Statistics
Demographic, and sexual behavior of participants were summarized as means or proportions. Our primary aim was to evaluate the clinical diagnostic performance of the S5 methylation classifier. The standardized equation for S5 scoring was used to calculate the average methylation values of the five target regions:
S5 = EPB41L3*(30.9) + HPV16L1.3*(13.7) + HPV16L2*(4.3) + HPV18L2*(8.4) + HPV31L1*(22.4) + HPV33L2*(20.3)
We created boxplots to illustrate the distribution of the S5 classifier histopathological diagnosis of the lesions (No-lesion, LSIL, HSIL and cervical cancer (CC)). We used the Mann-Whitney U test for comparing S5 scoring differences between different categories and the Cuzick test for trend to determine if methylation increase significantly as a function of great histopathology result.
To maximize the sensitivity and specificity of the S5 score after the triage test (HPV16/18 and cytology), we created receiver operating characteristic (ROC) curve to estimate areas under the curve (AUC), and we validated an effective S5 cutoff value from several S5cutoff values to discriminate ≥ (His)HSIL+ cases from < (His)HSIL+ cases via the post-hoc analysis. Another analysis was done using the establishment 0.8 cutoff validated in UK screening population30,32for detection of ≥ (His)HSIL+.
We compared the sensitivity and specificity as the disease endpoint of ≥HSIL+, and compared with the other tests such as cytology and HPV detection, which are the currently recommended triage tests for women in the Chinese screening guidelines.
A ROC curve was also computed for compare the performance of S5 methylation and EPB41L3.
All p values were estimated as two sided, with a confidence interval of 95%. Statistical analyses were performed by SPSS statistical software version 25.0 (IBM, NY) and Excel. p < 0.05 was considered significant statistically.