Noninvasive self-sampling is a convenient option that may be highly accepted by women for home-based detection, which could increase the screening rate for cervical cancer (CC) and reduce its incidence and mortality.


To compare the distribution of high-risk human papillomavirus (hr-HPV) between the vulva and cervix and to explore the clinical value of vulvar HPV detection in CC screening.


The study was nested within a clinical trial on recombinant HPV 9–valent vaccine for women ages 20 to 45 years. Women with paired vulvar and cervical specimens were included and received cytology and HPV detection. The consistency of HPV detection between vulvar and cervical specimens was evaluated using Cohen κ statistics. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were used to evaluate the diagnostic accuracy of primary CC screening. The primary end points were cervical intraepithelial neoplasia (CIN) grade 2/3 or worse (CIN2+/3+).


A total of 7999 women were enrolled, and 83/33 cases were diagnosed as CIN2+/CIN3+. The HPV-positive rate in vulvar specimens (1785 of 7999; 22.32%) was higher than that in cervical specimens (1390 of 7999; 17.38%), and there were no significant differences in the distribution of hr-HPV genotypes between the vulva and cervix in patients with CIN2+/CIN3+. Vulva-based HPV primary screening showed sensitivity, specificity, PPV, and NPV comparable to those for cervix-based HPV primary CC screening in the detection of CIN3+.


The distribution of vulvar and cervical HPV was similar in patients with CIN2+/CIN3+. Vulva-based HPV primary CC screening had acceptable diagnostic efficacy and might be used as a modality for primary CC screening.

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Author notes

This study was funded by the Key Research and Development Program of Zhejiang Province, China (grant No. 2023C03169).

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Competing Interests

The authors have no relevant financial interest in the products or companies described in this article.

Li and Xie contributed equally to this manuscript.

Supplementary data