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Logistic回归模型在预测直肠癌肠旁淋巴结转移中的应用价值 被引量:4

The Application Value of Prediction of Logistic Regression Model in Rectal Cancer Patients with Lymph Node Metastasis
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摘要 [目的]建立直肠癌原发病灶和肠旁淋巴结CT表现的Logistic回归模型,探讨其预测肠旁淋巴结转移的应用价值。[方法]回顾性分析行直肠癌根治术的102例患者的临床和CT影像学资料,分析原发肿瘤及肠旁淋巴结CT表现情况,并以术后病理淋巴结转移结果为金标准。单因素分析采用χ2检验,将有统计学意义的因素建立Logistic回归模型,绘制模型受试工作者特征曲线(ROC),并记录曲线下面积(AUC),评估该模型预测淋巴结转移的能力。[结果]单因素分析结果显示病变部位、浆膜外侵、生长方式、淋巴结总数和淋巴结短径与淋巴结转移阳性率有显著相关性(P<0.05),其AUC分别为0.618、0.638、0.630、0.703和0.692;病变强化程度、肿瘤长径、肿瘤血供及淋巴结强化与淋巴结转移阳性率无相关性(P>0.05)。单因素分析有意义指标纳入Logistic回归模型,Logit P=-2.46-0.701×病变部位+0.138×浆膜侵犯-1.814×生长方式+2.14×淋巴结总数+1.379×淋巴结短径,其AUC为0.850,临界值取0.39时,灵敏度为88.2%,特异性为72.9%,准确率为75.5%。[结论]综合分析直肠癌原发肿瘤和肠旁淋巴结CT表现,有助提高术前淋巴结转移预测的准确性。 [Purpose] To investigate the prediction of lymph node metastasis in rectal cancer and its application value,the Logistic regression model of CT findings of primary foci and perirectal fascial lymph nodes were recruited. [Methods] The clinical and radiographic data,collected from 102 cases of rectal cancer patients with postoperative pathological diagnosis as the gold standard.In this study,the morphological characteristics of the primary tumors and perirectal fascial lymph nodes were analyzed. Logistic regression models were built up from the statistically significant factors. Furthermore,the receiver operating characteristic curve(ROC) and the area under the curve(AUC) were produced to evaluate the predictive ability of the model in respect of lymph node metastasis. [Results] Univariate analysis showed that lymph node metastasis related to the location of lesions,the depth of serosal invasion,the growth way of lesions,the total number of lymph nodes and the short axis diameter of lymph nodes(P〈0.05),and AUC were 0.618,0.638,0.630,0.703 and 0.692 respectively. Lymph node metastasis did not relate to the enriched degree of lesions,the maximum diameter of lesions,the tumor blood supply and the enriched degree of lymph nodes(P〈0.05). The factors which had statistically significant were used to build Logistic regression model,Logit P=-2.46-0.701×the location of lesions+0.138×the depth of serosal invasion-1.814×the growth way of lesions+2.14×the total number of lymph nodes+1.379 ×the short axis diameter of lymph nodes,and AUC was 0.850. When cut-off value was 0.39,the sensitivity was 88.2%,specificity was 72.9% and the accuracy rate was 75.5%. [Conclusion] Comprehensive analysis of the CT findings of primary focus and perirectal fascial lymph nodes may contribute to improve the preoperative diagnosis of lymph node metastasis.
出处 《肿瘤学杂志》 CAS 2015年第4期297-303,共7页 Journal of Chinese Oncology
基金 黑龙江省卫生厅课题(2102-671)
关键词 直肠肿瘤 淋巴结转移 ROC曲线 LOGISTIC回归 rectal neoplasms lymph node metastasis ROC curve Logistic regression
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