Relation of prediabetes and type 2 diabetes mellitus to thyroid cancer

in Endocrine Connections

Correspondence should be addressed to T Grimmichova: tgrimmichova@endo.cz

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.

Abstract

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.

Introduction

Thyroid cancer (TC) is a relatively rare cancer, with an incidence from 1 to 5.3% of all malignancies, but it represents the most common malignancy originating from the endocrine organs. The most common TCs are differentiated carcinomas, with majority being papillary carcinomas (PTC), especially micropapillary carcinoma (PMTC). TC is more frequent in women than in men and it is currently the third most common cancer in women under the age of 45 in highly developed countries (1, 2, 3). In spite of its striking increase of incidence in both men and women, the mortality rate for thyroid cancer has not changed and has remained low (women 3%; men 5%). Nevertheless, in some studies, mortality is increased in ≥40 years-old age groups, and annual mortality has increased by 1% in men by 3% for advanced PTC (1974–2013). An increase of larger TC tumors (>5 cm) has also been noted (4, 5).

TC differs from other tumors in age distribution, with the most-commonly affected group patients in the economic productive age of 24–60 years, while in other malignancies the risk of carcinoma increases continuously with age. Therefore, secondary causes of this increase in TC incidence have been suggested. They include, briefly: (1) ionizing radiation, which is dose dependent with the highest sensitivity in childhood; however, less than 5% of all TC are associated with radiotherapy (6). (2) Environmental factors, including endocrine disrupting chemicals affecting the endocrine system, though there is lack of direct evidence in humans (7). (3) Hormonal changes especially estrogens in the reproductive period of women contribute to the higher TC incidence in women. It should be emphasized that while women are diagnosed with TC more frequently than men, in autopsy studies the female/male ratio is the same (8). (4) Autoimmune thyroid disease (AITD). Studies have produced contradictory results and AITD can even be a protective factor in TC progression (9, 10). (5) Both iodine deficiency and overconsumption have been suggested to be risk factors for TC. Obviously, follicular thyroid cancer occurs predominantly in iodine-deficient countries in comparison with PTC in iodine-sufficient countries (11). (6) Familial non-medullary thyroid carcinoma, which with a 3–10% prevalence is more frequent in comparison with other tumors (12). (7) TC incidence may have also been increased due to better TC detection (’overdiagnosis’) depending on the numbers of physicians providing ultrasound and ultrasound-guided fine-needle aspiration (6). Finally, and the topic of our study, (8) type 2 diabetes (T2DM), obesity and insulin resistance (IR) in the framework of the worldwide epidemic of diabetes and obesity. In general, patients with diabetes have an approximately 20–25% higher risk of cancer in comparison with patients without diabetes. Epidemiological studies have consistently reported that individuals who are either overweight or obese are at an increased risk of thyroid cancer, but the results are inconsistent for diabetic patients. Both obesity and type 2 diabetes are characterized by insulin resistance, hyperinsulinemia and the overproduction of other growth factors (13, 14). The relationship between T2DM and thyroid cancer is unclear, so in our study we explored whether the presence of diabetes affects the risk of thyroid cancer.

Materials and methods

The protocol of this study complies with the Declaration of Helsinki, and before entering the study, written informed consent was obtained from patients after they received both written and oral information. The study was approved by the ethical committee of Institute of Endocrinology. In our prospective case-control study, we included randomly 561 women and 161 men in a country with iodine sufficiency (15). The power of the sample size was established. The patients were recruited from October 2013 to February 2018. Patient history, ultrasound of neck (US), and biochemical testing were done at the Institute of Endocrinology and 2nd Department of Internal Medicine, University Hospital Kralovske Vinohrady (a secondary referral center). The patients were recruited into the study during the first appointment at the outpatient clinic (Fig. 1). These patients were recommended to our department from primary care mainly due to suspicions of thyropathy, other endocrinopathy or diabetes. Patients with negative history of prediabetes or diabetes were screened for diabetes following the standards of the American Diabetes Association and the European Association for the Study of Diabetes. Patients with prediabetes are defined by the presence of impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT) and/or HbA1c 39–47 mmol/mol. IFG is defined as fasting plasma glucose (FPG) levels between 5.6 and 6.9 mmol/L and IGT as 2-h plasma glucose levels during a 75 g oral glucose tolerance test (OGTT) between 7.8 and 11.0 mmol/L. Diabetes may be diagnosed based on plasma glucose criteria, either using the FPG value or the 2-h plasma glucose (2-h PG) value during an OGTT, or A1C criteria. Criteria for the diagnosis of diabetes: FPG ≥7.0 mmol/L or 2-h PG ≥11.1 mmol/L during OGTT or A1C ≥6.5% (48 mmol/mol) or in a patient with classic symptoms of hyperglycemia or hyperglycemic crisis, a random plasma glucose ≥11.1 mmol/L (16, 17). The homeostatic model assessment of insulin resistance (HOMA-IR) was calculated using the following formula: HOMA-IR = (fasting C-peptide (nmol/L) × fasting glucose (mmol/L)/22.5). The HOMA estimates steady state beta-cell function (%B; HOMA-B) and insulin sensitivity (%S; HOMA-S), as percentages of a normal reference population (18). Antidiabetic treatment data were not assessed in detail. However, the antidiabetic treatment was as follows: metformin 53%, intensive insulin therapy 15.2%, diet 12.1%, combination of insulin with peroral antidiabetics (PAD) 7.6%, combination of PAD 6.1%, GLP-1 analogs 3%, gliptins 1.5%, and sulfonylureas 1.5% patients.

Figure 1
Figure 1

Flow chart of the study.

Citation: Endocrine Connections 9, 7; 10.1530/EC-20-0180

The diagnosis of autoimmune thyroid disease (AITD) was based on positive thyroid autoantibodies and/or the hypoechogenic pattern typical for AITD during the US examination. Only 28 patients with Graves-Basedow disease were included in the study. Patients with hypo- or hyperthyroidism were re-checked for glucose disorders after reaching a euthyroid state. Basal blood samples for the determination of TSH, fT4, fT3, anti-thyroid peroxidase antibodies (anti-TPO), anti-thyroglobulin (anti-Tg), thyrotropin receptor antibodies (TRAbs), calcitonin, glucose, C-peptide, and hemoglobin A1c (HbA1c) were taken.

The patients were sorted to groups of prediabetes (PDM) (n = 55; 7.5%), type 2 diabetes (T2DM) (n = 79; 10.9%) or a non-diabetic group (NDM) (n = 588).

Fine-needle aspiration biopsy (FNA) was performed in 263 thyroid nodules using the pistol technique under US guidance. FNA was generally performed on thyroid nodules sized >1 cm. Thyroid nodules with suspicious US features such as hypoechogenicity, irregular or microlobulated margins, taller-than-wide, punctate echogenic foci and solid components were preferentially chosen for FNA. FNA was performed once for each thyroid nodule using a 20-gauge needle attached to a 20 mL syringe. Local anesthesia was not applied. In mixed nodules, solid areas were chosen. Aspirated material was expelled onto glass slides and sent for cytopathology examinations. May-Grünwald/Giemsa and hematoxylin and eosin stained specimens were evaluated by expert cytopathologists following the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) 2017: (1) nondiagnostic or unsatisfactory; (2) benign; (3) atypia of undetermined significance (AUS) or follicular lesion of undetermined significance (FLUS); (4) follicular neoplasm or suspicious for a follicular neoplasm; (5) suspicious for malignancy; and (6) malignant (19). US was performed at a frequency of 12.5 MHz on a Phillips Epiq5.

By the end of the study, histological examinations had been done in 109 patients, with 57 findings being malignant (MS; 8.0%) and 52 benign (BS).

Serum TSH (0.270–4.200 mUI/L), fT4 (12.00–22.00 pmol/L), fT3 (3.10–6.80 pmol/L), TRAbs (0.30–1.75 IU/L), calcitonin (1.0–4.8 ng/L) and C-peptide (268–1274 pmol/L) concentrations were measured using the ECLIA method (Roche). The HbA1C (20.0–42.0 mmol/mol) test was performed using an ion exchange HPLC method that is certified by the NGSP (www.ngsp.org) and standardized or traceable to the Diabetes Control and Complications Trial (DCCT) reference assay. Serum anti-Tg (0.01–120 IU/mL) and anti-TPO (0.01–40 IU/mL) were measured by ELISA (Aeskulisa). Glucose (3.9–5.6 mmol/L) was measured by a spectrophotometry (UV)-hexokinase method.

Statistical significance was set for P-values < 0.05. Two-way ANOVA consisting of factors and diagnostic group (NDM, PDM, and T2DM) as well as age group (45–59 vs >60 years of age) with interactions between these factors was used to evaluate the effects of status and age. Due to the non-Gaussian data distribution and non-constant variance in most variables, the original continuous variables were transformed by power transformations prior to further processing to attain data symmetry and homoscedasticity (20). The homogeneity and distribution of transformed data were checked as described elsewhere (21, 22). Statistical software Statgraphics Centurion 18 from Statpoint (The Plains, VA, USA) was used for Box-Cox transformations and ANOVA testing. Kruskal–Wallis multiple comparisons with Bonferroni correction for multiplicity were used for comparisons between diagnostic groups and age groups. The importance of individual predictors to discriminate between individual groups was evaluated using multivariate regression with a reduction of dimensionality known as orthogonal projections to latent structure (OPLS) for one predicted (dependent) variable in the model (23, 24). The method is effective in coping with the problem of multicollinearity within the matrix of predictors (high intercorrelations) where ordinary multiple regression fails to correctly evaluate such data (25).

Results

The patients (n = 722) were divided into groups of prediabetes (PDM) (n = 55; 7.5%; age (years) medians with quartiles 67.4 (60.4–74.1), type 2 diabetes (T2DM) (n = 79; 10.9%; age 71.8 (63–76.6) and a non-diabetes group (NDM) (n = 588; age 48.3 (36.6–64.5), with a significant difference for age between study groups (P < 0.001). The influence of age on the observed parameters and groups of PDM and T2DM in comparison to NDM was tested. BMI was significantly different between the study groups (P < 0.001) and followed by a significant impact of age on BMI (P = 0.004). Further, we observed a significant impact of age on TSH; especially, TSH level in NDM 2.02 (CI 95% 1.79–2.26) vs PDM 4.17 (CI 95% 2.5–6.91) (P = 0.028).

In general, the PDM/T2DM group of patients had higher values of glycemia, Hb1Ac and HOMA-IR (P < 0.001). The patients with T2DM had larger thyroid gland volume (P = 0.007) and higher fT4 (P = 0.011) in comparison to NDM. In contrast, the NDM group tended to have higher levels of anti-Tg (P = 0.064). The data are summarized in Table 1.

Table 1

Characteristics of the study groups. Dependence of parameters on age and status (retransformed means with 95% confidence limits).

VariableGroupANOVA
NDMPDMT2DM
BMI (kg/m2)26.2a,b

(25.7, 26.6)
30.4a

(28.4, 32.7)
31.7b

(30.4, 33.2)
Age: F = 3.5, P = 0.062, ηp2 = 0.0104; Group: F = 31.6, P < 0.001, ηp2 = 0.159; Age × Group F = 5.7, P = 0.004, ηp2 = 0.0327
Thyroid gland

volume (mL)
11.7a

(11.1, 12.3)
12.4

(10.2, 15.5)
15a

(13.2, 17.2)
Age: F = 0.5, P = 0.477, ηp2 = 0.00123; Group: F = 5.1, P = 0.007, ηp2 = 0.024; Age × Group F = 0.1, P = 0.928, ηp2 = 0.000364
Thyroid nodule

volume (mL)
0.5

(0.4, 0.7)
0.5

(0.1, 1.5)
1.0

(0.51, 2.0)
Age: F = 1.3, P = 0.262, ηp2 = 0.00301; Group: F = 1.1, P = 0.345, ηp2 = 0.00507; Age × Group F = 1, P = 0.37, ηp2 = 0.00475
TSH

(mIU/L)
2.02a

(1.79, 2.26)
4.17a

(2.5, 6.91)
2.06

(1.57, 2.68)
Age: F = 8.5, P = 0.004, ηp2 = 0.0206; Group: F = 2.7, P = 0.066, ηp2 = 0.0134; Age × Group F = 3.6, P = 0.028, ηp2 = 0.0176
fT4

(pmol/l)
14.5a

(14.2, 14.7)
14.6

(13.4, 15.9)
15.6a

(15, 16.3)
Age: F = 0.5, P = 0.489, ηp2 = 0.00134; Group: F = 4.5, P = 0.011, ηp2 = 0.0247; Age × Group F = 0.1, P = 0.874, ηp2 = 0.000748
fT3

(pmol/l)
4.66

(4.58, 4.73)
4.74

(4.44, 5.05)
4.82

(4.62, 5.02)
Age: F = 4.1, P = 0.045, ηp2 = 0.0167; Group: F = 0.9, P = 0.406, ηp2 = 0.00753; Age × Group F = 0.8, P = 0.474, ηp2 = 0.00622
anti-TPO (IU/mL)0.92

(0.77, 1.09)
0.68

(0.20, 1.39)
0.48

(0.22, 0.78)
Age: F = 0.3, P = 0.617, ηp2 = 0.0006; Group: F = 2.4, P = 0.09, ηp2 = 0.0115; Age × Group F = 0.5, P = 0.601, ηp2 = 0.00243
anti-Tg (IU/mL)0.40a

(0.34, 0.48)
0.27

(0.05, 0.56)
0.19a

(0.08, 0.33)
Age: F = 0.8, P = 0.371, ηp2 = 0.00191; Group: F = 2.8, P = 0.064, ηp2 = 0.013; Age × Group: F = 0.3, P = 0.738, ηp2 = 0.00145
TRAbs

(IU/L)
0.06

(0.05, 0.07)
0.08

(0.03, 0.16)
0.06

(0.04, 0.09)
Age: F = 1.1, P = 0.3, ηp2 = 0.00257; Group: F = 0.2, P = 0.844, ηp2 = 0.000814; Age × Group F = 0.8, P = 0.461, ηp2 = 0.0037
C peptide (pmol/L)713

(646, 789)
817

(660, 1020)
886

(769, 1020)
Age: F = 0.4, P = 0.52, ηp2 = 0.00307; Group: F = 2.4, P = 0.095, ηp2 = 0.0343; Age × Group F = 0.4, P = 0.667, ηp2 = 0.00599
Glycaemia (3.9–5.6)

(mmol/L)
5.06

(5.02, 5.11)
6.09

(5.83, 6.39)
7.6

(7.23, 8.06)
Age: F = 0, P = 0.868, ηp2 = 0.0000965; Group: F = 236.7, P < 0.001, ηp2 = 0.621; Age × Group F = 0.7, P = 0.508, ηp2 = 0.00468, P>C, D>P, D>C
HbA1c (20.0–42.0)

(mmol/mol)
36.1a,b

(35.5, 36.6)
38.9b,c

(37.4, 40.7)
50.7a,c (48.2, 53.8)Age: F = 3.2, P = 0.074, ηp2 = 0.0166; Group: F = 98.8, P < 0.001, ηp2 = 0.509; Age × Group F = 1.8, P = 0.175, ηp2 = 0.0181
HOMA-IR1.58a

(1.43, 1.73)
1.9

(1.54, 2.36)
2.37a

(2.05, 2.76)
Age: F = 1.6, P = 0.212, ηp2 = 0.0116; Group: F = 8.3, P < 0.001, ηp2 = 0.11; Age × Group F = 0.3, P = 0.724, ηp2 = 0.00481
HOMAB

(%)
126a,b

(118, 133)
101a,c

(85.8, 116)
61b,c

(51.8, 70.4)
Age: F = 0.2, P = 0.658, ηp2 = 0.00152; Group: F = 41.2, P < 0.001, ηp2 = 0.388; Age × Group F = 2.2, P = 0.117, ηp2 = 0.0325
HOMAS

(%)
63.8a

(57.8, 70.2)
52.8

(42.2, 65.2)
42a

(35.9, 48.7)
Age: F = 1.6, P = 0.212, ηp2 = 0.0116; Group: F = 8.3, P < 0.001, ηp2 = 0.11; Age × Group F = 0.3, P = 0.722, ηp2 = 0.00485

anti-Tg, anti-thyroglobulin antibodies; anti-TPO, anti-thyroid peroxidase antibodies; HOMA-B (%), steady state β cell function; HOMA-IR, the homeostatic model assessment of insulin resistance; HOMA-S (%), insulin sensitivity; NDM, non-diabetes group; PDM, prediabetes; T2DM, type 2 diabetes; TRAbs, TSH receptor autoantibodies.

Significance for multiple comparisons with Bonferroni correction (P < 0.05). Glycaemia (3.9–5.6) (mmol/L); 5.06a,b (5.02, 5.11); 6.09b,c (5.83, 6.39); 7.6a,c (7.23, 8.06); Age: F = 0, P = 0.868, ηp2 = 0.0000965; Group: F = 236.7, P < 0.001, ηp2 = 0.621; Age × Group F = 0.7, P = 0.508, ηp2 = 0.00468.

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. Thyroid nodule and/or multinodular thyroid gland (MNTG) were present in 66% PDM, 62% T2DM and 50% NDM patients. Fine-needle aspiration (FNA) was carried out in 263 patients. FNA Bethesda findings were: (1) (n = 20; 9.1%), (2) (n = 170; 76.9%), (3) (n = 12; 5.4%), (4) (n = 7; 3.2%), (5) (n = 6; 2.7%), and (6) (n = 6; 2.7%). Histological examination was done in 109 patients who underwent total thyroidectomy, with 57 findings malignant (8.0%): 43 papillary thyroid carcinomas (75.4%), 3 micromedullary thyroid carcinoma (MTC), 3 MTC, 2 anaplastic carcinoma, 1 follicular thyroid carcinoma, 1 oncocytic carcinoma, 1 metastasis and 3 poorly differentiated carcinoma. Malignant tumors according to diagnosis were 7/55 in PDM (12.7%), 9/79 in T2DM (11.4%), and 41/588 in NDM (7.0%). The percentage of malignant tumors did not significantly differ between the groups (χ2 test = 0.461; P = 0.794).

Relevant positive 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) included thyroid volume (mL) (4.79; P < 0.01), multinodular thyroid gland (MNTG) (4.83; P < 0.01), thyroid nodule volume (mL) (3.25; P < 0.01), BMI (22.47; P < 0.01), age (16.98; P < 0.01), smoking or history of smoking (2.61; P < 0.05) and non-thyroid cancer (2.86; P < 0.05), while negative relevant predictors included the occurrence of autoimmune thyroid disease (AITD) (−2.01; P < 0.05), anti-TPO (−5.89; P < 0.01), anti-Tg (−5.75; P < 0.01) and fT3 (−2.86; P < 0.05) (Table 2). Further, the relationships between the duration of PDM/T2DM and predictors were established. Due to the small number of patients in the PDM group, the PDM and T2DM groups were pooled for this analysis. Glycemia (2.67; P < 0.05) and Hb1Ac (5.12; P < 0.01) were positive relevant predictors for the duration of T2DM/PDM (4.52; P < 0.01). C-peptide (−12.94; P < 0.01), HOMA-IR (−7.85; P < 0.01), smoking or history of smoking (−3.29; P < 0.01) and AITD (−2.3; P < 0.05) were negative relevant predictors for the duration of T2DM and PDM (4.52; P < 0.01) (Table 3).

Table 2

Relationships between groups of patients with prediabetes (PDM), type 2 diabetes (T2DM), and a control group (non-diabetes group; NDM) and predictors for the first predictive component as evaluated by the O2PLS model (for details see Statistical analysis).



VariablePredictive component
Component loadingt-statisticsRa
Relevant predictors (matrix X)Male0.1854.530.280c
Age0.46016.980.708c
BMI0.38822.470.604c
Smoking0.0792.610.112b
NTC0.1982.860.295b
MNTG0.1764.830.249c
Thyroid nodule volume0.0903.250.116c
Thyroid gland volume0.1354.790.201c
AITD−0.056−2.01−0.076b
fT3−0.071−2.86−0.114b
anti-TPO−0.144−5.89−0.201c
anti-Tg−0.132−5.75−0.180c
Glycaemia0.65552.630.885c
(matrix Y)T2DM0.59725.870.508c
PDM0.35521.690.255c
NDM−0.721−26.90−0.583c
Explained variability22% (20.8% after cross-validation)

AITD, autoimmune thyroid disease; anti-Tg, anti-thyroglobulin antibodies; anti-TPO, anti-thyroid peroxidase antibodies; MNTG, multinodular thyroid gland; NTC, non-thyroid cancer; Smoking or history of smoking.

aR, Component loadings expressed as correlation coefficients with predictive component, bP < 0.05, cP < 0.01.

Table 3

Relationships between the duration of prediabetes (PDM) and type 2 diabetes (T2DM) and predictors for the first predictive component as evaluated by the O2PLS model (for details see the Statistical analysis section).

VariablePredictive component
Component loadingt-statisticsRa
Relevant predictors (matrix X)AITD−0.189−2.30−0.334b
Smoking−0.140−3.29−0.249c
C-peptide−0.497−12.94−0.889c
Glycemia0.2232.670.391b
HbA1c0.2545.120.427c
HOMA-IR−0.442−7.85−0.793c
HOMA-B−0.479−8.85−0.855c
HOMA-S0.4437.720.794c
(matrix Y)Duration of PDM/T2DM1.0004.520.529c
Explained variability27.9% (21.5% after cross-validation)

AITD, autoimmune thyroid disease; HOMA-B, steady state beta cell function; HOMA-IR, the homeostatic model assessment of insulin resistance; HOMA-S, insulin sensitivity; Smoking or history of smoking.

aR, Component loadings expressed as correlation coefficients with predictive component, bP < 0.05, cP < 0.01.

Next, the group of patients undergoing thyroid surgery was analyzed, comparing malignant (n = 57; MS) to benign thyroid histology (n = 52; BS). Relevant positive predictors for MS with explained variability 35.5% after cross-validation (t-statistic = 5.45; P < 0.01) contrary to BS were TSH (4.35; P < 0.01), anti-Tg (9.06; P < 0.01) and FNA results (4.94; P < 0.01), while negative relevant predictors were thyroid gland volume (−3.61; P < 0.01) and thyroid nodule volume (−3.55; P < 0.01). Differences between group of patients with benign and malignant thyroid tumors are described in more detail in Table 4.

Table 4

Differences between group of patients with benign (BS) and malignant thyroid tumors (MS) for metric variables (Mann–Whitney U-test).

VariableBSMSP-value
Median (quartiles)Mean (s.d.)Median (quartiles)Mean (s.d.)
Age47 (38.8, 65.3)49.8 (15.9)53 (39, 67)53 (16.8)0.402
BMI25.2 (22.2, 29.9)27 (6.61)26.8 (22.5, 30.1)26.7 (5.27)0.786
TN8.2 (2, 16.5)12.8 (16.8)1.8 (0.22, 7.3)6.24 (14.4)<0.001
TG24.5 (16.6, 34.8)32.8 (37.4)17 (10.8, 27.4)22.5 (17.5)0.021
TSH1.08 (0.117, 1.96)1.23 (1.09)2.14 (1.25, 3.37)3.86 (7.75)<0.001
fT415.7 (14.1, 18.4)21.8 (16.4)15.4 (14, 16.4)15 (3.31)0.145
fT35 (4.76, 5.79)7.99 (8.53)4.8 (4.5, 5.21)4.83 (0.624)0.071
anti-TPO5.02 (1.88, 12)31 (68.6)6.1 (2.98, 144)154 (317)0.259
anti-Tg0.86 (0.36, 3.55)4.74 (9.61)12.8 (1.63, 33.8)284 (1330)0.001
TRAbs0.39 (0.3, 10.8)5.77 (9.88)0.32 (0.3, 0.6)0.915 (1.82)0.293
C-peptide818 (598, 1110)895 (516)729 (434, 887)866 (669)0.484
Glycaemia5.31 (4.87, 5.58)5.62 (1.55)5.2 (4.9, 5.58)5.44 (1.1)0.792
Hb1Ac41 (36, 53)48.9 (22.8)36 (34.4, 38.2)37.2 (7.14)0.080
HOMA-IR2.26 (1.61, 2.52)2.39 (1.28)1.61 (0.98, 2.35)2 (1.58)0.178
Calcitonin2 (0.9, 3.35)2.84 (2.67)3.2 (1.3, 6.93)20 (69.8)0.184

anti-Tg, anti-thyroglobulin antibodies; anti-TPO, anti-thyroid peroxidase antibodies; HOMA-IR, the homeostatic model assessment of insulin resistance; TG, thyroid gland volume (mL); TN, thyroid nodule volume (mL); TRAbs, TSH receptor autoantibodies.

The history of non-thyroid cancer (NTC) was also analyzed in the PDM, T2DM and NDM groups. Thirty percent of T2DM and 10% of PDM patients had a positive history for NTC in comparison to 8.4% of the NDM group excluding non-melanoma skin cancers. The most common types of cancers were colon, prostate, breast, melanoma and urothelial carcinoma. Four patients in the PDM/T2DM group had cancer duplicity. Relevant positive predictors for NTC with explained variability 9% after cross-validation (t-statistic 3.01; P < 0.01) were T2DM (24.99; P < 0.01), duration of PDM/T2DM (13.30; P < 0.01), male gender (6.51; P < 0.01), age (12.95; P < 0.01), BMI (13.68; P < 0.01), smoking or history of smoking (6.01; P < 0.01), multinodular thyroid gland (12.00; P < 0.01), thyroid nodule volume (6.78; P < 0.01) and glycemia (21.13; P < 0.01). In contrast, relevant negative predictors for NTC were anti-TPO (−3.90; P < 0.01) and anti-Tg (−3.84; P < 0.01).

Discussion

Generally, there is a higher prevalence of thyroid disorders among diabetic patients compared with the general population (10.8% vs 6.6%) (26). Epidemiological studies suggest that the incidence of thyroid cancer (TC) is dependent on modifiable risk factors such as environmental carcinogens, dietary habits, and lifestyle (27, 28). In our study, we focused on the links between prediabetes, type 2 diabetes and thyroid disease. Specifically, we concentrated on the risk of TC and the modifiable factors, diabetes, obesity and insulin resistance.

In our study, the typical patient with PDM or DM was an elderly, overweight or obese man with benign multinodular goiter. In addition, smoking or ex-smoking was a common history of these patients. On the other hand, the typical control proband was younger with a higher incidence of autoimmune thyroid disorder. Our findings are supported by other studies showing that type 2 diabetes is not convincingly associated with the prevalence of hypo- or hyperthyroidism or the presence of anti-TPO positivity (29, 30, 31). After statistical analyses of PDM/T2DM duration on relevant predictors, we found that the typical course of PDM/T2DM is a gradual decline of insulin secretion, progression of hyperglycemia and worsening of glucose control as measured by Hb1Ac, with insulin sensitivity assessed by HOMA-S at a maximum. Finally, autoimmune thyroid disorder did not develop frequently during the course of prediabetes and type 2 diabetes.

In a multivariate analysis, insulin resistance, and not TSH, determines the thyroid nodules development and higher thyroid volume in comparison to non-insulin resistant controls (32, 33, 34). Our study brings similar findings, with the group of prediabetic and diabetic patients having both larger thyroid gland volume and larger thyroid nodule size. We have to emphasize that ageing is crucial in this pathogenesis. The key role of TSH signaling in thyroid carcinogenesis has been supported by large epidemiological studies showing a strong association between serum TSH levels and TC development and progression. On the other hand, it is known that TSH levels can be increased in differentiated thyroid carcinoma (DTC) compared to benign thyroid disease (BTD), but not in comparison to the background population. A lower TSH among patients with BTD may be due to co-existing functional nodular autonomy (35, 36, 37). This bias can lead to misinterpretations of a positive relation between higher TSH and risk of DTC. In our study, we did not observe any difference in TSH levels between the PDM, T2DM and NDM groups of patients. Our results are supported by a large population-based study that showed no convincing evidence that people with type 2 diabetes are at increased risk of hypothyroidism (29). However, we observed significantly higher levels of TSH in patients undergoing thyroid surgery with histologically proven malignancy in comparison to lower TSH levels in the benign group. Multinodular goiter, multinodular toxic goiter, toxic nodule and Graves-Basedow thyrotoxicosis were the reasons for our benign surgery results. Generally, toxic nodules have a very low risk of malignancy (6). This clearly explains the TSH level differences between the MS and BS groups, and TSH levels have not generally been helpful in the prediction of TC risk.

Additionally, we observed lower fT3 levels but higher fT4 levels in the normal range in PDM and T2DM patients. There are some studies supporting our findings. One explanation can be genetic polymorphism in the selenodeiodinases D2 in diabetic patients. The major role of D2 is to control the intracellular T3 concentration, its accessibility to the nucleus, and the saturation of the nuclear T3 receptor in target tissues. In some diabetic patients lower D2 activity is present, and therefore, intrinsic thyroid disease is expected with possible metabolic consequences (38, 39).

Case-control and cohort studies have confirmed an increased TC risk in approximately 20% in diabetic patients, independently of geographic region, study design, and quality analysis. Despite the high heterogeneity among studies, the observation that the risk is increased among diabetic women, but not among men, has been always confirmed. In addition, the TC risk associated with DM is more evident in geographic areas of the world with high rates of TC (40, 41, 42).

In our study, we did not observe any TC risk difference between PDM and T2DM in comparison to NDM similarly to other study published previously (43). We suppose that one of the explanations is the overdiagnosis of TC in diabetics. Diabetic patients are more prone to be screened for thyroid dysfunction, thus contributing to the increased detection of thyroid cancer in this population. Further, they have larger thyroid gland volume and larger thyroid nodule size, perhaps leading to earlier TC manifestation and detection. Generally, thyroid incidentalomas are very frequent findings (26). In our study, we used histologically proven results as the gold reference standard to compare patients with TC and control group. We believe that sample selection bias of the control group could be the reason for different study results in comparison to previous studies. Finally, in our study the patients with proven TC had a smaller thyroid volume and thyroid nodule volume, in contrast to diabetic patients with typical multinodular goiter.

As mentioned previously, we did not observe a higher incidence of TC in PDM/T2DM patients compared to NDM. In contrast, 30% of T2DM and 10% of PDM patients had a positive history for non-thyroid cancer (NTC) in comparison to 8.4% in NDM. Our study also supports the relation between diabetes and cancer. The incidence of NTC increases with the duration of PDM/T2DM. As previously described, the positivity of anti-TPO and/or anti-Tg were relevant negative predictors for both PDM/T2DM and NTC. Perhaps, patients with autoimmune thyroid disorder have a different background in comparison to diabetics and the NTC group of patients. Furthermore, multinodular thyroid gland and larger thyroid nodules were more often present in the NTC group. This may support the idea of the growth stimulation of various types of both benign and malignant tumors in diabetics.

Epidemiological studies, followed by the systematic review suggest that obesity is associated with an increased risk of thyroid cancer; however, the relationships between obesity and thyroid cancer stage or behavior are uncertain (44, 45). In our study, we did not observe higher BMI (P = 0.786) or insulin resistance (P = 0.178) in group of patients with thyroid carcinoma. In contrast, BMI was one of relevant positive predictors for non-thyroid cancers. We suppose that obesity is not significantly related to thyroid cancer compared to other malignancies.

Finally, we would like to emphasize that TC differs from other tumors in age distribution, with the most commonly affected group of patients in the economic productive age of 24–60 years, while in other malignancies the risk of carcinoma increases continuously with age. In contrast, in developed countries, more than half of the people with type 2 diabetes mellitus are older than 65 years and only 8% are less than 44 years of age (46).

One limitation of our study is the difference between the study groups in age – the PDM and T2DM group of patients were older in comparison to the NDM group. For that reason, we adjusted the data on age, but we did not observe significant interactions between age and the tested parameters except BMI and TSH. Another limitation is the small size of the prediabetic group. This may have been the reason why some significant results seen in T2DM were not significant for PDM. The number of patients with histologically proven thyroid tumors was limited; however, the sample size reached sufficient statistical power. Further, C-peptide levels were not available in all patients, but it was sufficient for the statistical analysis. However, a strength of our study is the prospective design with active screening for glucose disorders and the use of histology as the reference standard. It should be noted that in some previous studies the diagnosis of prediabetes/diabetes was ascertained by a self-administered questionnaire. In our study 72% patients with PDM and 6.5% with T2DM were diagnosed by our active screening. Self-reported PDM and T2DM can be quite misleading, with some studies supporting our findings of undiagnosed glucose disorders of up to 45.8% globally (47). Our study also includes prediabetes, and to our knowledge, limited data is available for this subgroup of patients. Taken together, we believe that our study can, to some extent, explain the inconsistencies in previously published studies focused on diabetes and links to thyroid cancer and other thyroid diseases.

Conclusions

In the most insulin-resistant subjects, the diabetic and prediabetic groups, we did not observe an increased risk for thyroid cancer, in spite of the well-established increased risk for other malignancies. Structural and benign changes such as larger and multinodular thyroid gland, in comparison to autoimmune thyroid disease, were present more often in patients with prediabetes and 2 type diabetes. Intrinsic thyroid disease cannot be ruled out even under euthyroidism in these patients. Reasons for this finding may simply be overdiagnosis and/or stimulation of tumor growth with earlier manifestations in pre/diabetics or other unknown reasons remaining to be clarified.

Declaration of interest

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Funding

This work was supported by Ministry of Health, Czech Republic – conceptual development of research organization (Institute of Endocrinology – EU, 00023761).

Author contribution statement

Tereza Grimmichova conceived of the presented idea. Martin Haluzik and Karel Vondra supervised the findings of this work. Martin Hill and Petr Matucha analyzed the data. All authors discussed the results and contributed to the final manuscript.

Acknowledgements

The authors are grateful to the director of Institute of Endocrinology and Ass. Prof RNDr. Bela Bendlova, Csc., Mgr. Josef Vcelak and MUDr. Katerina Dvorakova for general support and manuscript preparation.

References

  • 1

    ItoYNikiforovYESchlumbergerMVigneriR. Increasing incidence of thyroid cancer: controversies explored. Nature Reviews. Endocrinology 2013 9 178184. (https://doi.org/10.1038/nrendo.2012.257)

    • Search Google Scholar
    • Export Citation
  • 2

    RotiEDegli UbertiECBravermanLE. Thyroid papillary microcarcinoma: a descriptive and meta-analysis study. European Journal of Endocrinology 2008 159 659673. (https://doi.org/10.1530/EJE-07-0896)

    • Search Google Scholar
    • Export Citation
  • 3

    FerlayJShinHRBrayFFormanDMathersCParkinDM. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. International Journal of Cancer 2010 127 28932917. (https://doi.org/10.1002/ijc.25516)

    • Search Google Scholar
    • Export Citation
  • 4

    La VecchiaCNegriE. Thyroid cancer: the thyroid cancer epidemic – overdiagnosis or a real increase? Nature Reviews Endocrinology 2017 13 318319. (https://doi.org/10.1038/nrendo.2017.53)

    • Search Google Scholar
    • Export Citation
  • 5

    EnewoldLZhuKRonEMarrogiAJStojadinovicAPeoplesGEDevesaSS. Rising thyroid cancer incidence in the United States by demographic and tumor characteristics, 1980–2005. Cancer Epidemiology Biomarkers & Prevention 2009 18 784791. (https://doi.org/10.1158/1055-9965.EPI-08-0960)

    • Search Google Scholar
    • Export Citation
  • 6

    HaugenBRAlexanderEKBibleKCDohertyGMMandelSJNikiforovYEPaciniFRandolphGWSawkaAMSchlumbergerMet al. 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: the American Thyroid Association guidelines task force on thyroid nodules and differentiated thyroid cancer. Thyroid 2016 26 1133. (https://doi.org/10.1089/thy.2015.0020)

    • Search Google Scholar
    • Export Citation
  • 7

    BergmanAHeindelJJKastenTKiddKAJoblingSNeiraMZoellerRTBecherGBjerregaardPBornmanR The impact of endocrine disruption: a consensus statement on the state of the science. Environmental Health Perspectives 2013 121 A104A106. (https://doi.org/10.1289/ehp.1205448)

    • Search Google Scholar
    • Export Citation
  • 8

    HarachHRFranssilaKOWaseniusVM. Occult papillary carcinoma of the thyroid. A normal finding in Finland. A systematic autopsy study. Cancer 1985 56 531538. (https://doi.org/10.1002/1097-0142(19850801)56:3<531::aid-cncr2820560321>3.0.co;2-3)

    • Search Google Scholar
    • Export Citation
  • 9

    AnilCGokselSGursoyA. Hashimoto’s thyroiditis is not associated with increased risk of thyroid cancer in patients with thyroid nodules: a single-center prospective study. Thyroid 2010 20 601606. (https://doi.org/10.1089/thy.2009.0450)

    • Search Google Scholar
    • Export Citation
  • 10

    SinghBShahaARTrivediHCarewJFPoluriAShahJP. Coexistent Hashimoto’s thyroiditis with papillary thyroid carcinoma: impact on presentation, management, and outcome. Surgery 1999 126 10701076; discussion 1076. (https://doi.org/10.1067/msy.2099.101431)

    • Search Google Scholar
    • Export Citation
  • 11

    BhargavPRMishraAAgarwalGAgarwalAPradhanPKGambhirSVermaAKMishraSK. Long-term outcome of differentiated thyroid carcinoma: experience in a developing country. World Journal of Surgery 2010 34 4047. (https://doi.org/10.1007/s00268-009-0293-y)

    • Search Google Scholar
    • Export Citation
  • 12

    LupoliGVitaleGCaragliaMFittipaldiMRAbbruzzeseATagliaferriPBiancoAR. Familial papillary thyroid microcarcinoma: a new clinical entity. Lancet 1999 353 637639. (https://doi.org/10.1016/S0140-6736(98)08004-0)

    • Search Google Scholar
    • Export Citation
  • 13

    La VecchiaCNegriEFranceschiSD’AvanzoBBoyleP. A case-control study of diabetes mellitus and cancer risk. British Journal of Cancer 1994 70 950953. (https://doi.org/10.1038/bjc.1994.427)

    • Search Google Scholar
    • Export Citation
  • 14

    PaesJEHuaKNagyRKloosRTJarjouraDRingelMD. The relationship between body mass index and thyroid cancer pathology features and outcomes: a clinicopathological cohort study. Journal of Clinical Endocrinology & Metabolism 2010 95 42444250. (https://doi.org/10.1210/jc.2010-0440)

    • Search Google Scholar
    • Export Citation
  • 15

    ZamrazilVBilekRCerovskaJDelangeF. The elimination of iodine deficiency in the Czech Republic: the steps toward success. Thyroid 2004 14 4956. (https://doi.org/10.1089/105072504322783849)

    • Search Google Scholar
    • Export Citation
  • 16

    American Diabetes Association. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes – 2018. Diabetes Care 2018 41 S13S27. (https://doi.org/10.2337/dc18-S002)

    • Search Google Scholar
    • Export Citation
  • 17

    InzucchiSEBergenstalRMBuseJBDiamantMFerranniniENauckMPetersALTsapasAWenderRMatthewsDR. Management of hyperglycaemia in type 2 diabetes, 2015: a patient-centred approach. Update to a position statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetologia 2015 58 429442. (https://doi.org/10.1007/s00125-014-3460-0)

    • Search Google Scholar
    • Export Citation
  • 18

    OhkuraTShiochiHFujiokaYSumiKYamamotoNMatsuzawaKIzawaSKinoshitaHOhkuraHKatoMet al. 20/(fasting C-peptide × fasting plasma glucose) is a simple and effective index of insulin resistance in patients with type 2 diabetes mellitus: a preliminary report. Cardiovascular Diabetology 2013 12 21. (https://doi.org/10.1186/1475-2840-12-21)

    • Search Google Scholar
    • Export Citation
  • 19

    CibasESAliSZ. The 2017 Bethesda system for reporting thyroid cytopathology. Thyroid 2017 27 13411346. (https://doi.org/10.1089/thy.2017.0500)

    • Search Google Scholar
    • Export Citation
  • 20

    MelounMHillMMilitkyJKupkaK. Transformation in the PC-aided biochemical data analysis. Clinical Chemistry and Laboratory Medicine 2000 38 553559. (https://doi.org/10.1515/CCLM.2000.081)

    • Search Google Scholar
    • Export Citation
  • 21

    MelounMMilitkyJHillMBreretonRG. Crucial problems in regression modelling and their solutions. Analyst 2002 127 433450. (https://doi.org/10.1039/b110779h)

    • Search Google Scholar
    • Export Citation
  • 22

    MelounMHillMMilitkyJVrbikovaJStanickaSSkrhaJ. New methodology of influential point detection in regression model building for the prediction of metabolic clearance rate of glucose. Clinical Chemistry and Laboratory Medicine 2004 42 311322. (https://doi.org/10.1515/CCLM.2004.057)

    • Search Google Scholar
    • Export Citation
  • 23

    TryggJHolmesELundstedtT. Chemometrics in metabonomics. Journal of Proteome Research 2007 6 469479. (https://doi.org/10.1021/pr060594q)

    • Search Google Scholar
    • Export Citation
  • 24

    TryggJWoldS. Orthogonal projections to latent structures (O-PLS). Journal of Chemometrics 2002 16 119128. (https://doi.org/10.1002/cem.695)

    • Search Google Scholar
    • Export Citation
  • 25

    MadsenRLundstedtTTryggJ. Chemometrics in metabolomics – a review in human disease diagnosis. Analytica Chimica Acta 2010 659 2333. (https://doi.org/10.1016/j.aca.2009.11.042)

    • Search Google Scholar
    • Export Citation
  • 26

    WuP. Thyroid disease and diabetes. Clinical Diabetes 2000 18 365372.

  • 27

    MalaguarneraRVellaVNicolosiMLBelfioreA. Insulin resistance: any role in the changing epidemiology of thyroid cancer? Frontiers in Endocrinology 2017 8 314. (https://doi.org/10.3389/fendo.2017.00314)

    • Search Google Scholar
    • Export Citation
  • 28

    MackWJPreston-MartinSBernsteinLQianD. Lifestyle and other risk factors for thyroid cancer in los Angeles County females. Annals of Epidemiology 2002 12 395401. (https://doi.org/10.1016/s1047-2797(01)00281-2)

    • Search Google Scholar
    • Export Citation
  • 29

    FleinerHFBjøroTMidthjellKGrillVÅsvoldBO. Prevalence of thyroid dysfunction in autoimmune and type 2 diabetes: the population-based HUNT study in Norway. Journal of Clinical Endocrinology and Metabolism 2016 101 669677. (doi:10.1210/jc.2015-3235)

    • Search Google Scholar
    • Export Citation
  • 30

    SotakŠLazurovaIFelsociMNovakovaBWagnerovaH. The prevalence of type 2 diabetes mellitus in patients with autoimmune thyroiditis in hypothyroid stadium. Vnitrni Lekarstvi 2018 64 232235.

    • Search Google Scholar
    • Export Citation
  • 31

    NishiM. Diabetes mellitus and thyroid diseases. Diabetology International 2018 9 108112. (https://doi.org/10.1007/s13340-018-0352-4)

  • 32

    GuoHSunMHeWChenHLiWTangJTangWLuJBiYNingG The prevalence of thyroid nodules and its relationship with metabolic parameters in a Chinese community-based population aged over 40 years. Endocrine 2014 45 230235. (https://doi.org/10.1007/s12020-013-9968-0)

    • Search Google Scholar
    • Export Citation
  • 33

    AyturkSGursoyAKutAAnilCNar DemirerATutuncuNB. Metabolic syndrome and its components are associated with increased thyroid volume and nodule prevalence in a mild-to-moderate iodine deficient area. European Journal of Endocrinology 2009 161 599605. (https://doi.org/10.1530/EJE-09-0410)

    • Search Google Scholar
    • Export Citation
  • 34

    BoelaertKHoracekJHolderRLWatkinsonJCSheppardMCFranklynJA. Serum thyrotropin concentration as a novel predictor of malignancy in thyroid nodules investigated by fine-needle aspiration. Journal of Clinical Endocrinology and Metabolism 2006 91 42954301. (https://doi.org/10.1210/jc.2006-0527)

    • Search Google Scholar
    • Export Citation
  • 35

    HaymartMRRepplingerDJLeversonGEElsonDFSippelRSJaumeJCChenH. Higher serum thyroid stimulating hormone level in thyroid nodule patients is associated with greater risks of differentiated thyroid cancer and advanced tumor stage. Journal of Clinical Endocrinology and Metabolism 2008 93 809814. (https://doi.org/10.1210/jc.2007-2215)

    • Search Google Scholar
    • Export Citation
  • 36

    FioreERagoTProvenzaleMAScutriMUgolinuCBasoloFCoscio DiGMiccoliPGrassoLPincheraA L-thyroxine-treated patients with nodular goiter have lower serum TSH and lower frequency of papillary thyroid cancer: results of a cross-sectional study on 27914 patients. Endocrine-Related Cancer 2010 17 231239. (https://doi.org/10.1677/ERC-09-0251)

    • Search Google Scholar
    • Export Citation
  • 37

    DuranAOAnilCGursoyANarAAltundagOTutuncuNB. The relationship between glucose metabolism disorders and malignant thyroid disease. International Journal of Clinical Oncology 2013 18 585589. (https://doi.org/10.1007/s10147-012-0435-3)

    • Search Google Scholar
    • Export Citation
  • 38

    YalakantiDDoliaPB. Association of type II 5′ monodeiodinase Thr92Ala single nucleotide gene polymorphism and circulating thyroid hormones among type 2 diabetes mellitus patients. Indian Journal of Clinical Biochemistry 2016 31 152161. (https://doi.org/10.1007/s12291-015-0518-9)

    • Search Google Scholar
    • Export Citation
  • 39

    BagchiN. Thyroid function in a diabetic population. Special Topics in Endocrinology & Metabolism 1982 3 4555.

  • 40

    ShihSRChiuWYChangTCTsengCH. Diabetes and thyroid cancer risk: literature review. Experimental Diabetes Research 2012 2012 578285. (https://doi.org/10.1155/2012/578285)

    • Search Google Scholar
    • Export Citation
  • 41

    ChodickGHeymannADRosenmannLGreenMSFlashSPorathAKokiaEShalevV. Diabetes and risk of incident cancer: a large population-based cohort study in Israel. Cancer Causes & Control 2010 21 879887. (https://doi.org/10.1007/s10552-010-9515-8)

    • Search Google Scholar
    • Export Citation
  • 42

    Aschebrook-KilfoyBSabraMMBrennerAMooreSCRonESchatzkinAHollenbeckAWardMH. Diabetes and thyroid cancer risk in the National Institutes of Health – AARP Diet and Health Study. Thyroid 2011 21 957963. (https://doi.org/10.1089/thy.2010.0396)

    • Search Google Scholar
    • Export Citation
  • 43

    LuoJPhillipsLLiuSWactawski-WendeJMargolisKL. Diabetes, diabetes treatment, and risk of thyroid cancer. Journal of Clinical Endocrinology and Metabolism 2016 101 12431248. (https://doi.org/10.1210/jc.2015-3901)

    • Search Google Scholar
    • Export Citation
  • 44

    PaesJEHuaKNagyRKloosRTJarjouraDRingelMD. The relationshipbetween body mass index and thyroid cancer pathology features and outcomes: aclinicopathological cohort study. Journal of Clinical Endocrinology and Metabolism 2010 95 42444250. (https://doi.org/10.1210/jc.2010-0440)

    • Search Google Scholar
    • Export Citation
  • 45

    HarikrishnaAIshakAEllinidesASaadRChristodoulouHSpartalisEPaschouSA. The impact of obesity and insulin resistance on thyroid cancer: a systematic review. Maturitas 2019 125 4549. (https://doi.org/10.1016/j.maturitas.2019.03.022)

    • Search Google Scholar
    • Export Citation
  • 46

    World Health Organization. Diabetes Action Now: an initiative of the World Health Organization and the International Diabetes Federation. Geneva, Switzerland: World Health Organization2004. (available at: https://apps.who.int/iris/handle/10665/42934)

  • 47

    BeagleyJGuariguataLWeilCMotalaAA. Global estimates of undiagnosed diabetes in adults. Diabetes Research and Clinical Practice 2014 103 150160. (https://doi.org/10.1016/j.diabres.2013.11.001)

    • Search Google Scholar
    • Export Citation

If the inline PDF is not rendering correctly, you can download the PDF file here.

 

     European Society of Endocrinology

     Society for Endocrinology

Sept 2018 onwards Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 168 168 168
PDF Downloads 38 38 38
  • 1

    ItoYNikiforovYESchlumbergerMVigneriR. Increasing incidence of thyroid cancer: controversies explored. Nature Reviews. Endocrinology 2013 9 178184. (https://doi.org/10.1038/nrendo.2012.257)

    • Search Google Scholar
    • Export Citation
  • 2

    RotiEDegli UbertiECBravermanLE. Thyroid papillary microcarcinoma: a descriptive and meta-analysis study. European Journal of Endocrinology 2008 159 659673. (https://doi.org/10.1530/EJE-07-0896)

    • Search Google Scholar
    • Export Citation
  • 3

    FerlayJShinHRBrayFFormanDMathersCParkinDM. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. International Journal of Cancer 2010 127 28932917. (https://doi.org/10.1002/ijc.25516)

    • Search Google Scholar
    • Export Citation
  • 4

    La VecchiaCNegriE. Thyroid cancer: the thyroid cancer epidemic – overdiagnosis or a real increase? Nature Reviews Endocrinology 2017 13 318319. (https://doi.org/10.1038/nrendo.2017.53)

    • Search Google Scholar
    • Export Citation
  • 5

    EnewoldLZhuKRonEMarrogiAJStojadinovicAPeoplesGEDevesaSS. Rising thyroid cancer incidence in the United States by demographic and tumor characteristics, 1980–2005. Cancer Epidemiology Biomarkers & Prevention 2009 18 784791. (https://doi.org/10.1158/1055-9965.EPI-08-0960)

    • Search Google Scholar
    • Export Citation
  • 6

    HaugenBRAlexanderEKBibleKCDohertyGMMandelSJNikiforovYEPaciniFRandolphGWSawkaAMSchlumbergerMet al. 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: the American Thyroid Association guidelines task force on thyroid nodules and differentiated thyroid cancer. Thyroid 2016 26 1133. (https://doi.org/10.1089/thy.2015.0020)

    • Search Google Scholar
    • Export Citation
  • 7

    BergmanAHeindelJJKastenTKiddKAJoblingSNeiraMZoellerRTBecherGBjerregaardPBornmanR The impact of endocrine disruption: a consensus statement on the state of the science. Environmental Health Perspectives 2013 121 A104A106. (https://doi.org/10.1289/ehp.1205448)

    • Search Google Scholar
    • Export Citation
  • 8

    HarachHRFranssilaKOWaseniusVM. Occult papillary carcinoma of the thyroid. A normal finding in Finland. A systematic autopsy study. Cancer 1985 56 531538. (https://doi.org/10.1002/1097-0142(19850801)56:3<531::aid-cncr2820560321>3.0.co;2-3)

    • Search Google Scholar
    • Export Citation
  • 9

    AnilCGokselSGursoyA. Hashimoto’s thyroiditis is not associated with increased risk of thyroid cancer in patients with thyroid nodules: a single-center prospective study. Thyroid 2010 20 601606. (https://doi.org/10.1089/thy.2009.0450)

    • Search Google Scholar
    • Export Citation
  • 10

    SinghBShahaARTrivediHCarewJFPoluriAShahJP. Coexistent Hashimoto’s thyroiditis with papillary thyroid carcinoma: impact on presentation, management, and outcome. Surgery 1999 126 10701076; discussion 1076. (https://doi.org/10.1067/msy.2099.101431)

    • Search Google Scholar
    • Export Citation
  • 11

    BhargavPRMishraAAgarwalGAgarwalAPradhanPKGambhirSVermaAKMishraSK. Long-term outcome of differentiated thyroid carcinoma: experience in a developing country. World Journal of Surgery 2010 34 4047. (https://doi.org/10.1007/s00268-009-0293-y)

    • Search Google Scholar
    • Export Citation
  • 12

    LupoliGVitaleGCaragliaMFittipaldiMRAbbruzzeseATagliaferriPBiancoAR. Familial papillary thyroid microcarcinoma: a new clinical entity. Lancet 1999 353 637639. (https://doi.org/10.1016/S0140-6736(98)08004-0)

    • Search Google Scholar
    • Export Citation
  • 13

    La VecchiaCNegriEFranceschiSD’AvanzoBBoyleP. A case-control study of diabetes mellitus and cancer risk. British Journal of Cancer 1994 70 950953. (https://doi.org/10.1038/bjc.1994.427)

    • Search Google Scholar
    • Export Citation
  • 14

    PaesJEHuaKNagyRKloosRTJarjouraDRingelMD. The relationship between body mass index and thyroid cancer pathology features and outcomes: a clinicopathological cohort study. Journal of Clinical Endocrinology & Metabolism 2010 95 42444250. (https://doi.org/10.1210/jc.2010-0440)

    • Search Google Scholar
    • Export Citation
  • 15

    ZamrazilVBilekRCerovskaJDelangeF. The elimination of iodine deficiency in the Czech Republic: the steps toward success. Thyroid 2004 14 4956. (https://doi.org/10.1089/105072504322783849)

    • Search Google Scholar
    • Export Citation
  • 16

    American Diabetes Association. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes – 2018. Diabetes Care 2018 41 S13S27. (https://doi.org/10.2337/dc18-S002)

    • Search Google Scholar
    • Export Citation
  • 17

    InzucchiSEBergenstalRMBuseJBDiamantMFerranniniENauckMPetersALTsapasAWenderRMatthewsDR. Management of hyperglycaemia in type 2 diabetes, 2015: a patient-centred approach. Update to a position statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetologia 2015 58 429442. (https://doi.org/10.1007/s00125-014-3460-0)

    • Search Google Scholar
    • Export Citation
  • 18

    OhkuraTShiochiHFujiokaYSumiKYamamotoNMatsuzawaKIzawaSKinoshitaHOhkuraHKatoMet al. 20/(fasting C-peptide × fasting plasma glucose) is a simple and effective index of insulin resistance in patients with type 2 diabetes mellitus: a preliminary report. Cardiovascular Diabetology 2013 12 21. (https://doi.org/10.1186/1475-2840-12-21)

    • Search Google Scholar
    • Export Citation
  • 19

    CibasESAliSZ. The 2017 Bethesda system for reporting thyroid cytopathology. Thyroid 2017 27 13411346. (https://doi.org/10.1089/thy.2017.0500)

    • Search Google Scholar
    • Export Citation
  • 20

    MelounMHillMMilitkyJKupkaK. Transformation in the PC-aided biochemical data analysis. Clinical Chemistry and Laboratory Medicine 2000 38 553559. (https://doi.org/10.1515/CCLM.2000.081)

    • Search Google Scholar
    • Export Citation
  • 21

    MelounMMilitkyJHillMBreretonRG. Crucial problems in regression modelling and their solutions. Analyst 2002 127 433450. (https://doi.org/10.1039/b110779h)

    • Search Google Scholar
    • Export Citation
  • 22

    MelounMHillMMilitkyJVrbikovaJStanickaSSkrhaJ. New methodology of influential point detection in regression model building for the prediction of metabolic clearance rate of glucose. Clinical Chemistry and Laboratory Medicine 2004 42 311322. (https://doi.org/10.1515/CCLM.2004.057)

    • Search Google Scholar
    • Export Citation
  • 23

    TryggJHolmesELundstedtT. Chemometrics in metabonomics. Journal of Proteome Research 2007 6 469479. (https://doi.org/10.1021/pr060594q)

    • Search Google Scholar
    • Export Citation
  • 24

    TryggJWoldS. Orthogonal projections to latent structures (O-PLS). Journal of Chemometrics 2002 16 119128. (https://doi.org/10.1002/cem.695)

    • Search Google Scholar
    • Export Citation
  • 25

    MadsenRLundstedtTTryggJ. Chemometrics in metabolomics – a review in human disease diagnosis. Analytica Chimica Acta 2010 659 2333. (https://doi.org/10.1016/j.aca.2009.11.042)

    • Search Google Scholar
    • Export Citation
  • 26

    WuP. Thyroid disease and diabetes. Clinical Diabetes 2000 18 365372.

  • 27

    MalaguarneraRVellaVNicolosiMLBelfioreA. Insulin resistance: any role in the changing epidemiology of thyroid cancer? Frontiers in Endocrinology 2017 8 314. (https://doi.org/10.3389/fendo.2017.00314)

    • Search Google Scholar
    • Export Citation
  • 28

    MackWJPreston-MartinSBernsteinLQianD. Lifestyle and other risk factors for thyroid cancer in los Angeles County females. Annals of Epidemiology 2002 12 395401. (https://doi.org/10.1016/s1047-2797(01)00281-2)

    • Search Google Scholar
    • Export Citation
  • 29

    FleinerHFBjøroTMidthjellKGrillVÅsvoldBO. Prevalence of thyroid dysfunction in autoimmune and type 2 diabetes: the population-based HUNT study in Norway. Journal of Clinical Endocrinology and Metabolism 2016 101 669677. (doi:10.1210/jc.2015-3235)

    • Search Google Scholar
    • Export Citation
  • 30

    SotakŠLazurovaIFelsociMNovakovaBWagnerovaH. The prevalence of type 2 diabetes mellitus in patients with autoimmune thyroiditis in hypothyroid stadium. Vnitrni Lekarstvi 2018 64 232235.

    • Search Google Scholar
    • Export Citation
  • 31

    NishiM. Diabetes mellitus and thyroid diseases. Diabetology International 2018 9 108112. (https://doi.org/10.1007/s13340-018-0352-4)

  • 32

    GuoHSunMHeWChenHLiWTangJTangWLuJBiYNingG The prevalence of thyroid nodules and its relationship with metabolic parameters in a Chinese community-based population aged over 40 years. Endocrine 2014 45 230235. (https://doi.org/10.1007/s12020-013-9968-0)

    • Search Google Scholar
    • Export Citation
  • 33

    AyturkSGursoyAKutAAnilCNar DemirerATutuncuNB. Metabolic syndrome and its components are associated with increased thyroid volume and nodule prevalence in a mild-to-moderate iodine deficient area. European Journal of Endocrinology 2009 161 599605. (https://doi.org/10.1530/EJE-09-0410)

    • Search Google Scholar
    • Export Citation
  • 34

    BoelaertKHoracekJHolderRLWatkinsonJCSheppardMCFranklynJA. Serum thyrotropin concentration as a novel predictor of malignancy in thyroid nodules investigated by fine-needle aspiration. Journal of Clinical Endocrinology and Metabolism 2006 91 42954301. (https://doi.org/10.1210/jc.2006-0527)

    • Search Google Scholar
    • Export Citation
  • 35

    HaymartMRRepplingerDJLeversonGEElsonDFSippelRSJaumeJCChenH. Higher serum thyroid stimulating hormone level in thyroid nodule patients is associated with greater risks of differentiated thyroid cancer and advanced tumor stage. Journal of Clinical Endocrinology and Metabolism 2008 93 809814. (https://doi.org/10.1210/jc.2007-2215)

    • Search Google Scholar
    • Export Citation
  • 36

    FioreERagoTProvenzaleMAScutriMUgolinuCBasoloFCoscio DiGMiccoliPGrassoLPincheraA L-thyroxine-treated patients with nodular goiter have lower serum TSH and lower frequency of papillary thyroid cancer: results of a cross-sectional study on 27914 patients. Endocrine-Related Cancer 2010 17 231239. (https://doi.org/10.1677/ERC-09-0251)

    • Search Google Scholar
    • Export Citation
  • 37

    DuranAOAnilCGursoyANarAAltundagOTutuncuNB. The relationship between glucose metabolism disorders and malignant thyroid disease. International Journal of Clinical Oncology 2013 18 585589. (https://doi.org/10.1007/s10147-012-0435-3)

    • Search Google Scholar
    • Export Citation
  • 38

    YalakantiDDoliaPB. Association of type II 5′ monodeiodinase Thr92Ala single nucleotide gene polymorphism and circulating thyroid hormones among type 2 diabetes mellitus patients. Indian Journal of Clinical Biochemistry 2016 31 152161. (https://doi.org/10.1007/s12291-015-0518-9)

    • Search Google Scholar
    • Export Citation
  • 39

    BagchiN. Thyroid function in a diabetic population. Special Topics in Endocrinology & Metabolism 1982 3 4555.

  • 40

    ShihSRChiuWYChangTCTsengCH. Diabetes and thyroid cancer risk: literature review. Experimental Diabetes Research 2012 2012 578285. (https://doi.org/10.1155/2012/578285)

    • Search Google Scholar
    • Export Citation
  • 41

    ChodickGHeymannADRosenmannLGreenMSFlashSPorathAKokiaEShalevV. Diabetes and risk of incident cancer: a large population-based cohort study in Israel. Cancer Causes & Control 2010 21 879887. (https://doi.org/10.1007/s10552-010-9515-8)

    • Search Google Scholar
    • Export Citation
  • 42

    Aschebrook-KilfoyBSabraMMBrennerAMooreSCRonESchatzkinAHollenbeckAWardMH. Diabetes and thyroid cancer risk in the National Institutes of Health – AARP Diet and Health Study. Thyroid 2011 21 957963. (https://doi.org/10.1089/thy.2010.0396)

    • Search Google Scholar
    • Export Citation
  • 43

    LuoJPhillipsLLiuSWactawski-WendeJMargolisKL. Diabetes, diabetes treatment, and risk of thyroid cancer. Journal of Clinical Endocrinology and Metabolism 2016 101 12431248. (https://doi.org/10.1210/jc.2015-3901)

    • Search Google Scholar
    • Export Citation
  • 44

    PaesJEHuaKNagyRKloosRTJarjouraDRingelMD. The relationshipbetween body mass index and thyroid cancer pathology features and outcomes: aclinicopathological cohort study. Journal of Clinical Endocrinology and Metabolism 2010 95 42444250. (https://doi.org/10.1210/jc.2010-0440)

    • Search Google Scholar
    • Export Citation
  • 45

    HarikrishnaAIshakAEllinidesASaadRChristodoulouHSpartalisEPaschouSA. The impact of obesity and insulin resistance on thyroid cancer: a systematic review. Maturitas 2019 125 4549. (https://doi.org/10.1016/j.maturitas.2019.03.022)

    • Search Google Scholar
    • Export Citation
  • 46

    World Health Organization. Diabetes Action Now: an initiative of the World Health Organization and the International Diabetes Federation. Geneva, Switzerland: World Health Organization2004. (available at: https://apps.who.int/iris/handle/10665/42934)

  • 47

    BeagleyJGuariguataLWeilCMotalaAA. Global estimates of undiagnosed diabetes in adults. Diabetes Research and Clinical Practice 2014 103 150160. (https://doi.org/10.1016/j.diabres.2013.11.001)

    • Search Google Scholar
    • Export Citation