关键词: 乳腺肿瘤, 癌胚抗原, 诊断，鉴别, 中性粒细胞与淋巴细胞比值, 凝血指标

Abstract:

Objective To explore the value of neutrophil to lymphocyte ratio （NLR）， carcinoembryonic antigen （CEA） combined with coagulation indicators prothrombin time （PT）， activated partialthromboplastin time （APTT）， thrombin time （TT）， fibrinogen （FIB） in the differential diagnosis of benign and malignant breast nodules with a diameter of ≤1.0 cm. Methods Patients with breast nodule diameter ≤1.0 cm who underwent physical examination in the Cancer Hospital of Xinjiang Medical University from January 2017 to March 2023 were selected as the study objects. Patients admitted from January 2017 to June 2020 were defined as the training set， and patients admitted from July 2020 to March 2023 were defined as the validation set. In the training set， there were 83 patients with benign breast nodules and 106 patients with breast cancer； In the validation set， there were 109 patients with benign breast nodules and 136 patients with breast cancer. The influencing factors of benign and malignant breast nodules were analyzed by logistic regression. Binary logistic regression was used to construct the diagnosis and prediction model of benign and malignant breast nodules. Receiver operating characteristic （ROC） curve was used to evaluate the diagnostic performance of each index and diagnostic prediction model for benign and malignant breast nodules. Results There were statistically significant differences between patients with benign breast nodules and patients with breast cancer in the training and validation sets in neutrophils（t=6.76， P<0.001； t=9.14， P<0.001）， lymphocytes （t=7.67， P<0.001； t=17.00， P<0.001）， NLR（t=13.97， P<0.001； t=17.41， P<0.001）， CEA （t=33.44， P<0.001； t=8.15， P<0.001）， PT （t=15.81， P<0.001； t=60.15， P<0.001）， APTT （t=39.50， P<0.001； t=16.34， P<0.001）， TT （t=13.34， P<0.001； t=14.37， P<0.001）， FIB （t=16.66， P<0.001； t=20.30， P<0.001）. The results of univariate analysis showed that neutrophils （OR=3.52， 95%CI： 1.26-5.37， P=0.036）， lymphocytes （OR=2.64， 95%CI： 1.52-3.72， P=0.033）， NLR （OR=1.96， 95%CI： 1.15-3.42， P<0.001）， CEA （OR=2.16， 95%CI： 1.29-3.05， P<0.001）， PT （OR=1.75， 95%CI： 1.17-2.69， P<0.001）， APTT （OR=3.11， 95%CI： 1.55-5.38， P<0.001）， TT （OR=2.59， 95%CI： 1.38-4.11， P<0.001）， FIB （OR=2.89， 95%CI： 1.36-4.55， P<0.001） were all influencing factors that affected the benign and malignant breast nodules with a diameter ≤1.0 cm. The results of multivariate analysis showed that NLR （OR=2.06， 95%CI： 1.32-2.76， P<0.001）， CEA （OR=1.19， 95%CI： 1.09-1.37， P=0.008）， PT （OR=1.63， 95%CI： 1.05-2.11， P<0.001）， APTT （OR=1.52， 95%CI： 1.13-2.34， P<0.001）， TT （OR=1.64， 95%CI： 1.14-2.74， P<0.001）， FIB （OR=1.42， 95%CI： 1.11-1.89， P<0.001） were all independent influencing factors on the benign and malignant breast nodules with a diameter ≤1.0 cm. ROC curve analysis results showed that the area under curve （AUC） of NLR， CEA， PT， APTT， TT， FIB in the diagnosis of breast cancer was 0.83， 0.65， 0.69， 0.72， 0.73， 0.70 respectively， in the training set. The sensitivity of NLR in the diagnosis of breast cancer was 76%， and the specificity was 69%. A diagnostic prediction model was established based on statistically significant indicators in multivariate analysis， with logit （P）=1.76×NLR+21.42×CEA+5.14×PT+5.34×APTT+5.78×TT+6.52×FIB. ROC curve analysis showed that the AUC of the diagnostic prediction model used for patient differential diagnosis in the training and validation sets was 0.81 and 0.80 respectively. The AUC of diagnosis prediction model for breast cancer diagnosis of patients aged ≤60 years old and >60 years old was 0.79 and 0.77 respectively， with sensitivity of 82% and 80%， specificity of 75% and 83% respectively. The AUC of diagnosis prediction model for breast cancer with tumor diameter <0.3 cm， 0.3-0.6 cm and 0.7-1.0 cm was 0.63， 0.74 and 0.91 respectively， with sensitivity of 68%， 73%， 81%， and specificity of 72%， 77%， 84%. Conclusion NLR， CEA， PT， APTT， TT and FIB are all independent influencing factors that affect the benign and malignant breast nodules with a diameter ≤1.0 cm. The prediction model constructed by NLR and CEA combined with coagulation indexes PT， APTT， TT and FIB has high diagnostic efficiency for benign and malignant breast nodules with a diameter ≤1.0 cm.

Key words: Breast neoplasms, Carcinoembryonic antigen, Diagnosis， differential, Neutrophil to lymphocyte ratio, Coagulation indicators