Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Department of Etiology and Carcinogenesis, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Adv Ther. 2020 Jun;37(6):2902-2915. doi: 10.1007/s12325-020-01356-4. Epub 2020 May 3.
Gastric cancer (GC) is the fifth most common cancer worldwide, and every year approximately 950,000 individuals are diagnosed worldwide. Our study aimed to establish an effective nomogram to predict the prognosis of GC based on inflammation biomarkers.
We retrospectively analysed GC patients from the Sun Yat-sen University Cancer Center. The nomogram was developed with a primary cohort (n = 1067), and 537 patients were included in the validation cohort. The univariate survival analyses included 19 biomarkers.
The multivariate analysis showed that tumour stage, metastasis stage and C-reactive protein (CRP), albumin (ALB), carcinoembryonic antigen (CEA) and carbohydrate antigen-199 (CA199) levels as well as the lymphocyte (LYM) count were independent risk factors for the prognosis of GC patients. The nomogram was based on the above factors. In the primary cohort, the nomogram had a concordance index (C-index) of 0.825 (95% CI 0.796-0.854), which was higher than the C-index of the AJCC TNM stage and that of the other biomarkers (CEA and CA199). The calibration plot suggested good agreement between the actual and nomogram-predicted overall survival (OS) probabilities, and the decision curve analyses showed that the nomogram model had a higher overall net benefit in predicting OS than the AJCC TNM stage. Moreover, we divided the patients into the following three distinct risk groups for OS based on the nomogram points: low, middle and high risk. The differences in OS rates were significant among the subgroups (P < 0.001).
A novel nomogram integrated with inflammatory prognostic factors was proposed, which is highly predictive of OS in GC patients.
胃癌（GC）是全球第五大常见癌症，每年全球约有 95 万人被诊断患有胃癌。我们的研究旨在建立一种基于炎症生物标志物预测 GC 预后的有效列线图。
我们回顾性分析了中山大学肿瘤中心的 GC 患者。该列线图是使用主要队列（n=1067）建立的，验证队列纳入了 537 名患者。单因素生存分析包括 19 个生物标志物。
多因素分析显示，肿瘤分期、转移分期以及 C 反应蛋白（CRP）、白蛋白（ALB）、癌胚抗原（CEA）和糖类抗原 199（CA199）水平以及淋巴细胞（LYM）计数是 GC 患者预后的独立危险因素。该列线图是基于上述因素建立的。在主要队列中，该列线图的一致性指数（C 指数）为 0.825（95%CI 0.796-0.854），高于 AJCC TNM 分期和其他生物标志物（CEA 和 CA199）的 C 指数。校准图表明实际和列线图预测的总生存（OS）概率之间具有良好的一致性，决策曲线分析表明，该列线图模型在预测 OS 方面的整体净获益高于 AJCC TNM 分期。此外，我们根据列线图积分将患者分为 OS 的以下三个不同风险组：低、中、高风险。亚组之间 OS 率的差异具有统计学意义（P<0.001）。
我们提出了一种新的列线图，该列线图综合了炎症预后因素，对 GC 患者的 OS 具有高度预测性。
