Disease burden of liver cancer attributable to specific etiologies in China from 1990 to 2019: An age-period-cohort analysis

1990年至2019年中国特定病因导致的肝癌疾病负担:一项基于年龄-时期-队列的分析

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Abstract

Temporal trends of total liver cancer have been well reported in China, especially the trends caused by hepatitis B (HBV); however, the trends of liver cancer attributable to specific etiologies have rarely been reported in China. Thus, this study aims to describe the temporal trends in the incidence, mortality and DALYs of total and etiology-specific liver cancer in China from 1990 to 2019. We extracted the incidence, mortality and disability-adjusted life years (DALYs) of total and etiology-specific liver cancer in China from 1990 to 2019 from global disease burden (GBD) 2019. We plotted the trends in the age-standardized rates for incidence, mortality, and DALYs using locally weighted regression (LOESS)-smoothed data from 1990 to 2019. The age-standardized rate for the incidence of liver cancer was analyzed with an age-period-cohort method. The age-standardized rates for incidence, death, and DALYs decreased by -58.8%, -63.8%, and -65.6%, respectively, between 1990 and 2019. The age-standardized rates of incidence, mortality, and DALYs of total liver cancer showed similar temporal patterns, presenting an overall decline, with the average annual percentage change (AAPC) ranging from -3.3% to -3.8%. People in the period before 2007 had a higher risk, and people after 2007 had a lower risk. The cohort risk ratios (RRs) showed decreasing patterns, with the most rapid decline observed in the 1910 to 1960 cohorts. Our study generally revealed favorable decreasing trends for total and etiology-specific liver cancer in China from 1990 to 2019. Despite the overall decline in liver cancer due to heavy alcohol use and obesity from 1990 to 2019, there have been apparent upward trends since 2006. Planned population-wide interventions targeting heavy alcohol use and obesity may mitigate the increasing trends in liver cancer attributable to alcohol use and NASH.

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