Background: We sought to identify the absolute risk of specific HPV genotype for cervical intraepithelial neoplasia grade 2/3 or worse (CIN2+/3+) and to develop a risk-based management strategy in an HPV-positive population. Methods: HPV genotyping was performed based on a 3-year cervical cancer screening cohort. The study endpoints were histologic CIN2+/3+. The prevalence of specific HPV genotype was calculated by minimum, any type, and hierarchical attribution estimate. The absolute CIN2+/3+ risks of specific HPV genotype were estimated and risk-based management strategy was established according to the American Society for Colposcopy and Cervical Pathology guideline. The efficacy of conventional and risk-based management strategies for non-16/18 HPVs were further evaluated. Results: Eligible data were available for 8,370 women with a median age of 48 years (interquartile range, 42–53 years). At baseline, there were 1,062 women with HPV-positive disease, including 424 with multiple and 639 with single infections. CIN2+/3+ cases represented 113/74, 23/8, 20/7, and 52/31 patients at baseline and first-, second-, and third-year visits, respectively. Women with multiple HPV infections at baseline were more prone to persistent infection than those with single infection (P<.0001). HPV16 and HPV52 were the top 2 ranking among baseline and 3-year cumulative CIN2+/3+ cases. Based on the absolute risk of specific HPV genotype combined with cytology for CIN2+/3+, all non-16/18 HPVs were divided into 4 risk-stratified groups. Compared with conventional strategy, the risk-based strategy had higher specificity (P=.0000) and positive predictive value (P=.0322) to detect CIN3+ and needed fewer colposcopies for each CIN3+ case. Conclusions: Based on our study findings, we propose a new extended HPV genotyping protocol, which would provide a better strategy for achieving precise risk-based management of HPV-positive populations.
Submitted December 14, 2021; final revision received April 25, 2022; accepted for publication May 10, 2022.
Disclosures: The authors have disclosed that they have not received any financial consideration from any person or organization to support the preparation, analysis, results, or discussion of this article.
Author contributions: Conceptualization: Li, Wang. Data curation: Li, Rao, Wei. Formal analysis: Li, Rao. Software: Rao, Wei. Methodology: Rao. Supervision: Lu, Xie, Wang. Validation: All authors. Writing—original draft: Li, Rao, Wei. Writing—review and editing: Li, Lu, Xie, Wang.
Funding: This study was supported by National Key R&D Program of China (grant number, 2021YFC2701204) and the Key Research and Development Program of Zhejiang province, China (grant number, 2020C03025).