Monocyte-to-High-Density Lipoprotein Cholesterol Ratio Together With the Lymphocyte-to-Monocyte Ratio in Predicting the Malignancy of the Thyroid Nodule in Patients Complicated With Type 2 Diabetes.

Abstract

Thyroid nodules, although mostly benign and symptomless, have a small chance of being cancerous, necessitating accurate diagnosis. This study aims to develop and validate a nomogram for differentiating malignant and non-malignant thyroid nodules in individuals with type 2 diabetes. The study included 484 patients with both thyroid nodules and type 2 diabetes who underwent thyroid gland lobectomy at Wenzhou Medical University Hospital. Optimal cutoff values for continuous variables were determined using ROC curve analysis. Significant factors identified in univariable analysis were used to construct the nomogram. The monocyte-to-high-density lipoprotein cholesterol ratio (MHR) was visualized through a histogram and scatter diagram. Discriminatory power was assessed using ROC analysis, and calibration curves ensured consistency. Decision curve analysis (DCA) evaluated clinical benefits. The cohort was divided into a training group (70%) and an internal validation group (30%). The scatter diagram revealed a correlation between MHR levels and the proportion of goiter cases, with higher MHR levels associated with increased goiter incidence. The histogram showed higher average MHR levels in goiter patients compared to those with papillary thyroid carcinoma (PTC) in both groups. Multivariate logistic regression identified age, total cholesterol (TC), triglyceride (TG), fasting blood sugar (FSG), fibrinogen, lymphocyte-to-monocyte ratio (LMR), and MHR as independent predictive factors for malignancy in thyroid nodules with type 2 diabetes. The nomogram achieved high discrimination, with C-index values of 0.901 (training data set) and 0.760 (internal validation data set). Calibration curves displayed good agreement, and DCA demonstrated significant net clinical benefits. MHR is associated with sex, serum cholesterol levels, and peripheral blood cell counts, making it a potential novel biomarker for differentiating between PTC and goiter in type 2 diabetes patients.