Development of a predictive model integrating urogenital pathogens and inflammatory markers for human papillomavirus infection.

OBJECTIVE

The objective of the present study was to evaluate the relationship between common urogenital pathogens and human papillomavirus (HPV) infection and to assess the impact of coinfections on vaginal microecology.

METHODS

This hospital-based cross-sectional study included 330 reproductive-aged women. Multiplex polymerase chain reaction (PCR) was applied to detect Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), Ureaplasma urealyticum (UU), Ureaplasma parvum (UP), Mycoplasma hominis (MH), and Mycoplasma genitalium (MG). HPV DNA genotyping was also performed. Clinical characteristics and laboratory results were evaluated using univariate and multivariate logistic regression analyses to identify independent risk factors for HPV infection. A logistic regression model was constructed, and its predictive performance was evaluated by receiver operating characteristic (ROC) curve and calibration analyses.

RESULTS

The overall HPV positivity rate was 46.4%. Univariate analysis revealed associations of HPV infection with CT, NG, UU, UP, MH, elevated leukocyte count, and vaginitis (all P < 0.05). Multivariate analysis revealed that CT infection (aOR=4.115), UU infection (aOR=3.937), elevated leukocyte count (aOR=2.076), and abnormal vaginal discharge (aOR=2.987) were independent predictors for HPV. The prediction model demonstrated good discrimination (AUC≈0.85). In addition, UU, MH, CT, and UP infections were significantly linked to bacterial vaginosis and other vaginal disorders.

CONCLUSIONS

CT and UU infections are strongly associated with HPV infection. Elevated leukocyte count and abnormal vaginal discharge serve as inflammatory indicators that increase prediction accuracy. The proposed model, which integrates pathogen detection and host inflammatory status, performs well in identifying women at high risk of HPV, thereby supporting early screening and cervical cancer prevention.