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.