Role of antibiotic resistance in urinary tract infection management: a cost-effectiveness analysis

Abstract

Urinary tract infections and recurrent urinary tract infections pose substantial burdens on patients and healthcare systems. Testing and treatment strategies are increasingly important in the age of antibiotic resistance and stewardship. This study aimed to evaluate the cost effectiveness of urinary tract infection testing and treatment strategies with a focus on antibiotic resistance. We designed a decision tree to model the following 4 strategies for managing urinary tract infections: (1) empirical antibiotics first, followed by culture-directed antibiotics if symptoms persist; (2) urine culture first, followed by culture-directed antibiotics; (3) urine culture at the same time as empirical antibiotics, followed by culture-directed antibiotics, if symptoms persist; and (4) symptomatic treatment first, followed by culture-directed antibiotics, if symptoms persist. To model both patient- and society-level concerns, we built 3 versions of this model with different outcome measures: quality-adjusted life-years, symptom-free days, and antibiotic courses given. Societal cost of antibiotic resistance was modeled for each course of antibiotics given. The probability of urinary tract infection and the level of antibiotic resistance were modeled from 0% to 100%. We also extended the model to account for patients requiring catheterization for urine specimen collection. In our model, the antibiotic resistance rate was based either on the local antibiotic resistance patterns for patients presenting with sporadic urinary tract infections or on rate of resistance from prior urine cultures for patients with recurrent urinary tract infections. With the base case assumption of 20% antibiotic resistance, urine culture at the same time as empirical antibiotics was the most cost-effective strategy and maximized symptom-free days. However, empirical antibiotics was the most cost-effective strategy when antibiotic resistance was below 6%, whereas symptomatic treatment was the most cost-effective strategy when antibiotic resistance was above 80%. To minimize antibiotic use, symptomatic treatment first was always the best strategy followed by urine culture first. Sensitivity analyses with other input parameters did not affect the cost-effectiveness results. When we extended the model to include an office visit for catheterized urine specimens, empirical antibiotics became the most cost-effective option. We developed models for urinary tract infection management strategies that can be interpreted for patients initially presenting with urinary tract infections or those with recurrent urinary tract infections. Our results suggest that, in most cases, urine culture at the same time as empirical antibiotics is the most cost-effective strategy and maximizes symptom-free days. Empirical antibiotics first should only be considered if the expected antibiotic resistance is very low. If antibiotic resistance is expected to be very high, symptomatic treatment is the best strategy and minimizes antibiotic use.