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中华结直肠疾病电子杂志 ›› 2022, Vol. 11 ›› Issue (03) : 205 -211. doi: 10.3877/cma.j.issn.2095-3224.2022.03.004

论著

预测结直肠癌远处转移的临床预测模型:结合术前CEA、CA19-9及临床病理因素
王春林1, 王玉柳明1, 张浩1, 刘云霄1, 王猛2, 王贵玉2,()   
  1. 1. 150081 哈尔滨医科大学附属第二医院结直肠肿瘤外科
    2. 310022 杭州,中国科学院大学附属肿瘤医院(浙江省肿瘤医院)结直肠外科
  • 收稿日期:2021-09-02 出版日期:2022-06-25
  • 通信作者: 王贵玉
  • 基金资助:
    国家自然科学基金青年科学基金项目(82002506)

Clinical predictive model for predicting distant metastasis of colorectal cancer: combined with preoperative CEA, CA19-9 and clinicopathological factors

Chunlin Wang1, Yuliuming Wang1, Hao Zhang1, Yunxiao Liu1, Meng Wang2, Guiyu Wang2,()   

  1. 1. Department of Colorectal Cancer Surgery, the Second Affiliated Hospital of Harbin Medical University, Harbin 150081, China
    2. Department of Colorectal Surgery, Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou 310022, China
  • Received:2021-09-02 Published:2022-06-25
  • Corresponding author: Guiyu Wang
引用本文:

王春林, 王玉柳明, 张浩, 刘云霄, 王猛, 王贵玉. 预测结直肠癌远处转移的临床预测模型:结合术前CEA、CA19-9及临床病理因素[J/OL]. 中华结直肠疾病电子杂志, 2022, 11(03): 205-211.

Chunlin Wang, Yuliuming Wang, Hao Zhang, Yunxiao Liu, Meng Wang, Guiyu Wang. Clinical predictive model for predicting distant metastasis of colorectal cancer: combined with preoperative CEA, CA19-9 and clinicopathological factors[J/OL]. Chinese Journal of Colorectal Diseases(Electronic Edition), 2022, 11(03): 205-211.

目的

探讨术前肿瘤标志物CEA、CA19-9联合检测相关临床病理因素在结直肠癌远处转移中的预测价值。

方法

回顾性分析了接受R0根治术的2 758例结直肠癌患者临床资料,包括年龄、性别、肿瘤分化程度、肿瘤直径、肿瘤位置、CEA、CA19-9、肿瘤组织学类型、远处转移等临床资料,通过对可能反映结直肠癌患者出现远处转移的因素进行单因素及多因素分析,进而选择合适的变量构建列线图,并通过校准曲线来验证列线图的识别性。绘制受试者工作特征曲线(ROC)检验列线图对于伴随远处转移的结直肠癌患者的预测性能。

结果

单因素及多因素分析结果表示,术前CEA、CA19-9、肿瘤部位、肿瘤分化程度是反映结直肠癌患者出现远处转移的重要因素(P<0.05)。上述变量构建列线图,该预测模型的ROC值为0.771(95%置信区间:0.730~0.813)。

结论

术前CEA、CA19-9联合临床病理信息构建的预测模型是无创预测结直肠癌患者发生远处转移的有效方法。

Objective

To explore the predictive value of preoperative tumor markers CEA and CA19-9 in predicting distant metastasis of colorectal cancer.

Methods

The clinical data of 2 758 patients with colorectal cancer who underwent radical resection of R0 were analyzed retrospectively, including age, sex, degree of tumor differentiation, tumor diameter, tumor site, CEA, CA19-9, tumor histological type and distant metastasis. The factors that may reflect distant metastasis in patients with colorectal cancer were analyzed by univariate and multivariate analysis, and then appropriate variables were selected to construct the Nomogram. The recognition of the Nomogram is verified by the calibration curve. Subject operating characteristic analysis (ROC) was used to compare the ability of the Nomogram to predict distant metastasis in patients with colorectal cancer.

Results

Univariate and multivariate results showed that preoperative CEA, CA19-9, tumor site and tumor differentiation were important factors reflecting distant metastasis in patients with colorectal cancer(P<0.05). The above variables are used to construct the Nomogram, and the ROC value of the prediction model is 0.771 (95% confidence interval: 0.730~0.813).

Conclusion

The predictive model constructed by preoperative CEA and CA19-9 combined with basic pathological information is an effective method for non-invasive prediction of distant metastasis in patients with colorectal cancer.

表1 结直肠癌远处转移危险因素单因素分析
表2 结直肠癌远处转移危险因素多因素Logistic回归分析
图1 预测结直肠癌远处转移的列线图风险模型
图2 预测结直肠癌远处转移风险的列线图模型校准曲线
图3 预测结直肠癌远处转移风险的列线图模型的ROC曲线。3A:建模组ROC曲线,3B:验证组ROC曲线
图4 列线图模型中的决策曲线
图5 列线图模型的临床影响曲线
图6 依据风险评分,计算截断点
图7 研究人群中高风险组与低风险组发生远处转移患者比例对比
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