Boyoung Park, Yoosoo Chang, Seungho Ryu, Thi Xuan Mai Tran
{"title":"Trajectories of breast density change over time and subsequent breast cancer risk: longitudinal study","authors":"Boyoung Park, Yoosoo Chang, Seungho Ryu, Thi Xuan Mai Tran","doi":"10.1136/bmj-2024-079575","DOIUrl":null,"url":null,"abstract":"Objective To identify clusters of women with similar trajectories of breast density change over four longitudinal assessments and to examine the association between these trajectories and the subsequent risk of breast cancer. Design Retrospective cohort study. Setting Data from the national breast cancer screening programme, which is embedded in the National Health Insurance Service database in Korea. Breast density was assessed using the four category Breast Imaging Reporting and Data System (BI-RADS) classification. Group based trajectory modelling was performed to identify the trajectories of breast density. Participants Women aged ≥40 years who underwent four biennial mammographic screenings between 2009 and 2016. Main outcome measures Breast cancer development was determined to 31 December 2021. Cox proportional hazard models were used to assess the associations between trajectories and breast cancer outcomes after adjusting for covariates. Results Among a cohort of 1 747 507 women (mean age 61.4 years), five breast density trajectory groups were identified. Group 1 included women with persistently fatty breast tissue, group 2 included women with fatty breast tissue at baseline but increased breast density over time, and groups 3-5 included women with denser breasts, with a slight decrease in density over time. Women in group 2 had a 1.60-fold (95% confidence interval 1.49 to 1.72) increased risk of breast cancer compared with those in group 1. Women in groups 3-5 had higher risks compared with those in group 1, with adjusted hazard ratios of 1.86 (1.74 to 1.98), 2.49 (2.33 to 2.65), and 3.07 (2.87 to 3.28), respectively. Similar results were observed across different age groups, regardless of changes in menopausal status or body mass index. Conclusions This study identified five distinct groups of women with similar trajectories of breast density change over time. Future risk of breast cancer was found to vary in these groups. Increasingly dense or persistently dense breasts were associated with a higher risk. Changes in breast density over time should be carefully considered during breast cancer risk stratification and incorporated into future risk models. Data supporting the findings of this study are provided by the National Health Insurance Sharing Service website (<http://nhiss.nhis.or.kr>) through a data use agreement. We accessed the database after submitting the study protocol and IRB approval document and reviewed the request form provided by the committee. Additional information is available from the corresponding author upon request. The analytic SAS codes are available from the corresponding author and can also be found in supporting materials (SAS codes supplemental material).","PeriodicalId":22388,"journal":{"name":"The BMJ","volume":"19 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The BMJ","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/bmj-2024-079575","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective To identify clusters of women with similar trajectories of breast density change over four longitudinal assessments and to examine the association between these trajectories and the subsequent risk of breast cancer. Design Retrospective cohort study. Setting Data from the national breast cancer screening programme, which is embedded in the National Health Insurance Service database in Korea. Breast density was assessed using the four category Breast Imaging Reporting and Data System (BI-RADS) classification. Group based trajectory modelling was performed to identify the trajectories of breast density. Participants Women aged ≥40 years who underwent four biennial mammographic screenings between 2009 and 2016. Main outcome measures Breast cancer development was determined to 31 December 2021. Cox proportional hazard models were used to assess the associations between trajectories and breast cancer outcomes after adjusting for covariates. Results Among a cohort of 1 747 507 women (mean age 61.4 years), five breast density trajectory groups were identified. Group 1 included women with persistently fatty breast tissue, group 2 included women with fatty breast tissue at baseline but increased breast density over time, and groups 3-5 included women with denser breasts, with a slight decrease in density over time. Women in group 2 had a 1.60-fold (95% confidence interval 1.49 to 1.72) increased risk of breast cancer compared with those in group 1. Women in groups 3-5 had higher risks compared with those in group 1, with adjusted hazard ratios of 1.86 (1.74 to 1.98), 2.49 (2.33 to 2.65), and 3.07 (2.87 to 3.28), respectively. Similar results were observed across different age groups, regardless of changes in menopausal status or body mass index. Conclusions This study identified five distinct groups of women with similar trajectories of breast density change over time. Future risk of breast cancer was found to vary in these groups. Increasingly dense or persistently dense breasts were associated with a higher risk. Changes in breast density over time should be carefully considered during breast cancer risk stratification and incorporated into future risk models. Data supporting the findings of this study are provided by the National Health Insurance Sharing Service website () through a data use agreement. We accessed the database after submitting the study protocol and IRB approval document and reviewed the request form provided by the committee. Additional information is available from the corresponding author upon request. The analytic SAS codes are available from the corresponding author and can also be found in supporting materials (SAS codes supplemental material).