Development and evaluation of a method to assess breast cancer risk using a longitudinal history of mammographic density: a cohort study.
Breast cancer risk
Longitudinal data
Mammographic density
Mammography screening
Repeated measures
Journal
Breast cancer research : BCR
ISSN: 1465-542X
Titre abrégé: Breast Cancer Res
Pays: England
ID NLM: 100927353
Informations de publication
Date de publication:
24 Nov 2023
24 Nov 2023
Historique:
received:
25
07
2023
accepted:
08
11
2023
medline:
27
11
2023
pubmed:
25
11
2023
entrez:
24
11
2023
Statut:
epublish
Résumé
Women with dense breasts have an increased risk of breast cancer. However, breast density is measured with variability, which may reduce the reliability and accuracy of its association with breast cancer risk. This is particularly relevant when visually assessing breast density due to variation in inter- and intra-reader assessments. To address this issue, we developed a longitudinal breast density measure which uses an individual woman's entire history of mammographic density, and we evaluated its association with breast cancer risk as well as its predictive ability. In total, 132,439 women, aged 40-73 yr, who were enrolled in Kaiser Permanente Washington and had multiple screening mammograms taken between 1996 and 2013 were followed up for invasive breast cancer through 2014. Breast Imaging Reporting and Data System (BI-RADS) density was assessed at each screen. Continuous and derived categorical longitudinal density measures were developed using a linear mixed model that allowed for longitudinal density to be updated at each screen. Predictive ability was assessed using (1) age and body mass index-adjusted hazard ratios (HR) for breast density (time-varying covariate), (2) likelihood-ratio statistics (ΔLR-χ In total, 2704 invasive breast cancers were diagnosed during follow-up (median = 5.2 yr; median mammograms per woman = 3). When compared with an age- and body mass index-only model, the gain in statistical information provided by the continuous longitudinal density measure was 23% greater than that provided by BI-RADS density (follow-up after baseline mammogram: ΔLR-χ Estimating mammographic density using a woman's history of breast density is likely to be more reliable than using the most recent observation only, which may lead to more reliable and accurate estimates of individual breast cancer risk. Longitudinal breast density has the potential to improve personal breast cancer risk estimation in women attending mammography screening.
Sections du résumé
BACKGROUND
BACKGROUND
Women with dense breasts have an increased risk of breast cancer. However, breast density is measured with variability, which may reduce the reliability and accuracy of its association with breast cancer risk. This is particularly relevant when visually assessing breast density due to variation in inter- and intra-reader assessments. To address this issue, we developed a longitudinal breast density measure which uses an individual woman's entire history of mammographic density, and we evaluated its association with breast cancer risk as well as its predictive ability.
METHODS
METHODS
In total, 132,439 women, aged 40-73 yr, who were enrolled in Kaiser Permanente Washington and had multiple screening mammograms taken between 1996 and 2013 were followed up for invasive breast cancer through 2014. Breast Imaging Reporting and Data System (BI-RADS) density was assessed at each screen. Continuous and derived categorical longitudinal density measures were developed using a linear mixed model that allowed for longitudinal density to be updated at each screen. Predictive ability was assessed using (1) age and body mass index-adjusted hazard ratios (HR) for breast density (time-varying covariate), (2) likelihood-ratio statistics (ΔLR-χ
RESULTS
RESULTS
In total, 2704 invasive breast cancers were diagnosed during follow-up (median = 5.2 yr; median mammograms per woman = 3). When compared with an age- and body mass index-only model, the gain in statistical information provided by the continuous longitudinal density measure was 23% greater than that provided by BI-RADS density (follow-up after baseline mammogram: ΔLR-χ
CONCLUSIONS
CONCLUSIONS
Estimating mammographic density using a woman's history of breast density is likely to be more reliable than using the most recent observation only, which may lead to more reliable and accurate estimates of individual breast cancer risk. Longitudinal breast density has the potential to improve personal breast cancer risk estimation in women attending mammography screening.
Identifiants
pubmed: 38001476
doi: 10.1186/s13058-023-01744-y
pii: 10.1186/s13058-023-01744-y
pmc: PMC10668455
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
147Subventions
Organisme : NCI NIH HHS
ID : P01 CA154292
Pays : United States
Organisme : Breast Cancer Now
ID : 2019DecPR1395
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : P01CA154292; R50CA211115; U01CA63731; HHSN261201300012I; N01 PC-2013-00012
Pays : United States
Organisme : NCI NIH HHS
ID : R50 CA211115
Pays : United States
Organisme : Cancer Research UK
ID : C569/A16891
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : U01 CA063731
Pays : United States
Informations de copyright
© 2023. The Author(s).
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