Abstract: Objective To explore the characteristics of vaginal microenvironment changes in elderly patients with cervical cancer, and to construct and validate an early-warning prognostic risk model for elderly patients with cervical cancer. Methods A total of 129 elderly patients with cervical cancer admitted to the Affiliated Obstetrics and Gynecology Hospital of Nanjing Medical University from January 2018 to January 2021 were selected as the training set. An additional 76 elderly patients with cervical cancer admitted to the same hospital from February 2021 to August 2022 were selected as the validation set. Based on therapeutic efficacy evaluation, patients in the training set were divided into a good prognosis group (71 cases) and a poor prognosis group (58 cases). Vaginal secretions and cervical epithelial cells were collected from all patients to analyze the relationships among high-risk human papillomavirus (HR-HPV) infection, vaginal microenvironment changes and prognosis. Multivariate logistic regression was used to identify risk factors for prognosis and a risk predictive model was constructed. The diagnostic performance of the model was evaluated using the receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow (H-L) test. Results The proportion of vaginal pH＞4.5, and the positive rates of Lactobacilli, leukocyte esterase, coagulase, β-glucuronidase and Candida in the HR-HPV infection group were significantly different from those in the non-infection group (P<0.05). The proportion of vaginal pH, ＞4.5, and the positive rates of H₂O₂, leukocyte esterase, sialidase, coagulase, β-glucuronidase, Lactobacilli, Candida, Ureaplasma urealyticum, Chlamydia trachomatis, Gardnerella pneumoniae, and HR-HPV in the poor prognosis group were statistically different compared with those in the good prognosis group (P<0.05 or P<0.01). Vaginal pH>4.5, H₂O₂ positivity, low levels of Lactobacilli, Ureaplasma urealyticum positivity, Chlamydia trachomatis positivity, and HR-HPV positivity were independent risk factors for poor prognosis of elderly patients with cervical cancer. The area under the curve (AUC) for the model predicting prognosis in the training set was 0.855(95%CI:0.782-0.911,P<0.001), with a sensitivity and specificity of 94.83% and 69.01%, respectively. In the validation set, the AUC was 0.864(95%CI:0.792-0.918,P<0.001), with a sensitivity and specificity of 89.66% and 74.65%, respectively. Goodness-of-fit tests indicated that the model fitted well both in the training set (χ²=4.640, P=0.326) and the validation set (χ²=1.827, P=0.767). Conclusions The prognostic risk predictive model for elderly patients with cervical cancer developed based on the vaginal microenvironment demonstrates excellent diagnostic performance. It can serve as a valuable reference for clinical risk stratification and the formulation of targeted intervention strategies for this population.

Key words: cervical cancer, aged, high risk human papillomavirus, vaginal microenvironment, prognosis, predictive model