The role of a two-assay serological testing strategy for anti-HCV screening in low-prevalence populations

Laboratory Biochemical and Hematological Parameters: Early Predictive Biomarkers for Diagnosing Hepatitis C Virus Infection

BACKGROUND

Hepatitis C virus (HCV) infection is a worldwide concern, causing liver damage and necessitating early detection to prevent its spread. Studies indicate that evaluating changes in biochemical and hematological parameters, which serve as suitable predictors of inflammation, can be a reasonable method for diagnosing hepatitis C infection.

METHODS

This study analyzed 100 samples from high-risk patients positively identified via quantitative real-time PCR (qPCR). Anti-HCV titers, biochemical and inflammatory tests, and complete blood cell counts (CBCs) were performed for these individuals. Additionally, 100 HCV-negative individuals with normal laboratory results were selected as the control group. Receiver operating characteristic (ROC) curves were plotted to determine the cutoff values of the laboratory parameters.

RESULTS

According to the findings, the age, average white blood cell (WBC) count, platelet-to-lymphocyte ratio (PLR), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), lactate dehydrogenase (LDH), total bilirubin (TBIL), direct bilirubin (DBIL), alkaline phosphatase (ALP), serum glutamic-pyruvic transaminase (SGPT), and ferritin levels were significantly higher in HCV patients. On the other hand, red blood cell (RBC) counts, neutrophils, lymphocytes, hemoglobin-to-platelet ratio (HPR), and iron (Fe) levels were significantly lower in the case group compared to those in the control group (p < 0.05). Furthermore, the ROC curve analysis revealed that lymphocyte count, neutrophil count, and PLR were very strong predictors for hepatitis C infection (p < 0.0001, AUC = 1).

CONCLUSION

The study highlights significant biochemical and hematological differences between HCV patients and healthy subjects. These biomarkers are crucial for early diagnosis, potentially preventing liver damage and reducing HCV transmission.

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.

High false discovery rate of the Architect anti-HCV screening test in blood donors in Uganda and evaluation of an algorithm for confirmatory testing

BACKGROUND AND OBJECTIVES

Adequate supplies of donor blood remain a major challenge in sub-Saharan Africa. This is exacerbated by a lack of confirmatory testing for transfusion-transmitted infections by blood transfusion services (BTS), leading to significant blood disposal owing to putatively high seroprevalence rates amongst Ugandan blood donors. We aimed to ascertain the false discovery rate of the Architect anti-hepatitis C virus (HCV) screening assay and categorize screen-reactive samples into three groups: presumed false positive, active and past infection, and develop an algorithm for confirmatory testing.

MATERIALS AND METHODS

A total of 470 screen-reactive HCV blood donations were retested using the Architect anti-HCV assay, an alternative antibody test (SD Biosensor) and a core antigen (cAg) test. signal-to cut-off (S/CO) ratios and pre-analytical factors (centrifugation speed, haemolysis check, time between collection and testing) were recorded. Based on the S/CO ratio evaluation, we propose a testing algorithm to guide supplemental tests.

RESULTS

The false discovery rate of the Architect anti-HCV assay was 0.84 as 395/470 (84%) screen-reactive samples had no evidence of HCV infection (SD Biosensor and cAg negative) (presumed false positive), 38/470 (8.1%) were antigenaemic, and 32/470 (6.8%) had evidence of past infection. The median S/CO ratios of the presumed false-positive and active infection samples were 1.8 and 17.3, respectively. The positive predictive value of HCV positivity in samples with ratios above 12 was 91.8%. On retesting, 104/470 (22.1%) samples became negative.

CONCLUSION

The Architect anti-HCV assay has a very high false discovery rate in Ugandan BTSs, leading to excessive blood disposal. Pre-analytical factors likely contribute to this. An introduction of confirmatory testing using an algorithm based on S/CO ratio evaluation could limit unnecessary blood wastage and donor deferral.