Objective: To evaluate the clinical performance and utility for risk stratification of DH3 HPV assay in women (≥30 years) with NILM cytology.
Methods: A prospective cohort was established in Central China between November 8 to December 14, 2016 which consisted of 2180 women aging 30-64 years with NILM cytology. At baseline, all women were screened using DH3 HPV assay. HPV 16/18 positive women would be assigned to colposcopy and biopsied if necessary. Then, hr-HPV positive women without CIN2+ lesions would be followed up by cytology every 12 months for two years. In the 3rd year of follow up, all women that were not biopsy proven CIN2+ would be called back and screened by cytology again. In follow-up period, women with ASC-US and above were referred to colposcopy and biopsied if clinically indicated. CIN2+ was the primary endpoint in analysis. The clinical performance and utility for risk stratification of DH3 HPV assay were assessed by SPSS 22.0 and SAS 9.4.
Results: Of 2180 qualified women, the prevalence of hr-HPV was 8.5% (185/2180), 45(2.1%) were HPV 16/18 positive. The clinical performance for HPV16/18 was 91.7% for sensitivity, 98.4% for specificity, respectively against CIN2+ detection at baseline. In four years of study, the corresponding rates of HPV 16/18 were 51.5% and 98.7%, respectively. The cumulative absolute risk for the development of CIN2+ was as high as 37.8% for HPV 16/18 positive women, followed by hr-HPV positive (14.6%), other hr-HPV positive (11.0%) and HPV negative (0.3%) in three years. The relative risk was 125.6 and 3.4 for HPV 16/18 positive group when compared with HPV negative and other hr-HPV positive group, respectively.
Conclusions: DH3 HPV assay demonstrated excellent clinical performance against CIN2+ detection in cervical cancer screening and utility of risk stratification by genotyping to promote scientific management of women with NILM cytology.
Keywords: HPV genotyping; cervical cancer; performance; risk stratification; screening.
Copyright © 2021 Xu, Liu, Luo, Zhao, Jia, Chen, Li, Sun, Liu, Sun and Zhang.