Xin-Xin Yan, Juan Zhu, Yan-Jie Li, Meng-Di Cao, Xin Wang, Hong Wang, Cheng-Cheng Liu, Jing Wang, Yang Li, Ju-Fang Shi
{"title":"估算 2015-2030 年中国女性乳腺癌的残疾调整寿命年数和筛查的影响：应用地方权重的基于患病率的探索性分析。","authors":"Xin-Xin Yan, Juan Zhu, Yan-Jie Li, Meng-Di Cao, Xin Wang, Hong Wang, Cheng-Cheng Liu, Jing Wang, Yang Li, Ju-Fang Shi","doi":"10.1186/s12963-022-00296-1","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Most cancer disability-adjusted life year (DALY) studies worldwide have used broad, generic disability weights (DWs); however, differences exist among populations and types of cancers. Using breast cancer as example, this study aimed to estimate the population-level DALYs in females in China and the impact of screening as well as applying local DWs.</p><p><strong>Methods: </strong>Using multisource data, a prevalence-based model was constructed. (1) Overall years lived with disability (YLDs) were estimated by using numbers of prevalence cases, stage-specific proportions, and local DWs for breast cancer. Numbers of females and new breast cancer cases as well as local survival rates were used to calculate the number of prevalence cases. (2) Years of life lost (YLLs) were estimated using breast cancer mortality rates, female numbers and standard life expectancies. (3) The prevalence of and mortality due to breast cancer and associated DALYs from 2020 to 2030 were predicted using Joinpoint regression. (4) Assumptions considered for screening predictions included expanding coverage, reducing mortality due to breast cancer and improving early-stage proportion for breast cancer.</p><p><strong>Results: </strong>In Chinese females, the estimated number of breast cancer DALYs was 2251.5 thousand (of 17.3% were YLDs) in 2015, which is predicted to increase by 26.7% (60.3% among those aged ≥ 65 years) in 2030 (2852.8 thousand) if the screening coverage (25.7%) stays unchanged. However, if the coverage can be achieved to 40.7% in 2030 (deduced from the \"Healthy China Initiative\"), DALYs would decrease by 1.5% among the screened age groups. Sensitivity analyses found that using local DWs would change the base-case values by ~ 10%.</p><p><strong>Conclusion: </strong>Estimates of DALYs due to breast cancer in China were lower (with a higher proportion of YLDs) than Global Burden of Disease Study numbers (2527.0 thousand, 8.2% were YLDs), suggesting the importance of the application of population-specific DWs. If the screening coverage remains unchanged, breast cancer-caused DALYs would continue to increase, especially among elderly individuals.</p>","PeriodicalId":51476,"journal":{"name":"Population Health Metrics","volume":"20 1","pages":"19"},"PeriodicalIF":3.2000,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9547451/pdf/","citationCount":"0","resultStr":"{\"title\":\"Estimating disability-adjusted life years for breast cancer and the impact of screening in female populations in China, 2015-2030: an exploratory prevalence-based analysis applying local weights.\",\"authors\":\"Xin-Xin Yan, Juan Zhu, Yan-Jie Li, Meng-Di Cao, Xin Wang, Hong Wang, Cheng-Cheng Liu, Jing Wang, Yang Li, Ju-Fang Shi\",\"doi\":\"10.1186/s12963-022-00296-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Most cancer disability-adjusted life year (DALY) studies worldwide have used broad, generic disability weights (DWs); however, differences exist among populations and types of cancers. Using breast cancer as example, this study aimed to estimate the population-level DALYs in females in China and the impact of screening as well as applying local DWs.</p><p><strong>Methods: </strong>Using multisource data, a prevalence-based model was constructed. (1) Overall years lived with disability (YLDs) were estimated by using numbers of prevalence cases, stage-specific proportions, and local DWs for breast cancer. Numbers of females and new breast cancer cases as well as local survival rates were used to calculate the number of prevalence cases. (2) Years of life lost (YLLs) were estimated using breast cancer mortality rates, female numbers and standard life expectancies. (3) The prevalence of and mortality due to breast cancer and associated DALYs from 2020 to 2030 were predicted using Joinpoint regression. (4) Assumptions considered for screening predictions included expanding coverage, reducing mortality due to breast cancer and improving early-stage proportion for breast cancer.</p><p><strong>Results: </strong>In Chinese females, the estimated number of breast cancer DALYs was 2251.5 thousand (of 17.3% were YLDs) in 2015, which is predicted to increase by 26.7% (60.3% among those aged ≥ 65 years) in 2030 (2852.8 thousand) if the screening coverage (25.7%) stays unchanged. However, if the coverage can be achieved to 40.7% in 2030 (deduced from the \\\"Healthy China Initiative\\\"), DALYs would decrease by 1.5% among the screened age groups. Sensitivity analyses found that using local DWs would change the base-case values by ~ 10%.</p><p><strong>Conclusion: </strong>Estimates of DALYs due to breast cancer in China were lower (with a higher proportion of YLDs) than Global Burden of Disease Study numbers (2527.0 thousand, 8.2% were YLDs), suggesting the importance of the application of population-specific DWs. If the screening coverage remains unchanged, breast cancer-caused DALYs would continue to increase, especially among elderly individuals.</p>\",\"PeriodicalId\":51476,\"journal\":{\"name\":\"Population Health Metrics\",\"volume\":\"20 1\",\"pages\":\"19\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2022-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9547451/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Population Health Metrics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12963-022-00296-1\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Population Health Metrics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12963-022-00296-1","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Estimating disability-adjusted life years for breast cancer and the impact of screening in female populations in China, 2015-2030: an exploratory prevalence-based analysis applying local weights.
Background: Most cancer disability-adjusted life year (DALY) studies worldwide have used broad, generic disability weights (DWs); however, differences exist among populations and types of cancers. Using breast cancer as example, this study aimed to estimate the population-level DALYs in females in China and the impact of screening as well as applying local DWs.
Methods: Using multisource data, a prevalence-based model was constructed. (1) Overall years lived with disability (YLDs) were estimated by using numbers of prevalence cases, stage-specific proportions, and local DWs for breast cancer. Numbers of females and new breast cancer cases as well as local survival rates were used to calculate the number of prevalence cases. (2) Years of life lost (YLLs) were estimated using breast cancer mortality rates, female numbers and standard life expectancies. (3) The prevalence of and mortality due to breast cancer and associated DALYs from 2020 to 2030 were predicted using Joinpoint regression. (4) Assumptions considered for screening predictions included expanding coverage, reducing mortality due to breast cancer and improving early-stage proportion for breast cancer.
Results: In Chinese females, the estimated number of breast cancer DALYs was 2251.5 thousand (of 17.3% were YLDs) in 2015, which is predicted to increase by 26.7% (60.3% among those aged ≥ 65 years) in 2030 (2852.8 thousand) if the screening coverage (25.7%) stays unchanged. However, if the coverage can be achieved to 40.7% in 2030 (deduced from the "Healthy China Initiative"), DALYs would decrease by 1.5% among the screened age groups. Sensitivity analyses found that using local DWs would change the base-case values by ~ 10%.
Conclusion: Estimates of DALYs due to breast cancer in China were lower (with a higher proportion of YLDs) than Global Burden of Disease Study numbers (2527.0 thousand, 8.2% were YLDs), suggesting the importance of the application of population-specific DWs. If the screening coverage remains unchanged, breast cancer-caused DALYs would continue to increase, especially among elderly individuals.
期刊介绍：
Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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