Revisiting Anti-HCV Seropositivity: Signal Intensity, Diagnostic Uncertainty, and the Limitations of Fixed Cut-Offs

Background/Objectives: A reactive anti-HCV antibody result requires confirmatory testing because seropositivity does not necessarily indicate active hepatitis C virus (HCV) infection. Although anti-HCV signal intensity may provide clinically useful information, it remains underutilized, particularly in low-reactivity ranges where diagnostic uncertainty is substantial. This study evaluated the diagnostic performance of anti-HCV signal-to-cutoff (S/Co) values and aimed to define a clinically meaningful uncertainty interval. Methods: In this retrospective study, 565,726 anti-HCV test results were screened, and the analysis was performed within the anti-HCV reactive cohort (≥1.0 S/Co; n = 2950), comprising 1581 patients with true HCV infection and 1369 without infection. Infection status was assigned using a uniform virological reference standard, every case being supported by at least one documented positive HCV-RNA PCR result. Receiver operating characteristic (ROC) analysis was used to assess discrimination, and multivariable logistic regression to model the probability of true infection. Results: Anti-HCV signal intensity discriminated true infection well across the reactive cohort (AUC 0.991), but less within the diagnostic uncertainty interval (1.00-4.99 S/Co; AUC 0.832), where only 5.7% of reactive results represented true infection. A Youden-optimal threshold of 4.65 S/Co provided >95% sensitivity, specificity and positive predictive value in the reactive cohort. The probability of true infection rose steeply with signal level, and each doubling of the S/Co value increased the odds of infection 23-fold. No threshold within the uncertainty interval raised the positive predictive value above 58.2%. Restricting confirmatory testing to values above 2.50 S/Co would avoid 41.7% of confirmatory tests while missing 1.96% of true infections. Conclusions: Anti-HCV signal intensity is strongly associated with the probability of true infection, but a single fixed cut-off is insufficient for clinical interpretation. Graded, signal-based interpretation may improve diagnostic accuracy, clarify low-level reactivity, and reduce unnecessary confirmatory testing.