The Risk Evaluation Of Thyroid Nodule Based On The Components Of Metabolic Syndrome And Urine Iodine

Part ⅠRelationship between the Prevalence of Thyroid Nodules and Metabolic Syndrome:A cross-sectional studyObjectiveTo investigate the correlations between the prevalence of thyroid nodules (TN) and metabolic syndrome (MetS).Material and MethodA cross-sectional study analyzed19622subjects of medical data in Hangzhou area from January to December2009in the second affiliated hospital Zhejiang university school of medicine. All of those subjects were asked to fill the questionnaire, voluntarily underwent general health screening, which included thyroid ultrasound, the parameters of thyroid function, thyroid autoantibodies, and anthropometric data including waist circumference (WC), height, weight,systolic blood pressure (SBP), diastolic blood pressure (DBP)), and laboratory data. The sera were measured for fasting plasma glucose (FPG), fasting insulin (FINS), triglyceride (TG), HDL-cholesterol (HDL-C), Total tetraiodothyronine(TT4), Free tetraiodothyronine (FT4), Total triiodothyronine (TT3), Free triiodothyronine (FT3), thyrotropin (TSH), thyroid globulin (Tg), antithyroglobulin antibody (TG-Ab), thyroid peroxidase antibody (TPO-Ab) Homeostasis model assessment for insulin resistance (HOMA-IR) was calculated by dividing the product of FBG (mmol/L) and FINS (mIU/L) by22.5. Body mass index (BMI) was cauculated as the ratio between weight and height squared (kg/m2). The Metabolic Syndrome Was defined according toMetS was defined according to2004the Chinese Diabetes Society (CDS) criteria. Subjects with any of the following characteristics were excluded from the study:(a) individuals with history of thyroid diseases including thyroid cancer and Hashimoto’s thyroiditis highly suggested by ultrasound and laboratory data;(b) individuals with history of thyroid therapy at any time including medicines (L-thyroxine, antithyroid gland medicine), operation, or radiotherapy for head and neck;(c) individuals with some chronic diseases (hepatic or renal dysfunction, cardiac failure);(d) pregnant or women in a year postpartum;(e) individuals with significant mental or neurological disorders (depression, epilepsy, and schizophrenia);(f) individuals with history of other endocrine diseases or autoimmune diseases;(g) individuals with history of cancer(s);(h) individuals with iodinated contrast material exposure in the previous6months;(i) individuals with history of taking amiodarone. In the end,13522participants (8926men,4596women) were included, who aged between20and90years. Subjects were divided into MetS(+) group and MetS(-) group according to2004CDS criteria. Subjects were also divided into TN(+) group and TN(-) group according to whether or not with TN.Results1. The prevalence of TN:The crosssectional study included a total of13522participants (8926men and4596women). The prevalence of TN was34.97%(33.97%for men and36.92%for women).2. The standardized prevalence rate of TN was33.70%(31.82%for men and35.35%for women), which was calculated from the population distribution in China, Hangzhou, in2009. 3. Comparison the prevalence of TN in gender:The prevalence of TN for women was statistically higher than for men in the age ranges40to59and>70(χ2=11.651, P=0.001)4. The prevalence of TN increased along with increased age (trend χ2test:χ2=1200.33for both sexes, P<0.001; χ2=515.22for men, P<0.001; χ2=921.56, P<0.001for women).5. The Relationship between TN and MetS:According to the standard of the CDS, the prevalence of TN in the MetS (+) group was higher than that in the MetS (-) group (χ2=69.63for both sexes, P<0.001; χ2=50.80for men, P<0.001; χ2==33.10for women, P<0.001).6. The Relationship between TN and Metabolic Components using univariate binary logistic regression analysis:SBP, DBP, WC, BMI, FBG, FINS, HOMA-IR were the risk factors for the prevalenceof TN. When adjusted for age and gender, the risk factors for the prevalenceof TN were SBP, DBP, WC, BMI, FINS, HOMA-IR. After adjusted for age, gender, TSH and TT4, the risk factors for the prevalence of TN were SBP, DBP, WC, BMI, FINS, HOMA-IR. When adjusted for other parameter such as FT3or FT4or TT3or TT4or TSH, WC and BMI were the independent risk factors for the prevalence of TN.7. The Relationship between TN and Metabolic Components using multivariate binary logistic regression analysis:The results were almost consistent with the multivariate binary logistic regression analysis when either the enter method or the forward LR method or the Backward LR method was use, age, gender, WC, BMI, TT4and FT3were the risk factors for the prevalenceof TN.Conclusions1. The prevalence of TN for women was statistically higher than for men in the age ranges40to59and>70.2. The prevalence of TN increased along with increased age. 3. The prevalence of TN in the MetS (+) group was higher than that in the MetS (-) group.4. WC and BMI were independent risk factors for the prevalence of TN. Part ⅡAnalysis the value of B ultrasound and TG-Ab for the diagnosis of thyroid cancer and Hashimoto’s thyroiditisObjective:To evaluate the value of B ultrasound (BU) for the diagnosis of thyroid cancer, and the value of the combination of BU and thyroglobulin antibodies (TG-Ab) for the diagnosis of Hashimoto’s thyroiditis.Method:A total of431subjects who had thyroid disease and were the first time hospitalized in the surgery department of the second affiliated hospital Zhejiang university school of medicine between September2013and December2014.334of the control group subjects, who were come from the same hospital for health examination and had no thyroid disease, were recruited at the same time. To analyzed the data of surgery patients’preoperative diagnosis of BU and TG-Ab and postoperative pathologic diagnosis. A ROC curve and Kappa test were used to verify the value of BU and TG-Ab for evaluation of thyroid cancer and hashimoto’s thyroiditis. Such as Sensitivity, False Positive, False Negative, Specificity, Positive Predictive Value and Negative Predictive Value were calculated.Results:Sensitivity, False Positive, False Negative, Specificity, Positive Predictive Value and Negative Predictive Value for BU diagnosis of differentiated thyroid cancer were92.9%,2.5%,7.1%,97.5%,98.1%,91.1%, respectively. AUC value was0.913and Kappa value was0.897. Sensitivity, False Positive, False Negative, Specificity, Positive Predictive Value and Negative Predictive Value for BU alone diagnosis of Hashimoto’s thyroiditis were46.0%,3.7%,54.0%,96.3%,52.7%,95.2%, respectinely. AUC value was0.712and Kappa value was0.449. Combining BU and TG-Ab, Sensitivity, False Positive, False Negative, Specificity, Positive Predictive Value and Negative Predictive Value were81.0%,13.5%,19.0%,86.5%,34.9%,98.1%, respectinely. AUC value was0.814, Kappa value was0.421.Conclusion:The diagnosis value is high for BU alone on differentiated thyroid cancer. The power of excluding thyroid cancer is91.1%if the diagnosis of BU is negative. The diagnosis value of BU on Hashimoto’s thyroiditis is not so good as the combination BU and TG-Ab. The power of excluding thyroid cancer is98.1%if the combined diagnosis is negative. Part ⅢMultifactor analysis of urinary iodine and metabolic syndrome with nodular goiterObjective:To analyze the multifactor correlation of urinary iodine and components of metabolic syndrome with nodular goiter and establish the multifactor risk model.Method:A nested case-control study. A total of88patients who had thyroid disease and were the first time hospitalized in the surgery department of the second affiliated hospital Zhejiang university school of medicine and finally diagnosed as nodular goiter (including cystic degeneration) by pathology after operation between September2013and December2014.334of the control group subjects, who were come from the same hospital for health examination and had no thyroid disease, were recruited at the same time. Logistic regression analysis was applied to analyze the risk factors of nodular goiter. The multiple regression model was used to establish the regression equation of nodular goiter.Results:When using univariate logistic regression analysis, female and urinary iodine were the risk factors for nodular goiter (OR=4.65, P<0.001; OR=1.004, P<0.001; respectively). When using multivariate logistic regression analysis, female, urinary iodine, DBP were the risk factors for nodular goiter (OR=6.45, P<0.001; OR=1.002, P<0.001; OR=1.108) P<0.001, respectively). Patients with nodular goiter had a higher level within the reference range of serum FT4, thyroglobulin, and thyroid globulin antibody, while had a lower level within the reference range of serum TSH. DBP was the largest contribution to nodular goiter with maximum absolute value of standardized regression coefficient, and other contributions were gender, urinary iodine, successively.Conclusion:Women, high urinary iodine, high DBP were the risk factors for nodular goiter. BMI was protective factors. Part ⅣMultifactor analysis of urinary iodine and metabolic syndrome with differentiated thyroid cancerObjective:To analyze the multifactor correlation of urinary iodine and components of metabolic syndrome with differentiated thyroid cancer (DTC) and establish the multifactor risk model.Method:A nested case-control study. A total of174patients who had thyroid disease and were the first time hospitalized in the surgery department of the second affiliated hospital Zhejiang university school of medicine and finally diagnosed as DTC by pathology after operation between September2013and December2014.334of the control group subjects, who were come from the same hospital for health examination and had no thyroid disease, were recruited at the same time. Logistic regression analysis was applied to analyze the risk factors of DTC. The multiple regression model was used to establish the regression equation of DTC.Results:When using univariate logistic regression analysis, female, urinary iodine, SBP were the risk factors for DTC (OR=2.53, P<0.001; OR=1.002, P<0.001; OR=1.017, P=0.034, respectively). Serum TT3,TT4,FT4, Tg,TG-Ab,TPO-Ab in the group of DTC were higher than which in the control group,while serum TSH in the group of DTC were lower than which in the control group. When using multivariate logistic regression analysis, female, urinary iodine, DBP were the risk factors for DCT (OR=4.46, P<0.001;OR=1.002, P<0.001;OR=1.117, P<0.001, respectively). Male was protective factors (OR=0.944, P<0.001). Serum TT3, TT4, FT4, Tg and TG-Ab in the group of DTC were higher than which in the control group, while serum TSH in the group of DTC were lower than which in the control group. DBP was the largest contribution to DTC with maximum absolute value of standardized regression coefficient, and other contributions were SBP, gender and urinary iodine, successively.Conclusion:Female, high urinary iodine, high DBP were the risk factors for DTC and high DBP was the largest contribution to DCT. Part ⅤThe differences between differentiated thyroid carcinoma and nodular goiter in urinary iodine and metabolic syndromeObjective:To analyze the differences between differentiated thyroid carcinoma (DTC) and nodular goiter in urinary iodine and the components of metabolic syndrome.Method:A nested case-control study.174patients who had thyroid disease and were the first time hospitalized in the surgery department of the second affiliated hospital Zhejiang university school of medicine and finally diagnosed as DTC by pathology after operation between September2013and December2014. At the same time,88patients were diagnosed as nodular goiter by pathology after operation. Compare the differences of urine iodine and the components of metabolic syndrome between the two groups.101patients were diagnosed as nodular goiter with DTC by pathology after operation. Compare the differences of urine iodine and components of metabolic syndrome between nodular goiter and nodular goiter with DTC, too. Logistic regression analysis was applied to analyze the differences between the two groups.Results:The differences between nodular goiter and DTC were gender, BMI and HDL-c. There were no differences in urine iodine and thyroid function. DTC had higher proportion of female, larger BMI and lower HDL-c. The difference between nodular goiter and nodular goiter with DTC was BMI. There were no differences in urine iodine and the components of metabolic syndrome. Nodular goiter with DTC had larger BMI. Conclusion:There was a significant difference in BMI between nodular goiter and DTC and the latter had larger BMI. There were no differences in urine iodine and components of metabolic syndrome. Part ⅥRetrospective cohort study on the relationship between new thyroid nodule and metabolic syndromeObjective:To analyze the relationship between components of metabolic syndrome and new thyroid nodule (TN).Method: A total of1061participants, who were come from the second affiliated hospital Zhejiang university school of medicine for health examination and had no thyroid disease, were recruited in2009and follow-up3-year. To analyze the relationship between components of metabolic syndrome and new TN.Results:When not adjusted for age and gender, participants with metabolic syndrome, higher BMI and greater WC or hypertension in2009had higher rate of new TN in2012. There was statistical difference between them. When adjusted for gender, male participants with metabolic syndrome, higher BMI and greater WC in2009had higher rate of new TN in2012. There was statistical difference between them. Female did not have this difference. When using multivariate binary logistic regression analysis, male higher BMI in2009is the risk factor for new TN in2012(OR=1.524, P=0.006). Female hypertention in2009is the risk factor for new TN in2012(OR=1.802, P=0.036). Among MetS, MetS-related components and WC, men with the progress of MetS and higher blood lipid may contribute to increase the rate of new TN, while women with the progress of blood pressure and blood suger and lower HDL-c may contribute to increase the rate of new TN. When using multivariate binary logistic regression analysis, elevated triglyceride is independent risk factor for new TN (OR=1.001, P=0.035). Conclusions:Men with higher BMI or elevated triglyceride may contribute to increase the rate of new TN. Women with high blood pressure or the progress of blood pressure and blood suger and lower HDL-c may contribute to increase the rate of new TN. Eevated triglyceride is independent risk factor for new TN.