Objective:To explore the predictive value of a model based on serum metabolic markers in predicting the risk of lymph node metastasis in patients with thyroid cancer(TC). Methods:A total of 207 patients who were diagnosed with TC in our hospital from January 2020 to January 2021 were selected for surgical treatment, then 20% of the patients were selected as the validation set by random number table method, and the remaining 80% were used as the training set for comparison to establish a prediction model. According to imaging data and intraoperative pathological examination results of specimens, all patients were divided into metastatic group and non-metastatic group. All of the patients' clinical data, laboratory examination and imaging examination results were collected. Peripheral venous blood was drawn from patients before the operation to detect the levels of 3-hydroxybutyric acid(BHB), docosahexaenoic acid(DHA) and pregnadiol-3-glucuronic acid(PdG). The logistic model was used to analyze the factors related to lymph node metastasis, then the prediction model was established through the nomogram and the prediction effectiveness was verified. Results:The patients in the metastatic group were older than those in the non-metastatic group, and the proportion of Hashimoto's thyroiditis history was higher than that in the non-metastatic group. The difference was statistically significant(P<0.05). The levels of TSH, TGAb, BHB and DHA of the metastatic group were higher than those of the non-metastatic group, while PdG was lower than that of the non-metastatic group, the difference being statistically significant(P<0.05). The maximum diameter of the tumor in the metastatic group was larger than that in the non-metastatic group. There were differences in the number of tumors, morphology, association with enveloping membrane, and blood flow between the two groups, and the difference was statistically significant(P<0.05). The results showed that age, BHB, DHA, PdG, the maximum diameter of tumor, and the relationship with the enveloping membrane were the related factors that affect TC lymph node metastasis(P<0.05). The C-index of the nomogram model in predicting the occurrence of TC lymph node metastasis was 0.924(95% CI 0.901-0.974), and the calibration curve showed that the absolute error of the nomogram model prediction probability was 0.025, which showed a good consistency. Conclusion:The model established based on serum metabolic indicators has a certain value in the prediction of TC lymph node metastasis, and can provide reference for clinical diagnosis and surgical options.
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