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The impact of BMI on clinical progress, response to treatment, and disease course in patients with differentiated thyroid cancer

Abstract

Introduction

Obesity is a serious health problem worldwide, particularly in developed countries. It is a risk factor for many diseases, including thyroid cancer. The relationship between obesity and prognostic factors of thyroid cancer is unclear.

Aims

We sought to ascertain the relationship between body mass index (BMI) and clinicopathological features increasing the risk of poor clinical course, treatment response, and clinical outcome in patients with differentiated thyroid cancer (DTC).

Subjects & methods

The study included 1181 patients with DTC (88% women and 12% men) treated at a single center from 2000 to 2016. BMI before surgery and aggressive clinicopathological features, according to the American Thyroid Initial Risk stratification system, were analyzed. The relationship between BMI and initial risk, treatment response, and final status of the disease was evaluated, incorporating the revised 2015 American Thyroid Association guidelines and the 8th edition of the American Joint Committee on Cancer/Tumor-Node-Metastasis (AJCC/TNM) staging system. Patients were stratified according to the World Health Organization classification of BMI. Statistical analysis was performed using univariate and multivariate logistic regression analysis.

Results

Median follow-up was 7.7 years (1–16 years). There were no significant associations between BMI and extrathyroidal extension (microscopic and gross), cervical lymph node metastasis, or distant metastasis in univariate and multivariate analyses. BMI did not affect initial risk, treatment response or disease outcome. Obesity was more prevalent in men (p = 0.035) and in patients ≥55 years old (p = 0.001). There was no statistically significant relationship between BMI and more advanced TNM stage in patients ≤55 years old (stage I vs. stage II) (p = 0.266) or in patients >55 years old (stage I–II vs. III–IV) (p = 0.877).

Conclusions

Obesity is not associated with more aggressive clinicopathological features of thyroid cancer. Obesity is not a risk factor for progression to more advanced stages of disease, nor is it a prognostic factor for poorer treatment response and clinical outcome.

Introduction

Differentiated thyroid cancer (DTC) is the most common endocrine cancer worldwide, and incidence of this cancer, especially of the papillary carcinoma (PTC) type, has been increasing for several decades [15]. To a large extent, this increase is related to better access to modern diagnostic imaging and biopsies, which contribute to improved detection of early stages of PTC that might have remained undiagnosed in the past [59]. However, some authors report an increase in the number of invasive, large, or small thyroid cancers [2, 1012], which suggests a real increase in the incidence of thyroid cancer. Improvements in the quality of imaging studies alone cannot explain the increased incidence of DTC. Genetic and environmental factors, such as exposure to ionizing radiation and iodine consumption, as well as factors associated with lifestyle, are also associated with the increase in cancer incidence [1315].

Obesity is one of the most common public health problems worldwide, and its incidence has been increasing steadily over the past two decades in both developed and developing countries [16]. In Poland in the last decade, the percentage of obese adults has increased by 7%, and is similar to the percentage of obese Caucasian adults in the United States [17]. Epidemiological data confirm that obesity is independently associated with an increased incidence of various solid tumors, including DTC [1822], but at the same time, there are studies that show no connection between obesity and thyroid cancer [2325]. Links between obesity and predictors of thyroid cancer are also uncertain [26, 27]. Despite the existence of studies demonstrating the impact of obesity on thyroid cancer, no clear mechanism explaining the link has been shown. It has been hypothesized that potential mediators may include insulin, IGF-1, cytokines, inflammation, TSH, adiponectins, leptin, and estrogens [15, 28, 29].

We sought to analyze the relationship between body mass index (BMI) and clinical and pathological characteristics increasing the risk of poor clinical course, primary treatment response, and outcome of the disease in DTC patients treated in one center in Poland.

Materials and methods

Patients and study design

A retrospective analysis was performed of the medical records of 2100 Caucasian patients with DTC who had undergone total thyroidectomy or lobectomy at a single center during the years 2000–2016. The following data were obtained: BMI at the time of surgery, prognostic clinicopathological features (sex, age at diagnosis, tumor diameter, multifocality, lymph node metastasis, and extrathyroidal extension), response to primary treatment, and clinical outcome of disease (remission, recurrence, or death). Patients who did not have complete BMI data, patients with a follow-up period of less than 12 months, and patients whose anti-thyroglobulin antibody (TgAb) levels were monitored with an anti-thyroglobulin (Tg) recovery test rather than a direct measurement of antibodies were excluded. The study ultimately included 1181 patients.

Postoperative Tumor Node Metastasis (TNM) staging of all included patients was re-classified according to the most recent 8th edition of the American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) TNM staging system and the ATA-modified initial risk stratification system (low, intermediate, and high risk of recurrence) [30, 31]. At the stage of diagnosis, clinicopathological features pNx and Mx were analyzed in detail. Subsequently pNx was clinically reclassified as N0b or N1, while Mx was reclassified as 0 or 1, according to the 8th edition of the AJCC/UICC TNM staging system. All suspicious changes in Nx observed in postoperative ultrasound were verified by fine-needle biopsy with the evaluation of Tg from the aspirate, as described previously [32].

Summary of the course of the disease in the present study was dated December 31, 2016; in the case of patients who died prior to this date (22/1181, 1.9%), the state of follow-up was summarized according to the condition of the disease at the time of death.

The study plan was accepted by the Bioethics Committee at the Holycross Chamber of Physicians in Kielce, Poland. It was not necessary to obtain written informed consent from patients because the data was retrospectively obtained from patients’ medical history collected during routine diagnostic procedures during hospitalization. All patient records and information were anonymized and de-identified prior to analysis.

Treatment protocol and patient monitoring

All patients included in the study were subjected to primary surgical treatment. The scope of surgery included lobectomy, total thyroidectomy (TT), or total thyroidectomy with central compartment lymphadenectomy. In our center, total thyroidectomy with central compartment lymphadenectomy was performed if the primary tumors were >10 mm, multiple or bilateral, or extrathyroidal, or when metastases to the lymph nodes (LN) of the central neck compartment were detected during pre-operative evaluation or surgery. We routinely performed central compartment node dissection on the primary tumor side. On the other hand, we performed bilateral central compartment node dissection when the tumor was bilateral or the LNs were enlarged on the opposite side, as demonstrated during pre-operative staging or surgery. However, the decision to remove lateral LNs depended on the pre- or intra-operative diagnosis of metastases to LNs, or a strong clinical suspicion of their involvement. Lobectomy (total excision of the entire thyroid lobe with isthmus) was performed in patients diagnosed with pre-operative unifocal PTC with a diameter of ≤10 mm, in clinical stage N0 (no lymph node metastases diagnosed in preoperative ultrasound), when there were no evident indications for bilateral surgery in the form of changes visible in the ultrasound in the contralateral lobe, and in patients who had previously undergone lobectomy and were diagnosed with low-risk thyroid cancer. TT without central compartment node dissection was performed in patients with nodular goiter who were diagnosed with PTC ≤10 mm (pT1a) after surgery if they had no evidence of cervical node metastasis in clinical N0 (no LN metastases in postoperative ultrasound) and no distant metastases, and after a careful histopathological examination of the postoperative material to exclude multifocal growth.

All patients with initial postoperative tumor stage higher than pT1aN0-xM0 qualified for radioactive iodine (I-131) treatment with a subsequent suppressive dose of levothyroxine (LT4). The standard procedure, 1100–3700 MBq I-131, was administered depending on the TNM status. Protocols for I-131 treatment and evaluation of the efficacy of primary treatment in patients treated with I-131 in our center have been described previously [33]. Evaluation of treatment response was carried out 9–12 months after administration of I-131. As we previously reported, patients with ineffective ablation, defined as focal I-131 uptake in the thyroid bed >0.1% without any other features of the disease, were treated with a second dose of I-131 and reevaluated after 9–12 months [33].

The efficacy of surgical treatment in patients with pT1aN0-xM0 who were not treated with I-131 was assessed based on a clinical examination, neck ultrasound, and levels of Tg and TgAb within 4–6 weeks after surgery, before levothyroxine was administered. Patients who received a TT underwent neck and whole body scans. When the results indicated that the primary surgery was not radical enough, patients were referred to secondary TT. Further tests were carried out every 6–12 months, depending on the risk degree of the clinical course, as previously described [34].

Diagnostic tests and imaging

Measurements of TSH, Tg, and TgAb were all performed in the same laboratory. The testing methodology has been described in detail previously [34, 35]. The details of neck ultrasound and whole body scintigraphy procedures in our center have also been reported previously [33, 34].

Assessment of treatment response

Patients treated with I-131 were assessed for response to initial therapy (surgery with I-131) using criteria proposed by Tuttle et al. [36], which were accepted by the ATA [31]. The response was classified as excellent, indeterminate, biochemically incomplete, or structurally incomplete. Procedures performed during the follow-up until the end of I-131 treatment and assessment of the response were described previously [33]. Patients not treated with I-131 were assessed for response to initial therapy (TT or lobectomy) using criteria proposed by Momesso and Tuttle [37]. The response was classified as excellent, indeterminate, biochemically incomplete, or structurally incomplete. Procedures performed during monitoring of the course of the disease from the end of surgical treatment to evaluation of response were described previously [34].

Anthropometric measurements

All patients included in the study were measured for height and weight without shoes and outer clothing on the day of surgery. BMI was calculated as weight in kilograms divided by the square of height in meters (kg/m2). BMI values were stratified according to the World Health Organization (WHO) classification: underweight (BMI, <18.5 kg/m2), normal (BMI, 18.5–24.9 kg/m2), overweight (BMI, 25.0–29.9 kg/m2), and obese (BMI, ≥30.0 kg/m2). Obesity was then further stratified into Grade 1 obesity (BMI, 30–34.9 kg/m2), Grade 2 obesity (BMI, 35–39.9 kg/m2), and Grade 3 obesity (BMI ≥40 kg/m2). The relationship between BMI and clinical and pathological features, the response to primary treatment, and the outcome of the disease (recurrent/persistent disease, death) was analyzed.

Final oncological assessment

Follow-up concluded with an oncological assessment on December 31, 2016. Based on the medical documentation, patients’ health was assessed by applying the latest ATA guidelines [31] and assigning them to groups: no evidence of disease (NED), recurrent/persistent disease, death from cancer, and death from other causes.

Statistical analyses

Basic statistics (mean, standard deviation) were determined for continuous variables (age, BMI, tumor size, years of follow-up). Percentages were determined for discrete and ordinal variables. A t-test was applied for testing differences between means. A chi-square test was used to examine the interrelationship of pairs of features. Logistic regression (univariate and multivariate) analysis was used to examine the dependence of selected clinicopathological features from selected prognostic factors. An odds ratio (OR) with a 95% confidence interval was determined. Kaplan-Meier curves were used to analyze overall survival. P-values <0.05 were considered statistically significant. All statistical analysis was performed using MedCalc Statistical Software version 17.9.7 (MedCalc Software bvba, Ostend, Belgium; http://www.medcalc.org; 2017).

Results

Baseline characteristics

Clinical and pathological features of patients, tumor staging, ATA Initial Risk Stratification System, category of response and final outcome of the disease are summarized in Table 1. We stratified patients into six groups: underweight (BMI, <18.5 kg/m2), normal weight (BMI, 18.5–24.9 kg/m2), overweight (BMI, 25.0–29.9 kg/m2), Grade 1 obesity (BMI, 30–34.9 kg/m2), Grade 2 obesity (BMI, 35–39.9 kg/m2), and Grade 3 obesity (BMI, ≥40 kg/m2). The numbers of patients in each group are indicated in Table 1.

The patients had diseases of differing severities and clinical characteristics, as specified in the Table 1. Histologically, the vast majority of tumors were papillary; in terms of clinical severity, the majority were stage pT1. Most patients received I-131 treatment, at a range of doses (1100–3700 MBq) depending on tumor stage, whereas patients with small tumors without metastasis (pT1aN0-xM0) did not. Most patients (83.9%) responded well to therapy, although 5.3% presented with features of biochemically or structurally persistent disease at the end of follow-up.

Associations between BMI and clinicopathological features of DTC

The clinicopathological features of DTC were evaluated in relation to BMI groups (Table 2). We observed no statistically significant dependence of the primary tumor size, more aggressive DTC histopathologic type or histopathologic PTC subtype, multifocality, extrathyroidal extension (microscopic or gross), vascular invasion, lymph node metastases, distant metastases, intermediate or high risk of recurrence according to ATA, poorer response to primary treatment, or outcome of the disease in relation to BMI (all six groups).

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Table 2. Clinicopathologic characteristics according to the six BMI groups.

https://doi.org/10.1371/journal.pone.0204668.t002

We observed a statistically significant relationship between sex and BMI (p = 0.007), and age and BMI (<55 years vs. ≥55 years) (p <0.001) was found. In this study population, obesity was significantly (p = 0.035) more prevalent in men (59/142; 41.5%) than in women (339/1039; 32.5%) (S1 Table). According to the updated 8th edition of AJCC/TNM staging system, BMI was not significantly associated with more advanced TNM stage in patients <55 years of age (stage I vs. stage II) (p = 0.266) or ≥55 years of age (stage I-II vs. III-IV) (p = 0.877) (S1 Dataset).

Predictive factors for aggressive pathology, response to therapy, and outcome of DTC

We performed logistic regression analysis (univariate and multivariate) to determine the dependence of selected features of pathological aggressiveness of cancer [extrathyroidal extension, lymph node metastasis, distant metastases, and ATA Initial Risk Stratification System score (high and intermediate), treatment response, and disease outcome] on prognostic factors such as age, sex, tumor size, multifocality, and BMI (Table 3). In the univariate analysis, many prognostic factors apart from BMI had a significant impact on the analyzed clinical features. In multivariate analysis of BMI (all six groups), there was no statistically significant relationship to pathological aggressiveness (i.e. extrathyroidal extension, lymph node metastases, or distant metastases).

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Table 3. Predictive factors for aggressive pathologic features, response to therapy, and outcome of DTC, as defined by multiple logistic regression analysis.

https://doi.org/10.1371/journal.pone.0204668.t003

Prognostic factors for extrathyroidal extension were tumor size and multifocality. Prognostic factors for lymph node metastases were age, male gender, tumor diameter, and multifocality. The only prognostic factor for distant metastases was tumor diameter.

BMI was not a statistically significant predictive factor, in contrast to tumor size and multifocality, which were prognostic factors for intermediate and high recurrence risk according to the ATA system. In addition, according to the multivariate logistic regression analysis, BMI was not a predictor of microscopic or gross extrathyroidal extension, either in BMI groups or when BMI was considered as a continuous variable (Table 4). Likewise, BMI was not a statistically significant prognostic factor for poorer clinical response to the primary treatment (indeterminate, biochemically or structurally incomplete) or disease outcome (persistent/recurrent disease or death from cancer) (Table 3).

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Table 4. Multivariate logistic regression analyses, using BMI groups and BMI as a continuous variable.

https://doi.org/10.1371/journal.pone.0204668.t004

By contrast, male sex and tumor size were associated with worse response to treatment (indeterminate, biochemically or structurally incomplete), and age and tumor size were prognostic factors for disease outcome (persistent/recurrent disease or death from cancer) (Table 3).

Overall survival according to BMI group

Median duration of the follow-up of the studied group was 7.7 years (range, 1–16 years). The overall survival was compared between groups using the log-rank test (Fig 1, Table 5). Overall survival did not differ significantly according to BMI (all six groups).

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Fig 1. Comparison of overall survival according to BMI group.

No significant differences were detected among individuals in the underweight (BMI < 18.5), normal body weight (18.5 ≤ BMI < 25), overweight (25 ≤ BMI < 30), grade 1 obese (30 ≤ BMI < 35), grade 2 obese (35 ≤ BMI < 40), or grade 3 obese (BMI ≥ 40) groups (p = 0.7723).

https://doi.org/10.1371/journal.pone.0204668.g001

Discussion

Obesity is a serious global health problem, especially in developed countries, and its prevalence is increasing. It is the cause of many chronic diseases and has been linked to some types of cancer [3840]. It has been posited that thyroid cancer is related to obesity [18], and the rise in the number of new thyroid cancer cases in recent decades may be due in part to the increased prevalence of obesity [21, 4143]. However, a causal link between obesity and thyroid cancer is not widely accepted. A retrospective study of fine-needle aspiration biopsies of 4849 thyroid nodules showed no relationship between obesity and cancer risk; the incidence of suspicious or malignant nodules did not differ between five BMI groups (normal body weight, overweight, and Grade 1–3 obesity) [44]. Similarly, no association was found between obesity and thyroid cancer in a study of people undergoing preventive screening for various risk factors for thyroid cancer [45], nor in one other cohort study [24, 46].

In addition to studies on the association of obesity with the incidence of thyroid cancer, several studies have investigated the role of obesity in the aggressiveness of the course of the disease. The results of these studies are mixed, with some studies showing a positive relationship [4750] and others showing no relationship [26, 27, 51]. In the current study of patients with DTC, there was no relationship between BMI and aggressive clinicopathological features, the degree of clinical progression, the response to primary treatment, or the outcome of the disease. In addition, BMI was not a significant predictor of high or intermediate risk of recurrence according to the ATA Risk Stratification system, as reported by Grani et al. [52]. Our results are in line with those of Kwon et al. [51], in which the authors did not find any association between BMI and clinicopathological features of thyroid cancer or disease outcome. Kim et al. reported that there was no independent association between BMI and stage of PTC at diagnosis [27]. Paes et al. showed no relationship between BMI and aggressive clinicopathological features of thyroid cancer or disease outcome (recurrent/persistent disease) [26]. In the Paes et al. study, the majority of patients were Caucasian (93%), with a median BMI of 27.8 kg/m2 [26]. In the present study, the median BMI was similar (28.1 kg/m2), and all patients included in the study were Caucasian. By contrast, Kim et al. showed that higher BMI was significantly associated with large tumor size, extrathyroidal extension, and more advanced stage of cancer [48]. In the Kim et al. study, median BMI was 23.8 kg/m2 and all patients were Korean. As in the Paes et al. and Kim et al. studies [26, 48], no correlation was found between higher BMI and recurrent/persistent disease, despite differences in clinicopathological features that are known prognostic factors for DTC. Discrepancies between the results of these studies probably arise from the number of obese patients (BMI ≥30 kg/m2) enrolled in each study; 101/259 (38.9%) patients in the Paes et al. study were obese, and 398/1181 patients (33.7%) were obese in the present study [26], but only 95/2057 (4.6%) patients in the Kim et al. study were obese [48]. Findings consistent with those of Kim et al. were also obtained in studies performed in China [48, 53, 54]. Paes et al., like the present study, lacked data on such parameters as TSH, fasting glucose, and total cholesterol [26]. The composition of our study population was similar in race and range of obesity to that of the Paes et al. study, which may contribute to the similarity of our research results [26]. Differences pertaining to the small number of obese Asians may result from specific ethnic features of this group. Asians are typically of shorter height and less obese, and their typical diet differs from that of Caucasians [49]. Differences may also result from the type of obesity, duration of obesity, and differences in physical activity. Moreover, the use of the same WHO classification for the Caucasian and Asian populations, as well as the difference in BMI distributions, may be responsible for the conflicting results [54]. These features may explain, among others, discrepancies regarding the relationship between BMI and prognostic factors for thyroid cancer. Consequently, the relationship between BMI and clinicopathological features of thyroid cancer remains controversial.

Another factor that should be taken into account when considering the role of obesity in thyroid cancer is the potential for a delay in diagnosis due to difficulties in detecting thyroid nodules during neck examinations of obese patients. Although the present study and others did not find increased BMI to be associated with larger tumor [26, 51, 52], other studies have observed this trend [47, 48, 55]. Additionally, Tresallet et al. reported that obese patients with PTC >10 mm had an increased risk of persistent / recurrent disease (OR = 3.8, 95% CI: 1.6–8.8; p = 0.03)[55]. However, in this study and in Chung et al. and Kwon et al., no such relationship was observed [51, 56]. In our study, we analyzed the effects of tumor diameter > 10 mm and the tumor diameter considered as a continuous variable on disease outcome in patients with BMI <30 kg/m2 and BMI ≥30 kg/m2. We observed an increased risk of persistent/recurrent disease in patients with tumor diameter >10 mm, and as a function of tumor diameter when used as a continuous variable in both groups (S2 Table). Thus, the size of the tumor itself, in both obese and non-obese patients, is a strong prognostic factor affecting disease outcome.

In univariate and multivariate analysis, higher BMI was not a predictor of aggressive clinicopathological features of DTC [extrathyroidal extension (microscopic or gross), lymph node metastases, and distant metastases]. Many studies report that BMI is a predictor of microscopic extrathyroidal extension, but our findings and those of Kwon et al. do not confirm this conclusion [48, 5254, 57]. In our study, tumor size and multifocality were prognostic factors for microscopic extrathyroidal extension. According to the 8th edition of AJCC/TNM staging system, microscopic extrathyroidal extension does not affect cancer stage [58]. Also, higher BMI was not a prognostic factor for a poorer treatment response (indeterminate, biochemically incomplete, or structurally incomplete), nor for a worse outcome of the disease (persistent/recurrent disease or death from cancer). Our results agree with those of Chung et al. [56], in which the authors did not find a significant difference between BMI groups in the outcome of the disease. They found that BMI was not a prognostic factor for PTC, which we also found in the present study.

We investigated the relationship between BMI and the survival of DTC patients and found that there was no significant difference in the overall survival of patients in relation to BMI groups. These results are in line with those of Yousif Al-Ammar et al. [59].

This retrospective study has several strengths. Firstly, it contains a large, ethnically homogeneous ethnic group of patients diagnosed and treated at a single center in Poland, in accordance with current guidelines for thyroid cancer. Secondly, this study included a larger group of obese patients (398 obese out of a total 1181 patients) than previous studies, with more Grade 2 and Grade 3 obese patients (BMI, ≥35 kg/m2; n = 123) [26, 48, 52, 55]. Because of this, we were able to perform separate analysis of six different BMI groups for the first time. Lastly, our follow-up period was approximately 7.7 years, similar to that in the work of Kwon et al. (approximately 8.4 years), and longer than those of several other studies [26, 51, 55, 56].

This work also has some limitations. Firstly, because this was a retrospective study, no information was available regarding the duration of obesity and thyroid cancer, waist-to-hip ratio, body fat percentage, skin fold thickness, and abdominal fat evaluation. Thus, this study defined obesity based solely on BMI, similar to many other studies [26, 48, 49, 51, 52, 55, 56]. For most patients, there was no information regarding TSH at the time of the cancer diagnosis available, so the relationship between TSH and thyroid status at the time of the diagnosis could not be assessed. There was also no detailed information on comorbidities such as diabetes, insulin resistance, and hypercholesterolemia, or lifestyle factors such as nutrition, smoking, alcohol consumption, and physical activity.

In conclusion, obesity was not associated with more aggressive clinicopathological features of thyroid cancer in our study. Obesity was not a risk factor for more advanced stages of cancer, nor was it a prognostic factor for poorer treatment response or worse clinical outcome in DTC patients.

References

  1. 1. Davies L, Welch HG: Current thyroid cancer trends in the United States. JAMA Otolaryngol Head Neck Surg 2014, 140(4):317–322. pmid:24557566
  2. 2. Vaccarella S, Franceschi S, Bray F, Wild CP, Plummer M, Dal Maso L: Worldwide Thyroid-Cancer Epidemic? The Increasing Impact of Overdiagnosis. N Engl J Med 2016, 375(7):614–617. pmid:27532827
  3. 3. Roman BR, Morris LG, Davies L: The thyroid cancer epidemic, 2017 perspective. Curr Opin Endocrinol Diabetes Obes 2017, 24(5):332–336. pmid:28692457
  4. 4. Jung KW, Won YJ, Kong HJ, Oh CM, Cho H, Lee DH et al. Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2012. Cancer Res Treat 2015, 47(2):127–141. pmid:25761484
  5. 5. Brito JP, Morris JC, Montori VM: Thyroid cancer: zealous imaging has increased detection and treatment of low risk tumours. BMJ 2013, 347:f4706. pmid:23982465
  6. 6. Hughes DT, Haymart MR, Miller BS, Gauger PG, Doherty GM: The most commonly occurring papillary thyroid cancer in the United States is now a microcarcinoma in a patient older than 45 years. Thyroid 2011, 21(3):231–236. pmid:21268762
  7. 7. Kowalska A, Sygut J, Sluszniak J, Walczyk A, Palyga I, Gasior-Perczak D et al. Variation of the epidemiological structure of thyroid cancer between year 2000 and 2012. Thyroid Research 2013, 6(Suppl 2):A30.
  8. 8. Agate L, Lorusso L, Elisei R: New and old knowledge on differentiated thyroid cancer epidemiology and risk factors. J Endocrinol Invest 2012, 35(6 Suppl):3–9. pmid:23014067
  9. 9. Davies L, Ouellette M, Hunter M, Welch HG: The increasing incidence of small thyroid cancers: where are the cases coming from? Laryngoscope 2010, 120(12):2446–2451. pmid:21108428
  10. 10. Gomez Segovia I, Gallowitsch HJ, Kresnik E, Kumnig G, Igerc I, Matschnig S et al. Descriptive epidemiology of thyroid carcinoma in Carinthia, Austria: 1984–2001. Histopathologic features and tumor classification of 734 cases under elevated general iodination of table salt since 1990: population-based age-stratified analysis on thyroid carcinoma incidence. Thyroid 2004, 14(4):277–286. pmid:15142361
  11. 11. Enewold L, Zhu K, Ron E, Marrogi AJ, Stojadinovic A, Peoples GE et al. Rising thyroid cancer incidence in the United States by demographic and tumor characteristics, 1980–2005. Cancer Epidemiol Biomarkers Prev 2009, 18(3):784–791. pmid:19240234
  12. 12. Pazaitou-Panayiotou K, Iliadou PK, Chrisoulidou A, Mitsakis P, Doumala E, Fotareli A et al. The increase in thyroid cancer incidence is not only due to papillary microcarcinomas: a 40-year study in 1 778 patients. Exp Clin Endocrinol Diabetes 2013, 121(7):397–401. pmid:23696480
  13. 13. Mangano JJ: Geographic variation in U.S. thyroid cancer incidence and a cluster near nuclear reactors in New Jersey, New York, and Pennsylvania. Int J Health Serv 2009, 39(4):643–661. pmid:19927407
  14. 14. How J, Tabah R: Explaining the increasing incidence of differentiated thyroid cancer. CMAJ 2007, 177(11):1383–1384. pmid:18025430
  15. 15. Pazaitou-Panayiotou K, Polyzos SA, Mantzoros CS: Obesity and thyroid cancer: epidemiologic associations and underlying mechanisms. Obes Rev 2013, 14(12):1006–1022. pmid:24034423
  16. 16. Baskin ML, Ard J, Franklin F, Allison DB: Prevalence of obesity in the United States. Obes Rev 2005, 6(1):5–7. pmid:15655032
  17. 17. Stepaniak U, Micek A, Waskiewicz A, Bielecki W, Drygas W, Janion M et al. Prevalence of general and abdominal obesity and overweight among adults in Poland. Results of the WOBASZ II study (2013–2014) and comparison with the WOBASZ study (2003–2005). Pol Arch Med Wewn 2016, 126(9):662–671. pmid:27535012
  18. 18. Renehan AG, Tyson M, Egger M, Heller RF, Zwahlen M: Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet 2008, 371(9612):569–578. pmid:18280327
  19. 19. Zhao ZG, Guo XG, Ba CX, Wang W, Yang YY, Wang J et al. Overweight, obesity and thyroid cancer risk: a meta-analysis of cohort studies. J Int Med Res 2012, 40(6):2041–2050. pmid:23321160
  20. 20. Peterson E, De P, Nuttall R: BMI, diet and female reproductive factors as risks for thyroid cancer: a systematic review. PLoS One 2012, 7(1):e29177. pmid:22276106
  21. 21. Xu L, Port M, Landi S, Gemignani F, Cipollini M, Elisei R et al. Obesity and the risk of papillary thyroid cancer: a pooled analysis of three case-control studies. Thyroid 2014, 24(6):966–974. pmid:24555500
  22. 22. Ma J, Huang M, Wang L, Ye W, Tong Y, Wang H: Obesity and risk of thyroid cancer: evidence from a meta-analysis of 21 observational studies. Med Sci Monit 2015, 21:283–291. pmid:25612155
  23. 23. Rinaldi S, Lise M, Clavel-Chapelon F, Boutron-Ruault MC, Guillas G, Overvad K et al. Body size and risk of differentiated thyroid carcinomas: findings from the EPIC study. Int J Cancer 2012, 131(6):E1004–1014. pmid:22511178
  24. 24. Farfel A, Kark JD, Derazne E, Tzur D, Barchana M, Lazar L et al. Predictors for thyroid carcinoma in Israel: a national cohort of 1,624,310 adolescents followed for up to 40 years. Thyroid 2014, 24(6):987–993. pmid:24483833
  25. 25. Kitahara CM, Gamborg M, Berrington de Gonzalez A, Sorensen TI, Baker JL: Childhood height and body mass index were associated with risk of adult thyroid cancer in a large cohort study. Cancer Res 2014, 74(1):235–242. pmid:24247722
  26. 26. Paes JE, Hua K, Nagy R, Kloos RT, Jarjoura D, Ringel MD: The relationship between body mass index and thyroid cancer pathology features and outcomes: a clinicopathological cohort study. J Clin Endocrinol Metab 2010, 95(9):4244–4250. pmid:20519347
  27. 27. Kim JY, Jung EJ, Jeong SH, Jeong CY, Ju YT, Lee YJ et al. The indices of body size and aggressiveness of papillary thyroid carcinoma. J Korean Surg Soc 2011, 80(4):241–244. pmid:22066042
  28. 28. Pappa T, Alevizaki M: Obesity and thyroid cancer: a clinical update. Thyroid 2014, 24(2):190–199. pmid:23879222
  29. 29. Marcello MA, Cunha LL, Batista FA, Ward LS: Obesity and thyroid cancer. Endocr Relat Cancer 2014, 21(5):T255–271. pmid:24741026
  30. 30. Tuttle M ML, Haugen B, Shah J, Sosa JA, Rohren E, Subramaniam RM HJ et al. AJCC Cancer Staging Manual, 8th edn: Springer; 2017.
  31. 31. Haugen BR, Alexander EK, Bible KC, Doherty GM, Mandel SJ, Nikiforov YE et 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(1):1–133.
  32. 32. Kowalska A, Walczyk A, Kowalik A, Palyga I, Gasior-Perczak D, Trybek T et al. Response to therapy of papillary thyroid cancer of known BRAF status. Clin Endocrinol (Oxf) 2017.
  33. 33. Kowalska A, Walczyk A, Palyga I, Gasior-Perczak D, Gadawska-Juszczyk K, Szymonek M et al. The Delayed Risk Stratification System in the Risk of Differentiated Thyroid Cancer Recurrence. PLoS One 2016, 11(4):e0153242. pmid:27078258
  34. 34. Gasior-Perczak D, Palyga I, Szymonek M, Kowalik A, Walczyk A, Kopczynski J et al. Delayed risk stratification system in pT1aN0/Nx DTC patients treated without radioactive iodine. Endocr Connect 2017, 6(7):522–527. pmid:28821486
  35. 35. Kowalska A, Palyga I, Gasior-Perczak D, Walczyk A, Trybek T, Sluszniak A et al. The Cut-Off Level of Recombinant Human TSH-Stimulated Thyroglobulin in the Follow-Up of Patients with Differentiated Thyroid Cancer. PLoS One 2015, 10(7):e0133852. pmid:26230494
  36. 36. Tuttle RM, Tala H, Shah J, Leboeuf R, Ghossein R, Gonen M et al. Estimating risk of recurrence in differentiated thyroid cancer after total thyroidectomy and radioactive iodine remnant ablation: using response to therapy variables to modify the initial risk estimates predicted by the new American Thyroid Association staging system. Thyroid 2010, 20(12):1341–1349. pmid:21034228
  37. 37. Momesso DP, Tuttle RM: Update on differentiated thyroid cancer staging. Endocrinol Metab Clin North Am 2014, 43(2):401–421. pmid:24891169
  38. 38. Reynolds JV, Donohoe CL, Doyle SL: Diet, obesity and cancer. Ir J Med Sci 2011, 180(2):521–527. pmid:21174166
  39. 39. Flegal KM, Carroll MD, Kit BK, Ogden CL: Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010. JAMA 2012, 307(5):491–497. pmid:22253363
  40. 40. Ljungvall A, Zimmerman FJ: Bigger bodies: long-term trends and disparities in obesity and body-mass index among U.S. adults, 1960–2008. Soc Sci Med 2012, 75(1):109–119. pmid:22551821
  41. 41. Davies L, Morris LG, Haymart M, Chen AY, Goldenberg D, Morris J et al. American Association of Clinical Endocrinologists and American College of Endocrinology Disease State Clinical Review: The Increasing Incidence of Thyroid Cancer. Endocr Pract 2015, 21(6):686–696. pmid:26135963
  42. 42. Simard EP, Ward EM, Siegel R, Jemal A: Cancers with increasing incidence trends in the United States: 1999 through 2008. CA Cancer J Clin 2012, 62(2):118–128. pmid:22281605
  43. 43. Kitahara CM, McCullough ML, Franceschi S, Rinaldi S, Wolk A, Neta G et al. Anthropometric Factors and Thyroid Cancer Risk by Histological Subtype: Pooled Analysis of 22 Prospective Studies. Thyroid 2016, 26(2):306–318. pmid:26756356
  44. 44. Rotondi M, Castagna MG, Cappelli C, Ciuoli C, Coperchini F, Chiofalo F et al. Obesity Does Not Modify the Risk of Differentiated Thyroid Cancer in a Cytological Series of Thyroid Nodules. Eur Thyroid J 2016, 5(2):125–131. pmid:27493887
  45. 45. Iribarren C, Haselkorn T, Tekawa IS, Friedman GD: Cohort study of thyroid cancer in a San Francisco Bay area population. Int J Cancer 2001, 93(5):745–750. pmid:11477590
  46. 46. Samanic C, Chow WH, Gridley G, Jarvholm B, Fraumeni JF Jr.: Relation of body mass index to cancer risk in 362,552 Swedish men. Cancer Causes Control 2006, 17(7):901–909. pmid:16841257
  47. 47. Dieringer P, Klass EM, Caine B, Smith-Gagen J: Associations between body mass and papillary thyroid cancer stage and tumor size: a population-based study. J Cancer Res Clin Oncol 2015, 141(1):93–98. pmid:25113832
  48. 48. Kim HJ, Kim NK, Choi JH, Sohn SY, Kim SW, Jin SM et al. Associations between body mass index and clinico-pathological characteristics of papillary thyroid cancer. Clin Endocrinol (Oxf) 2013, 78(1):134–140.
  49. 49. Kim SH, Park HS, Kim KH, Yoo H, Chae BJ, Bae JS et al. Correlation between obesity and clinicopathological factors in patients with papillary thyroid cancer. Surg Today 2015, 45(6):723–729. pmid:25059345
  50. 50. Wu C, Wang L, Chen W, Zou S, Yang A: Associations between body mass index and lymph node metastases of patients with papillary thyroid cancer: A retrospective study. Medicine (Baltimore) 2017, 96(9):e6202.
  51. 51. Kwon H, Kim M, Choi YM, Jang EK, Jeon MJ, Kim WG et al. Lack of Associations between Body Mass Index and Clinical Outcomes in Patients with Papillary Thyroid Carcinoma. Endocrinol Metab (Seoul) 2015, 30(3):305–311.
  52. 52. Grani G, Lamartina L, Montesano T, Ronga G, Maggisano V, Falcone R et al. Lack of association between obesity and aggressiveness of differentiated thyroid cancer. J Endocrinol Invest 2018.
  53. 53. Liu Z, Maimaiti Y, Yu P, Xiong Y, Zeng W, Li X et al. Correlation between body mass index and clinicopathological features of papillary thyroid microcarcinoma. Int J Clin Exp Med 2015, 8(9):16472–16479. pmid:26629173
  54. 54. Yu ST, Chen W, Cai Q, Liang F, Xu D, Han P et al. Pretreatment BMI Is Associated with Aggressive Clinicopathological Features of Papillary Thyroid Carcinoma: A Multicenter Study. Int J Endocrinol 2017, 2017:5841942. pmid:29085428
  55. 55. Tresallet C, Seman M, Tissier F, Buffet C, Lupinacci RM, Vuarnesson H, et al. The incidence of papillary thyroid carcinoma and outcomes in operative patients according to their body mass indices. Surgery 2014, 156(5):1145–1152. pmid:24878452
  56. 56. Chung YS, Lee JH, Lee YD: Is body mass index relevant to prognosis of papillary thyroid carcinoma? A clinicopathological cohort study. Surg Today 2017, 47(4):506–512. pmid:27654453
  57. 57. Choi JS, Kim EK, Moon HJ, Kwak JY: Higher body mass index may be a predictor of extrathyroidal extension in patients with papillary thyroid microcarcinoma. Endocrine 2015, 48(1):264–271. pmid:24858734
  58. 58. Tuttle RM, Haugen B, Perrier ND: Updated American Joint Committee on Cancer/Tumor-Node-Metastasis Staging System for Differentiated and Anaplastic Thyroid Cancer (Eighth Edition): What Changed and Why? Thyroid 2017, 27(6):751–756. pmid:28463585
  59. 59. Al-Ammar Y, Al-Mansour B, Al-Rashood O, Tunio MA, Islam T, Al-Asiri M, et al. Impact of body mass index on survival outcome in patients with differentiated thyroid cancer. Braz J Otorhinolaryngol 2017.