An Easy-to-Implement Risk Score for Targeted Hepatitis C Virus Testing in the General Population

Comparison of effectiveness and cost of different HCV testing strategies in high-risk populations in China

High-risk populations are the predominant populations affected by hepatitis C virus (HCV) infection, and there is an urgent need for efficient and cost-effective HCV testing strategies for high-risk populations to identify potential undiagnosed HCV-infected individuals. This study compared several commonly used testing strategies and conducted effectiveness and cost analysis to select the appropriate testing strategy for diagnosing HCV infection in high-risk populations. Among the 2093 samples from high-risk populations in this study, 1716 were HCV negative, 237 were current HCV infection, 137 were past HCV infection, and three were acute early HCV infection. It was found that out of 237 patients with HCV current infection, Strategy A could detect 225 cases, with a missed detection rate of 5.06%, and the total cost was 33 299 RMB. In addition, Strategy B could detect 237 cases of current HCV infection, and the HCV missed detection rate was 0.00%, and the total cost was 147 221 RMB. While 137 cases of past HCV infection could be distinguished by strategy C, but 14 cases with current HCV infection were missed, with an HCV-positive missed detection rate of 5.91%, and the total cost for Strategy C was 43 059 RMB. In conclusion, in high-risk populations, the HCV positivity rate is typically higher. If feasible, the preferred approach is to directly conduct HCV RNA testing, which effectively minimizes the risk of missing cases. However, in situations with limited resources, it is advisable to initially choose a highly sensitive method for anti-HCV screening, followed by HCV RNA testing on reactive samples.

Development and Validation of a Risk Prediction Tool to Identify People at Greater Risk of Having Hepatitis C among Drug Users

BACKGROUND

People who use drugs (PWUD) are among those with the highest risk for hepatitis C virus (HCV) infection. Highly effective direct-acting antiviral agents offer an opportunity to eliminate HCV. A simple tool for the prediction of HCV infection risk in PWUD is urgently needed. This study aimed to develop and validate a risk prediction tool to identify people at greater risk of having hepatitis C among PWUD that is applicable in resource-limited settings.

METHODS

We extracted data from national HIV/AIDS sentinel surveillance in PWUD (Zhejiang Province, 2016-2021) and developed and validated a risk score to improve HCV testing in PWUD. This risk score consists of seven risk factors identified using multivariable logistic regression modeling (2016-2020, exploratory group). We validated this score using surveillance data for 2021 (validation group). The accuracy of the model was determined using C-statistics.

RESULTS

We identified seven risk factors, including sex, age, marital status, educational attainment, and the use of heroin, morphine, and methamphetamine. In the exploratory group, the positive rates of detecting the HCV antibody in the low-risk (0-9 points), intermediate-risk (10-16 points), and high-risk (≥17 points) groups were 6.72%, 17.24%, and 38.02%, respectively (P_trend < 0.001). In the validation group, the positive rates in the low-, medium-, and high-risk groups were 4.46%, 12.23%, and 38.99%, respectively (P_trend < 0.001).

CONCLUSIONS

We developed and validated a drug-specific risk prediction tool for identifying PWUD at increased risk of HCV infection. This tool can complement and integrate the screening strategy for the purpose of early diagnosis and treatment.