Xiao Zhengping, Nie Guole, Xiao Xi, Li Baosong, Jiang Hong
Department of Colorectal Hernia Surgery, Binzhou Medical University Hospital, Binzhou, Shandong Province, China.
Binzhou Medical University, Binzhou, Shandong Province, China.
Medicine (Baltimore). 2025 Jul 18;104(29):e43369. doi: 10.1097/MD.0000000000043369.
Employing multivariate statistical methods, we aimed to construct and validate predictive models for distant metastasis (DM) risk and overall survival (OS) in patients with gallbladder cancer (GBC), using data from the surveillance, epidemiology, and end results database maintained by the National Cancer Institute. These models were visualized through the development of intuitive nomograms. We extracted clinical data of all patients diagnosed with GBC between 2010 and 2015 from the surveillance, epidemiology, and end results database. Both univariate and multivariate logistic regression analyses were conducted utilizing R software (Version 4.2.1) to identify independent risk predictors for DM in GBC patients, and univariate and multivariate Cox regression analyses were performed to determine independent prognostic factors for OS among GBC patients with DM. The discriminatory capabilities and predictive accuracies of the developed nomograms were examined through calibration curves, receiver operating characteristic curves, and decision curve analysis. In our study, 3071 patients with GBC were included, of which 759 (24.72%) had DM. Race, T stage, N stage, and tumor size were identified as independent risk factors for DM, while age, surgical intervention, and chemotherapy were independent prognostic factors for OS in GBC patients with DM. The area under the curve for the prognostic nomogram reached 0.726 and 0.730 in the training and validation sets, respectively. The area under the curve for the same nomogram at 6, 9, and 12 months was 0.744, 0.740, and 0.704 for the training set, and 0.798, 0.774, and 0.776 for the validation set, respectively. The calibration curves, decision curve analysis, and Kaplan-Meier survival curves further demonstrated the effectiveness of the nomograms in predicting DM occurrence and the prognosis of GBC patients with DM. Race, T stage, N stage, and tumor size emerged as independent risk factors for DM in GBC patients; whereas age, surgical treatment, and chemotherapy were found to be independent prognostic factors for OS in GBC patients with DM. We successfully established and validated a predictive nomogram for DM occurrence and a prognostic nomogram for OS in GBC patients with DM, both showing high accuracy and clinical utility.
我们运用多变量统计方法，旨在利用美国国立癌症研究所维护的监测、流行病学和最终结果数据库中的数据，构建并验证胆囊癌（GBC）患者远处转移（DM）风险和总生存期（OS）的预测模型。这些模型通过直观列线图的开发进行可视化展示。我们从监测、流行病学和最终结果数据库中提取了2010年至2015年间所有诊断为GBC的患者的临床数据。利用R软件（版本4.2.1）进行单变量和多变量逻辑回归分析，以确定GBC患者DM的独立风险预测因素，并进行单变量和多变量Cox回归分析，以确定GBC合并DM患者OS的独立预后因素。通过校准曲线、受试者操作特征曲线和决策曲线分析来检验所开发列线图的辨别能力和预测准确性。在我们的研究中，纳入了3071例GBC患者，其中759例（24.72%）发生了DM。种族、T分期、N分期和肿瘤大小被确定为DM的独立风险因素，而年龄、手术干预和化疗是GBC合并DM患者OS的独立预后因素。预后列线图在训练集和验证集中的曲线下面积分别达到0.726和0.730。同一列线图在训练集6个月、9个月和12个月时的曲线下面积分别为0.744、0.740和0.704，在验证集分别为0.798、0.774和0.776。校准曲线、决策曲线分析和Kaplan-Meier生存曲线进一步证明了列线图在预测DM发生和GBC合并DM患者预后方面的有效性。种族、T分期、N分期和肿瘤大小是GBC患者DM的独立风险因素；而年龄、手术治疗和化疗被发现是GBC合并DM患者OS的独立预后因素。我们成功建立并验证了GBC合并DM患者DM发生的预测列线图和OS的预后列线图，两者均显示出高准确性和临床实用性。
