Glucose-to-Lymphocyte Ratio (GLR) as a Predictor of Preoperative Central Lymph Node Metastasis in Papillary Thyroid Cancer Patients With Type 2 Diabetes Mellitus and Construction of the Nomogram

Abstract

BackgroundDetection of metastasis of central lymph nodes in papillary thyroid cancer is difficult before surgery. The role of routine or preventive central lymph node dissection in the management of papillary thyroid cancer remains inconclusive. Moreover, glucose metabolism and systemic inflammation are related to the aggressiveness of several malignant tumors and the prognoses of these patients. This study aimed to construct a nomogram based on the readily available preoperative clinical features for predicting the occurrence of preoperative central lymph node metastasis in patients with papillary thyroid cancer and type 2 diabetes mellitus. The findings may underlie clinical implications for determining the appropriate treatment strategies for these patients.MethodsA total of 419 patients were enrolled. We used the receiver operating characteristic curves to determine the best cut-off value and converted the continuous into categorical variables. Next, a single-factor logistic analysis for the independent variables was performed, following which a multivariate regression analysis was conducted for the selected significant risk factors. Finally, the nomogram was constructed and verified using external data; the existing data were compared with the original model.ResultsAccording to the receiver operating characteristic curves, the best cut-off values ​​for glucose-to-lymphocyte ratio and tumor size were 4.23 cm and 0.95 cm, respectively. Findings from the multivariate logistic regression analysis suggested that age, bilateral tumors, maximum tumor size, and the ratio of glucose-to-lymphocytes were independent risk factors for preoperative central lymph node metastasis. The C-indexes in the training and the external validation data sets were 0.733 and 0.664, respectively. Both calibration curves and the Hosmer-Lemeshow tests indicated that the model was well-calibrated. Through decision curve analysis, the predictive model was estimated to have strong clinical applicability and greater benefits. To compare the performance of the new with that of the original model, we performed a net reclassification index and the integrated discrimination improvement analyses, both of which indicated that the new model had a better predictive ability.ConclusionIn patients with type 2 diabetes mellitus and papillary thyroid cancer, a high preoperative glucose-to-lymphocyte ratio was an independent predictor of the preoperative central lymph node metastasis. The nomogram so constructed could better predict the preoperative central lymph node metastasis in these patients.