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. 2018 Jul;22(3):219-224.
doi: 10.1097/LGT.0000000000000391.

Statistical Modeling for Quality Assurance of Human Papillomavirus DNA Batch Testing

Emily N Beylerian  1 , Rose C Slavkovsky  1 , Francesca M Holme  1 , Jose A Jeronimo  2
Affiliations

Statistical Modeling for Quality Assurance of Human Papillomavirus DNA Batch Testing

Emily N Beylerian et al. J Low Genit Tract Dis. 2018 Jul.

Abstract

Objectives: 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.

Materials and methods: 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.

Results: 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.

Conclusions: 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.

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Conflict of interest statement

F.H. presented at a meeting of QIAGEN's shipping and logistics department, for which her travel expenses were paid by QIAGEN. J.J. was the co-owner and deputy manager of Onco Prev International, a Peruvian company, from 2012 to March 2017. Onco Prev International offers cervical cancer screening services. E.B. and R.S. have declared they have no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Output for one 12 × 8 matrix representing a hypothetical assay microplate. Clusters of positive results are outlined in red. See Appendix A for details of the algorithm.
FIGURE 2
FIGURE 2
Frequency distributions of the number of positive cells under simulation conditions of 12% and 16% (simulated HPV prevalence). Each simulation results in 10,000 matrices. As the simulated prevalence increases, the distribution range shifts to the right.
FIGURE 3
FIGURE 3
Maximum possibilities for the number of clusters and the size of the largest cluster when the number of positive cells in a matrix is constrained.
See this image and copyright information in PMC

References

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