Dataset Information

Projection of morbidity and mortality due to breast cancer between 2020 and 2050 across 42 low- and middle-income countries.

ABSTRACT:

Objective

Aim of the study is to predict trends in morbidity and mortality due to breast cancer in 42 LMICs between 2020 and 2050.

Design

and Setting: National level cross-sectional breast cancer related data between 1990 and 2019 were used. Recurrent Neural Network, Long-Short-Term Memory (RNN-LSTM) model was employed to forecast the trend in breast cancer burden.

Main outcomes and measures

Age standardized breast cancer incidence, mortality, and disability adjusted life years (DALYs) rates.

Results

By 2050, the age standardized breast cancer incidence rate is expected to increase in 38 LMICs with highest incidence rate in Namibia; 127.0 (78.0-176.0) followed by Nigeria 71.1 (53.9-88.3) and Papua New Guinea 70.6 (88.7-74.6). Similarly, the age standardized breast cancer mortality and DALYs rates in 2050 are expected to increase in 33 and 35 LMICs respectively. The highest mortality and DALYs rates in 2050 are expected to be 64.7 (42.6-86.7) in Namibia and 1543.6 (1463.1-1624.1) in Pakistan. The estimated annual percentage change (EAPC) is expected to increase uniformly in all the countries during the same period. Due to considerable variation in exposure risk, such as high plasma glucose level, high body mass index (BMI) and socio-demographic index (SDI), high regional disparity in burden of breast cancer is expected among the countries.

Conclusion

and Relevance: Breast cancer burden is expected to increase in most of the LMICs with high regional disparity by 2050. Our study's finding focuses on LMICs with high breast cancer burden that require tailored strategies and effective action plans to ensure prevention from catastrophic consequences in the future. Minimizing the exposure to behavioral and metabolic risk factors such as high plasma glucose, high BMI, along with tackling the issue of low fertility rate would be important in managing breast cancer burden in LMICs.

SUBMITTER: Rauniyar SK

PROVIDER: S-EPMC10238690 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Projection of morbidity and mortality due to breast cancer between 2020 and 2050 across 42 low- and middle-income countries.

Rauniyar Santosh Kumar SK Hashizume Masahiro M Yoneoka Daisuke D Nomura Shuhei S

Heliyon 20230519 6

<h4>Objective</h4>Aim of the study is to predict trends in morbidity and mortality due to breast cancer in 42 LMICs between 2020 and 2050.<h4>Design</h4>and Setting: National level cross-sectional breast cancer related data between 1990 and 2019 were used. Recurrent Neural Network, Long-Short-Term Memory (RNN-LSTM) model was employed to forecast the trend in breast cancer burden.<h4>Main outcomes and measures</h4>Age standardized breast cancer incidence, mortality, and disability adjusted life y ...[more]

PMID: 37274661

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Dataset Information

Projection of morbidity and mortality due to breast cancer between 2020 and 2050 across 42 low- and middle-income countries.

Objective

Design

Main outcomes and measures

Results

Conclusion

Publications

Projection of morbidity and mortality due to breast cancer between 2020 and 2050 across 42 low- and middle-income countries.

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