More recent insights into the breast cancer burden across BRICS-Plus: Health consequences in key nations with emerging economies using the global burden of disease study 2019

Abstract

Background: Brazil, Russia, India, China, South Africa, and 30 other Asian nations make up the BRICS-Plus, a group of developing countries that account for about half of the world's population and contribute significantly to the global illness burden. This study aimed to analyzed the epidemiological burden of female breast cancer (BC) across the BRICS-Plus from 1990 to 2019 and studied the associations with age, period, birth cohort and countries' sociodemographic index (SDI).

Methods: The BC mortality and incidence estimates came from the 2019 Global Burden of Disease Study. We estimated cohort and period effects in BC outcomes between 1990 and 2019 using age-period-cohort (APC) modeling. The maximum likelihood (ML) of the APC-model Poisson with log (Y) based on the natural-spline function was used to estimate the rate ratio (RR). We used annualized rate of change (AROC) to quantify change over the previous 30 years in BC across BRICS-Plus and compare it to the global.

Results: In 2019, there were about 1.98 million female BC cases (age-standardized rate of 45.86 [95% UI: 41.91, 49.76]) and 0.69 million deaths (age-standardized rate of 15.88 [95% UI: 14.66, 17.07]) around the globe. Among them, 45.4% of incident cases and 51.3% of deaths were attributed to the BRICS-Plus. China (41.1% cases and 26.5% deaths) and India (16.1% cases and 23.1% deaths) had the largest proportion of incident cases and deaths among the BRICS-Plus nations in 2019. Pakistan came in third with 5.6% cases and 8.8% deaths. Over the past three decades, from 1990 to 2019, the BRICS-Plus region's greatest AROC was seen in Lesotho (2.61%; 95%UI: 1.99-2.99). The birth cohort impacts on BC vary significantly among the BRICS-Plus nations. Overall, the risk of case-fatality rate tended to decline in all BRICS-Plus nations, notably in South Asian Association for Regional Cooperation (SAARC) and China-ASEAN Free Trade Area (China-ASEAN FTA) countries, and the drop in risk in the most recent cohort was lowest in China and the Maldives. Additionally, there was a substantial negative link between SDI and case fatality rate (r₁₉₉₀= -0.91, p<0.001; r₂₀₁₉= -0.89, p<0.001) in the BRICS-Plus in both 1990 and 2019, with the Eurasian Economic Union (EEU) nations having the highest case fatality rate.

Conclusions: The BC burden varies remarkably between different BRICS-Plus regions. Although the BRICS' efforts to regulate BC succeeded, the overall improvements lagged behind those in high-income Asia-Pacific nations. Every BRICS-Plus country should strengthen specific public health approaches and policies directed at different priority groups, according to BRIC-Plus and other high-burden nations.

Keywords: APC; BRICS-Plus; SDI; breast cancer; case fatality; mortality.

Figure 1

(A) Relative proportion of BRICS-Plus to Global burden of breast cancer incidence and death in year 2019, (B) Country specific breast cancer burden within BRICS-Plus; percent cases (incidence and death) indicate proportion of country specific cases to total cases in BRICS-Plus.

Figure 2

Comparison of annualized rate of change (AROC) BRICS-Plus to Global burden of breast cancer. IR, Incidence rate; MR, Mortality rate.

Figure 3

Age-specific mortality rates of breast cancer by period across 35 BRICS-Plus countries and Globally between 1990 to 2019.

Figure 4

Cohort-specific mortality rates of breast cancer by age group across 35 BRICS-Plus countries and Globally between 1990 to 2019.

Figure 5

Age period cohort related female breast cancer trends in (A) death rate (B) incidence rate and (C) case fatality rate (CFR) from 1990-2019 with ages 20 to 84. Rate ratio was estimated using ML of APC-model Poisson with log(Y) based on natural-spline function, for each BRICS-Plus region separately. ML, maximum likelihood; APC, age-period-cohort; Reference cohort for age-effects was chosen as the median date of birth among cases; and Median date of diagnosis among cases was selected as reference period; SACU, South African Customs Union; SAARC, South Asian Association for Regional Cooperation; China-ASEAN FTA, China-ASEAN Free Trade Area; EEU, Eurasian Economic Union; Mercosur, core members as well as acceding members.

Figure 6

Country wise correlation between age-standardised BC rate and country’s sociodemographic index (SDI) across BRICS-Plus; (A) mortality rate in 1990 (B) incidence rate in 1990 (C) Case fatality percent (CFP) in 1990; (D) mortality rate in 2019 (E) incidence rate in 2019 (F) Case fatality percent (CFP) in 2019; Case-fatality percent was calculated by dividing age-standardised death rate by age-standardised incidence rate and multiplied by 100; LSE, Least Square Error fit; LAE, Least Absolute Error fit; SDI ranges from 0 (less developed) to 1 (most developed).