Abstract
OBJECTIVE: To quantify the global macroeconomic burden of breast cancer in 2021, reveal disparities in economic losses across regions, age groups, and gender groups, and provide a basis for optimizing the allocation of prevention and control resources. METHODS: Based on breast cancer disability-adjusted life years (DALY) data from the Global Burden of Disease (GBD 2021) database, combined with World Bank economic indicators, the value of lost welfare (VLW) model was employed to assess economic losses. The model standardized losses across countries using the statistical value of life (VSL), with a core parameter income elasticity of 1.0. Regional disparities were analyzed through stratification by Socio-demographic Index (SDI), and statistical uncertainty was calculated using a Bayesian model with 95% uncertainty intervals. RESULTS: In 2021, the global VLW due to breast cancer reached 2,538.849 billion US dollars, accounting for 1.65% of global GDP. Regional analysis revealed significant inequality: High-income North America bore the highest economic loss (557.9 billion US dollars), followed by Western Europe (551.4 billion US dollars), while Central Europe, Eastern Europe, and Central Asia, despite lower absolute losses, had an economic burden as a proportion of GDP as high as 3.01%, far exceeding the global average. In terms of population distribution, the female group dominated absolutely (accounting for 24% of female cancer deaths), and economic losses for patients aged 50 and above accounted for over 70%, highlighting the characteristic burden of disease aging. The forecast indicates that the total VLW caused by breast cancer worldwide in 2050 will reach US$21,008.2 billion, with the top regions incurring the highest economic losses being South Asia, East Asia, High-income North America, and Southeast Asia. CONCLUSION: Breast cancer causes significant macroeconomic losses and exhibits marked regional inequality, with high-income countries bearing the highest absolute burden, while low- and middle-income regions face more severe relative economic impacts. It is imperative to implement targeted prevention and control strategies based on SDI stratification to promote optimal allocation of global health resources.