Sha Hong, Hu Dan, Wu Sinan, Peng Feng, Xu Guodong, Fan Guohui, Lin Xiandong, Chen Gang, Liang Binying, Chen Ying, Li Chao, Zhang Hejun, Xia Yan, Lin Jinxiu, Zheng Xiongwei, Niu Wenquan
Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Department of Pathology, Fujian Cancer Hospital and Fujian Medical University Cancer Hospital, Fuzhou, Fujian, China.
J Cancer. 2018 Mar 8;9(7):1173-1181. doi: 10.7150/jca.23631. eCollection 2018.
Compelling evidence has emerged to support a close relationship between metabolic syndrome and esophageal cancer (EC). Using five baseline metabolism-related markers, we constructed a metabolic risk score (MRS), aiming to test whether MRS can improve the prediction of postsurgical EC-specific mortality over traditional demographic and clinicopathologic characteristics. Total 2535 EC patients who received three-field lymphadenectomy were enrolled from January 2000 to December 2010, and they were followed up until December 2015. All EC patients were randomly split into derivation group (n=1512, 60%) and validation group (n=1014, 40%). MRS was generated in derivation group by adopting the Framingham 'points' system and shrinkage method, and it ranged from -9 to 17. EC-specific mortality risk increased with the increase of MRS, and adjusted estimates were more obvious in patients with upper tertile (MRS>6) than patients with lower MRS (≤2) in either derivation (hazard ratio [HR]=2.28, 95% confidence interval [CI]: 1.90-2.73, P<0.001) or validation group (HR=2.11, 95% CI: 1.66-2.67, P<0.001) or both groups (HR=2.37, 95% CI: 1.95-2.88, P<0.001). In Kaplan-Meier curve, cumulative survival rates differed significantly across tertiles of MRS. Further analysis indicated that MRS can improve classification accuracy and discriminatory ability over clinicopathologic parameters. Our findings supported the usefulness of baseline MRS in predicting the prognosis of postsurgical EC-specific mortality.
越来越多的确凿证据支持代谢综合征与食管癌（EC）之间存在密切关系。我们使用五个基线代谢相关标志物构建了一个代谢风险评分（MRS），旨在检验MRS是否能比传统的人口统计学和临床病理特征更好地预测食管癌术后特定病因死亡率。2000年1月至2010年12月期间，共有2535例接受三野淋巴结清扫术的食管癌患者入组，并随访至2015年12月。所有食管癌患者被随机分为推导组（n = 1512，60%）和验证组（n = 1014，40%）。通过采用弗雷明汉“积分”系统和收缩法在推导组中生成MRS，其范围为 -9至17。食管癌特异性死亡风险随MRS增加而升高，在推导组（风险比[HR]=2.28，95%置信区间[CI]：1.90 - 2.73，P<0.001）、验证组（HR = 2.11，95% CI：1.66 - 2.67，P<0.001）或两组合并分析（HR = 2.37，95% CI：1.95 - 2.88，P<0.001）中，上三分位数（MRS>6）患者的校正估计值比低MRS（≤2）患者更明显。在Kaplan-Meier曲线中，MRS三分位数间的累积生存率差异显著。进一步分析表明，MRS比临床病理参数能提高分类准确性和鉴别能力。我们的研究结果支持基线MRS在预测食管癌术后特定病因死亡率预后方面的有用性。
