A novel nomogram to predict lymph node metastasis in cT1 non-small-cell lung cancer based on PET/CT and peripheral blood cell parameters

BACKGROUND: Accurately evaluating the lymph node status preoperatively is critical in determining the appropriate treatment plan for non-small-cell lung cancer (NSCLC) patients. This study aimed to construct a novel nomogram to predict the probability of lymph node metastasis in clinical T1 stage patients based on non-invasive and easily accessible indicators. METHODS: From October 2019 to June 2022, the data of 84 consecutive cT1 NSCLC patients who had undergone PET/CT examination within 30 days before surgery were retrospectively collected. Univariate and multivariate logistic regression analyses were performed to identify the risk factors of lymph node metastasis. A nomogram based on these predictors was constructed. The area under the receiver operating characteristic (ROC) curve and the calibration curve was used for assessment. Besides, the model was confirmed by bootstrap resampling. RESULTS: Four predictors (tumor SUVmax value, lymph node SUVmax value, consolidation tumor ratio and platelet to lymphocyte ratio) were identified and entered into the nomogram. The model indicated certain discrimination, with an area under ROC curve of 0.921(95%CI 0.866–0.977). The calibration curve showed good concordance between the predicted and actual possibility of lymph node metastasis. CONCLUSIONS: This nomogram was practical and effective in predicting lymph node metastasis for patients with cT1 NSCLC. It could provide treatment recommendations to clinicians.