Combination of Fluorine-18 Fluorodeoxyglucose Positron-Emission Tomography/Computed Tomography ((18)F-FDG PET/CT) and Tumor Markers to Diagnose Lymph Node Metastasis in Non-Small Cell Lung Cancer (NSCLC): A Retrospective and Prospective Study

BACKGROUND: The early diagnosis of lymph node (LN) metastasis is crucial for patients with non-small cell lung cancer (NSCLC). However, the diagnosis of LN metastasis mainly dependent on (18)F-FDG PET/CT (fluorine-18 fluorodeoxyglucose positron-emission tomography/computed tomography) which exhibited high false positive/negative rate. MATERIAL/METHODS: In retrospective analysis, 135 patients with NSCLC from February 2014 to March 2017 were enrolled. Based on the pathological examination, 71 patients were distributed to the LN Metastasis Group while 64 patients were distributed to the No LN Metastasis Group. Data from (18)F-FDG PET/CT and tumor marker (TM) examination were collected to establish a logistic model. The receiver operating characteristic (ROC) curve analysis set the threshold of diagnostic factors. Finally, the diagnostic values of these factors were verified in a prospective analysis that included 78 patients with NSCLC from July 2017 to April 2019. RESULTS: In our retrospective analysis, compared with the No LN Metastasis Group, the maximum standardized uptake value (SUVmax)/size of primary lesion, the CT value/SUVmax/short diameter of LN, the level of TM were all significantly different than the LN Metastasis Group (All P<0.05). Our logistic model showed that SUVmax of primary lesion (odds ratio [OR]=1.491), short diameter of LN (OR=1.310) and grade of TM (OR=2.927) were significant variables. The ROC curve analysis showed the specificity and sensitivity of our logistic model was 90.6% and 90.1%, respectively. In our prospective analysis, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the logistic model were calculated as 85.7%, 90.9%, 87.2%, 96.0%, and 71.4%, respectively. CONCLUSIONS: Our study found that combining (18)F-FDG PET/CT data and TM to establish a logistic model performed better in the diagnosis of LN metastasis with low false positive/negative rates in patients with NSCLC.