Thyroid cancer (TC) is the third most common cancer, following lung and stomach cancer, and the highest age-standardized incidence rate in Korea in 2020 (1). In women, it has the second highest crude and age-standardized incidence rates following breast cancer (1). In the past several decades, the incidence of TC has increased rapidly, in part due to improved detection technology and generalized fine-needle aspiration biopsies (2, 3). However, other risk factors for the development of TC cannot be ignored (4).

Metabolic syndrome (MetS) includes a cluster of metabolic disorders, including overweight, dysglycemia, hypertension, and dyslipidemia, and is significantly associated with an increased risk of developing diabetes mellitus and cardiovascular disease (5–7). Insulin resistance (IR) is known as one of the major mechanisms of MetS (7). Several models, such as hyperinsulinemic-euglycemic glucose clamp technique, homeostatic model assessment (HOMA), has been developed for determining insulin sensitivity or resistance (8, 9). However, these methods have some problems, including that is labor- and time-intensive or clinically less useful (8, 9). Thus, with the increasing interest for IR assessment in clinical settings, easier and more clinically practical markers have been in need. In 2018, the novel score, metabolic score for IR (METS-IR) was developed, which was calculated based on fasting blood glucose (FBG) levels, fasting triglyceride (TG) levels, body mass index (BMI), and high-density lipoprotein cholesterol (HDL-C) levels (10). As METS-IR demonstrated the better diagnostic and/or predicting performance to determine MetS compared to other makers, it has been used as surrogate marker for IR, which is valuable in predicting the development of MetS (10–13).

IR was reported to impact the incidence of several solid tumors, including colorectal, lung, and pancreatic cancer (14–17). A previous study reported that thyroid volumes were larger, and the risk of thyroid nodules was higher in IR patients (18). The relationship between MetS and TC has been suggested in several studies (19, 20), and it was also reported in a systemic review and meta-analysis (21). However, the study did not use METS-IR as a predictive value for TC and had a limitation due to differences in IR definitions between the studies analyzed (21).

The aim of this large retrospective cohort study was to evaluate the relationship between METS-IR, a novel score for insulin sensitivity, and the incidence of TC, especially in Korean individuals who participated in the National Health Screening Program (NHSP).

MetS refers to the presence of a cluster of risk factors specific to cardiovascular disease. According to the National Heart, Lung, and Blood Institute, the cluster of metabolic factors includes abdominal obesity, high blood pressure, impaired fasting blood glucose levels, high TG levels, and low HDL-C levels (23). MetS has been reported to possibly increase the risk of cancers, such as liver, colorectum, and mammary tissue cancer, as well as cardiovascular disease (16). MetS changes the microenvironment of the organism and is accompanied by insulin resistance, both of which are related to tumor formation (19). As with these malignancies, previous studies showed that the incidence of thyroid cancer was associated with MetS (19–21).

Son et al. suggested that obesity was positively correlated with the risk of TC after an average follow-up of seven years in Koreans aged over 20 years (24). Another prospective cohort study found a positive association between BMI and thyroid cancer, especially in women (20). Kown et al. concluded that weight gain significantly increased the incidence of TC, but weight loss was a protective factor for TC (25). Like obesity, high blood pressure and dyslipidemia have been positively linked to TC (21, 26). High FBG levels and diabetes mellitus suggest insulin resistance, but their impact on TC risk is still controversial (19, 27). A prospective cohort study showed that glucose was associated with an increase in TC risk in men. In contrast, an inverse association was seen between glucose and TC risk in women (20). In another matched study, history and the duration of diabetes mellitus were not associated with TC risk, but women with diabetes mellitus for fewer than five years had a reduced risk of TC (27).

In Korea, TC was expected to be the most common form of solid tumor in the 15–34 age group in both sexes, and the incidence of TC is higher in women compared to men (1). In women, the age-specific incidence of TC, along with breast cancer, is expected to level off after the age of 40 years (1). Similar differences in the incidence of TC between the sexes worldwide have been reported (28). In a previous cohort study and meta-analysis, gender disparity was mostly confined to the detection of small subclinical papillary TC (PTC) (29), which has the best prognosis of any subtype of TC. While TC incidence differs between the sexes, the difference in mortality due to TC is not significant (28), which could also be explained by the higher frequency of PTC in women than in men. The reasons for the gender disparity in TC incidence are not fully understood, but female sex hormones possibly play a role (30). Several risk factors for TC, including thyroid-stimulating hormone (TSH), adipokines, and angiotensin II, as well as MetS and estrogen, have been identified (19). A previous study concluded that the aggressiveness of PTC was associated with MetS, which was still significant after adjusting for age, sex, TSH, and BMI (31). However, less is known about the relationship between other thyroid cancer subtypes and MetS.

Given this, a causal relationship between METS-IR and TC incidence would be expected to be stronger in women. As expected, in this study, the female population showed a clearer association between METS-IR values and TC incidence in the adjusted model. However, in the crude model, the relationship was clear in men ( Table 2 ). In women, as METS-IR values increased beyond a certain point, the incidence of TC tended to decrease ( Figure 3C ). We suspect that the risk factors used in the adjustment affected the results. Thus, further research is needed to determine which risk factors have an impact, especially if the METS-IR value is above a certain level. Also, the diagnosis of other cancers, such as breast cancer, before TC diagnosis might affect the incidence of TC in the female population with high METS-IR values.

In subgroup analysis, the association between METS-IR scores and TC risk was stronger in younger patients (< 65 years old) and in patients with low BMI (BMI < 25 kg/m²). The relationship between METS-IR scores and TC risk was much clearer, with statistical significance in the subgroup < 65 years old. However, in the subgroup ≥ 65 years old, there were no statistically significant differences between METS-IR scores and TC risk ( Figure 4 ). Based on this, it is thought that age and BMI play a more important role than other MetS factors in the development of TC, although further study is needed.

This study had some limitations. First, whereas TCs are known as heterogenous in histologic and genetics and have different prognoses according to the subtypes (32), this study could not include information on heterogeneity. Second, information about hormones, such as TSH and estrogen, and other hidden covariates that could affect the incidence of TC was lacking. Also, as this study was retrospective, it utilized only TG, FBG, HDL-C, and BMI measurements at the time of health examination. Thus, we could not assess the extent of changes in these metrics and their potential impact on TC incidence. Despite these limitations, we think that this study is valuable in several ways. To the best of our knowledge, this was the first large cohort study to compare the association between METS-IR and TC incidence. Also, it is thought that this study could be representative of the Korean population because it used nationwide population-based data. Furthermore, we explored the relationship between METS-IR values and TC incidence using various analytic methods.

Despite the high incidence of TC, thyroid ultrasonography is still not included in basic health screening in Korea. One of the reasons for this is concern about overdiagnosis of TC (33), because differentiated TC, including PTC and follicular TC, has good prognosis (34). However, there is a concern that many cases of TC might exist but remain undetected. Also, in the clinic, some advanced TC afflicts many patients and increases socioeconomic costs. Thus, selective screening could be implemented for people at high risk of TC. Also, when the relationship between the aggressiveness of PTC and MetS is additionally considered (31), the results of this study are expected to provide information for which population should be screened for TC. As various targeted therapies have been developed and used in cancer treatment, including TC (35, 36), it would be worthwhile to further investigate the correlation of METS-IR and molecular genetic alterations in TC.

METS-IR was positively correlated with TC incidence in Korea.

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Requests to access these datasets should be directed to Hye Ryeon Kim, hyeryeon13@dau.ac.kr.

The studies involving humans were approved by Institutional Review Board of Dong-A University Hospital (DAUHIRB-EXP-23-177). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required from the participants or the participants’ legal guardians/next of kin in accordance with the national legislation and institutional requirements.

HK: Writing – original draft, Writing – review & editing. MS: Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing. SH: Writing – review & editing. SM: Writing – review & editing. HM: Writing – review & editing. YK: Writing – review & editing. MK: Writing – review & editing. JL: Conceptualization, Writing – review & editing.