Construction of nomogram prognostic model for gastric signet ring cell carcinoma: Signet ring cell proportion influencing prognosis

被引:2
作者
Sui, Wannian [1 ]
Chen, Peifeng [1 ]
Chen, Zhangming [1 ]
Han, Wenxiu [1 ]
机构
[1] Anhui Med Univ, Affiliated Hosp 1, Dept Gen Surg, Hefei 230022, Anhui, Peoples R China
来源
EJSO | 2025年 / 51卷 / 08期
关键词
Gastric cancer; Signet ring cell carcinoma; Prognosis; Nomogram prediction model; LYMPH-NODE METASTASIS; INTRAMUCOSAL;
D O I
10.1016/j.ejso.2025.110012
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Signet ring cell (SRC) carcinoma significantly impacts the prognosis of gastric cancer (GC) patients, yet the influence of SRC proportion is often overlooked. This study aims to clarify the relationship between SRC proportion and prognosis and to construct a prognostic prediction model for gastric cancer patients with SRC components (GSRCC). Methods: Clinical data from 628 GSRCC patients who underwent gastrectomy at the First Affiliated Hospital of Anhui Medical University from November 2011 to December 2018 were collected. Patients were randomly divided into a training set (442 patients) and a validation set (186 patients). Prognostic risk factors were identified in the training set, and a nomogram prediction model was established. The internal and external validation were conducted on the training and validation sets. Results: The SRC proportion (hazard ratio [HR]: 9.569, P < 0.001), depth of invasion (HR: 6.838, P = 0.001), tumor size (HR: 1.573, P = 0.044), and N stage (HR: 6.511, P < 0.001) were independent prognostic factors for GSRCC. The nomogram showed excellent performance in predicting 1-year, 3-year, and 5-year overall survival (OS) with AUC values of 0.819, 0.832, and 0.874 in the training set, and of 0.815, 0.847, and 0.876 in the validation set, respectively. Calibration curves indicated good agreement between predicted and actual survival rates. Conclusions: The SRC proportion influences the prognosis of GSRCC patients. The establishment of the prognostic prediction model will provide assistance for clinical decision-making and prognosis assessment.
引用
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页数:7
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