Background: Although hepatitis C virus (HCV) has an estimated national prevalence of 1.8%, testing rates are lower than those recommended by guidelines, particularly in primary care. A critical step is the ability to identify patients at increased risk who should be screened. We sought to prospectively derive and validate a clinical predication tool to assist primary care providers in identifying patients who should be tested for HCV antibodies.
Methods: A total of 1000 randomly selected patients attending an inner-city primary care clinic filled out a 27-item questionnaire assessing 5 HCV risk factor domains: work, medical, exposure, personal care, and social history. Afterward, the patients underwent HCV antibody testing. Multivariable logistic regression analysis was performed to identify risk factors associated with HCV antibodies.
Results: There was an 8.3% (95% confidence interval, 6.7%-10.2%) prevalence of HCV antibodies. The patients who were HCV antibody positive were more likely to be male, older, and insured by Medicaid (P < or = .02). Those who had risk factors within the medical, exposure, and social history domains were more likely to be HCV antibody positive. The area under the receiver operating characteristic curve for the screening tool based on these 3 domains was 0.77. With an increasing number of positive domains, there was a higher likelihood of HCV antibody positivity. Only 2% of patients with 0 risk factors had HCV antibodies.
Conclusions: A prediction tool can be used to accurately identify patients at high risk of HCV who may benefit from serologic screening. Future studies should assess whether wider use of this tool may lead to improved outcomes.