The burden of thyroid cancer is associated with the level of national development in Asia: Evidence from 1990–2021 for 47 countries

The burden of thyroid cancer is associated with the level of national development in Asia: Evidence from 1990–2021 for 47 countries | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The burden of thyroid cancer is associated with the level of national development in Asia: Evidence from 1990–2021 for 47 countries Wenyi Qin, Jiong Lin, Haiqing Luo, Lili Yu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5911089/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective The aim was to examine the temporal patterns of the thyroid cancer (TC) burden and its association with the national development level. Methods The estimates of the incidence and mortality of TC for 47 countries were obtained from the Global Burden of Disease 2021 study for the period from 1990 to 2021. The human development level of each country was measured using the human development index (HDI), Social Progress Imperative (SPI) index, Nutrition and Medical Care (NMC) index, Density of Doctors per 100,000 people (DOD) and Personal Healthcare Spending (PHS) as summary indicators of health, education, and income reflecting the national development level. The associations between the burden of TC and these indices were measured via a scatterplot matrix, correlation heatmap and principal component analysis (PCA) plot. The mortality-to-incidence ratio (MIR) was employed as a proxy for the survival rate of patients with TC. Results The total number of TC-related deaths increased from 10,477 [95% uncertainty interval (UI), 9,394–12,252] in 1990 to 27,187 [95% UI, 23,128–30,091] in 2021 across all age groups. Asia accounted for 62.8% of the TC cases worldwide in 2021. In the working-age population, this mean number of deaths was 2,729 [3,243–2,394], and the incidence of TC increased from 1.41 cases per 100,000 people [1.23–1.63] in 1990 to 3.36 cases per 100,000 people [2.81–3.90] in 2021. In terms of TC incidence, very high- and high-HDI countries accounted for nine of the top ten countries. The total incidence rate of TC in the working-age population was positively correlated with four indicators, namely, the HDI (Corr = 0.365 * ), IHDI (Corr = 0.336 * ), SPI index (Corr = 0.384 * ), and NMC index (Corr = 0.332 * ), of which the incidence rate among males (Corr = 0.594 *** , 0.541 *** , 0.544 *** and 0.616 *** ), in particular, was strongly correlated with the indicators of social development. In terms of mortality, the HDI (Corr=-0.401*), IHDI (Corr=-0.387*), NMC index (Corr=-0.437**) and PHS (Corr=-0.446**) were negatively correlated with the total mortality rate. The global MIR decreased from 0.135 in 1990 to 0.068 in 2021. As seen from the data, Asia's working-age population presented a 21.1% increase in TC mortality and a 138% increase in TC incidence. Conclusion The increasing burden of TC within the working-age population across Asia has resulted in an overall increase in the incidence of TC, especially in developed countries, although the overall prognosis has gradually improved. Fewer developed countries should invest more in international cooperation and local research and development, including the management of primary healthcare systems and the development of high-level healthcare centres. Thyroid cancer Incidence Mortality Mortality-to-incidence ratio Human development index Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Thyroid cancer (TC) is one of the most common cancers worldwide and is prevalent in young people. The incidence of TC increased from 4.8 to 14.9 cases per 100,000 people, then stabilized and decreased again to approximately 13.5 cases per 100,000 people in 2018 1 . TC has a high incidence in both developed and developing countries and is estimated to cause an average of 500,000 to 600,000 new cases and more than 40,000 deaths per year worldwide 2 . The main histological types of TC are papillary thyroid carcinoma (PTC), follicular thyroid carcinoma (FTC), Hurthle's thyroid carcinoma (HCTC), medullary thyroid carcinoma (MTC), and interstitial thyroid carcinoma (ATC), which account for 80.2%, 11.4%, 3.1%, 3.5%, and 1.7% of all TCs, respectively 3 . Through the study of TC epidemiology, populations that should be prioritized for screening can be identified to improve the health of the population. TC is one of the most common tumours in the young and middle-aged population and is particularly prevalent in females 4,5 . Some studies reported a rapid increase in the incidence of TC only among patients with PTC 6 . In many countries in Asia, the increase in the incidence of PTC among females was particularly pronounced after 2000; however, in many American and European countries, the incidence has been stable since approximately 2009 6 . Therefore, a study of TC incidence and mortality in Asia over the last three decades would better reflect the local epidemiological changes in the disease. This study examined the burden (incidence and mortality) of TC in Asia (47 countries) from 1990–2021, with careful attention given to the temporal patterns of the burden of TC and their associations with a country’s level of development. The estimates of TC burden were obtained from the Global Burden of Disease (GBD) 2021 study 7 . The measures of national development and medical capacity include the Human Development Index (HDI), Inequality-adjusted Human Development Index (IHDI), Social Progress Imperative (SPI) index, Nutrition and Medical Care (NMC) index, Density of Doctors per 100,000 people (DOD) and Personal Healthcare Spending (PHS). The HDI and IHDI were obtained from the United Nations Development Program (UNDP). The SPI and NMC indices were collected from the Social Progress Imperative website, which provides official reference data for the GBD database. For the DOD and PHS, official data from the World Bank and the World Health Organization (WHO) were referenced. We investigated the burden of TC in many countries (47 countries) and scrutinized temporal patterns of the TC burden. In addition to investigating the incidence and mortality of TC, we also examined the mortality-to-incidence ratio (MIR), which has been shown to be a surrogate marker for 5-year survival 8 . In this study, we used multidimensional development indicators, including the HDI and IHDI, to compare and complement the Sociodemographic Index (SDI) used by the GBD study. Some researchers consider the SDI to be a composite measure of income, education and fertility, whereas the HDI is a measure of income, education and life expectancy. Since cancer burden is positively correlated with age, life expectancy seems to be a better indicator than fertility when describing cancer burden, hence the development of the HDI 9 . Examining past trends in morbidity, mortality and survival (expressed as the MIR) and their relationships with the HDI provides an idea of the rate of progress made in combating a disease that accounts for significant mortality and morbidity globally. TC is becoming progressively more prevalent among young people in developed countries 1 , and recent studies have confirmed that its global profile is characterized by male sex and that low-SDI areas have a worse prognosis, with a higher incidence in females than in males 10 . However, studies on the incidence and mortality characteristics of TC in working individuals aged 20–54 years, who are becoming increasingly likely to receive routine medical check-ups and have higher incomes in line with improvements in the working environment, are lacking 11 . Such studies could increase the probability of detecting various diseases and potentially improve disease prognosis 12,13 . Asia, the world's most populous continent, encompasses a wide range of economic states, from extremely developed countries to war-torn regions, providing a complete social span to study and inform the relevance of TC and national development. Methods The estimates of the incidence and mortality of TC (both male and female individuals aged 20–54 years) were obtained from the GBD 2021 study for the period from 1990–2021 7 (available at https://vizhub.healthdata.org/gbd-results/ ). The GBD 2021 study analysed disease and injury burdens by estimating the incidence, prevalence, mortality, years lived with disability (YLDs), disability-adjusted life years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100,983 data sources for 195 countries for the period from 1990 to 2021. The data sources include a variety of platforms, including autopsy databases, vital registration systems, household surveys, censuses, disease-specific registries and health service contact databases. In the GBD study, data are collected from various databases, and multiple modelling steps are performed to produce epidemiological data 14,15 . We briefly discuss how the GBD study produces estimates of TC incidence and mortality. The GBD study methodology involves processing incidence and mortality data from cancer registries and then matching the processed data by cancer, age, sex, year, and location to generate crude MIRs. Second, crude MIRs are included as inputs in the three-step modelling approach using general spatiotemporal Gaussian process regression (ST-GPR), and SDIs are used as covariates in the linear mixed-effects model using a log-link function to obtain the final MIRs. In the third step, the incidence rates obtained from the cancer registries are multiplied by the MIRs derived in the second step to obtain mortality estimates; these mortality estimates are then used as inputs in the cause‒death pooled model (CodeM) to obtain the final mortality estimates 15,16 . The CodeM model is developed to derive cause-specific mortality estimates; this is an ensemble modelling approach in which the predictive validity of many models is tested before final mortality estimates are derived. In this modelling approach, only the covariates that are considered reasonably related to a particular cause of death are selected. Some of the covariates used by CodeM to model TC mortality are as follows: education level, lagged distribution of income, sociodemographic indices, and accessibility and quality of health care indices. The final mortality estimate is divided by the estimated MIRs derived in the second step to obtain the final morbidity estimate 16 . In this study, we obtained estimates of TC incidence and mortality for the period from 1990 to 2021 and for 2021, respectively. We used TC incidence and mortality rates for the 20–54-year age group to describe the burden of TC in the main working population. TC survival was expressed as the MIR, which has been shown to be representative of survival for different tumours 8,17 . Although the MIR is not fully representative of survival, it can provide a useful direction for understanding the relative survival of individuals with TC in each country. The MIR is calculated directly from the mortality-to-crude incidence ratio obtained from the GBD 2021 report. In this study, we examined TC in Asian countries, including the Democratic People's Republic of Korea (DPRK). In line with GBD study practice, we report morbidity and mortality estimates with 95% uncertainty intervals. A country's level of development is measured by its HDI, which is a composite measure of three development indicators: health (life expectancy at birth), education (average years of schooling and expected years of schooling) and income (gross national income per capita). To calculate the HDI, each indicator is scored on a scale from 0 to 1, with 0 representing the lowest value and 1 representing the highest. The final HDI value for a country is calculated from the geometric mean of the health, education and income indices. The IHDI is based on a class of distributionally sensitive composite indices proposed by Foster, Lopez-Calva, and Szekely 18 , which are computed as geometric averages of inequality-adjusted dimensional indices. The IHDI ‘discounts’ the mean of each dimension according to the level of inequality, thus accounting for the inequality of the IHDI dimensions. The IHDI value is equal to the HDI value when there is no inequality between people but lower than the HDI value with increased inequality. In this sense, the IHDI measures the level of human development after inequality is considered. The HDI and IHDI data were obtained from the United Nations Development Programme (UNDP) database. For descriptive and analytical purposes, countries were classified into four categories on the basis of the United Nations Development Programme's classification: very-high-HDI (HDI > 0.800, 17 countries), high-HDI (0.700 < HDI < 0.799, 16 countries), medium-HDI (0.550 < HDI < 0.669, 10 countries) and low-HDI countries (HDI < 0.550, 3 countries). The HDI of the DPRK is not available, and its level of development was analysed by using other indicators. The SPI index measures the extent to which countries are meeting the social and environmental needs of their citizens. Fifty-four indicators in the areas of basic human needs, foundations of well-being, and opportunities for progress reflect a country’s relative performance. The index is published by the nonprofit organization Social Progress Imperative. Social and environmental factors include health (including health, housing and sanitation), equality, inclusion, sustainability, and personal freedom and security. The NMC index is part of the SPI index and includes the scores for child mortality, child stunting, the consumption of a diet low in fruits and vegetables, infectious diseases, maternal mortality and undernourishment. The SPI and NMC indices were obtained from the Social Progress Imperative website. The DOD and PHS reflect a country's basic health status and healthcare spending and provide a more intuitive picture of healthcare, which we used as a control and complement to the above statistical indicators. Data on the DOD and PHS indicators were obtained from the WHO and World Bank databases. The entire data analysis was conducted using Microsoft Excel and R Studio 4.2. Results The total number of TC-related deaths increased from 10,477 [95% uncertainty interval (UI), 9,394–12,252] in 1990 to 27,187 [95% UI, 23,128–30,091] in 2021 across all age groups. Asia accounted for 62.8% of the TC cases worldwide in 2021. In the working-age population, from the mean number of deaths was 2,729 [3,243–2,394], and the incidence of TC increased from 1.41 cases per 100,000 people [1.23–1.63] in 1990 to 3.36 cases per 100,000 people [2.81–3.90] in 2021. The mortality and incidence rates were significantly higher in the female population than in the male population, as shown in Table 1 and Fig. 1 . Table 1 Thyroid cancer burden among 20–54-year-olds in 2021 by country HDI, Human Development Index; IHDI, Inequality-adjusted Human Development Index; SPI, Social Progress Imperative; NMC, Nutrition and Medical Care; DOD, Density of Doctors per 100,000 people; PHS, Personal Healthcare Spending; Incidence, Number of cases per 100,000 people; mortality, Deaths per 100,000 people; MIR, Mortality‒to-incidence ratio. Data Source: Global Burden of Disease 2021 study. Incidence and Mortality of Thyroid Cancer in 2021 In terms of incidence, very-high-HDI and high-HDI countries accounted for nine of the top ten countries. Saudi Arabia had the highest incidence rate of 9.867 cases per 100,000 people, which is 303% of the global average rate of 3.26 cases per 100,000 people, followed by Vietnam, with a rate of 8.243 cases per 100,000 people, as shown in Table 1 and Fig. 2 . The analysis of the total and male and female incidence rates in relation to the level of development is presented in three ways: a scatterplot matrix, a correlation heatmap and a principal component analysis (PCA) plot. Map of the incidence of thyroid cancer in Asia. 2021; Incidence, number of cases per 100,000 people; source: Global Burden of Disease 2021 study. A scatterplot matrix is a graph that shows the relationships among multiple variables. It allows us to observe the linear or nonlinear relationships, correlations, trends, etc., between variables by creating a matrix where each matrix cell shows a scatter plot between two variables. Correlation coefficient values were added to the scatterplot matrix. If the correlation coefficient was close to 1 or -1, it indicated that the variables were highly correlated; if it was close to 0, it meant that there was almost no correlation, and values with statistical significance have an asterisk on the upper right corner of the coefficient. A heatmap indicates the correlation between different variables by colour, with the shade of the colour reflecting the strength of the correlation, indicating which variables have stronger or weaker linear relationships with each other. A PCA graph is a graphical representation that reduces multidimensional data to a few principal components. These graphs help us understand the relationships between complex variables, especially for discovering underlying structures or patterns in high-dimensional data. The main purpose of a PCA plot is to compress as much raw information (variation in variables) as possible into a handful of principal components (usually the first two). PCA biscale plots project sample points (individuals) and variables onto the plot at the same time, which makes it easy to visualize the distributions of individuals and the intervariable relationships. Each arrow represents the projection of an original variable into the principal component space. The longer an arrow is, the greater the contribution of the variable to the principal components (strong explanatory power); the shorter an arrow is, the weaker the explanatory power of the variable. An arrow angle close to 0 degrees indicates a positive correlation between two variables; an angle close to 90 degrees indicates no significant correlation between two variables; and an angle close to 180 degrees indicates a negative correlation between two variables. According to the results of the graph, the total incidence rate of TC in the working-age population was positively correlated with four indicators, namely, the HDI (Corr = 0.365 * ), IHDI (Corr = 0.336 * ), SPI index (Corr = 0.384 * ), and NMC index (Corr = 0.332 * ), of which the incidence rate among males (Corr = 0.594 *** , 0.541 *** , 0.544 *** and 0.616 *** ), in particular, was more strongly correlated with these indicators of social development; however, there was no significant correlation between the incidence rate among females and the above indicators (Corr = 0.303, 0.288, 0.312 and 0.228). The most significant indicator of incidence is the SPI index (Corr = 0.384 * ), whereas the DOD (Corr = 0.065), which reflects the prevalence of basic medicine, did not seem to be correlated with incidence. The contribution to the total incidence rate was greater for women, which is in line with the perception that TC is more common in women than in men, as shown in Fig. 3 . Correlation between thyroid cancer incidence and social development indicators, 2021: A: scatterplot matrix; B: correlation heatmap; C: principal component analysis plot; HDI, Human Development Index; IHDI, Inequality-adjusted Human Development Index; SPI, Social Progress Imperative; NMC, Nutrition and Medical Care; DOD, Density of Doctors per 100,000 people; PHS, Personal Healthcare Spending; Incidence, Number of cases per 100,000 people; source: Global Burden of Disease 2021 study. In terms of mortality, the HDI (Corr=-0.401 * ), IHDI (Corr=-0.387 * ), NMC index (Corr=-0.437 ** ) and PHS (Corr=-0.446 ** ) were negatively correlated with total mortality, with stronger correlations for the NMC index and PHS. However, in contrast to the morbidity results, the mortality results did not show a meaningful correlation with sociological indicators among males (Corr=-0.053, -0.052, -0.042 and − 0.306), whereas mortality was significantly negatively correlated with all indicators among females, especially the NMC index (Corr=-0.508 ** , -0.49 ** 0, -0.573 *** and − 0.457 ** ), as shown in Fig. 4 . Correlation between thyroid cancer mortality and social development indicators, 2021: A: scatterplot matrix; B: correlation heatmap; C: principal component analysis plot; HDI, Human Development Index; IHDI, Inequality-adjusted Human Development Index; SPI, Social Progress Imperative; NMC, Nutrition and Medical Care; DOD, Density of Doctors per 100,000 people; PHS, Personal Healthcare Spending; Mortality, Number of deaths per 100,000 people; source: Global Burden of Disease 2021 study. Changes in the Mortality, Incidence and MIR of Thyroid Cancer The global MIR decreased from 0.135 in 1990 to 0.068 in 2021. As seen from the data, Asia's working-age population experienced a 21.1% increase in TC mortality and a 138% increase in TC incidence. The incidence of TC increased in all countries except two, Kazakhstan and Tajikistan, where it decreased by 7.1% and 11.7%, respectively. The incidence rate increased in 23 of the 47 countries—4 of the 23 less-developed countries (low-/medium-HDI countries) and 18 of the 23 developed countries (high-/very-high-HDI countries)—and the DPRK did not have an HDI available for reference. The mortality rate increased in 24 of the 47 countries—9 of the 24 less-developed countries (low-/medium-HDI countries) and 15 of the 24 developed countries (high-/very-high-HDI countries). The MIR decreased in all countries, with the DPRK (-71.6%), Turkey (-66.2%), the Maldives (-63.0%), China (-62.4%), and Saudi Arabia (-60.9%) being the top five, as shown in Table 2 and Fig. 5 . Table 2 Thyroid cancer burden among individuals aged 20–54 years from 1990 to 2021 by country Development, 1. very high (HDI > 0.800, 17 countries), 2. high (0.700 < HDI < 0.799, 16 countries), 3. medium (0.550 < HDI < 0.669, 10 countries), and 4. low (HDI < 0.550, 3 countries); HDI, Human Development Index; Incidence, Number of cases per 100,000 people; Mortality, Number of deaths per 100,000 people; MIR, Mortality‒incidence ratio. Data Source: Global Burden of Disease 2021 study. Map of changes in the thyroid cancer mortality, incidence and MIR in Asia. 1990–2021; Incidence, Number of cases per 100,000 people; Mortality, Number of deaths per 100,000 people; source; MIR, mortality-to-incidence ratio: Global Burden of Disease 2021 study. Changes in the HDI were used in the correlation analysis as a reference marker for changes in the level of social development, as other indicators are not readily available. A scatterplot matrix, a correlation heatmap and a PCA plot were used to represent the correlation. In terms of mortality and incidence, changes in the HDI and MIR were significantly negatively correlated (Corr=-0.329 * ), but changes in these indicators were not significantly related to the level of social development (very high (HDI > 0.800), high (0.700 < HDI < 0.799), medium (0.550 < HDI < 0.669), and low (HDI < 0.550)). Changes in the MIR were mainly due to the contribution of reductions in morbidity (Corr=-0.379 * ), particularly in men (Corr=-0.431 ** ), as shown in Fig. 6 . Correlation between changes in the HDI and the mortality, incidence and MIR of thyroid cancer in individuals aged 20–54 years: A: scatterplot matrix; B: correlation heatmap; C: principal component analysis plot; HDI, Human Development Index; Incidence, Number of cases per 100,000 people; Mortality, Number of deaths per 100,000 people; source; MIR, mortality-to-incidence ratio; source: Global Burden of Disease 2021 study. Discussion This study examined the burden of TC and its temporal patterns in 47 Asian countries between 1990 and 2021. Using GBD 2021 data, we found that the global burden of TC has increased significantly over the past three decades and that there are wide inequalities between geographic regions due to different levels of development. Developed countries (those with high/very high HDIs) have relatively high incidence rates, whereas developed and less developed countries account for equal proportions of the top 10 countries in terms of mortality. The high prevalence of TC in working-age populations in developed countries can be attributed to the level of screening 11–13 , and the similarity in TC mortality between developed and developing countries can be attributed to several factors. One of the main reasons is the advancement in diagnostic technology, particularly in more affluent nations. In developed countries, the increased detection of small, indolent TCs, which are not typically life-threatening, has led to higher incidence rates without a corresponding increase in mortality. This is known as "overdiagnosis" and does not necessarily reflect a higher risk of death from TC. Another reason is that the actual mortality rates of TC remain low and stable across both developed and developing nations. This trend is partially because individuals with most TCs, especially well-differentiated types, have excellent survival rates regardless of geographical or socioeconomic differences 19 . Overall, the incidence of TC in the working-age population and the level of national development have increased in most Asian countries, whereas approximately half of the countries have experienced a decrease in mortality. The MIR has decreased across Asia, which could reflect a general improvement in the prognosis of TC, especially 5-year survival. However, there are differences in the MIR between developed and less developed countries, with the 10 countries with the lowest MIRs all being developed countries, whereas 8 of the 10 countries with the highest MIRs are less developed countries. Studies suggest that improved healthcare infrastructure in developed countries, including better postsurgical management and the use of radioactive iodine therapy, has contributed to reducing mortality rates and better prognoses 19,20 . This seems to indicate that less developed countries need to further improve their medical services. In our study, we found that the incidence of TC, especially in the male population, was strongly correlated with the level of social development, whereas there was no such trend in the female population. This may be attributed to hormonal differences, particularly the effect of oestrogen, which may promote tumour growth in women and is not influenced by the social environment 21 . Studies have shown that oestrogen-related genes are associated with immune regulation, tumour immune evasion, defence systems, signal transduction, the tumour microenvironment and immune regulation in individuals with TC. High-risk patients in the immunotherapy dataset had considerably shorter survival times than low-risk patients did 22 . On the other hand, there is evidence that men's participation in regular health checks is increasing, particularly among men of working age. Historically, men have been less likely than women to seek preventive health care, often seeking care when they have symptoms, which often represents advanced disease progression; however, this trend is changing because of greater awareness of the benefits of early detection and preventive health care. A study that included a predominantly under-45 population in Guangdong Province, China, revealed that although the detection rate of thyroid nodules was higher in women than in men (13.51 percent vs. 7.71 percent), the number of working-age men who presented for medical check-ups reached 121,883, which was significantly greater than the number of working-age women (70,680) who presented for check-ups. This seems to indicate that the willingness to attend medical check-ups is already great among younger men 23 . Our study also revealed a negative correlation between TC mortality and various indices related to social development, with the contribution coming mainly from the reduction in mortality among women with TC. A previous study concluded that overdiagnosis, as a general phenomenon, could improve the survival of patients with TC (the risk of mortality decreased by half for men and by 2/3 for women) 24 , but this benefit was not evident in patients with more malignant subtypes, which occur more often in males 25 . In terms of both incidence and mortality, the NMC index showed a statistically significant correlation compared with the other indicators, and this index can be considered to have a greater impact on TC given that it is an SPI-affiliated indicator reflecting mainly hygiene-, health- and nutrition-related indicators, probably since TC involves a tumour of the endocrine system. The MIR generally decreased across Asia but did not show a clear correlation with the HDI; however, our findings suggest a clear decrease in the MIR with increasing development, which may be due to the scientific and technological developments described earlier, including better management processes and advancements in therapy 19,20 . When conducting the study, we found that changes in the MIR and HDI were correlated, but statistical significance was lost when the HDI was stratified using a four-point scale, which may indicate the limitations of the HDI as a sociological indicator and the direct application of its stratification method to the medical field. The reason may be that the index is the result of a combination of multiple indicators and that some countries have a high level of development in the field of health care but do not show a similar lead in other fields under this statistical method, resulting in inflated ratings. In our study of the factors associated with changes in TC incidence and mortality, we used the HDI as the independent variable, partly because several other indicators are not readily available due to time limitations and partly because previous studies have reported an association between the burden of cancer and the HDI, which confirms the reliability of such comparisons 9 . The DOD is associated with a high incidence of TC but is not clearly correlated with mortality. Previous studies have revealed a potential correlation between physician density and mortality in patients with highly malignant cancer such as bladder and prostate cancer but without clear statistical significance 26 ; we believe that this indicator primarily reflects primary care equity because a greater density of physicians facilitates screening of patients with early-stage cancers 27 . However, for malignant subtypes of TC, which are much more lethal, the prognosis should largely depend on the level of treatment and care at advanced medical centres. Limitations First, estimates of the burden of TC were derived from the GBD 2021 study, and the quality of the estimates is highly dependent on the availability of cancer registry data. Because cancer registry coverage lacks completeness in many low-income countries, spatial and temporal data from neighbouring regions were used to assess the global burden of TC. The lack of cancer registry data leads to large UIs that may be too large to provide meaningful data on policy implications for these countries. Second, in less developed countries, the estimates used and reported here may be biased downwards because of underreporting or misclassification of cancer deaths. Third, it is well known that cancers detected early (clinical stage 1) are less severe and less life-threatening than those detected late (clinical stage 3 or 4), but there are no estimates of cases diagnosed at different clinical stages. Fourth, the lack of effective grassroots management and health organizations in some Middle Eastern and Southeast Asian countries due to prolonged wars may have led to the inclusion of data from only some of the larger cities, thus introducing bias; furthermore, many countries lack effective grassroots management and health organizations due to weak governments, which may lead to deaths caused by war-related trauma, plague, or starvation and to a lower number of cancer deaths than the actual number of deaths. Last, some countries are missing key data, such as the DPRK, which is unable to provide valid data on indicators such as the HDI, and others, such as Bhutan, which lack data on the HDI for 1990 for rate-of-change purposes. This can lead to bias in the results. Conclusions The increasing burden of TC within the working-age population across Asia has resulted in an overall increase in the incidence of TC, especially in developed countries, although the overall prognosis has gradually improved. This may be attributed to further human development leading to early detection of malignant tumours, increased awareness and better treatment modalities in developed countries. On the basis of past trends, the incidence of TC is expected to increase further in the future due to irregular patterns of work and rest and lifestyles, unhealthy diets, the disruption of hormone secretion, and exposure to ionizing radiation in the working-age population. However, the lack of early detection, late onset and lack of active surveillance systems in less developed countries are expected to strain health-care systems with limited resources. In underdeveloped countries, TC has an overall high mortality rate, which can be attributed to the relative disadvantage of cancer patients due to late diagnosis, misdiagnosis, lack of access to good surgeons or chemotherapeutic agents, high cost of treatment and lack of health insurance coverage. These factors contribute to the relatively high burden borne by cancer patients in these countries. Since TC shows relatively pronounced sex differences, increased awareness of the need for ultrasound screening in working-aged men is necessary. Regardless of sex, a pathway from regular check-ups to prevention and individualized treatment will improve the prognosis of the disease. Owing to the large intercountry developmental differences in Asian countries, improving the capacity of and education by healthcare systems in underdeveloped countries, increasing the purchase of most products, and decreasing the hidden costs of taxes and logistics, which further increase the burden on patients, are urgently needed, and less developed countries should invest more in international cooperation and local research and development, including the management of primary healthcare systems and the development of high-level healthcare centres. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials The datasets analyzed in this study are publicly accessible through the following sources: 1.Global Burden of Disease (GBD) 2021 data: [https://vizhub.healthdata.org/gbd-results/](https://vizhub.healthdata.org/gbd-results/) 2.Human Development Index (HDI) data: United Nations Development Programme (UNDP) 3.Social Progress Imperative (SPI) and Nutrition and Medical Care (NMC) indices: [Social Progress Imperative](https://www.socialprogress.org/) 4.Density of Doctors (DOD) and Personal Healthcare Spending (PHS): World Bank and World Health Organization (WHO) databases. Competing interests The authors declare no competing interests, financial or non-financial, related to this work. Funding This research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contributions Wenyi Qin: Conceptualization, formal analysis, data curation, visualization, writing – original draft. Wenyi Qin: Conceptualization, Formal analysis, Writing - Original Draft. Jiong Lin: Investigation, Data curation. Haiqing Luo: Supervision, Writing - Review & Editing. Lili Yu: Supervision, Validation, Writing - Review & Editing. Acknowledgements We thank Jianhan Yin ( [email protected] ) for sharing methodological insights on the GBD database. We also acknowledge the Global Burden of Disease Collaborators for their efforts in compiling and maintaining the GBD dataset. References Powers AE, Marcadis AR, Lee M, Morris LGT, Marti JL. Changes in Trends in Thyroid Cancer Incidence in the United States, 1992 to 2016. Jama 2019;322(24):2440-2441. (In eng). DOI: 10.1001/jama.2019.18528. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68(6):394-424. (In eng). DOI: 10.3322/caac.21492. Pellegriti G, Frasca F, Regalbuto C, Squatrito S, Vigneri R. Worldwide increasing incidence of thyroid cancer: update on epidemiology and risk factors. J Cancer Epidemiol 2013;2013:965212. (In eng). DOI: 10.1155/2013/965212. Hirsch D, Yackobovitch-Gavan M, Lazar L. Infertility and Pregnancy Rates in Female Thyroid Cancer Survivors: A Retrospective Cohort Study Using Health Care Administrative Data from Israel. Thyroid 2023;33(4):456-463. (In eng). DOI: 10.1089/thy.2022.0501. Bleyer A, Barr R, Hayes-Lattin B, Thomas D, Ellis C, Anderson B. The distinctive biology of cancer in adolescents and young adults. Nat Rev Cancer 2008;8(4):288-98. (In eng). DOI: 10.1038/nrc2349. Miranda-Filho A, Lortet-Tieulent J, Bray F, et al. Thyroid cancer incidence trends by histology in 25 countries: a population-based study. Lancet Diabetes Endocrinol 2021;9(4):225-234. (In eng). DOI: 10.1016/s2213-8587(21)00027-9. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024;403(10440):2100-2132. (In eng). DOI: 10.1016/s0140-6736(24)00367-2. Sharma R. Breast cancer incidence, mortality and mortality-to-incidence ratio (MIR) are associated with human development, 1990-2016: evidence from Global Burden of Disease Study 2016. Breast Cancer 2019;26(4):428-445. (In eng). DOI: 10.1007/s12282-018-00941-4. Sharma R. The burden of prostate cancer is associated with human development index: evidence from 87 countries, 1990-2016. Epma j 2019;10(2):137-152. (In eng). DOI: 10.1007/s13167-019-00169-y. Zhou T, Wang X, Zhang J, et al. Global burden of thyroid cancer from 1990 to 2021: a systematic analysis from the Global Burden of Disease Study 2021. J Hematol Oncol 2024;17(1):74. (In eng). DOI: 10.1186/s13045-024-01593-y. Rao KD, Bairwa M, Mehta A, et al. Improving urban health through primary health care in south Asia. Lancet Glob Health 2024 (In eng). DOI: 10.1016/s2214-109x(24)00121-9. Kuwabara Y, Fujii M, Kinjo A, Osaki Y. Abstaining from annual health check-ups is a predictor of advanced cancer diagnosis: a retrospective cohort study. Environ Health Prev Med 2022;27:1. (In eng). DOI: 10.1265/ehpm.21-00292. Walker N, Heuer A, Sanders R, Tong H. The costs and benefits of scaling up interventions to prevent poor birth outcomes in low-income and middle-income countries: a modelling study. Lancet Glob Health 2024;12(9):e1526-e1533. (In eng). DOI: 10.1016/s2214-109x(24)00238-9. Fitzmaurice C, Akinyemiju TF, Al Lami FH, et al. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2016: A Systematic Analysis for the Global Burden of Disease Study. JAMA Oncol 2018;4(11):1553-1568. (In eng). DOI: 10.1001/jamaoncol.2018.2706. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017;390(10100):1151-1210. (In eng). DOI: 10.1016/s0140-6736(17)32152-9. Foreman KJ, Lozano R, Lopez AD, Murray CJ. Modeling causes of death: an integrated approach using CODEm. Popul Health Metr 2012;10:1. (In eng). DOI: 10.1186/1478-7954-10-1. Chen SL, Wang SC, Ho CJ, et al. Prostate Cancer Mortality-To-Incidence Ratios Are Associated with Cancer Care Disparities in 35 Countries. Sci Rep 2017;7:40003. (In eng). DOI: 10.1038/srep40003. Foster JE, Lopez‐Calva LF, Szekely M. Measuring the distribution of human development: methodology and an application to Mexico. Journal of Human Development 2005;6(1):5-25. Huang J, Ngai CH, Deng Y, et al. Incidence and mortality of thyroid cancer in 50 countries: a joinpoint regression analysis of global trends. Endocrine 2023;80(2):355-365. DOI: 10.1007/s12020-022-03274-7. Pizzato M, Li M, Vignat J, et al. The epidemiological landscape of thyroid cancer worldwide: GLOBOCAN estimates for incidence and mortality rates in 2020. The Lancet Diabetes & Endocrinology 2022;10(4):264-272. DOI: 10.1016/S2213-8587(22)00035-3. Lu Y, Li J, Li J. Estrogen and thyroid diseases: an update. Minerva Med 2016;107(4):239-44. (In eng). Zhang L, Zhou M, Gao X, et al. Estrogen-related genes for thyroid cancer prognosis, immune infiltration, staging, and drug sensitivity. BMC Cancer 2023;23(1):1048. (In eng). DOI: 10.1186/s12885-023-11556-0. Lai X, Ouyang P, Zhu H, et al. [Detection rate of thyroid nodules in routine health check-up and its influencing factors: a 10-year survey of 309 576 cases]. Nan Fang Yi Ke Da Xue Xue Bao 2020;40(2):268-273. (In chi). DOI: 10.12122/j.issn.1673-4254.2020.02.20. Tichanek F, Försti A, Liska V, et al. Early mortality critically impedes improvements in thyroid cancer survival through a half century. European Journal of Endocrinology 2023;189(3):355-362. DOI: 10.1093/ejendo/lvad117. Hellman P, Norlén O, Stålberg P, Daskalakis K. Thyroid Cancer. In: Yalcin S, Öberg K, eds. Neuroendocrine Tumours: Diagnosis and Management. Cham: Springer International Publishing; 2024:445-483. Colli J, Sartor O, Thomas R, Lee BR. Does urological cancer mortality increase with low population density of physicians? J Urol 2011;186(6):2342-6. (In eng). DOI: 10.1016/j.juro.2011.07.069. Fleming NH, Grade MM, Bendavid E. Impact of primary care provider density on detection and diagnosis of cutaneous melanoma. PLoS One 2018;13(7):e0200097. (In eng). DOI: 10.1371/journal.pone.0200097. Tables Table 1 and 2 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Onlinefloatimage2.png Table 1. Thyroid cancer burden among 20–54-year-olds in 2021 by country HDI, Human Development Index; IHDI, Inequality-adjusted Human Development Index; SPI, Social Progress Imperative; NMC, Nutrition and Medical Care; DOD, Density of Doctors per 100,000 people; PHS, Personal Healthcare Spending; Incidence, Number of cases per 100,000 people; mortality, Deaths per 100,000 people; MIR, Mortality‒to-incidence ratio. Data Source: Global Burden of Disease 2021 study. Onlinefloatimage6.png Table 2. Thyroid cancer burden among individuals aged 20-54 years from 1990 to 2021 by country Development, 1. very high (HDI > 0.800, 17 countries), 2. high (0.700 < HDI < 0.799, 16 countries), 3. medium (0.550 < HDI < 0.669, 10 countries), and 4. low (HDI < 0.550, 3 countries); HDI, Human Development Index; Incidence, Number of cases per 100,000 people; Mortality, Number of deaths per 100,000 people; MIR, Mortality‒incidence ratio. Data Source: Global Burden of Disease 2021 study. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5911089","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":409405320,"identity":"fc3cc303-34ed-4571-9675-97a0a7587513","order_by":0,"name":"Wenyi Qin","email":"","orcid":"","institution":"Macau University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Wenyi","middleName":"","lastName":"Qin","suffix":""},{"id":409405321,"identity":"0aa9007b-e934-459f-9143-fc54400f494b","order_by":1,"name":"Jiong Lin","email":"","orcid":"","institution":"Macau University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Jiong","middleName":"","lastName":"Lin","suffix":""},{"id":409405322,"identity":"09d2a7af-3a58-4d25-a6f1-730c079c3aad","order_by":2,"name":"Haiqing Luo","email":"","orcid":"","institution":"Affiliated Hospital of Guangdong Medical University","correspondingAuthor":false,"prefix":"","firstName":"Haiqing","middleName":"","lastName":"Luo","suffix":""},{"id":409405323,"identity":"0770fc72-7e8a-43ca-a3e9-2d845ea1022f","order_by":3,"name":"Lili Yu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArElEQVRIiWNgGAWjYBACPnYg8QHKkSBKCxszAwPjDCCDhyQtzDwkauExk7bNOWxvz8B88DYPwzY54rTkbjuc2MPAlmzNw3DbmGgtCTwMQAZQS2IDUVostx2252Hg/0aCFsZthxl7GHjYiNXCVmzZuy09secwm7HlHAMi/MLP3rzxxs9t1vbs7c0Pb7ypuE04xBgYOAwgNDOIMCBCAwMD+wOilI2CUTAKRsEIBgARrCuVzcRIMAAAAABJRU5ErkJggg==","orcid":"","institution":"Macau University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Lili","middleName":"","lastName":"Yu","suffix":""}],"badges":[],"createdAt":"2025-01-27 09:38:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5911089/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5911089/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75406697,"identity":"8fa9ee07-ddfb-464e-ba53-0c51e6009dbd","added_by":"auto","created_at":"2025-02-04 08:53:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":143745,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal changes in key global thyroid cancer indicators, 1990-2021: A: incidence rates per 10,000 population of all ages; B: incidence rates of all ages; C: mortality rates among males and females aged 20-54 years; D: morbidity rates among males and females aged 20-54 years. Incidence, number of cases; mortality, number of deaths; a green line is shown for males; and a purple line is shown for females; source: Global Burden of Disease 2021 study.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5911089/v1/8376a2e027c74ffc90b88046.png"},{"id":75406700,"identity":"657f71d1-2920-44cc-9d45-49c8d92eba8e","added_by":"auto","created_at":"2025-02-04 08:53:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":117828,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the incidence of thyroid cancer in Asia. 2021; Incidence, number of cases per 100,000 people; source: Global Burden of Disease 2021 study.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5911089/v1/c3c32df04f835e9eea6c0951.png"},{"id":75406728,"identity":"52a9be6c-0b55-4c02-bc01-b5515abb1a31","added_by":"auto","created_at":"2025-02-04 08:53:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":137315,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between thyroid cancer incidence and social development indicators, 2021: A: scatterplot matrix; B: correlation heatmap; C: principal component analysis plot; HDI, Human Development Index; IHDI, Inequality-adjusted Human Development Index; SPI, Social Progress Imperative; NMC, Nutrition and Medical Care; DOD, Density of Doctors per 100,000 people; PHS, Personal Healthcare Spending; Incidence, Number of cases per 100,000 people; source: Global Burden of Disease 2021 study.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5911089/v1/1113f869ddf664d20aafaac2.png"},{"id":75406717,"identity":"800595c6-25b6-4a3f-a268-1896fab52524","added_by":"auto","created_at":"2025-02-04 08:53:36","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":142528,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between thyroid cancer mortality and social development indicators, 2021: A: scatterplot matrix; B: correlation heatmap; C: principal component analysis plot; HDI, Human Development Index; IHDI, Inequality-adjusted Human Development Index; SPI, Social Progress Imperative; NMC, Nutrition and Medical Care; DOD, Density of Doctors per 100,000 people; PHS, Personal Healthcare Spending; Mortality, Number of deaths per 100,000 people; source: Global Burden of Disease 2021 study.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5911089/v1/060929fbd3d2efb76a436218.png"},{"id":75406787,"identity":"486b554d-dbc4-4f16-bdb7-f15cd10e160b","added_by":"auto","created_at":"2025-02-04 08:53:39","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":239101,"visible":true,"origin":"","legend":"\u003cp\u003eMap of changes in the thyroid cancer mortality, incidence and MIR in Asia. 1990-2021; Incidence, Number of cases per 100,000 people; Mortality, Number of deaths per 100,000 people; source; MIR, mortality-to-incidence ratio: Global Burden of Disease 2021 study.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5911089/v1/86755c2cda27d0ccf79f4099.png"},{"id":75406746,"identity":"c177603d-86a7-4d26-a04c-39ab1d05b467","added_by":"auto","created_at":"2025-02-04 08:53:37","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":105020,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between changes in the HDI and the mortality, incidence and MIR of thyroid cancer in individuals aged 20–54 years: A: scatterplot matrix; B: correlation heatmap; C: principal component analysis plot; HDI, Human Development Index; Incidence, Number of cases per 100,000 people; Mortality, Number of deaths per 100,000 people; source; MIR, mortality-to-incidence ratio; source: Global Burden of Disease 2021 study.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5911089/v1/8140d8b5d3b068e31ef7c7a4.png"},{"id":75408901,"identity":"4c32db8e-9579-4c23-8efe-cd02d273d14b","added_by":"auto","created_at":"2025-02-04 09:01:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1150286,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5911089/v1/2ee422e5-d5b3-4a76-ba95-a6b30fd2fbf5.pdf"},{"id":75406767,"identity":"cac5a52d-c919-42b2-9826-89319d4e4442","added_by":"auto","created_at":"2025-02-04 08:53:38","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21593,"visible":true,"origin":"","legend":"\u003cp\u003eTable 1.\u003c/p\u003e\n\u003cp\u003eThyroid cancer burden among 20–54-year-olds in 2021 by country\u003c/p\u003e\n\u003cp\u003eHDI, Human Development Index; IHDI, Inequality-adjusted Human Development Index; SPI, Social Progress Imperative; NMC, Nutrition and Medical Care; DOD, Density of Doctors per 100,000 people; PHS, Personal Healthcare Spending; Incidence, Number of cases per 100,000 people; mortality, Deaths per 100,000 people; MIR, Mortality‒to-incidence ratio. Data Source: Global Burden of Disease 2021 study.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5911089/v1/538f7f4735e5c4bf2b1861bf.png"},{"id":75406705,"identity":"d52a241b-aaab-455e-8aa6-fa6add3d0929","added_by":"auto","created_at":"2025-02-04 08:53:36","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2358,"visible":true,"origin":"","legend":"\u003cp\u003eTable 2.\u003c/p\u003e\n\u003cp\u003eThyroid cancer burden among individuals aged 20-54 years from 1990 to 2021 by country\u003c/p\u003e\n\u003cp\u003eDevelopment, 1. very high (HDI \u0026gt; 0.800, 17 countries), 2. high (0.700 \u0026lt; HDI \u0026lt; 0.799, 16 countries), 3. medium (0.550 \u0026lt; HDI \u0026lt; 0.669, 10 countries), and 4. low (HDI \u0026lt; 0.550, 3 countries); HDI, Human Development Index; Incidence, Number of cases per 100,000 people; Mortality, Number of deaths per 100,000 people; MIR, Mortality‒incidence ratio. Data Source: Global Burden of Disease 2021 study.\u003c/p\u003e","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-5911089/v1/d3d759445fa7f22a288edb7a.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"The burden of thyroid cancer is associated with the level of national development in Asia: Evidence from 1990–2021 for 47 countries","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThyroid cancer (TC) is one of the most common cancers worldwide and is prevalent in young people. The incidence of TC increased from 4.8 to 14.9 cases per 100,000 people, then stabilized and decreased again to approximately 13.5 cases per 100,000 people in 2018\u003csup\u003e1\u003c/sup\u003e. TC has a high incidence in both developed and developing countries and is estimated to cause an average of 500,000 to 600,000 new cases and more than 40,000 deaths per year worldwide\u003csup\u003e2\u003c/sup\u003e. The main histological types of TC are papillary thyroid carcinoma (PTC), follicular thyroid carcinoma (FTC), Hurthle's thyroid carcinoma (HCTC), medullary thyroid carcinoma (MTC), and interstitial thyroid carcinoma (ATC), which account for 80.2%, 11.4%, 3.1%, 3.5%, and 1.7% of all TCs, respectively\u003csup\u003e3\u003c/sup\u003e. Through the study of TC epidemiology, populations that should be prioritized for screening can be identified to improve the health of the population.\u003c/p\u003e \u003cp\u003eTC is one of the most common tumours in the young and middle-aged population and is particularly prevalent in females\u003csup\u003e4,5\u003c/sup\u003e. Some studies reported a rapid increase in the incidence of TC only among patients with PTC\u003csup\u003e6\u003c/sup\u003e. In many countries in Asia, the increase in the incidence of PTC among females was particularly pronounced after 2000; however, in many American and European countries, the incidence has been stable since approximately 2009\u003csup\u003e6\u003c/sup\u003e. Therefore, a study of TC incidence and mortality in Asia over the last three decades would better reflect the local epidemiological changes in the disease.\u003c/p\u003e \u003cp\u003eThis study examined the burden (incidence and mortality) of TC in Asia (47 countries) from 1990–2021, with careful attention given to the temporal patterns of the burden of TC and their associations with a country’s level of development. The estimates of TC burden were obtained from the Global Burden of Disease (GBD) 2021 study\u003csup\u003e7\u003c/sup\u003e. The measures of national development and medical capacity include the Human Development Index (HDI), Inequality-adjusted Human Development Index (IHDI), Social Progress Imperative (SPI) index, Nutrition and Medical Care (NMC) index, Density of Doctors per 100,000 people (DOD) and Personal Healthcare Spending (PHS). The HDI and IHDI were obtained from the United Nations Development Program (UNDP). The SPI and NMC indices were collected from the Social Progress Imperative website, which provides official reference data for the GBD database. For the DOD and PHS, official data from the World Bank and the World Health Organization (WHO) were referenced. We investigated the burden of TC in many countries (47 countries) and scrutinized temporal patterns of the TC burden. In addition to investigating the incidence and mortality of TC, we also examined the mortality-to-incidence ratio (MIR), which has been shown to be a surrogate marker for 5-year survival\u003csup\u003e8\u003c/sup\u003e. In this study, we used multidimensional development indicators, including the HDI and IHDI, to compare and complement the Sociodemographic Index (SDI) used by the GBD study. Some researchers consider the SDI to be a composite measure of income, education and fertility, whereas the HDI is a measure of income, education and life expectancy. Since cancer burden is positively correlated with age, life expectancy seems to be a better indicator than fertility when describing cancer burden, hence the development of the HDI\u003csup\u003e9\u003c/sup\u003e. Examining past trends in morbidity, mortality and survival (expressed as the MIR) and their relationships with the HDI provides an idea of the rate of progress made in combating a disease that accounts for significant mortality and morbidity globally.\u003c/p\u003e \u003cp\u003eTC is becoming progressively more prevalent among young people in developed countries\u003csup\u003e1\u003c/sup\u003e, and recent studies have confirmed that its global profile is characterized by male sex and that low-SDI areas have a worse prognosis, with a higher incidence in females than in males\u003csup\u003e10\u003c/sup\u003e. However, studies on the incidence and mortality characteristics of TC in working individuals aged 20–54 years, who are becoming increasingly likely to receive routine medical check-ups and have higher incomes in line with improvements in the working environment, are lacking\u003csup\u003e11\u003c/sup\u003e. Such studies could increase the probability of detecting various diseases and potentially improve disease prognosis\u003csup\u003e12,13\u003c/sup\u003e. Asia, the world's most populous continent, encompasses a wide range of economic states, from extremely developed countries to war-torn regions, providing a complete social span to study and inform the relevance of TC and national development.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eThe estimates of the incidence and mortality of TC (both male and female individuals aged 20–54 years) were obtained from the GBD 2021 study for the period from 1990–2021\u003csup\u003e7\u003c/sup\u003e (available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://vizhub.healthdata.org/gbd-results/\u003c/span\u003e\u003cspan address=\"https://vizhub.healthdata.org/gbd-results/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The GBD 2021 study analysed disease and injury burdens by estimating the incidence, prevalence, mortality, years lived with disability (YLDs), disability-adjusted life years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100,983 data sources for 195 countries for the period from 1990 to 2021. The data sources include a variety of platforms, including autopsy databases, vital registration systems, household surveys, censuses, disease-specific registries and health service contact databases. In the GBD study, data are collected from various databases, and multiple modelling steps are performed to produce epidemiological data\u003csup\u003e14,15\u003c/sup\u003e. We briefly discuss how the GBD study produces estimates of TC incidence and mortality. The GBD study methodology involves processing incidence and mortality data from cancer registries and then matching the processed data by cancer, age, sex, year, and location to generate crude MIRs. Second, crude MIRs are included as inputs in the three-step modelling approach using general spatiotemporal Gaussian process regression (ST-GPR), and SDIs are used as covariates in the linear mixed-effects model using a log-link function to obtain the final MIRs. In the third step, the incidence rates obtained from the cancer registries are multiplied by the MIRs derived in the second step to obtain mortality estimates; these mortality estimates are then used as inputs in the cause‒death pooled model (CodeM) to obtain the final mortality estimates\u003csup\u003e15,16\u003c/sup\u003e. The CodeM model is developed to derive cause-specific mortality estimates; this is an ensemble modelling approach in which the predictive validity of many models is tested before final mortality estimates are derived. In this modelling approach, only the covariates that are considered reasonably related to a particular cause of death are selected. Some of the covariates used by CodeM to model TC mortality are as follows: education level, lagged distribution of income, sociodemographic indices, and accessibility and quality of health care indices. The final mortality estimate is divided by the estimated MIRs derived in the second step to obtain the final morbidity estimate\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn this study, we obtained estimates of TC incidence and mortality for the period from 1990 to 2021 and for 2021, respectively. We used TC incidence and mortality rates for the 20–54-year age group to describe the burden of TC in the main working population. TC survival was expressed as the MIR, which has been shown to be representative of survival for different tumours\u003csup\u003e8,17\u003c/sup\u003e. Although the MIR is not fully representative of survival, it can provide a useful direction for understanding the relative survival of individuals with TC in each country. The MIR is calculated directly from the mortality-to-crude incidence ratio obtained from the GBD 2021 report. In this study, we examined TC in Asian countries, including the Democratic People's Republic of Korea (DPRK). In line with GBD study practice, we report morbidity and mortality estimates with 95% uncertainty intervals.\u003c/p\u003e\u003cp\u003eA country's level of development is measured by its HDI, which is a composite measure of three development indicators: health (life expectancy at birth), education (average years of schooling and expected years of schooling) and income (gross national income per capita). To calculate the HDI, each indicator is scored on a scale from 0 to 1, with 0 representing the lowest value and 1 representing the highest. The final HDI value for a country is calculated from the geometric mean of the health, education and income indices. The IHDI is based on a class of distributionally sensitive composite indices proposed by Foster, Lopez-Calva, and Szekely\u003csup\u003e18\u003c/sup\u003e, which are computed as geometric averages of inequality-adjusted dimensional indices. The IHDI ‘discounts’ the mean of each dimension according to the level of inequality, thus accounting for the inequality of the IHDI dimensions. The IHDI value is equal to the HDI value when there is no inequality between people but lower than the HDI value with increased inequality. In this sense, the IHDI measures the level of human development after inequality is considered. The HDI and IHDI data were obtained from the United Nations Development Programme (UNDP) database. For descriptive and analytical purposes, countries were classified into four categories on the basis of the United Nations Development Programme's classification: very-high-HDI (HDI \u0026gt; 0.800, 17 countries), high-HDI (0.700 \u0026lt; HDI \u0026lt; 0.799, 16 countries), medium-HDI (0.550 \u0026lt; HDI \u0026lt; 0.669, 10 countries) and low-HDI countries (HDI \u0026lt; 0.550, 3 countries). The HDI of the DPRK is not available, and its level of development was analysed by using other indicators.\u003c/p\u003e\u003cp\u003eThe SPI index measures the extent to which countries are meeting the social and environmental needs of their citizens. Fifty-four indicators in the areas of basic human needs, foundations of well-being, and opportunities for progress reflect a country’s relative performance. The index is published by the nonprofit organization Social Progress Imperative. Social and environmental factors include health (including health, housing and sanitation), equality, inclusion, sustainability, and personal freedom and security. The NMC index is part of the SPI index and includes the scores for child mortality, child stunting, the consumption of a diet low in fruits and vegetables, infectious diseases, maternal mortality and undernourishment. The SPI and NMC indices were obtained from the Social Progress Imperative website.\u003c/p\u003e\u003cp\u003eThe DOD and PHS reflect a country's basic health status and healthcare spending and provide a more intuitive picture of healthcare, which we used as a control and complement to the above statistical indicators. Data on the DOD and PHS indicators were obtained from the WHO and World Bank databases. The entire data analysis was conducted using Microsoft Excel and R Studio 4.2.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe total number of TC-related deaths increased from 10,477 [95% uncertainty interval (UI), 9,394\u0026ndash;12,252] in 1990 to 27,187 [95% UI, 23,128\u0026ndash;30,091] in 2021 across all age groups. Asia accounted for 62.8% of the TC cases worldwide in 2021. In the working-age population, from the mean number of deaths was 2,729 [3,243\u0026ndash;2,394], and the incidence of TC increased from 1.41 cases per 100,000 people [1.23\u0026ndash;1.63] in 1990 to 3.36 cases per 100,000 people [2.81\u0026ndash;3.90] in 2021. The mortality and incidence rates were significantly higher in the female population than in the male population, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eTable 1\u003c/p\u003e\u003cp\u003eThyroid cancer burden among 20\u0026ndash;54-year-olds in 2021 by country\u003c/p\u003e \u003cp\u003eHDI, Human Development Index; IHDI, Inequality-adjusted Human Development Index; SPI, Social Progress Imperative; NMC, Nutrition and Medical Care; DOD, Density of Doctors per 100,000 people; PHS, Personal Healthcare Spending; Incidence, Number of cases per 100,000 people; mortality, Deaths per 100,000 people; MIR, Mortality‒to-incidence ratio. Data Source: Global Burden of Disease 2021 study.\u003c/p\u003e \u003cp\u003eIncidence and Mortality of Thyroid Cancer in 2021\u003c/p\u003e \u003cp\u003eIn terms of incidence, very-high-HDI and high-HDI countries accounted for nine of the top ten countries. Saudi Arabia had the highest incidence rate of 9.867 cases per 100,000 people, which is 303% of the global average rate of 3.26 cases per 100,000 people, followed by Vietnam, with a rate of 8.243 cases per 100,000 people, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The analysis of the total and male and female incidence rates in relation to the level of development is presented in three ways: a scatterplot matrix, a correlation heatmap and a principal component analysis (PCA) plot.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMap of the incidence of thyroid cancer in Asia. 2021; Incidence, number of cases per 100,000 people; source: Global Burden of Disease 2021 study.\u003c/p\u003e \u003cp\u003eA scatterplot matrix is a graph that shows the relationships among multiple variables. It allows us to observe the linear or nonlinear relationships, correlations, trends, etc., between variables by creating a matrix where each matrix cell shows a scatter plot between two variables. Correlation coefficient values were added to the scatterplot matrix. If the correlation coefficient was close to 1 or -1, it indicated that the variables were highly correlated; if it was close to 0, it meant that there was almost no correlation, and values with statistical significance have an asterisk on the upper right corner of the coefficient. A heatmap indicates the correlation between different variables by colour, with the shade of the colour reflecting the strength of the correlation, indicating which variables have stronger or weaker linear relationships with each other. A PCA graph is a graphical representation that reduces multidimensional data to a few principal components. These graphs help us understand the relationships between complex variables, especially for discovering underlying structures or patterns in high-dimensional data. The main purpose of a PCA plot is to compress as much raw information (variation in variables) as possible into a handful of principal components (usually the first two). PCA biscale plots project sample points (individuals) and variables onto the plot at the same time, which makes it easy to visualize the distributions of individuals and the intervariable relationships. Each arrow represents the projection of an original variable into the principal component space. The longer an arrow is, the greater the contribution of the variable to the principal components (strong explanatory power); the shorter an arrow is, the weaker the explanatory power of the variable. An arrow angle close to 0 degrees indicates a positive correlation between two variables; an angle close to 90 degrees indicates no significant correlation between two variables; and an angle close to 180 degrees indicates a negative correlation between two variables.\u003c/p\u003e \u003cp\u003eAccording to the results of the graph, the total incidence rate of TC in the working-age population was positively correlated with four indicators, namely, the HDI (Corr\u0026thinsp;=\u0026thinsp;0.365\u003csup\u003e*\u003c/sup\u003e), IHDI (Corr\u0026thinsp;=\u0026thinsp;0.336\u003csup\u003e*\u003c/sup\u003e), SPI index (Corr\u0026thinsp;=\u0026thinsp;0.384\u003csup\u003e*\u003c/sup\u003e), and NMC index (Corr\u0026thinsp;=\u0026thinsp;0.332\u003csup\u003e*\u003c/sup\u003e), of which the incidence rate among males (Corr\u0026thinsp;=\u0026thinsp;0.594\u003csup\u003e***\u003c/sup\u003e, 0.541\u003csup\u003e***\u003c/sup\u003e, 0.544\u003csup\u003e***\u003c/sup\u003e and 0.616\u003csup\u003e***\u003c/sup\u003e), in particular, was more strongly correlated with these indicators of social development; however, there was no significant correlation between the incidence rate among females and the above indicators (Corr\u0026thinsp;=\u0026thinsp;0.303, 0.288, 0.312 and 0.228). The most significant indicator of incidence is the SPI index (Corr\u0026thinsp;=\u0026thinsp;0.384\u003csup\u003e*\u003c/sup\u003e), whereas the DOD (Corr\u0026thinsp;=\u0026thinsp;0.065), which reflects the prevalence of basic medicine, did not seem to be correlated with incidence. The contribution to the total incidence rate was greater for women, which is in line with the perception that TC is more common in women than in men, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCorrelation between thyroid cancer incidence and social development indicators, 2021: A: scatterplot matrix; B: correlation heatmap; C: principal component analysis plot; HDI, Human Development Index; IHDI, Inequality-adjusted Human Development Index; SPI, Social Progress Imperative; NMC, Nutrition and Medical Care; DOD, Density of Doctors per 100,000 people; PHS, Personal Healthcare Spending; Incidence, Number of cases per 100,000 people; source: Global Burden of Disease 2021 study.\u003c/p\u003e \u003cp\u003eIn terms of mortality, the HDI (Corr=-0.401\u003csup\u003e*\u003c/sup\u003e), IHDI (Corr=-0.387\u003csup\u003e*\u003c/sup\u003e), NMC index (Corr=-0.437\u003csup\u003e**\u003c/sup\u003e) and PHS (Corr=-0.446\u003csup\u003e**\u003c/sup\u003e) were negatively correlated with total mortality, with stronger correlations for the NMC index and PHS. However, in contrast to the morbidity results, the mortality results did not show a meaningful correlation with sociological indicators among males (Corr=-0.053, -0.052, -0.042 and \u0026minus;\u0026thinsp;0.306), whereas mortality was significantly negatively correlated with all indicators among females, especially the NMC index (Corr=-0.508\u003csup\u003e**\u003c/sup\u003e, -0.49\u003csup\u003e**\u003c/sup\u003e0, -0.573\u003csup\u003e***\u003c/sup\u003e and \u0026minus;\u0026thinsp;0.457\u003csup\u003e**\u003c/sup\u003e), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCorrelation between thyroid cancer mortality and social development indicators, 2021: A: scatterplot matrix; B: correlation heatmap; C: principal component analysis plot; HDI, Human Development Index; IHDI, Inequality-adjusted Human Development Index; SPI, Social Progress Imperative; NMC, Nutrition and Medical Care; DOD, Density of Doctors per 100,000 people; PHS, Personal Healthcare Spending; Mortality, Number of deaths per 100,000 people; source: Global Burden of Disease 2021 study.\u003c/p\u003e \u003cp\u003eChanges in the Mortality, Incidence and MIR of Thyroid Cancer\u003c/p\u003e \u003cp\u003eThe global MIR decreased from 0.135 in 1990 to 0.068 in 2021. As seen from the data, Asia's working-age population experienced a 21.1% increase in TC mortality and a 138% increase in TC incidence. The incidence of TC increased in all countries except two, Kazakhstan and Tajikistan, where it decreased by 7.1% and 11.7%, respectively. The incidence rate increased in 23 of the 47 countries\u0026mdash;4 of the 23 less-developed countries (low-/medium-HDI countries) and 18 of the 23 developed countries (high-/very-high-HDI countries)\u0026mdash;and the DPRK did not have an HDI available for reference. The mortality rate increased in 24 of the 47 countries\u0026mdash;9 of the 24 less-developed countries (low-/medium-HDI countries) and 15 of the 24 developed countries (high-/very-high-HDI countries). The MIR decreased in all countries, with the DPRK (-71.6%), Turkey (-66.2%), the Maldives (-63.0%), China (-62.4%), and Saudi Arabia (-60.9%) being the top five, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e Table 2 \u003c/p\u003e \u003cp\u003eThyroid cancer burden among individuals aged 20\u0026ndash;54 years from 1990 to 2021 by country\u003c/p\u003e \u003cp\u003eDevelopment, 1. very high (HDI\u0026thinsp;\u0026gt;\u0026thinsp;0.800, 17 countries), 2. high (0.700\u0026thinsp;\u0026lt;\u0026thinsp;HDI\u0026thinsp;\u0026lt;\u0026thinsp;0.799, 16 countries), 3. medium (0.550\u0026thinsp;\u0026lt;\u0026thinsp;HDI\u0026thinsp;\u0026lt;\u0026thinsp;0.669, 10 countries), and 4. low (HDI\u0026thinsp;\u0026lt;\u0026thinsp;0.550, 3 countries); HDI, Human Development Index; Incidence, Number of cases per 100,000 people; Mortality, Number of deaths per 100,000 people; MIR, Mortality‒incidence ratio. Data Source: Global Burden of Disease 2021 study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMap of changes in the thyroid cancer mortality, incidence and MIR in Asia. 1990\u0026ndash;2021; Incidence, Number of cases per 100,000 people; Mortality, Number of deaths per 100,000 people; source; MIR, mortality-to-incidence ratio: Global Burden of Disease 2021 study.\u003c/p\u003e \u003cp\u003eChanges in the HDI were used in the correlation analysis as a reference marker for changes in the level of social development, as other indicators are not readily available. A scatterplot matrix, a correlation heatmap and a PCA plot were used to represent the correlation. In terms of mortality and incidence, changes in the HDI and MIR were significantly negatively correlated (Corr=-0.329\u003csup\u003e*\u003c/sup\u003e), but changes in these indicators were not significantly related to the level of social development (very high (HDI\u0026thinsp;\u0026gt;\u0026thinsp;0.800), high (0.700\u0026thinsp;\u0026lt;\u0026thinsp;HDI\u0026thinsp;\u0026lt;\u0026thinsp;0.799), medium (0.550\u0026thinsp;\u0026lt;\u0026thinsp;HDI\u0026thinsp;\u0026lt;\u0026thinsp;0.669), and low (HDI\u0026thinsp;\u0026lt;\u0026thinsp;0.550)). Changes in the MIR were mainly due to the contribution of reductions in morbidity (Corr=-0.379\u003csup\u003e*\u003c/sup\u003e), particularly in men (Corr=-0.431\u003csup\u003e**\u003c/sup\u003e), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCorrelation between changes in the HDI and the mortality, incidence and MIR of thyroid cancer in individuals aged 20\u0026ndash;54 years: A: scatterplot matrix; B: correlation heatmap; C: principal component analysis plot; HDI, Human Development Index; Incidence, Number of cases per 100,000 people; Mortality, Number of deaths per 100,000 people; source; MIR, mortality-to-incidence ratio; source: Global Burden of Disease 2021 study.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined the burden of TC and its temporal patterns in 47 Asian countries between 1990 and 2021. Using GBD 2021 data, we found that the global burden of TC has increased significantly over the past three decades and that there are wide inequalities between geographic regions due to different levels of development. Developed countries (those with high/very high HDIs) have relatively high incidence rates, whereas developed and less developed countries account for equal proportions of the top 10 countries in terms of mortality. The high prevalence of TC in working-age populations in developed countries can be attributed to the level of screening\u003csup\u003e11\u0026ndash;13\u003c/sup\u003e, and the similarity in TC mortality between developed and developing countries can be attributed to several factors. One of the main reasons is the advancement in diagnostic technology, particularly in more affluent nations. In developed countries, the increased detection of small, indolent TCs, which are not typically life-threatening, has led to higher incidence rates without a corresponding increase in mortality. This is known as \"overdiagnosis\" and does not necessarily reflect a higher risk of death from TC. Another reason is that the actual mortality rates of TC remain low and stable across both developed and developing nations. This trend is partially because individuals with most TCs, especially well-differentiated types, have excellent survival rates regardless of geographical or socioeconomic differences\u003csup\u003e19\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOverall, the incidence of TC in the working-age population and the level of national development have increased in most Asian countries, whereas approximately half of the countries have experienced a decrease in mortality. The MIR has decreased across Asia, which could reflect a general improvement in the prognosis of TC, especially 5-year survival. However, there are differences in the MIR between developed and less developed countries, with the 10 countries with the lowest MIRs all being developed countries, whereas 8 of the 10 countries with the highest MIRs are less developed countries. Studies suggest that improved healthcare infrastructure in developed countries, including better postsurgical management and the use of radioactive iodine therapy, has contributed to reducing mortality rates and better prognoses\u003csup\u003e19,20\u003c/sup\u003e. This seems to indicate that less developed countries need to further improve their medical services.\u003c/p\u003e \u003cp\u003eIn our study, we found that the incidence of TC, especially in the male population, was strongly correlated with the level of social development, whereas there was no such trend in the female population. This may be attributed to hormonal differences, particularly the effect of oestrogen, which may promote tumour growth in women and is not influenced by the social environment\u003csup\u003e21\u003c/sup\u003e. Studies have shown that oestrogen-related genes are associated with immune regulation, tumour immune evasion, defence systems, signal transduction, the tumour microenvironment and immune regulation in individuals with TC. High-risk patients in the immunotherapy dataset had considerably shorter survival times than low-risk patients did\u003csup\u003e22\u003c/sup\u003e. On the other hand, there is evidence that men's participation in regular health checks is increasing, particularly among men of working age. Historically, men have been less likely than women to seek preventive health care, often seeking care when they have symptoms, which often represents advanced disease progression; however, this trend is changing because of greater awareness of the benefits of early detection and preventive health care. A study that included a predominantly under-45 population in Guangdong Province, China, revealed that although the detection rate of thyroid nodules was higher in women than in men (13.51 percent vs. 7.71 percent), the number of working-age men who presented for medical check-ups reached 121,883, which was significantly greater than the number of working-age women (70,680) who presented for check-ups. This seems to indicate that the willingness to attend medical check-ups is already great among younger men\u003csup\u003e23\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur study also revealed a negative correlation between TC mortality and various indices related to social development, with the contribution coming mainly from the reduction in mortality among women with TC. A previous study concluded that overdiagnosis, as a general phenomenon, could improve the survival of patients with TC (the risk of mortality decreased by half for men and by 2/3 for women)\u003csup\u003e24\u003c/sup\u003e, but this benefit was not evident in patients with more malignant subtypes, which occur more often in males\u003csup\u003e25\u003c/sup\u003e. In terms of both incidence and mortality, the NMC index showed a statistically significant correlation compared with the other indicators, and this index can be considered to have a greater impact on TC given that it is an SPI-affiliated indicator reflecting mainly hygiene-, health- and nutrition-related indicators, probably since TC involves a tumour of the endocrine system.\u003c/p\u003e \u003cp\u003eThe MIR generally decreased across Asia but did not show a clear correlation with the HDI; however, our findings suggest a clear decrease in the MIR with increasing development, which may be due to the scientific and technological developments described earlier, including better management processes and advancements in therapy\u003csup\u003e19,20\u003c/sup\u003e. When conducting the study, we found that changes in the MIR and HDI were correlated, but statistical significance was lost when the HDI was stratified using a four-point scale, which may indicate the limitations of the HDI as a sociological indicator and the direct application of its stratification method to the medical field. The reason may be that the index is the result of a combination of multiple indicators and that some countries have a high level of development in the field of health care but do not show a similar lead in other fields under this statistical method, resulting in inflated ratings. In our study of the factors associated with changes in TC incidence and mortality, we used the HDI as the independent variable, partly because several other indicators are not readily available due to time limitations and partly because previous studies have reported an association between the burden of cancer and the HDI, which confirms the reliability of such comparisons\u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe DOD is associated with a high incidence of TC but is not clearly correlated with mortality. Previous studies have revealed a potential correlation between physician density and mortality in patients with highly malignant cancer such as bladder and prostate cancer but without clear statistical significance\u003csup\u003e26\u003c/sup\u003e; we believe that this indicator primarily reflects primary care equity because a greater density of physicians facilitates screening of patients with early-stage cancers\u003csup\u003e27\u003c/sup\u003e. However, for malignant subtypes of TC, which are much more lethal, the prognosis should largely depend on the level of treatment and care at advanced medical centres.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eFirst, estimates of the burden of TC were derived from the GBD 2021 study, and the quality of the estimates is highly dependent on the availability of cancer registry data. Because cancer registry coverage lacks completeness in many low-income countries, spatial and temporal data from neighbouring regions were used to assess the global burden of TC. The lack of cancer registry data leads to large UIs that may be too large to provide meaningful data on policy implications for these countries. Second, in less developed countries, the estimates used and reported here may be biased downwards because of underreporting or misclassification of cancer deaths. Third, it is well known that cancers detected early (clinical stage 1) are less severe and less life-threatening than those detected late (clinical stage 3 or 4), but there are no estimates of cases diagnosed at different clinical stages. Fourth, the lack of effective grassroots management and health organizations in some Middle Eastern and Southeast Asian countries due to prolonged wars may have led to the inclusion of data from only some of the larger cities, thus introducing bias; furthermore, many countries lack effective grassroots management and health organizations due to weak governments, which may lead to deaths caused by war-related trauma, plague, or starvation and to a lower number of cancer deaths than the actual number of deaths. Last, some countries are missing key data, such as the DPRK, which is unable to provide valid data on indicators such as the HDI, and others, such as Bhutan, which lack data on the HDI for 1990 for rate-of-change purposes. This can lead to bias in the results.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe increasing burden of TC within the working-age population across Asia has resulted in an overall increase in the incidence of TC, especially in developed countries, although the overall prognosis has gradually improved. This may be attributed to further human development leading to early detection of malignant tumours, increased awareness and better treatment modalities in developed countries. On the basis of past trends, the incidence of TC is expected to increase further in the future due to irregular patterns of work and rest and lifestyles, unhealthy diets, the disruption of hormone secretion, and exposure to ionizing radiation in the working-age population. However, the lack of early detection, late onset and lack of active surveillance systems in less developed countries are expected to strain health-care systems with limited resources. In underdeveloped countries, TC has an overall high mortality rate, which can be attributed to the relative disadvantage of cancer patients due to late diagnosis, misdiagnosis, lack of access to good surgeons or chemotherapeutic agents, high cost of treatment and lack of health insurance coverage. These factors contribute to the relatively high burden borne by cancer patients in these countries. Since TC shows relatively pronounced sex differences, increased awareness of the need for ultrasound screening in working-aged men is necessary. Regardless of sex, a pathway from regular check-ups to prevention and individualized treatment will improve the prognosis of the disease. Owing to the large intercountry developmental differences in Asian countries, improving the capacity of and education by healthcare systems in underdeveloped countries, increasing the purchase of most products, and decreasing the hidden costs of taxes and logistics, which further increase the burden on patients, are urgently needed, and less developed countries should invest more in international cooperation and local research and development, including the management of primary healthcare systems and the development of high-level healthcare centres.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eConsent for publication \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed in this study are publicly accessible through the following sources: \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.Global Burden of Disease (GBD) 2021 data: [https://vizhub.healthdata.org/gbd-results/](https://vizhub.healthdata.org/gbd-results/) \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.Human Development Index (HDI) data: United Nations Development Programme (UNDP) \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3.Social Progress Imperative (SPI) and Nutrition and Medical Care (NMC) indices: [Social Progress Imperative](https://www.socialprogress.org/) \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e4.Density of Doctors (DOD) and Personal Healthcare Spending (PHS): World Bank and World Health Organization (WHO) databases. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests, financial or non-financial, related to this work. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWenyi Qin: Conceptualization, formal analysis, data curation, visualization, writing \u0026ndash; original draft. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWenyi Qin: Conceptualization, Formal analysis, Writing - Original Draft.\u003c/p\u003e\n\u003cp\u003eJiong Lin: Investigation, Data curation.\u003c/p\u003e\n\u003cp\u003eHaiqing Luo: Supervision, Writing - Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003eLili Yu: Supervision, Validation, Writing - Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003eAcknowledgements \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe thank Jianhan Yin ([email protected]) for sharing methodological insights on the GBD database. We also acknowledge the Global Burden of Disease Collaborators for their efforts in compiling and maintaining the GBD dataset. \u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003ePowers AE, Marcadis AR, Lee M, Morris LGT, Marti JL. Changes in Trends in Thyroid Cancer Incidence in the United States, 1992 to 2016. Jama 2019;322(24):2440-2441. (In eng). DOI: 10.1001/jama.2019.18528.\u003c/li\u003e\n \u003cli\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68(6):394-424. (In eng). DOI: 10.3322/caac.21492.\u003c/li\u003e\n \u003cli\u003ePellegriti G, Frasca F, Regalbuto C, Squatrito S, Vigneri R. Worldwide increasing incidence of thyroid cancer: update on epidemiology and risk factors. J Cancer Epidemiol 2013;2013:965212. (In eng). DOI: 10.1155/2013/965212.\u003c/li\u003e\n \u003cli\u003eHirsch D, Yackobovitch-Gavan M, Lazar L. Infertility and Pregnancy Rates in Female Thyroid Cancer Survivors: A Retrospective Cohort Study Using Health Care Administrative Data from Israel. Thyroid 2023;33(4):456-463. (In eng). DOI: 10.1089/thy.2022.0501.\u003c/li\u003e\n \u003cli\u003eBleyer A, Barr R, Hayes-Lattin B, Thomas D, Ellis C, Anderson B. The distinctive biology of cancer in adolescents and young adults. Nat Rev Cancer 2008;8(4):288-98. (In eng). DOI: 10.1038/nrc2349.\u003c/li\u003e\n \u003cli\u003eMiranda-Filho A, Lortet-Tieulent J, Bray F, et al. Thyroid cancer incidence trends by histology in 25 countries: a population-based study. Lancet Diabetes Endocrinol 2021;9(4):225-234. (In eng). 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Neuroendocrine Tumours: Diagnosis and Management. Cham: Springer International Publishing; 2024:445-483.\u003c/li\u003e\n \u003cli\u003eColli J, Sartor O, Thomas R, Lee BR. Does urological cancer mortality increase with low population density of physicians? J Urol 2011;186(6):2342-6. (In eng). DOI: 10.1016/j.juro.2011.07.069.\u003c/li\u003e\n \u003cli\u003eFleming NH, Grade MM, Bendavid E. Impact of primary care provider density on detection and diagnosis of cutaneous melanoma. PLoS One 2018;13(7):e0200097. (In eng). DOI: 10.1371/journal.pone.0200097.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Thyroid cancer, Incidence, Mortality, Mortality-to-incidence ratio, Human development index","lastPublishedDoi":"10.21203/rs.3.rs-5911089/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5911089/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThe aim was to examine the temporal patterns of the thyroid cancer (TC) burden and its association with the national development level.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe estimates of the incidence and mortality of TC for 47 countries were obtained from the Global Burden of Disease 2021 study for the period from 1990 to 2021. The human development level of each country was measured using the human development index (HDI), Social Progress Imperative (SPI) index, Nutrition and Medical Care (NMC) index, Density of Doctors per 100,000 people (DOD) and Personal Healthcare Spending (PHS) as summary indicators of health, education, and income reflecting the national development level. The associations between the burden of TC and these indices were measured via a scatterplot matrix, correlation heatmap and principal component analysis (PCA) plot. The mortality-to-incidence ratio (MIR) was employed as a proxy for the survival rate of patients with TC.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe total number of TC-related deaths increased from 10,477 [95% uncertainty interval (UI), 9,394\u0026ndash;12,252] in 1990 to 27,187 [95% UI, 23,128\u0026ndash;30,091] in 2021 across all age groups. Asia accounted for 62.8% of the TC cases worldwide in 2021. In the working-age population, this mean number of deaths was 2,729 [3,243\u0026ndash;2,394], and the incidence of TC increased from 1.41 cases per 100,000 people [1.23\u0026ndash;1.63] in 1990 to 3.36 cases per 100,000 people [2.81\u0026ndash;3.90] in 2021. In terms of TC incidence, very high- and high-HDI countries accounted for nine of the top ten countries. The total incidence rate of TC in the working-age population was positively correlated with four indicators, namely, the HDI (Corr\u0026thinsp;=\u0026thinsp;0.365\u003csup\u003e*\u003c/sup\u003e), IHDI (Corr\u0026thinsp;=\u0026thinsp;0.336\u003csup\u003e*\u003c/sup\u003e), SPI index (Corr\u0026thinsp;=\u0026thinsp;0.384\u003csup\u003e*\u003c/sup\u003e), and NMC index (Corr\u0026thinsp;=\u0026thinsp;0.332\u003csup\u003e*\u003c/sup\u003e), of which the incidence rate among males (Corr\u0026thinsp;=\u0026thinsp;0.594\u003csup\u003e***\u003c/sup\u003e, 0.541\u003csup\u003e***\u003c/sup\u003e, 0.544\u003csup\u003e***\u003c/sup\u003e and 0.616\u003csup\u003e***\u003c/sup\u003e), in particular, was strongly correlated with the indicators of social development. In terms of mortality, the HDI (Corr=-0.401*), IHDI (Corr=-0.387*), NMC index (Corr=-0.437**) and PHS (Corr=-0.446**) were negatively correlated with the total mortality rate. The global MIR decreased from 0.135 in 1990 to 0.068 in 2021. As seen from the data, Asia's working-age population presented a 21.1% increase in TC mortality and a 138% increase in TC incidence.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe increasing burden of TC within the working-age population across Asia has resulted in an overall increase in the incidence of TC, especially in developed countries, although the overall prognosis has gradually improved. Fewer developed countries should invest more in international cooperation and local research and development, including the management of primary healthcare systems and the development of high-level healthcare centres.\u003c/p\u003e","manuscriptTitle":"The burden of thyroid cancer is associated with the level of national development in Asia: Evidence from 1990–2021 for 47 countries","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-04 08:53:12","doi":"10.21203/rs.3.rs-5911089/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8876a03f-1ee0-4e99-b99a-dccaedce52fb","owner":[],"postedDate":"February 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-10T01:08:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-04 08:53:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5911089","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5911089","identity":"rs-5911089","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}