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葛宜枝, 许艳, 陈小军, 顾祥. 左右半结直肠肿瘤转移风险模型构建及评价[J]. 肿瘤防治研究, 2022, 49(9): 931-936. DOI: 10.3971/j.issn.1000-8578.2022.21.1481
引用本文: 葛宜枝, 许艳, 陈小军, 顾祥. 左右半结直肠肿瘤转移风险模型构建及评价[J]. 肿瘤防治研究, 2022, 49(9): 931-936. DOI: 10.3971/j.issn.1000-8578.2022.21.1481
GE Yizhi, XU Yan, CHEN Xiaojun, GU Xiang. Construction and Evaluation of Metastatic Risk Model in Left and Right Colorectal Cancer[J]. Cancer Research on Prevention and Treatment, 2022, 49(9): 931-936. DOI: 10.3971/j.issn.1000-8578.2022.21.1481
Citation: GE Yizhi, XU Yan, CHEN Xiaojun, GU Xiang. Construction and Evaluation of Metastatic Risk Model in Left and Right Colorectal Cancer[J]. Cancer Research on Prevention and Treatment, 2022, 49(9): 931-936. DOI: 10.3971/j.issn.1000-8578.2022.21.1481

左右半结直肠肿瘤转移风险模型构建及评价

Construction and Evaluation of Metastatic Risk Model in Left and Right Colorectal Cancer

  • 摘要:
    目的 探讨左右半结直肠肿瘤患者肝、肺、骨和脑转移的影响因素并对比构建Nomogram图预测转移概率。
    方法 回顾性筛选和分析2010年至2018年SEER数据库中结直肠肿瘤有肝、肺、骨和脑转移的患者信息。根据肿瘤部位分成左半、右半和直肠肿瘤,利用多因素Logistic回归分析分别筛选转移相关影响因素,建立Nomogram预测图并使用ROC曲线下面积AUC和校准曲线进行检验。
    结果 筛选出49 335例符合条件的结直肠癌患者。其中,N分期和CEA与肝、肺、骨及脑转移均相关,且与原发肿瘤部位无关,而种族在左右半不同部位对肝转移的影响不同(P < 0.05)。肝转移构建的Nomogram模型较好,根据左半,右半和直肠三个原发部位构建的预测肝转移Nomogram模型的AUC分别为0.821(95%CI: 0.813~0.830)、0.841(95%CI: 0.833~0.848)和0.796(95%CI: 0.782~0.811)。
    结论 影响不同原发肿瘤部位的结直肠癌患者远处转移的因素及其相应的预测模型存在差异。

     

    Abstract:
    Objective To identify the influence factors and construct a predicted model for liver, lung, bone, or brain metastasis among patients with left or right colorectal cancer.
    Methods Patients with colorectal cancer with information on liver, lung, bone, and brain metastasis were retrospectively filtered and analyzed from 2010 to 2018 from the SEER database. These patients were divided into three groups based on their primary tumor location. Multivariate logistic regression analysis was conducted to identify the influence factors on metastasis. A nomogram that could predict metastasis was established and further validated by the AUC of ROC curves.
    Results A total of 49335 eligible patients were chosen from the SEER database. N stage and CEA were identified as risk factors for all metastases, which were unrelated to primary tumor location. By contrast, race had varying effects on liver metastasis between different groups (P < 0.05). The nomogram model predicting liver metastasis was successfully established, and the AUCs based on the three groups were 0.821 (95%CI: 0.813-0.830), 0.841 (95%CI: 0.833-0.848), and 0.796 (95%CI: 0.782-0.811), respectively.
    Conclusion The influence factors and predictive models on liver metastasis were different in patients with colorectal cancer and different primary tumor locations.

     

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