0.05) in the maimed group, indignation score was high, depression score was low and self-esteem score was high ( P

Lung cancer is the most common cancer and the leading cause of cancer death. Non-small cell lung cancer (NSCLC) represents over 85% of all lung cancers, and up to 50% of Asian NSCLC patients harboring epidermal growth factor receptor (EGFR) gene mutations. A number of studies have consistently demonstrated that uncommon EGFR-mutated NSCLC patients treated with EGFR-tyrosine kinase inhibitors (EGFR-TKIs) can achieve better survival outcomes. However, because uncommon EGFR mutations are generally associated with reduced sensitivity to EGFR-TKIs, which will bring a negative impact on the result of the study, the majority of clinical trials investigating the efficacy of EGFR-TKIs have included only patients with common EGFR mutations. In addition, uncommon EGFR mutations are rare in themselves, leading to the small number of such patients enrolled in these trials. Due to the small number and highly heterogeneous sensitivity of uncommon EGFR mutations, the efficacy of EGFR-TKIs in patients harboring uncommon EGFR mutations remains elusive. This article reviews the efficacy of EGFR-TKIs in patients with uncommon EGFR mutations, and give some reasonable advice about the selection of treatments for patients with NSCLC who harbor uncommon EGFR mutations.

Objective    To analyze the correlation between folate receptor-positive circulating tumor cells (FR+CTC) and the benign or malignant lesions of the lung, and to establish a malignant prediction model for pulmonary neoplasm based on clinical data, imaging and FR+CTC tests. Methods    A retrospective analysis was done on 1 277 patients admitted to the Affiliated Hospital of Qingdao University from September 2018 to December 2019, including 518 males and 759 females, with a median age of 57 (29-85) years. They underwent CTC examination of peripheral blood and had pathological results of pulmonary nodules and lung tumors. The patients were randomly divided into a trial group and a validation group. Univariate and multivariate analyses were performed on the data of the two groups. Then the nomogram prediction model was established and verified internally and externally. Receiver operating characteristic (ROC) curve was used to test the differentiation of the model and calibration curve was used to test the consistency of the model. Results    Totally 925 patients suffered non-small cell lung cancer and 113 patients had benign diseases in the trial group; 219 patients suffered non-small cell lung cancer and 20 patients had benign diseases in the verification group. The FR+CTC in the peripheral blood of non-small cell lung cancer patients was higher than that found in the lungs of the patients who were in favorite conditions (P<0.001). Multivariate analysis showed that age≥60 years, female, FR+CTC value>8.7 FU/3 mL, positive pleural indenlation sign, nodule diameter, positive burr sign, consolidation/tumor ratio<1 were independent risk factors for benign and malignant lung tumors with a lesion diameter of ≤4 cm. Thereby, the nomogram prediction model was established. The area under the ROC curve (AUC) of the trial group was 0.918, the sensitivity was 86.36%, and the specificity was 83.19%. The AUC value of the verification group was 0.903, the sensitivity of the model was 79.45%, and the specificity was 90.00%, indicating nomogram model discrimination was efficient. The calibration curve also showed that the nomogram model calibration worked well. Conclusion    FR+CTC in the peripheral blood of non-small cell lung cancer patients is higher than that found in the lungs of the patients who carry benign pulmonary diseases. The diagnostic model of clinical stage Ⅰ non-small cell lung cancer established in this study owns good accuracy and can provide a basis for clinical diagnosis.