ArticleHealth science reports2026
Comparative Evaluation of CLIA and ELISA Serological Assays for HSV-1 IgG With Western Blot Confirmation in a Clinical Cohort: A Cross-Sectional Study.
Article in Health science reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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23 authors.
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Abstract
Background and Aims: Herpes simplex virus type 1 (HSV-1) is highly prevalent worldwide, making accurate serological testing essential for both clinical diagnosis and epidemiological surveillance. Automated chemiluminescent immunoassays (CLIAs) offer operational advantages over enzyme-linked immunosorbent assays (ELISAs); however, their diagnostic performance relative to Western blot (WB) confirmation in high-prevalence settings remains insufficiently characterized. The comparative diagnostic accuracy of CLIA- and ELISA-based assays for HSV-1 IgG detection, when benchmarked against a WB reference standard in endemic populations, remains unclear. This study aimed to evaluate HSV-1 IgG seroprevalence and diagnostic performance of one CLIA and two ELISA platforms using Western blot as the reference method. Methods: Four hundred archived serum samples from adult male craft and manual workers in Qatar were tested using the Mindray CL-900i CLIA, HerpeSelect ELISA, NovaLisa ELISA, and Euroimmun Western blot. Seroprevalence, diagnostic accuracy, and interassay agreement were assessed using WB as the reference standard, with equivocal and indeterminate results excluded from analysis. Results: HSV-1 IgG seroprevalence estimates were comparable across assays: HerpeSelect 72.5% (290/400), Mindray 70.3% (281/400), NovaLisa 66.3% (265/400), and Western blot 57.8% (231/400), with no statistically significant differences (all Conclusion: CLIA- and ELISA-based assays produced comparable HSV-1 seroprevalence estimates in this high-prevalence population; however, diagnostic accuracy varied across platforms. The CLIA platform demonstrated the strongest agreement with Western blot, supporting its use in high-throughput settings, while confirmatory testing remains important to minimize misclassification.
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