Statistical Modeling for Quality Assurance of Human Papillomavirus DNA Batch Testing

Our objective was to simulate the distribution of human papillomavirus (HPV) DNA test results from a 96-well microplate assay to identify results that may be consistent with well-to-well contamination, enabling programs to apply specific quality assurance parameters.

For this modeling study, we designed an algorithm that generated the analysis population of 900,000 to simulate the results of 10,000 microplate assays, assuming discrete HPV prevalences of 12%, 13%, 14%, 15%, and 16%. Using binomial draws, the algorithm created a vector of results for each prevalence and reassembled them into 96-well matrices for results distribution analysis of the number of positive cells and number and size of cell clusters (≥2 positive cells horizontally or vertically adjacent) per matrix.

For simulation conditions of 12% and 16% HPV prevalence, 95% of the matrices displayed the following characteristics: 5 to 17 and 8 to 22 total positive cells, 0 to 4 and 0 to 5 positive cell clusters, and largest cluster sizes of up to 5 and up to 6 positive cells, respectively.

Our results suggest that screening programs in regions with an oncogenic HPV prevalence of 12% to 16% can expect 5 to 22 positive results per microplate in approximately 95% of assays and 0 to 5 positive results clusters with no cluster larger than 6 positive results. Results consistently outside of these ranges deviate from what is statistically expected and could be the result of well-to-well contamination. Our results provide guidance that laboratories can use to identify microplates suspicious for well-to-well contamination, enabling improved quality assurance.