Burden of Mesothelioma in China, 1990–2023: Trends, Decomposition, and Projections Until 2045

Background: Mesothelioma is a rare but highly aggressive malignancy strongly associated with asbestos exposure. Owing to its long latency and poor prognosis, its burden requires systematic evaluation. Methods: Data on prevalence, incidence, deaths, disability-adjusted life years (DALYs), and age-standardized rates were extracted from the Global Burden of Disease Study 2023. The estimated annual percentage change, Joinpoint regression, Das Gupta decomposition, and Nordpred forecasting were used to assess temporal trends, identify turning points, quantify demographic and epidemiological contributions, and project future burden through 2045. Results: From 1990 to 2023, the absolute burden of mesothelioma in China increased substantially. Prevalent cases rose by 189%, incident cases by 150%, DALYs by 98%, and deaths by 142%. Males consistently showed a higher burden than females, and the burden was concentrated mainly among middle-aged and older adults. The age-standardized prevalence rate and age-standardized incidence rate increased, whereas the age-standardized DALY rate and age-standardized mortality rate remained stable or declined slightly. Decomposition analysis indicated that population growth and aging were the principal drivers of increased DALYs and deaths, while epidemiological change contributed negatively. Projections suggested that deaths may continue to increase through 2045, despite declining age-standardized fatal burden. Conclusions: This is the first update of the burden of mesothelioma in China over the past thirty-four years. The absolute burden of mesothelioma in China, as estimated by the GBD study, increased markedly, largely driven by demographic changes. Strengthening asbestos exposure surveillance, diagnostic standardization, and cancer registration systems would enable burden estimates to be derived from directly observed and certified data rather than relying primarily on model-based assumptions, while potentially identifying previously unrecognized sources of asbestos exposure.