JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES) ›› 2017, Vol. 55 ›› Issue (4): 60-64.doi: 10.6040/j.issn.1671-7554.0.2016.828

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Establishment and preliminary evaluation of a model for predicting the malignant probability of solitary pulmonary nodule with tumor markers

LI Xiaoying1, LIU Fang2, CHE Haijie3, ZHANG Jinhui4   

  1. 1. Department of Respiration, Yantai Affiliated Hospital of Binzhou Medical University, Yantai 264100, Shandong, China;
    2. Department of Statistics, Yantai Affiliated Hospital of Binzhou Medical University, Yantai 264100, Shandong, China;
    3. Department of Vascular Surgery, Yantai Yuhuangding Hospital, Yantai 264000, Shandong, China;
    4. Department of Respiration, The Sencond Affiliated Hospital of Dalian Medical University, Dalian 116023, Liaoning, China
  • Received:2016-07-11 Online:2017-04-10 Published:2017-04-10

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Abstract: Objective To establish a model for predicting the malignant probability of solitary pulmonary nodule(SPN)with the tumor markers and to evaluate its clinical value. Methods A retrospective cohort study in Yantai Yuhuangding Hospital of Shandong Province included 250 patients with definite pathological diagnosis of SPN from Jan. 2010 to Oct. 2015. Clinical data included age, gender, quantity of smoking history, symptoms, site, maximum diameter, the levels of CEA, CYFRA21-1 and NSE. By means of Logistic regression, 9 factors were analyzed to establish the model. Receiver operating characteristic curve(ROC)was performed and the area under the curve(AUC)was calculated. Our model was compared with the Mayo model to evaluate its clinical value. Results CEA level(P=0.002, OR=5.921, 95%CI=1.968-17.819), CYFRA21-1 level(P=0.046, OR=2.500, 95%CI=1.018-6.142), symptom 山 东 大 学 学 报 (医 学 版)55卷4期 -李笑莹,等.肿瘤标志物预测孤立性肺结节恶性概率模型的建立与初步评价 \=-(P=0.010, OR=2.384, 95%CI=1.234-4.607)and maximum diameter(P=0.001, OR=2.331, 95%CI=1.441-3.773)were associated with malignant SPN. Our prediction model: P=ex/(1+ex), X=-1.991+0.869×symptom+0.846×maximum diameter+1.779×CEA+0.916×CYFRA21-1. The goodness-of-fit of the model was fairly good. When the optimal cut-off point was 0.636, the sensitivity was 63.5% and specificity was 71.2%. The difference of AUC between our model and the Mayo clinic model was not statistically significant(P>0.05). Conclusion CEA, CYFRA21-1, symptom and maximum diameter are independent risk factors of malignant SPN. Our research shows that the Logistic regression model has high accuracy and clinical value.

Key words: Solitary pulmonary nodule, Tumor markers, Logistic regression model

CLC Number: 

  • R734.2
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