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Time trends in multiple myeloma incidence and mortality across the BRICS from 1992 to 2021 and projection to 2046
by
Zhang, Xiaoqian
, Ji, Xiaohui
, Wu, Tianhao
, Wang, Jiali
, Fang, Yongjun
, Zhang, Heng
, Yao, Yuqian
in
Adult
/ Age
/ Age groups
/ Age-period-cohort analysis
/ Aged
/ Aged, 80 and over
/ Aging
/ Analysis
/ Bayesian analysis
/ Biostatistics
/ Brazil
/ Brazil - epidemiology
/ BRICS
/ Cancer
/ Care and treatment
/ China
/ China - epidemiology
/ Demographic aspects
/ Diagnosis
/ Disease
/ Emerging markets
/ Environmental Health
/ Epidemiology
/ Female
/ Forecasting
/ Forecasts and trends
/ Humans
/ Incidence
/ India
/ India - epidemiology
/ Male
/ Medicine
/ Medicine & Public Health
/ Middle Aged
/ Mortality
/ Mortality - trends
/ Multiple myeloma
/ Multiple myeloma (MM)
/ Multiple Myeloma - epidemiology
/ Multiple Myeloma - mortality
/ Nations
/ Prevention
/ Public Health
/ Regression analysis
/ Regression models
/ Russia
/ Russia - epidemiology
/ South Africa
/ South Africa - epidemiology
/ Time trends (Statistics)
/ Trends
/ Vaccine
2025
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Time trends in multiple myeloma incidence and mortality across the BRICS from 1992 to 2021 and projection to 2046
by
Zhang, Xiaoqian
, Ji, Xiaohui
, Wu, Tianhao
, Wang, Jiali
, Fang, Yongjun
, Zhang, Heng
, Yao, Yuqian
in
Adult
/ Age
/ Age groups
/ Age-period-cohort analysis
/ Aged
/ Aged, 80 and over
/ Aging
/ Analysis
/ Bayesian analysis
/ Biostatistics
/ Brazil
/ Brazil - epidemiology
/ BRICS
/ Cancer
/ Care and treatment
/ China
/ China - epidemiology
/ Demographic aspects
/ Diagnosis
/ Disease
/ Emerging markets
/ Environmental Health
/ Epidemiology
/ Female
/ Forecasting
/ Forecasts and trends
/ Humans
/ Incidence
/ India
/ India - epidemiology
/ Male
/ Medicine
/ Medicine & Public Health
/ Middle Aged
/ Mortality
/ Mortality - trends
/ Multiple myeloma
/ Multiple myeloma (MM)
/ Multiple Myeloma - epidemiology
/ Multiple Myeloma - mortality
/ Nations
/ Prevention
/ Public Health
/ Regression analysis
/ Regression models
/ Russia
/ Russia - epidemiology
/ South Africa
/ South Africa - epidemiology
/ Time trends (Statistics)
/ Trends
/ Vaccine
2025
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Time trends in multiple myeloma incidence and mortality across the BRICS from 1992 to 2021 and projection to 2046
by
Zhang, Xiaoqian
, Ji, Xiaohui
, Wu, Tianhao
, Wang, Jiali
, Fang, Yongjun
, Zhang, Heng
, Yao, Yuqian
in
Adult
/ Age
/ Age groups
/ Age-period-cohort analysis
/ Aged
/ Aged, 80 and over
/ Aging
/ Analysis
/ Bayesian analysis
/ Biostatistics
/ Brazil
/ Brazil - epidemiology
/ BRICS
/ Cancer
/ Care and treatment
/ China
/ China - epidemiology
/ Demographic aspects
/ Diagnosis
/ Disease
/ Emerging markets
/ Environmental Health
/ Epidemiology
/ Female
/ Forecasting
/ Forecasts and trends
/ Humans
/ Incidence
/ India
/ India - epidemiology
/ Male
/ Medicine
/ Medicine & Public Health
/ Middle Aged
/ Mortality
/ Mortality - trends
/ Multiple myeloma
/ Multiple myeloma (MM)
/ Multiple Myeloma - epidemiology
/ Multiple Myeloma - mortality
/ Nations
/ Prevention
/ Public Health
/ Regression analysis
/ Regression models
/ Russia
/ Russia - epidemiology
/ South Africa
/ South Africa - epidemiology
/ Time trends (Statistics)
/ Trends
/ Vaccine
2025
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Time trends in multiple myeloma incidence and mortality across the BRICS from 1992 to 2021 and projection to 2046
Journal Article
Time trends in multiple myeloma incidence and mortality across the BRICS from 1992 to 2021 and projection to 2046
2025
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Overview
Objective
This study evaluates the long-term trends in Multiple Myeloma (MM) incidence, mortality, and Age-Period-Cohort (APC) effects in the BRICS nations (Brazil, Russia, India, China, and South Africa).
Methods
Data on age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and 95% uncertainty intervals (UIs), were obtained from the Global Burden of Disease Study 2021. Joinpoint regression model was used to estimate the average annual percentage change (AAPC) and annual percentage change (APC) trends from 1992 to 2021, and the Age-Period-Cohort model evaluated nonlinear impacts of age, period, and cohort effects. Projections to 2046 were calculated using Bayesian APC modeling.
Results
From 1992 to 2021, MM incidence and death cases in the BRICS nations increased nearly four to fivefold, with ASIR and ASMR nearly doubling. China and India had lower ASIR and ASMR than other BRICS countries despite accounting for over half of cases and deaths. South Africa consistently had the highest ASIR and ASMR in both 1992 and 2021. China experienced a significant increase in ASIR (AAPC 4.92%,
p
< 0.001) and ASMR (AAPC 4.07%,
p
< 0.001) over the past three decades. MM incidence and mortality increased with aging, and the age effect on MM was more pronounced among individuals aged greater than 40 years. Birth cohorts’ impact on MM varied greatly between BRICS, with China suffering the largest risk increase among those born after the 1970s. Projections indicate ASIR and ASMR will reach 2.44 and 1.82 per 100,000 by 2046, continuing to rise across the BRICS nations.
Conclusions
MM burden is rapidly increasing in the BRICS, closely tied to population aging. Targeted strategies addressing each country’s unique challenges are essential as the burden continues to grow.
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