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目的:探讨ⅠB1～ⅡA2期[按2018年国际妇产科联盟(FIGO)分期标准]宫颈癌术后辅助治疗的相关影响因素，建立个体化预测局部晚期宫颈癌术后辅助治疗风险的列线图模型。方法:以2009年1月至2019年12月于安徽省立医院行手术治疗的ⅠB1～ⅡA2期宫颈鳞状细胞癌患者714例为研究对象，分析其临床病理资料。采用多因素logistic回归分析宫颈癌术后辅助治疗的影响因素，并建立预测宫颈癌术后辅助治疗风险的列线图模型，用一致性系数(C-index)评估模型的预测性能，校准曲线评估模型的符合度。结果:单因素分析提示，宫颈癌术后辅助治疗与患者的孕次(n χ2＝11.506，n P＝0.001)、是否合并基础疾病(高血压或糖尿病)(n χ2＝7.668，n P＝0.006)、鳞状细胞癌抗原(SCC-Ag)水平(n χ2＝19.392，n P<0.001)、影像学检查是否伴有危险因素(n χ2＝16.392，n P<0.001)、FIGO分期(n χ2＝25.686，n P<0.001)、肿瘤大小(n χ2＝9.392，n P＝0.025)和手术路径(n χ2＝16.590，n P2次(n OR＝1.951，95%n CI为1.355～2.808，n P<0.001)、SCC-Ag≥1.5 μg/L(n OR＝2.021，95%n CI为1.444～2.829，n P<0.001)、FIGO分期为ⅠB3～ⅡA2期(ⅠB3期：n OR＝1.933，95%n CI为1.139～3.282，n P＝0.015；ⅡA1期：n OR＝2.723，95%n CI为1.556～4.765，n P<0.001；ⅡA2期：n OR＝3.159，95%n CI为1.502～6.646，n P＝0.002)、合并基础疾病(高血压或糖尿病)(n OR＝1.867，95%n CI为1.051～3.318，n P＝0.033)、影像学检查伴有危险因素(n OR＝1.997，95%n CI为1.127～3.537，n P＝0.018)、未行新辅助治疗(术前行辅助治疗1疗程：n OR＝0.402，95%n CI为0.207～0.783，n P＝0.007)、行腹腔镜手术(n OR＝2.177，95%n CI为1.524～3.112，n P2次、SCC-Ag≥1.5 μg/L、FIGO分期为ⅠB3～ⅡA2期、合并基础疾病(高血压或糖尿病)、影像学检查伴有危险因素、未行新辅助治疗、行腹腔镜手术为宫颈癌术后追加辅助治疗的独立影响因素，构建了可用于预测局部晚期宫颈癌术后辅助治疗风险的列线图模型，可为临床治疗选择提供依据。“,”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 (n χ2=11.506, n P=0.001), underlying disease (hypertension or diabetes) (n χ2=7.668, n P=0.006), squamous cell cancer antigen (SCC-AG) level (n χ2=19.392, n P<0.001), imaging risk factors (n χ2=16.392, n P<0.001), FIGO stage (n χ2=25.686, n P<0.001), tumor size (n χ2=9.392, n P=0.025) and surgical path (n χ2=16.590, n P2 times (n OR=1.951, 95%n CI: 1.355-2.808, n P<0.001), SCC-Ag ≥1.5 μg/L (n OR=2.021, 95%n CI: 1.444-2.829, n P<0.001), FIGO stage ⅠB3-ⅡA2 [ⅠB3 (n OR=1.933, 95%n CI: 1.139-3.282, n P=0.015); ⅡA1 (n OR=2.723, 95%n CI: 1.556-4.765, n P<0.001); ⅡA2 (n OR=3.159, 95%n CI: 1.502-6.646, n P=0.002)], with underlying disease (hypertension or diabetes) (n OR=1.867, 95%n CI: 1.051-3.318, n P=0.033), imaging risk factors (n OR=1.997, 95%n CI: 1.127-3.537, n P=0.018), without neoadjuvant therapy [preoperative neoadjuvant therapy for 1 cycle (n OR=0.402, 95%n CI: 0.207-0.783, n P=0.007)] and laparoscopic surgery (n OR=2.177, 95%n CI: 1.524-3.112, n P2 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.