Acceptability Limits for Inter-instrument Variability in Viral Serological Tests on Two Enhanced Chemiluminescence...

Background Reliable viral serological testing is essential for accurate diagnosis and public health management of HIV, hepatitis B, and hepatitis C. Chemiluminescent immunoassay platforms, particularly enhanced chemiluminescence (eCLIA) systems, are widely used; however, inter-instrument variability remains a challenge in laboratories operating multiple analyzers. Defining acceptable limits of variation is crucial for ensuring diagnostic accuracy, laboratory quality assurance, and clinical decision-making. Objectives To evaluate the correlation and agreement between two eCLIA platforms (Vitros ECi and Vitros 3600) in detecting HIV, HBsAg, and HCV, and to establish data-driven acceptability limits for inter-instrument variability. Methods An analytical cross‑sectional study was conducted in a diagnostic laboratory of a medical college in Bengaluru, India (January 2019-December 2024). Each day, one patient serum sample was selected at random and tested simultaneously on both eCLIA analyzers. Hemolyzed, lipemic, or insufficient samples were excluded. This random sampling approach, with one sample per day, was considered appropriate for inter‑instrument comparison, as most accreditation bodies recommend testing 1-2 samples only every three months. Results were expressed as S/CO values. Descriptive statistics, Pearson correlation, and Bland-Altman analyses were performed. Jarque-Bera testing assessed normality. Bootstrapping (1000 iterations) was conducted to evaluate the stability of out-of-limit findings and propose acceptable error thresholds. Results Of 830 samples processed, the final dataset (after excluding incomplete or zero values) showed high variability across parameters (CV > 50%; HCV > 100%). Pearson correlation demonstrated strong linear relationships for HCV (r = 0.85, R² = 0.72) and HBsAg (r = 0.85, R² = 0.73), but only moderate correlation for HIV (r = 0.64, R² = 0.41). Jarque-Bera statistics (p<0.0001) indicated non-normal distribution, supporting the use of Bland-Altman analysis. Bland-Altman plots revealed approximately 95% agreement for all three markers, with similar proportions of out-of-limit values despite differing correlation strengths. Bootstrapping analysis showed ≤5% error across simulated datasets, suggesting a 5% inter-instrument variability as a reasonable acceptability limit. Conclusion Correlation alone is insufficient to assess agreement between CLIA instruments, particularly for non-normally distributed diagnostic data. Bland-Altman analysis combined with bootstrapping provides a more robust approach for evaluating inter-instrument variability. Based on empirical error estimates, an acceptability threshold of ≤5% variability is proposed for laboratories using dual eCLIA platforms for viral serology. These findings support evidence-based quality assurance and instrument interchangeability in clinical diagnostics.