How to interpret borderline HCV antibody test results? A comparative study investigating four different anti-HCV assays

Introduction: The introduction of anti-HCV testing has been a milestone in medical history and markedly reduced transfusion-associated hepatitis C. Over the last 20 years, the performance of HCV antibody assays improved strikingly with sensitivities and specificities reaching >98% for most licensed tests. Still, a significant number of samples may yield borderline signal-to-cut-off ratios. Re-testing of samples and application of confirmatory recombinant blot assays or nucleic acid testing is time-consuming and costly. Moreover, false negative results should be avoided in particular in special risk groups such as immunocompromised patients. We here aimed to compare the performance of 4 licensed anti-HCV assays in samples with borderline signal-to-cut-off ratios obtained at a tertiary referral and transplant center.

Methods: Out of 12090 consecutive samples tested for anti-HCV with the Architect Anti-HCV assay (Abbott) over a period of 29 months, 95 plasma samples with a signal-to-cut-off ratio between 0.5 and 2 were selected for this study (46 classified as positive and 49 classified as negative). All samples were re-tested with the Enzygnost Anti-HCV 4.0 (Siemens Diagnostics), the Ortho anti-HCV 3.0 (96) and the Monolisa anti-HCV-Plus version 2 (BioRad) assays. The Inno-Lia Blot assay was applied to samples with discordant results.

Results: Overall, only 52% of the samples gave similar results in all 4 assays. Inter-assay concordance ranged between 58% and 80%. The highest discordance was observed between the Architect Anti-HCV and the Monolisa anti-HCV-Plus version 2 (42%) and the Enzygnost Anti-HCV 4.0 and the Architect Anti-HCV (27%). In contrast, a high level of concordance was found between the Encygnost Anti-HCV 4.0 and Ortho anti-HCV 3.0 (80%). Confirmatory immunoblot tests for discordant samples revealed the largest portion of correct classified samples for the Enzygnost Anti-HCV 4.0 assay (79%) and the smallest for the Architect Anti-HCV assay (26%). The Monolisa anti-HCV-Plus version 2 was best in identifying negative samples (100%), while the Encygnost Anti-HCV 4.0 was the strongest classifying positive samples (92%).

Conclusions: Anti-HCV antibody assays show significant differences in classifying samples with low signal-to-cut-off ratios. Different performances may have cost and management implications, as false-positive results are not infrequent. However, sensitivities were good for all assays if indeterminate results are not considered as negative.