Chang Zheng-Yao, Gao Wen-Xing, Zhang Yue, Zhao Wen, Wu Di, Chen Lin
Department of General Surgery, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China.
Department of Endocrinology, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China.
World J Clin Cases. 2024 May 6;12(13):2182-2193. doi: 10.12998/wjcc.v12.i13.2182.
Liver metastases (LM) is the primary factor contributing to unfavorable outcomes in patients diagnosed with gastric cancer (GC). The objective of this study is to analyze significant prognostic risk factors for patients with GCLM and develop a reliable nomogram model that can accurately predict individualized prognosis, thereby enhancing the ability to evaluate patient outcomes.
To analyze prognostic risk factors for GCLM and develop a reliable nomogram model to accurately predict individualized prognosis, thereby enhancing patient outcome assessment.
Retrospective analysis was conducted on clinical data pertaining to GCLM (type III), admitted to the Department of General Surgery across multiple centers of the Chinese PLA General Hospital from January 2010 to January 2018. The dataset was divided into a development cohort and validation cohort in a ratio of 2:1. In the development cohort, we utilized univariate and multivariate Cox regression analyses to identify independent risk factors associated with overall survival in GCLM patients. Subsequently, we established a prediction model based on these findings and evaluated its performance using receiver operator characteristic curve analysis, calibration curves, and clinical decision curves. A nomogram was created to visually represent the prediction model, which was then externally validated using the validation cohort.
A total of 372 patients were included in this study, comprising 248 individuals in the development cohort and 124 individuals in the validation cohort. Based on Cox analysis results, our final prediction model incorporated five independent risk factors including albumin levels, primary tumor size, presence of extrahepatic metastases, surgical treatment status, and chemotherapy administration. The 1-, 3-, and 5-years Area Under the Curve values in the development cohort are 0.753, 0.859, and 0.909, respectively; whereas in the validation cohort, they are observed to be 0.772, 0.848, and 0.923. Furthermore, the calibration curves demonstrated excellent consistency between observed values and actual values. Finally, the decision curve analysis curve indicated substantial net clinical benefit.
Our study identified significant prognostic risk factors for GCLM and developed a reliable nomogram model, demonstrating promising predictive accuracy and potential clinical benefit in evaluating patient outcomes.
肝转移（LM）是导致胃癌（GC）患者预后不良的主要因素。本研究的目的是分析胃癌肝转移（GCLM）患者的显著预后危险因素，并建立一个可靠的列线图模型，能够准确预测个体预后，从而提高评估患者预后的能力。
分析GCLM的预后危险因素，建立可靠的列线图模型以准确预测个体预后，从而加强患者预后评估。
对2010年1月至2018年1月在中国人民解放军总医院多个中心普通外科收治的GCLM（III型）患者的临床资料进行回顾性分析。数据集按2:1的比例分为开发队列和验证队列。在开发队列中，我们采用单因素和多因素Cox回归分析来确定与GCLM患者总生存相关的独立危险因素。随后，我们基于这些发现建立了一个预测模型，并使用受试者工作特征曲线分析、校准曲线和临床决策曲线评估其性能。创建了一个列线图以直观地表示预测模型，然后使用验证队列对其进行外部验证。
本研究共纳入372例患者，其中开发队列248例，验证队列124例。根据Cox分析结果，我们最终的预测模型纳入了五个独立危险因素，包括白蛋白水平、原发肿瘤大小、肝外转移情况、手术治疗状态和化疗给药情况。开发队列中1年、3年和5年的曲线下面积值分别为0.753、0.859和0.909；而在验证队列中，观察到的值分别为0.772、0.848和0.923。此外，校准曲线显示观察值与实际值之间具有良好的一致性。最后，决策曲线分析曲线表明具有显著的净临床获益。
我们的研究确定了GCLM的显著预后危险因素，并建立了一个可靠的列线图模型，在评估患者预后方面显示出有前景的预测准确性和潜在的临床获益。
