| Logistic回归模型在不典型浸润性导管癌诊断中的应用 |
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| 引用本文： | 李静,吴国柱,王芳,冯德喜,梁丹艳.Logistic回归模型在不典型浸润性导管癌诊断中的应用[J].中国现代医学杂志,2022(2):69-73. |
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| 作者姓名： | 李静 吴国柱 王芳 冯德喜 梁丹艳 |
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| 作者单位： | 内蒙古自治区人民医院 超声医学科， 内蒙古 呼和浩特 010017 |
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| 基金项目： | 内蒙古自治区自然科学基金（No：2017MS0850） |
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| 摘 要： | 目的 筛选不典型浸润性导管癌诊断的超声征象，建立Logistic回归预测模型。方法 回顾性分析42例经超声诊断为BI-RADS 4a类肿块且病理证实为浸润性导管癌患者的术前超声图像。建立Logistic回归模型，绘制ROC曲线，评价该模型的预测价值。结果 多因素Logistic回归分析结果显示：肿块边缘不光整［O^R=23.371（95% CI：2.207，247.442）］、微钙化［O^R=5.120（95% CI：1.481，17.697）］及RI > 0.7［O^R=12.912（95% CI：2.579，46.165）］对不典型浸润性导管癌具有癌诊断意义；利用这3个指标建立不典型浸润性导管癌的诊断模型：Logistics（P）=-1.674+3.152×（微钙化赋值）+1.633×（不光整赋值）+2.390×（RI > 0.7赋值）。模型诊断不典型浸润性导管癌的截断值为> 0.380，ROC曲线下面积为0.804（95% CI：0.711，0.897），敏感性为85.7%（95% CI：0.715，0.956），特异性为59.1%（95% CI：0.432，0.733），约登指数、准确率分别为0.448、72.1%。结论 利用超声征象建立的模型敏感性较高，临床实用性较好。
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| 关 键 词： | 浸润性导管癌 不典型 超声 Logistic模型 |
| 收稿时间： | 2021/8/20 0:00:00 |
Application of Logistic regression model in the diagnosis of atypical invasive ductal carcinoma |
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| Jing Li,Guo-zhu Wu,Fang Wang,De-xi Feng,Dan-yan Liang.Application of Logistic regression model in the diagnosis of atypical invasive ductal carcinoma[J].China Journal of Modern Medicine,2022(2):69-73. |
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| Authors: | Jing Li Guo-zhu Wu Fang Wang De-xi Feng Dan-yan Liang |
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| Affiliation: | Department of Ultrasound, Inner Mongolia People''s Hospital, Hohhot, Inner Mongolia 010017, China |
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| Abstract: | Objective To screen the ultrasound features of atypical invasive ductal carcinoma and to establish Logistic regression prediction models to assist in the diagnosis.Methods The preoperative ultrasound images of 42 cases diagnosed by ultrasound as BI-RADS 4A lesions yet confirmed by pathology as invasive ductal carcinoma, were retrospectively analyzed. Logistic regression models were established, and the receiver operating characteristic curve (ROC) was applied to evaluate the diagnostic efficacy of the models.Results The results of multivariate Logistic regression analysis showed that unclear tumor margin O^R = 23.371 (95% CI: 2.207, 247.442)], microcalcification O^R = 5.120 (95% CI: 1.481, 17.697)] and resistance index (RI) > 0.7 O^R = 12.912 (95% CI: 2.579, 46.165)] were of diagnostic significance for atypical invasive ductal carcinoma. The regression equation of the diagnostic model based on these indicators for atypical invasive ductal carcinoma was Logistics (P) = -1.674 + 3.152 × X1 (microcalcification) + 1.633 × X2 (unclear tumor margin) + 2.390 × X3 (RI > 0.7). When the cut-off value of the diagnostic model was set as 0.380, the area under the ROC curve (AUC) was 0.804 (95% CI: 0.711, 0.897), with a sensitivity of 85.7% (95% CI: 71.5%, 95.6%), a specificity of 59.1% (95% CI: 43.2%, 73.3%), a Youden index of 0.448, and an accuracy of 72.1%.Conclusions The Logistic regression model based on ultrasound signs exhibits a high sensitivity and clinical applicability for the diagnosis of atypical invasive ductal carcinoma. |
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| Keywords: | invasive ductal carcinoma atypical ultrasound Logistic model |
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