, adverse patient health outcomes, and increased health care costs. This study was conducted to help provide clinicians with more reliable and efficient approaches for supporting patients with uUTI.

Using electronic health record data from 87,487 patients with confirmed E. coli-related uUTI in the US, study investigators developed and validated predictive models to estimate probabilities of E. coli AMR to four commonly prescribed classes of antibiotics for uUTIs (nitrofurantoin, trimethoprim-sulfamethoxazole, β-lactams, and fluoroquinolones). The models identified key predictors of AMR and were used to create a novel risk categorization framework for contextualizing patients' risk for AMR. The predictive models were found to outperform those in existing literature, and the risk categorization framework provided strong separation of risk between patients with truly resistant and truly not resistant E-coli isolates.

The study, "Development of Predictive Models to Inform a Novel Risk Categorization Framework for Antibiotic Resistance in E. coli-Causing Uncomplicated Urinary Tract Infection," was published in April by Clinical Infectious Diseases.

Investigators included Analysis Group Managing Principals Lisa Pinheiro and Jimmy Royer, Managers Kalé Kponee-Shovein and Chi Gao, Associate Malena Mahendran, and Senior Research Professional Fernando Kuwer; Ryan K. Shields of the University of Pittsburgh; Richard Colgan of the University of Maryland School of Medicine; and Ashish V. Joshi, Fanny S. Mitrani-Gold, Patrick Schwab, Diogo Ferrinho, Madison T. Preib, and Jennifer Han of GSK. Funding for this study was provided by GSK.

To learn more about Analysis Group's HEOR capabilities, visit www.analysisgroup.com/healthoutcomes

About Analysis Group's HEOR, Epidemiology & Market Access Practice
Founded in 1981, Analysis Group is one of the largest international economics consulting firms, with more than 1,200 professionals across 14 offices. Analysis Group's health care experts apply analytical expertise to health economics and outcomes research (HEOR), clinical research, market access and commercial strategy, and health care policy engagements, as well as drug safety-related engagements in epidemiology. Analysis Group's internal experts, together with our network of affiliated experts from academia, industry, and government, provide our clients with exceptional breadth and depth of expertise and end-to-end consulting services globally.

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SOURCE Analysis Group