Does the Strategy of Risk Group Testing for Hepatitis C Hit the Target?

Hepatitis C risk score as a tool to identify individuals with HCV infection: a demonstration and cross-sectional epidemiological study in Egypt

OBJECTIVES

Hepatitis C virus (HCV) infection poses a global health challenge. By the end of 2021, the WHO estimated that less than a quarter of global HCV infections had been diagnosed. There is a need for a public health tool that can facilitate the identification of people with HCV infection and link them to testing and treatment, and that can be customised for each country.

METHODS

We derived and validated a risk score to identify people with HCV in Egypt and demonstrated its utility. Using data from the 2008 and 2014 Egypt Demographic and Health Surveys, two risk scores were constructed through multivariable logistic regression analysis. A range of diagnostic metrics was then calculated to evaluate the performance of these scores.

RESULTS

The 2008 and 2014 risk scores exhibited similar dependencies on sex, age and type of place of residence. Both risk scores demonstrated high and similar areas under the curve of 0.77 (95% CI: 0.76 to 0.78) and 0.78 (95% CI: 0.77 to 0.80), respectively. For the 2008 risk score, sensitivity was 73.7% (95% CI: 71.5% to 75.9%), specificity was 68.5% (95% CI: 67.5% to 69.4%), positive predictive value (PPV) was 27.8% (95% CI: 26.4% to 29.2%) and negative predictive value (NPV) was 94.1% (95% CI: 93.5% to 94.6%). For the 2014 risk score, sensitivity was 64.0% (95% CI: 61.5% to 66.6%), specificity was 78.2% (95% CI: 77.5% to 78.9%), PPV was 22.2% (95% CI: 20.9% to 23.5%) and NPV was 95.7% (95% CI: 95.4% to 96.1%). Each score was validated by applying it to a different survey database than the one used to derive it.

CONCLUSIONS

Implementation of HCV risk scores is an effective strategy to identify carriers of HCV infection and to link them to testing and treatment at low cost to national programmes.

Bioinformatics Analysis of Quantitative PCR and Reverse Transcription PCR in Detecting HCV RNA

Objective:

This research aimed to make comparisons of sensitivity and specificity between Quantitative real Time Polymerase Chain Reaction (Q-PCR) and Reverse Transcription PCR (RT-PCR) in detecting the ribonucleic acid (RNA) expression levels of Hepatitis C Virus (HCV).

Methods:

121 patients suffering from hepatitis C and 98 healthy participants with normal liver functions were identified. The venous blood collections were carried out, were subjected to detect the expression levels of HCV RNA via Q-PCR and RT-PCR. And then, the data obtained from these above two detection methods were compared, including the sensitivity and specificity.

Results:

In terms of Q-PCR, the positive rate of HCV RNA was 72.16%, which was significantly higher when compared with 55.26% of RT-PCR. After statistical analysis, the difference between them was statistically significant (P＜0.05). Among the healthy participants, 4 cases were false positive by means of RT-PCR, there was the possibility of missed diagnosis when the samples were evaluated by Q-PCR.

Conclusion:

: The Q-PCR detection technology performed well in testing HCV, with pretty high sensitivity and specificity. Nevertheless, the false negative results obtained from Q-PCR could not be avoided. In clinical practice, these above two detection methods should be referred to, in order to avoid missed diagnosis.