Optimizing Hepatitis B Surface Antigen Confirmation Thresholds by Chemiluminescence Microparticle Immunoassay on the Architect i1000SR
Methodological focus
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Abstract
Objective: To establish an optimal confirmation zone for initial hepatitis B surface antigen (HBsAg) results obtained via Chemiluminescence Microparticle Immunoassay (CMIA) on the Architect i1000SR platform, aiming to enhance diagnostic accuracy and reduce unnecessary confirmatory testing and associated costs.
Methods: A retrospective-prospective mixed study was conducted on 231 serum samples analyzed at the Centre Pasteur of Cameroon between April 2018 and December 2019. Initial results obtained using the Architect HBsAg Qualitative II assay were confirmed through the Architect HBsAg Confirmatory test. Samples encompassed a broad range of signal-to-cutoff (S/CO) ratios (0.9 – >500). Confirmation rates were analyzed across intervals. Fisher’s exact test with Bonferroni correction was applied to assess statistical differences.
Results: Of the 231 samples meeting inclusion criteria, 172 (74.5%; 95% CI: 68.3–79.9) were confirmed reactive, representing 74.8% of initially reactive samples (172/230). Confirmation rates were lowest in the 1.00–1.10 interval (9.1%) and the 1.10–10.00 interval (48.8%), both significantly lower than for samples above 200 S/CO (p < 0.0001). All samples above 200 S/CO were confirmed positive. The highest unconfirmed S/CO value observed was 170.01, supporting the effectiveness of the defined confirmation range (S/CO 0.90–200).
Conclusion: The optimal confirmation zone was defined as 0.90–200 S/CO. Confirmatory testing below this threshold is essential, while values >200 can be considered definitively positive. Implementing this strategy can reduce costs, streamline workflow and turnaround times especially in resource-limited settings without compromising accuracy.
Keywords: Hepatitis B surface antigen (HBsAg), Chemiluminescence Microparticule Immunoassay Method (CMIA), confirmation zone, signal-to-cutoff ratio (S/CO), Architect i1000SR.
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Copyright (c) 2025 Jeanne Manga-Mbeti, Elodie Edinga, Laure Ngono, Ghislain Landry Lonmi Ngassam, Laetitia Sado Mbakam, Jean Philippe Atangana Omgba, Settings Fatimatou Ndjoko , Annie Epote, Grace Dina , Suzanne Belinga
This work is licensed under a Creative Commons Attribution 4.0 International License.
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