The aim of our study was to address the potential for improvements in thyroid cancer detection in routine clinical settings using a clinical examination, the American College of Radiology Thyroid Imaging Reporting and Database System (ACR TI-RADS), and fine-needle aspiration cytology (FNAC) concurrently with molecular diagnostics. A prospective cohort study was performed on 178 patients. DNA from FNA samples was used for next-generation sequencing to identify mutations in the genes BRAF, HRAS, KRAS, NRAS, and TERT. RNA was used for real-time PCR to detect fusion genes. The strongest relevant positive predictors for malignancy were the presence of genetic mutations (p < 0.01), followed by FNAC (p < 0.01) and ACR TI-RADS (p < 0.01). Overall, FNAC, ACR TI-RADS, and genetic testing reached a sensitivity of up to 96.1% and a specificity of 88.3%, with a diagnostic odds ratio (DOR) of 183.6. Sensitivity, specificity, and DOR decreased to 75.0%, 88.9%, and 24.0, respectively, for indeterminate (Bethesda III, IV) FNAC results. FNA molecular testing has substantial potential for thyroid malignancy detection and could lead to improvements in our approaches to patients. However, clinical examination, ACR TI-RADS, and FNAC remained relevant factors.

Objective: Patients with type 2 diabetes (T2DM) generally experience a higher incidence of cancer. However, the association between T2DM and thyroid cancer is inconclusive. Methods: Case-control prospective study, where 722 patients were screened for T2DM and prediabetes (PDM) and underwent thyroid ultrasound and biochemical tests. The patients were assigned to groups of PDM (n = 55), T2DM (n = 79) or a non-diabetes group (NDM) (n = 588). Fine-needle aspiration biopsy was carried out in 263 patients. Histological examinations were done for 109 patients after surgery, with findings of 52 benign (BS) and 57 malignant tumors (MS). Results: Thirty-three percent of patients with T2DM and especially PDM were newly diagnosed by our screening: 6.5% with T2DM and 72% with PDM, respectively. The percentage of thyroid cancers did not significantly differ between the groups (χ² test = 0.461; P = 0.794). Relevant positive thyroid predictors for T2DM (t-statistic = 25.87; P < 0.01) and PDM (21.69; P < 0.01) contrary to NDM (−26.9; P < 0.01) were thyroid volume (4.79; P < 0.01), thyroid nodule volume (3.25; P < 0.01) and multinodular thyroid gland (4.83; P < 0.01), while negative relevant predictors included the occurrence of autoimmune thyroid disease (AITD) (−2.01; P < 0.05). Conclusion: In general, we did not observe an increased risk for thyroid cancer in the diabetic and prediabetic groups in comparison to controls, in spite of well-established increased risk for other malignancies. Structural and benign changes such as larger and multinodular thyroid glands, in comparison to autoimmune thyroid disease, are present more often in diabetics.

The aim of this prospective study was the validation of the risk stratification of thyroid nodules using ultrasonography with the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) and partly in comparison to American Thyroid Association (ATA) guidelines in a secondary referral center. Fine needle aspiration biopsy (FNA) (n=605) and histological examinations (n=63) were the reference standards for the statistical analysis. ACR TI-RADS cut-off value: TR4 with sensitivity 85.7 %, specificity 54.1 %, PPV 58.5 %, accuracy 67.7 % (AUC 0.738; p<0.001). ATA cut-off value: “high suspicion” with sensitivity 80 %, specificity 83.3 %, PPV 80 %, accuracy 81.8 % (AUC 0.800; p=0.0025). 18.4 % nodules (3 malignant) could not be assigned to a proper ATA US pattern group (p<0.0001). Both ACR TI-RADS and ATA have allowed fair selection of nodules requiring FNA with superiority of ACR TI-RADS according to classification of all thyroid nodules to the proper group. According to ACR TI-RADS almost one third of the patients were incorrectly classified with 17.9 % missed thyroid carcinomas, exclusively micropapillary carcinomas, even though, the amount of FNA would be reduced to 48 %.

Objectiveː patients with type 2 diabetes (T2DM) and obesity are generally known to have increased risk of various types of cancer, though studies addressing associations between T2DM/obesity and thyroid cancer are inconclusive. The aim of our study was to evaluate the risk of thyroid cancer focusing on diabetic patients under conditions of euthyroid status. A retrospective study in 184 patients was performed. Three cohorts were established according to tumor histology: malignant (M), benign (B) and low-risk carcinoma (MB). Fisher’s exact test and Kruskal-Wallis one-way ANOVA of ranks were used for statistical analysis. The M (39.1 %), B (57.6 %) and MB (3.3 %) cohorts had comparable age (p=0.4), BMI (p=0.452), glycaemia (p=0.834), Hb1AC (p=0.157) and HOMA-IR (p=0.235). T2DM patients had larger thyroid gland volumes (28.8 vs 17.6 mL;p=0.001) compared to the cohort with normal glucose tolerance. Compared to women, men had more frequently present distal metastases (p=0.017), minimally invasive disease (p=0.027), more advanced staging (p=0.01) and positive pathogenic mutations in the TERT gene (p=0.009);these results were also significant for the diabetic male cohort (p=0.026). Type 2 diabetes and obesity are not risk factors for thyroid cancer, but a subgroup of males seems to have thyroid cancers of poorer prognosis. In general, diabetic patients with insulin resistance and hyperinsulinemia are also prone to have a goiter.

The aim of our study was to evaluate rapid insulin pulses and insulin secretion regularity in fasting state in lean women with polycystic ovary syndrome (PCOS) in comparison to lean healthy women. PCOS (n=8) and controls (n=7) underwent every minute blood sampling for 60 min. Insulin pulsatility was assessed by deconvolution and insulin secretion regularity by approximate entropy methodology. PCOS had higher testosterone (p<0.02), prolactin (p<0.05) and lower sex hormone binding globulin (SHBG) (p<0.0006) levels than controls. Approximate entropy, insulin pulse frequency, mass, amplitude and interpulse interval did not differ between PCOS and controls. PCOS had broader insulin peaks determined by a common half-duration (p<0.07). Burst mass correlated positively with testosterone (p<0.05) and negatively with SHBG (p 0.0004) and common half-duration correlated positively with prolactin (p<0.008) and cortisol levels (p<0.03). Approximate entropy positively correlated with BMI (p<0.04) and prolactin (p<0.03). Lean PCOS patients tended to have broader insulin peaks in comparison to healthy controls. Prolactin, androgens and cortisol might participate in alteration of insulin secretion in PCOS-affected women. Body weight and prolactin levels could influence insulin secretion regularity.

Given that type 2 diabetes mellitus is common in several ciliopathies, the NME7 gene (non-metastatic cells 7), encoding a recognized member of the ciliome, was studied in connection with glucose metabolism. The aim was to find out whether the variability in the gene is associated with the response to administered glucose during the 3 h oral glucose tolerance test. The study included 1262 individuals with different levels of glucose tolerance. Glycemic curves were categorized according to their shape as monophasic, biphasic, triphasic, and more complex multiphasic. The analysis showed a significant association of five linked NME7 polymorphisms with the biphasic course of the glycemic curve, a shape that has been shown to be metabolically protective. Specifically, minor alleles of rs4656659 and rs2157597 in combination with wild-type alleles of rs10732287, rs4264046, and rs10800438 were more frequent within the biphasic category. Moreover, haplotype analysis confirmed higher insulin sensitivity in carriers of this specific haplotype. In conclusion, a cluster of five linked NME7 polymorphisms showed an association with a biphasic glycemic curve. Considering the health benefits of the biphasic curve in terms of glycoregulation and taking into account the demonstrated link of the NME7 haplotype with insulin sensitivity, variability in the NME7 gene represents another piece of the complex mosaic influencing healthy energy processing.