An analysis of the standard curve parameters of cytomegalovirus, BK virus and hepatitis B virus quantitative polymerase chain reaction from a clinical virology laboratory in eastern India

2021 
Abstract Purpose Quantitative real-time polymerase chain reactions (qPCRs) are important for accurate detection of nucleic acid target including that for viral load determination. Assessment of the quality of a PCR run is essential for quality control, diagnostics and research. In order to reduce subjectivity qPCR standard curves are accompanied with parametric values for slope, Y- intercept, correlation coefficient (R2) and PCR efficiency. In this study the performance of three qPCR assays-cytomegalovirus, hepatitis B virus and BK virus-with respect to standard curve parameters-slope, Y intercept, R2 and efficiency were examined. Methods Using ideal values (Slope (minus 3.32); Y intercept ​= ​the number of PCR cycles; R2 ​= ​1 and efficiency ​= ​100%) we estimated the intra-assay variability (range) and deviation from ideal parameters (Δ). We also calculated the standard deviation (SD) and coefficient of variation (CV) for each of these parameters. We have evaluated the quality of each of the three viral load assays (CMV, HBV, BKV) using these statistical approach. Results We found lab developed tests (CMV) to have least deviation from ideal Y intercept (limit of detection); however, commercial kit based assays had better linearity (scatter plot correlation between amplification factor and PCR efficiency). Using a scatter plot for the three assays we found the correlation with calculated amplification factor and PCR efficiency was most linear in case of BKV (0.9974), closely followed by the HBV assay (R2 ​= ​0.9968). Although the CMV quantitative standards were least linear (0.868), the CV (coefficient of variation) was also the least in case of the CMV assay. Conclusion The study highlights an objective way of assessing qPCR assay quality and demonstrates a method to compare assays, validate tests and perform quality control.
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