Global, regional, and national thyroid cancer age-period-cohort modeling and Bayesian predictive modeling studies: A systematic analysis of the global burden of disease study 2019

Objective: To analyze the changing trend of the global burden of thyroid cancer (TC) and its associated risk factors using data from the Global Burden of Disease study 2019 (GBD 2019). Methods: This study utilized the GBD 2019 database to analyze the burden trend of TC in various regions and countries from 1990 to 2019, while also examining the age-period-cohort (APC) effect. Additionally, the study used Bayesian age-period-cohort (BAPC) and predictive models to forecast TC incidence up until 2030. Results: According to data from 2019, there were 233,846.64 (95 % UI 211,636.89–252,806.55) cases of TC worldwide. The burden of TC varies among regions and countries, with higher incidence rates observed in moderate and above SDI regions. Age and gender also play a role, with incidence rates peaking in the >95 age group for men and the 70–74 age group for women. Additionally, women have a higher incidence than men. The APC model revealed that the impact of age was most significant among individuals aged 95 years and older, while it was lowest among those aged 0–14 years. Additionally, the period effect showed a relatively low risk of morbidity with a Period RR 0 during 2005–2019. Furthermore, the cohort effect demonstrated that the relative risk of developing the disease was lower before 1950 and higher after 1950. Predicted values show an increasing trend in thyroid incidence over the next 30 years. Conclusions: The findings of this study highlight the continued significance of thyroid cancer as a global public health issue. It is crucial to develop targeted interventions that address the specific risk factors associated with thyroid cancer. Furthermore, health policies should be customized and adapted to the unique needs of different regions and populations.