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Validation of a hepatitis C screening tool in primary care
Thomas McGinn1, Nicola O'Connor-Moore, David Alfandre
1Division of General Internal Medicine, Mount Sinai School of Medicine, 1470 Madison Ave, Box 1087, New York, NY 10029, USA. thomas.mcginn@mountsinai.org.
Archives of Internal Medicine
|October 15, 2008
Summary
A new clinical prediction tool can identify patients at high risk for hepatitis C virus (HCV) infection. This tool aids primary care providers in screening more effectively, improving detection rates for this common virus.
Area of Science:
- Hepatology and Infectious Diseases
- Clinical Prediction Modeling
- Public Health Screening
Background:
- Hepatitis C virus (HCV) affects 1.8% of the national population, yet screening rates remain suboptimal, especially in primary care settings.
- Identifying at-risk individuals is crucial for effective HCV screening and management.
- Current guidelines emphasize the need for improved methods to identify patients who require HCV antibody testing.
Purpose of the Study:
- To prospectively develop and validate a clinical prediction tool for identifying patients at increased risk of HCV infection.
- To assist primary care providers in making informed decisions about HCV antibody screening.
- To enhance the accuracy of HCV risk assessment in diverse patient populations.
Main Methods:
- A cohort of 1000 primary care patients completed a 27-item questionnaire covering work, medical, exposure, personal care, and social history.
- HCV antibody testing was performed on all participating patients.
- Multivariable logistic regression analysis identified significant risk factors associated with HCV antibodies.
Main Results:
- The prevalence of HCV antibodies in the study population was 8.3%.
- HCV antibody positivity was associated with male gender, older age, Medicaid insurance, and risk factors in medical, exposure, and social history domains.
- The derived screening tool, utilizing these three domains, achieved an area under the receiver operating characteristic curve of 0.77, with higher risk domain scores correlating with increased likelihood of HCV positivity.
Conclusions:
- A validated prediction tool can accurately identify patients at high risk for HCV, facilitating targeted serologic screening.
- Wider implementation of this tool in primary care settings has the potential to improve patient outcomes through earlier detection and treatment.
- Further research is warranted to evaluate the impact of this tool on clinical outcomes and HCV elimination efforts.
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