Chen Xijie, Chen Shi, Wang Xinyou, Nie Runcong, Chen Dongwen, Xiang Jun, Lin Yijia, Chen Yingbo, Peng Junsheng
Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China.
Guangdong Institute of Gastroenterology, Guangzhou 510655, China.
Chin J Cancer Res. 2020 Apr;32(2):197-207. doi: 10.21147/j.issn.1000-9604.2020.02.07.
Peritoneal dissemination is difficult to diagnose by conventional imaging technologies. We aimed to construct a nomogram to predict peritoneal dissemination in gastric cancer (GC) patients.
We retrospectively analyzed 1,112 GC patients in Sun Yat-sen University Cancer Center between 2001 and 2010 as the development set and 474 patients from The Sixth Affiliated Hospital, Sun Yat-sen University between 2010 and 2016 as the validation set. The clinicopathological variables associated with gastric cancer with peritoneal dissemination (GCPD) were analyzed. We used logistic regression analysis to identify independent risk factors for peritoneal dissemination. Then, we constructed a nomogram for the prediction of GCPD and defined its predictive value with a receiver operating characteristic (ROC) curve. External validation was performed to validate the applicability of the nomogram.
In total, 250 patients were histologically identified as having peritoneal dissemination. Logistic regression analysis demonstrated that age, sex, tumor location, tumor size, signet-ring cell carcinoma (SRCC), T stage, N stage and Borrmann classification IV (Borrmann IV) were independent risk factors for peritoneal dissemination. We constructed a nomogram consisting of these eight factors to predict GCPD and found an optimistic predictive capability, with a C-index of 0.791, an area under the curve (AUC) of 0.791, and a 95% confidence interval (95% CI) of 0.762-0.820. The results found in the external validation set were also promising.
We constructed a highly sensitive nomogram that can assist clinicians in the early diagnosis of GCPD and serve as a reference for optimizing clinical management strategies.
传统成像技术难以诊断腹膜播散。我们旨在构建一种列线图，以预测胃癌（GC）患者的腹膜播散情况。
我们回顾性分析了2001年至2010年间中山大学肿瘤防治中心的1112例GC患者作为开发集，并将2010年至2016年间中山大学附属第六医院的474例患者作为验证集。分析了与伴有腹膜播散的胃癌（GCPD）相关的临床病理变量。我们使用逻辑回归分析来确定腹膜播散的独立危险因素。然后，我们构建了一个用于预测GCPD的列线图，并用受试者工作特征（ROC）曲线定义其预测价值。进行外部验证以验证列线图的适用性。
总共250例患者经组织学确诊为腹膜播散。逻辑回归分析表明，年龄、性别、肿瘤位置、肿瘤大小、印戒细胞癌（SRCC）、T分期、N分期和Borrmann IV型（Borrmann IV）是腹膜播散的独立危险因素。我们构建了一个由这八个因素组成的列线图来预测GCPD，发现其具有良好的预测能力，C指数为0.791，曲线下面积（AUC）为O.791，95%置信区间（95%CI）为0.762-0.820。在外部验证集中得到的结果也很有前景。
我们构建了一种高度敏感的列线图，可协助临床医生早期诊断GCPD，并为优化临床管理策略提供参考。
