Data Sheet 1_Development and validation of a predictive nomogram for high-risk thyroid nodules: a retrospective analysis of sedentary time, insomnia, and elevated weight.pdf

BackgroundThyroid nodules are widely regarded as one of the most prevalent endocrine disorders, and high-risk thyroid nodules are gradually gaining attention due to their potential malignancy. Early detection and active intervention are key to improving prognosis. Therefore, establishing a predictive model for assessing the risk of high-risk thyroid nodules is crucial for adjunctive diagnosis.
MethodsThe clinical data of patients with thyroid nodules admitted to the Hospital of Chengdu University of Traditional Chinese Medicine from October 2023 to June 2024 were retrospectively analyzed. According to the Thyroid Imaging Reporting and Data System classification, the patients were divided into a low-to-moderate risk group and a high-risk group. Multivariate logistic regression analysis was used to explore the influencing factors of high-risk thyroid nodules, and a nomogram was constructed. Internal validation was conducted using bootstrap resampling methods. The predictive performance of the model was evaluated by comparing the area under the receiver operating characteristic curve, the calibration curve, and the decision curve.
ResultsA total of 164 patients with thyroid nodules were included in this study, with an average age of 42.31 years. Among them, 101 patients (61.59%) were diagnosed as high-risk for thyroid nodules. Dietary diversity score (OR: 0.773, 95% CI = 0.639-0.934) and nodule diameter (OR: 0.909, 95% CI = 0.871-0.95) were protective factors for high-risk thyroid nodules, while sedentary time of more than two hours per day (OR: 2.8, 95% CI = 1.276-6.148), the Athens Insomnia Scale score (OR: 1.078, 95% CI = 1.01-1.15), and elevated weight (OR: 1.049, 95% CI = 1.008-1.09) were independent risk factors (all P<0.05).
ConclusionThe nomogram model we constructed shows good predictive performance for high-risk thyroid nodules after internal validation, and may serve as a practical tool to guide the formulation of disease prevention strategies.