Risk factors for hrHPV infection with cervical lesions patient in Anhui Province of China from 2021 to 2024: A retrospective study.

Abstract

The association between high-risk HPV (hrHPV) infection and cervical cancer or precancerous lesions has been extensively established, highlighting the importance of preventing hrHPV infection in cervical lesions patients. This study aims to investigate the risk factors associated with hrHPV infection in patients with cervical lesions and develop a nomogram model for predicting the risk of infection. The study involved 154 patients with cervical lesions, all of whom underwent human papillomavirus (HPV) gene typing. Retrospectively analyze the HPV genotyping and assess the prevalence of HPV infection in patients. The patients with cervical lesions were separated into hrHPV (n = 100) and non-hrHPV group (n = 54) based on the results of HPV genotyping tests. Univariate and multivariate regression analyses were employed to identify independent risk factors and develop nomogram model. The performance of the nomogram model were evaluated using ROC analysis. There were a total of 114 patients who tested positive for HPV, comprising 100 hrHPV and 14 low-risk HPV. The most common types of HPV are HPV 16 (65.00%), followed by HPV 52 (3.00%) and HPV 58 (3.00%). Univariate and multivariate analyses showed that age of first sexual intercourse (odds ratio [OR] = 3.312), miscarriage (OR = 7.115), menopause (OR = 2.508), cervicitis (OR = 2.710), number of sexual partners (OR = 5.259) were identified as significant risk factors for hrHPV infection. The nomogram model shows an area under the curve value of 0.861 (95% confidence interval = 0.795-0.927), with a sensitivity of 95.6% and specificity of 92.3%. These findings indicate the significant practical value of the clinical risk nomogram model. Age of first sexual intercourse, miscarriage, menopause, cervicitis, and number of sexual partners were identified as risk factors for hrHPV infection in patients with cervical lesions. This nomogram model holds significant clinical value.