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. 2020 Mar 25;10(1):5480.
doi: 10.1038/s41598-020-62393-1.

Trends and Projections in Breast Cancer Mortality among four Asian countries (1990-2017): Evidence from five Stochastic Mortality Models

Sumaira Mubarik  1 , Fang Wang  1 , Muhammad Fawad  2   3 , Yafeng Wang  1 , Ishfaq Ahmad  4 , Chuanhua Yu  5   6
Affiliations

Trends and Projections in Breast Cancer Mortality among four Asian countries (1990-2017): Evidence from five Stochastic Mortality Models

Sumaira Mubarik et al. Sci Rep. .

Abstract

The current study aimed to explore some important insights into the breast cancer mortality (BCM) trends and projections among four Asian countries by using five advanced stochastic mortality models. BCM data over 28 years from 1990-2017 with ages 20-84 were retrieved from the Global Burden of Disease (GBD) Study 2017 for four Asian countries, namely, China, India, Pakistan, and Thailand. Five stochastic mortality models with the family of generalized age-period-cohort were implemented to find the present and future BCM trends in these four Asian countries. Based on Cairns-Blake-Dowd (CBD) model and Lee-Carter model (LCM), overall, results revealed that BCM increased with the passage of time. Aging factor was the most influential factor of elevated BCM in each Asian country under consideration. Projection of BCM showed that mortality rates might continue to grow with time, especially in older ages in each Asian country under study. The highest forecasted BCM rates were observed in Pakistan as compared to other countries. The obvious increase in BCM suggested that earlier tactics should be implemented to reduce the subsequent morbidity and mortality due to breast cancer. The last but not least, some additional tactics to mitigate the BCM in older ages must be adopted.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Trends of BCM rates by age, period, and cohort for four Asian countries from 1990 to 2017. response: BCM rates (per 100,000).
Figure 2
Figure 2
Growth of BCM in Asian women separately for each country aged 20 to 84 for the years 1990 to 2017.
Figure 3
Figure 3
Estimation of the (a) LCM (b) APC (c) CBD (d) M7 and (e) RH model parameters for four Asian countries.
Figure 4
Figure 4
Forecast of the BCM index using the CBD model and LCM model for (1990–2030) period by countries. Shades represent 80% and 95% prediction intervals.
Figure 5
Figure 5
Forecast of the BCM rates (per 100 000) using the LCM and CBD model for (1990–2030) period by age and countries. Actual rate (red dot ◦), fitted rate (black line-) and forecast rate (blue dashed line–).
See this image and copyright information in PMC

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