OBJECTIVES
We recently reported a high rate of nontherapeutic thymectomy. Mediastinal lymphomas are the malignancies most likely to be confused with thymic epithelial tumors. This study aimed to establish a predictive model by evaluating clinical variables and positron emission tomography to distinguish those diseases.
METHODS
From 2018 to 2021, consecutive patients who were pathologically diagnosed with thymic epithelial tumors or mediastinal lymphomas were retrospectively reviewed. Univariable and multivariable analyses were used to identify association factors. The Akaike information criterion was used to select variables. A nomogram was developed and validated to differentiate mediastinal lymphomas from thymic epithelial tumors.
RESULTS
A total of 198 patients were included. Compared with thymic epithelial tumors, patients with mediastinal lymphomas were more likely to be younger with higher metabolic tumour volume (154.1 versus 74.6 cm3), total lesion glycolysis (1388.8 versus 315.2 g/mL cm3), SUVmean (9.2 versus 4.8), SUVpeak (12.9 versus 6.3), and SUVmax (14.8 versus 7.5). A nomogram was established based on the stepwise regression results and the final model containing age and SUVmax had minimal Akaike information criterion value of 72.28. Receiver operating characteristic analyses indicated the area under the curve of predictive nomogram in differentiating MLs from TETs was 0.842 (95% CI: 0.754 – 0.907). The internal bootstrap resampling and calibration plots both demonstrated good consistence between the prediction and the observation.
CONCLUSIONS
Combination of age and SUVmax appears to be a useful tool to differentiate mediastinal lymphomas from thymic epithelial tumors. The novel predictive model prevents more patients from receiving nontherapeutic thymectomy.