RESUMO
Objective:To explore the related factors of postoperative adjuvant therapy for cervical cancer stagedⅠB1-ⅡA2 [according to 2018 International Federation of Gynecology and Obstetrics (FIGO) staging standard], and to establish a nomogram model to predict the risk of postoperative adjuvant therapy for locally advanced cervical cancer.Methods:A total of 714 patients with cervical squamous cell cancer staged FIGO ⅠB1-ⅡA2 treated by surgery in Anhui Provincial Hospital were selected as the research objects from January 2009 to December 2019, and their clinicopathological data were analyzed. Multiple logistic regression analysis was used to determine the influencing factors, and a nomogram model was established to predict the risk of postoperative adjuvant treatment of cervical cancer. The predictive performance of the model was evaluated with the consistency index (C-index), and the compliance of the model was evaluated with the calibration curve.Results:Univariate analysis suggested that postoperative adjuvant therapy for cervical cancer was associated with gravidity ( χ2=11.506, P=0.001), underlying disease (hypertension or diabetes) ( χ2=7.668, P=0.006), squamous cell cancer antigen (SCC-AG) level ( χ2=19.392, P<0.001), imaging risk factors ( χ2=16.392, P<0.001), FIGO stage ( χ2=25.686, P<0.001), tumor size ( χ2=9.392, P=0.025) and surgical path ( χ2=16.590, P<0.001). Multivariate logistic regression analysis suggested that the number of pregnancy >2 times ( OR=1.951, 95% CI: 1.355-2.808, P<0.001), SCC-Ag ≥1.5 μg/L ( OR=2.021, 95% CI: 1.444-2.829, P<0.001), FIGO stage ⅠB3-ⅡA2 [ⅠB3 ( OR=1.933, 95% CI: 1.139-3.282, P=0.015); ⅡA1 ( OR=2.723, 95% CI: 1.556-4.765, P<0.001); ⅡA2 ( OR=3.159, 95% CI: 1.502-6.646, P=0.002)], with underlying disease (hypertension or diabetes) ( OR=1.867, 95% CI: 1.051-3.318, P=0.033), imaging risk factors ( OR=1.997, 95% CI: 1.127-3.537, P=0.018), without neoadjuvant therapy [preoperative neoadjuvant therapy for 1 cycle ( OR=0.402, 95% CI: 0.207-0.783, P=0.007)] and laparoscopic surgery ( OR=2.177, 95% CI: 1.524-3.112, P<0.001) were independent influencing factors for postoperative adjuvant treatment of cervical cancer. Based on the screened variables, the nomogram model to predict the risk of postoperative adjuvant treatment for cervical cancer has good predictive performance (C-index was 0.702) and compliance. Conclusion:The number of pregnancy >2 times, SCC-Ag ≥1.5 μg/L, FIGO stage ⅠB3-ⅡA2, with underlying disease (hypertension or diabetes), imaging risk factors, without neoadjuvant therapy, and laparoscopic surgery are independent influencing factors for postoperative adjuvant treatment of cervical cancer. A nomogram model has been constructed to predict the risk of postoperative adjuvant therapy for locally advanced cerrical cancer, and it can provide evidence for clinical treatment selection.