Colorectal Cancer in China, 1990 to 2023: Trends, Modifiable Risks, and Prevention Priorities Based on Global Burden of Disease 2023 Estimates.

[BACKGROUND] We analyzed China's colorectal cancer (CRC) burden from 1990 to 2023, focusing on incidence, mortality, disability-adjusted life years (DALYs), prevalence, and risk-attributable burden, to assess temporal trends and evaluate future prevention needs.

[METHODS] Using Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 estimates, we summarized all-age numbers and age-standardized rates (ASR) by sex. Joinpoint log-linear models calculated the average annual percent change (AAPC), and risk-attributable deaths and DALYs were profiled for 2023. And we conducted a brief sensitivity comparison of trends for 2010-2019 and 2019-2023 for both sexes combined. All results are model-based estimates and are reported with uncertainty intervals (UIs).

[RESULTS] In 2023, China was estimated to have 611,364 incident CRC cases (95% UI 493,490-771,955), 258,088 deaths (225,359-305,788), 3,375,669 prevalent cases (2,710,191-4,159,613), and 6,279,382 DALYs (5,563,225-7,428,441). Over 1990-2023, ASIR and ASPR increased, while ASMR and ASDR declined. Males consistently had higher rates than females, and burden rose steeply with age. AAPCs showed an increase in incidence across the 15-49, 50-74, and ≥ 75 years age groups, particularly in those aged 75 years and older. Mortality and DALY rates declined at younger ages and were stable at ≥ 75. In 2023, the risk-attributable CRC burden was concentrated in dietary risks and metabolic and behavioural risks, including high fasting plasma glucose, smoking, alcohol use, and low physical activity. The brief pre- and post-2019 comparison suggested broadly similar directions with wide uncertainty.

[CONCLUSIONS] GBD 2023 estimates indicate that CRC remains a growing challenge in China, with rising ASIR and ASPR despite declining ASMR and ASDR. Prevention and screening planning should prioritise modifiable risks and strengthen service resilience, while interpreting model-based estimates in light of their uncertainty.