Trend analysis and age-period-cohort effects on morbidity and mortality of liver cancer from 2010 to 2020 in Guangzhou, China

Abstract

Introduction: Liver cancer is one of the most common malignant gastrointestinal tumors worldwide. This study intends to provide insight into the epidemiological characteristics and development trends of liver cancer incidence and mortality from 2010 to 2020 in Guangzhou, China.

Methods: Data were collected from the Cancer Registry and Reporting Office of Guangzhou Center for Disease Control and Prevention. Cross-sectional study, Joinpoint regression (JPR) model, and Age-Period-Cohort (APC) model were conducted to analyze the age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) trend of liver cancer among the entire study period.

Results: The age-standardized incidence and mortality of liver cancer in Guangzhou showed an overall decreasing trend. The disparity in risk of morbidity and mortality between the two sexes for liver cancer is increasing. The cohort effect was the most significant among those born in 1965~1969, and the risk of liver cancer incidence and mortality in the total population increased and then decreased with the birth cohort. Compared with the birth cohort born in 1950~1954 (the reference cohort), the risk of liver cancer incidence and mortality in the males born in 1995~1999 decreased by 32% and 41%, respectively, while the risk in the females decreased by 31% and 32%, respectively.

Conclusions: The early detection, prevention, clinical diagnosis, and treatment of liver cancer in Guangzhou have made remarkable achievements in recent years. However, the risk of liver cancer in the elderly and the middle-aged males is still at a high level. Therefore, the publicity of knowledge related to the prevention and treatment of liver cancer among the relevant population groups should be actively carried out to enhance the rate of early diagnosis and treatment of liver cancer and to advocate a healthier lifestyle.

Keywords: age-period-cohort model; cross-sectional study; joinpoint; liver cancer; trend analysis.

Figure 1

Trends of cases and age-standardized rates of liver cancer in Guangzhou, 2010~2020. (A–C) Number of cases and standardized incidence rates for the whole population, males and females; (D–F) Number of deaths and standardized mortality rates for the whole population, males and females; (G) Male-to-female ratios of liver cancer incidence and mortality; (H) The occupational composition of male liver cancer patients; (I) The occupational composition of female liver cancer patients.

Figure 2

Morbidity, mortality, and age composition of liver cancer in various districts of Guangzhou. (A) Morbidity and (B) mortality in different districts of Guangzhou, 2010~2020; (C) Morbidity density and (D) mortality density in different age groups among males and females, 2010~2020.

Figure 3

The age composition of (A–C) morbidity and (D–F) mortality of the whole population, males and females in Guangzhou, 2010~2020.

Figure 4

Results of the JPR model for ASIR and ASMR for the whole population, males and females, Guangzhou, 2010~2020. (A, D) Trends in ASIR and ASMR among different populations; (B, E) Age-related trends in liver cancer incidence and mortality among different populations; (C, F) Trends in ASIR and ASMR among different age groups.

Figure 5

Age-Period-Cohort modeling results of liver cancer incidence and mortality in Guangzhou, 2010~2020. (A) APC analysis for incidence of the total population by ZLT-P and ZLT-C method; (B) APC analysis for incidence of males and females by ZLT-P and ZLT-C method; (C) APC analysis for mortality of the total population by ZLT-P and ZLT-C method; (D) APC analysis for mortality of males and females by ZLT-P and ZLT-C method.