Evidence map›Paper›PMID 36207752›Full record

ArticlePopulation health metrics2022

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.

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

Abstract read
In one paragraph

Article in Population health metrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Epidemiology, early detection, and management of breast cancer in China: A comprehensive review.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Xin-Xin Yan *Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan South Lane, Chaoyang District, Beijing, 100021, China.
Juan Zhu *Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan South Lane, Chaoyang District, Beijing, 100021, China.
Yan-Jie Li *Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan South Lane, Chaoyang District, Beijing, 100021, China.
Meng-Di Cao *Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan South Lane, Chaoyang District, Beijing, 100021, China.
Xin WangOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan South Lane, Chaoyang District, Beijing, 100021, China.
Hong WangOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan South Lane, Chaoyang District, Beijing, 100021, China.
Cheng-Cheng LiuOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan South Lane, Chaoyang District, Beijing, 100021, China.
Jing WangDepartment of Statistics and Information, Beijing Center for Disease Prevention and Control, Beijing, 100013, China.
Yang LiDivision of Health Information Dissemination, Institute of Medical Information, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 3 Yabao Road, Chaoyang District, Beijing, 100020, China. li.yang@imicams.ac.cn.
Ju-Fang ShiOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan South Lane, Chaoyang District, Beijing, 100021, China. shijf@cicams.ac.cn.ORCID 0000-0001-5283-9762

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost 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.

methodsUsing 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.

resultsIn 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%.

conclusionEstimates 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.

Indexed as

Breast NeoplasmsAgedChinaDisability-Adjusted Life YearsEarly Detection of CancerFemaleGlobal Burden of DiseaseHumansPrevalenceQuality-Adjusted Life YearsBreast cancerChinaDALYsDisability weightsScreening

Identifiers

PMID36207752
PMCPMC9547451

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.