Abstract
Background This study aimed to describe the latest epidemiology of female breast cancer globally, analyze the change pattern of the incidence rates and the disease’s association with age, period, and birth cohort, and subsequently present a forecast of breast cancer incidence.Methods Data for analysis were obtained from Global Burden of Disease (GBD) Study 2019 and World Population Prospects 2019 revision by the United Nations (UN). We described the age-standardized incidence rates (ASIRs) from 1990 to 2019 and then calculated the relative risks of period and cohort using an age-period-cohort model, and predicted the trends of ASIRs to 2035.Results In 2019, the global incidence of breast cancer in women increased to 1,977,212 (95% uncertainty interval = 1 807 615 to 2 145 215), with an ASIR of 45.86 (41.91 to 49.76) per 100 000 persons. Among the six selected countries facing burdensome ASIRs, only the USA showed a downward trend from 1990 to 2019, whereas the others showed an increasing or stable trend. The overall net drift was similar in Japan (1.78%), India (1.66%), and Russia (1.27%), reflecting increasing morbidity from 1990 to 2019. The increase in morbidity was particularly striking in China (2.60%) and not significant in Germany (0.42%). The ASIRs were predicted to continue to increase globally, from 45.26 in 2010 to 47.36 in 2035. In most countries and regions, the age specific incidence rate is the highest in those aged over 70 years and will increase in all age groups until 2035. In high-income regions, the age specific incidence rates are expected to decline in women aged over 50 years. Conclusions The global burden of female breast cancer is becoming more serious, especially in developing countries. Raising awareness of the risk factors and prevention strategies for female breast cancer is necessary to reduce future burden.
Epidemiological and sociodemographic transitions of female breast cancer incidence, death, case fatality and DALYs in 21 world regions and globally, from 1990-2017: An Age-Period-Cohort Analysis
