High-risk human papillomavirus genotype distribution and attribution to cervical cancer and precancerous lesions in a rural Chinese population / 부인종양

ABSTRACT

OBJECTIVE: To explore the genotype distribution of high-risk human papillomavirus (HR-HPV) and its attribution to different grades of cervical lesions in rural China, which will contribute to type-specific HPV screening tests and the development of new polyvalent HPV vaccines among the Chinese population. METHODS: One thousand two hundred ninety-two subjects were followed based on the Shanxi Province Cervical Cancer Screening Study I (SPOCCS-I), and screened by HPV DNA testing (hybrid capture® 2 [HC2]), liquid-based cytology (LBC), and if necessary, directed or random colposcopy-guided quadrant biopsies. HPV genotyping with linear inverse probe hybridization (SPF10-PCR-LiPA) was performed in HC2 positive specimens. Attribution of specific HR-HPV type to different grades of cervical lesions was estimated using a fractional contribution approach. RESULTS: After excluding incomplete data, 1,274 women were included in the final statistical analysis. Fifteen point two percent (194/1,274) of women were HR-HPV positive for any of 13 HR-HPV types (HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, and 68) and the most common HR-HPV types were HPV16 (19.1%) and HPV52 (16.5%). The genotypes most frequently detected in HR-HPV-positive cervical intraepithelial neoplasia grade 1 (CIN1) were HPV52 (24.1%), HPV31 (20.7%), HPV16 (13.8%), HPV33 (13.8%), HPV39 (10.3%), and HPV56 (10.3%); in HR-HPV-positive cervical intraepithelial neoplasia grade 2 or worse (CIN2+) HPV16 (53.1%), HPV58 (15.6%), HPV33 (12.5%), HPV51 (9.4%), and HPV52 (6.3%). HPV52, 31, 16, 33, 39, and 56 together contributed to 89.7% of HR-HPV-positive CIN1, and HPV16, 33, 58, 51, and 52 together contributed to 87.5% of CIN2+. CONCLUSION: In summary, we found substantial differences in prevalence and attribution of CINs between different oncogenic HPV types in a rural Chinese population, especially for HPV16, 31, 33, 52, and 58. These differences may be relevant for both clinical management and the design of preventive strategies.