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中华普通外科学文献(电子版)

中华普通外科学文献(电子版) ›› 2024, Vol. 18 ›› Issue (01) : 39 -43. doi: 10.3877/cma.j.issn.1674-0793.2024.01.007

论著

基于血清肿瘤标志物预测结直肠癌肝转移模型价值分析
杨立胜, 刘梦鸾, 任维聃, 姜国胜, 刘桂伟†()   
  1. 061000　沧州市中心医院结直肠肛门外科
    061000　沧州市第三医院肝病四科
  • 收稿日期:2023-09-07 出版日期:2024-02-01
  • 通信作者: 刘桂伟
  • 基金资助:
    河北省中医药管理局中医药类科研计划项目(2021285)

Prognostic value of a prediction model for colorectal cancer liver metastasis based on serum tumor markers

Lisheng Yang, Mengluan Liu, Weidan Ren, Guosheng Jiang, Guiwei Liu†()   

  1. Department of Colorectal and Anal Surgery, Cangzhou Central Hospital, Cangzhou 061000, China
    No. 4 Department of Hepatology, Cangzhou Third Hospital, Cangzhou 061000, China
  • Received:2023-09-07 Published:2024-02-01
  • Corresponding author: Guiwei Liu
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杨立胜, 刘梦鸾, 任维聃, 姜国胜, 刘桂伟. 基于血清肿瘤标志物预测结直肠癌肝转移模型价值分析[J]. 中华普通外科学文献(电子版), 2024, 18(01): 39-43.

Lisheng Yang, Mengluan Liu, Weidan Ren, Guosheng Jiang, Guiwei Liu. Prognostic value of a prediction model for colorectal cancer liver metastasis based on serum tumor markers[J]. Chinese Archives of General Surgery(Electronic Edition), 2024, 18(01): 39-43.

目的

探讨血清肿瘤标志物与结直肠癌肝转移（CRLM）间的关系，建立CRLM预测模型并评价其价值。

方法

本研究为回顾性病例对照研究，纳入2021年4月至2022年10月沧州市中心医院收治的结直肠癌患者371例，依据有无肝转移将其分为CRLM组59例，无肝转移（non-CRLM）组312例。比较两组患者临床资料、治疗前血常规及血清肿瘤标志物检测结果。采用二元Logistic回归分析CRLM的独立影响因素，并以此建立预测模型，利用受试者工作特征（ROC）曲线及拟合优度检验评价预测模型的效能。

结果

单因素分析显示，CRLM组中性粒细胞-淋巴细胞比值（NLR）、癌胚抗原（CEA）、糖类抗原19-9（CA19-9）和唾液酸/羟脯氨酸（SA&Hyp）水平均高于non-CRLM组（均P<0.01）；多因素Logistic回归分析显示，经校正后血清CEA（OR=1.021，95% CI：1.012~1.030）、CA19-9（OR=1.003，95% CI：1.001~1.005）和SA&Hyp高表达（OR=1.055，95% CI：1.033~1.077）均为CRLM的独立危险因素（均P<0.01）。ROC曲线分析显示，与CEA、CA19-9和SA&Hyp单独检测相比，三者联合构建的预测模型对CRLM的诊断效能更佳（ROC曲线下面积0.867，95% CI：0.818~0.916，敏感度0.831，特异度0.785，均P<0.05）。拟合优度检验结果提示该预测模型拟合度较好（χ2=8.441，P=0.392）。

结论

血清CEA、CA19-9和SA&Hyp高表达是CRLM发生的独立危险因素，基于此3项指标构建的CRLM预测模型具有良好的诊断价值，可为临床工作中CRLM的早期诊断提供新参考。

关键词: 结直肠肿瘤, 肿瘤标志物, 肝转移, 预测模型, 唾液酸/羟脯氨酸, 癌胚抗原, CA19-9
Objective

To investigate the relationship between serum tumor markers and colorectal cancer liver metastasis (CRLM), thus to establish a prediction model for CRLM and evaluate its application value.

Methods

A total of 371 patients with colorectal cancer admitted to Cangzhou Central Hospital from April 2021 to October 2022 were included in this study. They were divided into two groups according to whether there were liver metastases. There were 59 patients in the CRLM group and 312 patients in the non-CRLM group. Clinical data, test results of pre-treatment blood and serum tumor markers of patients were collected retrospectively. Binary Logistic regression was used to analyze the independent influencing factors of CRLM, and the diagnostic efficacy of the prediction model was evaluated using receiver operating characteristics (ROC) curve and goodness-of-fit test.

Results

Compared with non-CRLM group, neutrophil to lymphocyte ratio (NLR), carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), and sialic acid/hydroxyproline (SA&Hyp) levels were significantly higher (all P<0.01). Binary Logistic regression analysis showed that the high levels of serum CEA (OR=1.021, 95% CI: 1.012-1.030), CA19-9 (OR=1.003, 95% CI: 1.001-1.005) and SA&Hyp (OR=1.055, 95% CI: 1.033-1.077) were independent risk factors for CRLM after correction (all P<0.01). ROC curve analysis revealed that the predictive modeling (AUC=0.867, 95% CI: 0.818-0.916, sensitivity was 0.831, specificity was 0.785) jointly constructed by CEA, CA19-9 and SA&Hyp was more effective in predicting CRLM compared with any single indicator (all P<0.05). The goodness-of-fit test results indicated that the prediction model had good matching (χ2=8.441, P=0.392).

Conclusions

High levels of serum CEA, CA19-9 and SA&Hyp are independent risk factors for CRLM. The prediction model of CRLM based on the joint detection of risk factors shows a reasonable predictive value and may provide new insights for the early diagnosis of CRLM in clinical work.

Key words: Colorectal neoplasms, Biomarkers, Tumor, Liver metastasis, Prediction model, Sialic acid/hydroxyproline, Carcinoembryonic antigen, Carbohydrate antigen 19-9
表1 两组结直肠癌患者临床资料比较
项目 non-CRLM组 CRLM组 统计值 P值
例数 312 59    
性别[例(%)]     χ2=0.151 0.697
男 183(58.654) 33(55.932)    
女 129(41.346) 26(44.068)    
肿瘤部位[例(%)]     χ2=0.334 0.563
右半结肠 39(12.500) 9(15.254)    
左半结直肠 273(87.500) 50(84.746)    
年龄(岁) 65(56,72) 68(59,73) U=10 531.500 0.079
体质指数(kg/m2) 24.084(21.543,26.298) 23.438(21.224,25.952) U=8 185.500 0.178
NLR 1.814(1.448,2.454) 2.429(1.696,3.262) U=11 680.000 0.001
LMR 4.727(3.433,5.667) 4.303(2.944,5.653) U=8 184.000 0.177
AFP (μg/L) 2.625(1.940,3.830) 2.830(2.070,4.090) U=9 917.500 0.345
CEA (μg/L) 3.860(2.033,8.978) 20.400(7.590,94.300) U=14 575.500 <0.001
CA19-9 (U/ml) 11.700(7.320,21.325) 32.900(15.400,126.000) U=13 563.500 <0.001
SA&Hyp (U/ml) 90.554±14.725 104.925±17.079 t= -6.695 <0.001
表2 血清CEA、CA19-9、SA&Hyp与结直肠癌肝转移的关系
项目 CEA CA19-9 SA&Hyp
OR值 95% CI P值 OR值 95% CI P值 OR值 95% CI P值
校正0 1.021 1.012~1.030 <0.001 1.003 1.001~1.005 0.002 1.055 1.033~1.077 <0.001
校正1 1.021 1.012~1.030 <0.001 1.003 1.001~1.005 0.002 1.055 1.033~1.077 <0.001
校正2 1.021 1.012~1.030 <0.001 1.003 1.001~1.005 0.002 1.055 1.033~1.077 <0.001
图1 癌胚抗原（CEA）、糖类抗原19-9（CA19-9）、唾液酸/羟脯氨酸（SA&Hyp）和预测模型预测结直肠癌肝转移（CRLM）的ROC曲线
表3 几种指标预测结直肠癌肝转移的效能分析
检测指标 曲线下面积(95% CI) 敏感度(95% CI) 特异度(95% CI) P值
CEA 0.792 (0.728~0.855) 0.797(0.672~0.890) 0.692(0.638~0.743) 0.019
CA19-9 0.737 (0.650~0.824) 0.712(0.579~0.822) 0.772(0.722~0.818) 0.006
SA&Hyp 0.739 (0.667~0.811) 0.593(0.457~0.719) 0.821(0.773~0.861) <0.001
预测模型 0.867 (0.818~0.916) 0.831(0.710~0.916) 0.785(0.735~0.830)  
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