Epidemiological and sociodemographic transitions of female breast cancer incidence, death, case fatality and DALYs in 21 world regions and globally, from 1990 to 2017: An Age-Period-Cohort Analysis

Abstract

Introduction: Breast cancer (BC) is the most widely studied disease due to its higher prevalence, heterogeneity and mortality.

Objectives: This study aimed to compare female BC trends among 21 world regions and globally over 28 year of data and to assess the association between sociodemographic transitions and female BC risks.

Methods: We used Global burden of disease study data and measure the female BC burden according to 21 world regions and sociodemographic indices (SDI). Age-period-cohort (APC) analysis was used to estimate time and cohort trend of BC in different SDI regions.

Results: By world regions, age-standardised rate of female BC incidence were high in high-income-North America (ASR, 92.9; (95 %UI, 89.2, 96.6)), Western Europe (84.7; (73.4, 97.2)) and Australia (86; (81.7, 90.2)) in 2017. Whereas this rate was significantly increased by 89.5% between 1990 and 2017 in East Asia. We observed negative association between SDI and death, and DALYs in 25th and below percentiles of death and DALYs for the worldwide regions. Further, there was observed a strong negative correlation between SDI and case fatality percent (r₂₀₁₇ = -0.93; r₁₉₉₀ = -0.92) in both 2017 and 1990 worldwide and highest case fatality percentage was observed in Central Sub-Saharan Africa. Overall, the risk of case-fatality rate tends to decrease most noticeably in high middle SDI countries, and the reduction of the risk of case-fatality rate in the recent cohort was the lowest in the low SDI countries.

Conclusions: Remarkable variations exist among various regions in BC burden. There is a need to reduce the health burden from BC in less developed and under developing countries, because under-developed countries are facing higher degree of health-related burden. Public health managers should execute more classified and cost-effective screening and treatment interferences to lessen the deaths caused by BC, predominantly among middle and low SDI countries having inadequate healthcare supplies.

Keywords: APC, age-period-cohort; ASDR, age-standardized death rates; ASIR, age-standardized incidence rates; Age-period-cohort; BC, breast cancer; Breast cancer; CFP, case-fatality-percent; CFR, case-fatality rates; Case fatality; DALYs, disability adjusted life years; DR, death rates; GBD, global burden of diseases; IR, incidence rates; Incidence; SDI, sociodemographic index; World regions; YLDs, years lived with disability; YLLs, years of life lost.

Graphical abstract

Fig. 1

Female breast cancer incidence, death and DALYs (rate per 100 k) in 1990 and 2017 stratified by age group, 15–49years, 50–69years, and 70+years (A) Incidence in 1990 and 2017, (B) death in 1990 and 2017 (C) DALYs in 1990 and 2017.

Fig. 2

Relationship between the age-standardized rates (ASRs, per 100 k) of female breast cancer and SDI over time (1990–2017) by globally and by 21 GBD regions. Each colored line represents a time trend of the relationship for the specified world regions. Each point represents a specific year for that region. The black line with 95% confidence band represents the average expected relationship between SDI and ASRs for breast cancer based on values from all countries from 1990 to 2017. The dashed lines represents the relationship between SDI and ASRs on conditional distributions across quantiles of breast cancer; SDI, social-demographic index; SDI ranges from 0 (less developed) to 1 (most developed).

Fig. 3

Time specific correlation between socio-demographic index (SDI) and female breast cancer case-fatality percent (CFP) in 1990 and 2017 worldwide. Case-fatality percent was calculated by dividing age-standardised death rate by age-standardised incidence rate and multiplied by 100, r represent the correlation coefficient between SDI and CFP among world regions, LSE, Least Square Error fit; LAE, Least Absolute Error fit; SDI(%) ranges from 0 (less developed) to 100 (most developed).

Fig. 4

Age period cohort related female breast cancer trends in (A) incidence rate (B) death rate and (C) DALYs from 1990 to 2017 with ages 20 to 80. Rate ratio was estimated using ML of APC-model Poisson with log(Y) based on natural-spline function, for each SDI region separately. DALYs, disability adjusted life years; ML, maximum likelihood; APC, age-period-cohort; Reference cohort for age-effects was chosen as the median date of birth among cases; Median date of diagnosis among cases was selected as reference period.

Fig. 5

Age period cohort trends in case-fatality rate of female breast cancer from 1990 to 2017 with ages 20 to 80. Rate ratio was estimated using ML of APC-model Poisson with log(Y) based on natural-spline function, for each SDI region separately. ML, maximum likelihood; APC, age-period-cohort; Reference cohort for age-effects was chosen as the median date of birth among cases; Median date of diagnosis among cases was selected as reference period.