Based on multiple regression analysis, the risk factors for cervical cancer included high-risk HPV infection, low education level of the individual and their spouse, young age at first parturition, HLA class II susceptibility alleles, and non-protective HLA alleles. Compared with uninfected women, the risk for cervical cancer in women with high-risk HPV infection increased approximately 7.6-fold (Table 2). High-risk HLA alleles also increased the risk of cervical cancer 2.3-fold in women lacking protective HLA alleles (Table 2). When women and their spouses had a lower level of education, the risk of cervical cancer increased 2.0- and 3.8-fold, respectively (Table 2). Back fitting indicated that the accuracy of predicting cervical cancer was 88.9% in the patient group and 98.4% in the control group (Table 3). The testing database showed that the accuracy of the risk model was 100% in the cancer group and reached 90% in the control group (Table 4), suggesting that this model has good predictive specificity and sensitivity.