Development and evaluation of a method to assess breast cancer risk using a longitudinal history of mammographic density: a cohort study

被引:1
作者
Atakpa, Emma C. [1 ]
Buist, Diana S. M. [2 ,3 ]
Bowles, Erin J. Aiello [2 ]
Cuzick, Jack [1 ]
Brentnall, Adam R. [1 ]
机构
[1] Queen Mary Univ London, Wolfson Inst Populat Hlth, Barts & London Sch Med & Dent, London EC1M 6BQ, England
[2] Kaiser Permanente Washington Hlth Res Inst, Seattle, WA USA
[3] Kaiser Permanente Bernard J Tyson Sch Med, Pasadena, CA USA
关键词
Mammographic density; Longitudinal data; Repeated measures; Breast cancer risk; Mammography screening; PARENCHYMAL PATTERNS; WOMEN; TAMOXIFEN; ASSOCIATION; MENOPAUSE; MODEL; AGE;
D O I
10.1186/s13058-023-01744-y
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundWomen 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.MethodsIn 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 (Delta LR-chi 2) and (3) concordance indices.ResultsIn 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: Delta LR-chi 2 = 379.6 (degrees of freedom (df) = 2) vs. 307.7 (df = 3)), which increased to 35% (Delta LR-chi 2 = 251.2 vs. 186.7) for follow-up after three mammograms (n = 76,313, 2169 cancers). There was a sixfold difference in observed risk between densest and fattiest eight-category longitudinal density (HR = 6.3, 95% CI 4.7-8.7), versus a fourfold difference with BI-RADS density (HR = 4.3, 95% CI 3.4-5.5). Discriminatory accuracy was marginally greater for longitudinal versus BI-RADS density (c-index = 0.64 vs. 0.63, mean difference = 0.008, 95% CI 0.003-0.012).ConclusionsEstimating 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.
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页数:13
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  • [1] Repeated measures of mammographic density and texture to evaluate prediction and risk of breast cancer: a systematic review of the methods used in the literature
    Anandarajah, Akila
    Chen, Yongzhen
    Stoll, Carolyn
    Hardi, Angela
    Jiang, Shu
    Colditz, Graham A.
    [J]. CANCER CAUSES & CONTROL, 2023, 34 (11) : 939 - 948
  • [2] [Anonymous], 1992, Breast Imaging Reporting and Data System (BI-RADS)
  • [3] Bayesian joint ordinal and survival modeling for breast cancer risk assessment
    Armero, C.
    Forne, C.
    Rue, M.
    Forte, A.
    Perpinan, H.
    Gomez, G.
    Bare, M.
    [J]. STATISTICS IN MEDICINE, 2016, 35 (28) : 5267 - 5282
  • [4] Atkinson C, 1999, CANCER EPIDEM BIOMAR, V8, P863
  • [5] Hormone replacement therapy and mammographic density: a systematic literature review
    Azam, Shadi
    Jacobsen, Katja Kemp
    Aro, Arja R.
    Lynge, Elsebeth
    Andersen, Zorana Jovanovic
    [J]. BREAST CANCER RESEARCH AND TREATMENT, 2020, 182 (03) : 555 - 579
  • [6] Mammographic Density Change and Risk of Breast Cancer
    Azam, Shadi
    Eriksson, Mikael
    Sjolander, Arvid
    Hellgren, Roxanna
    Gabrielson, Marike
    Czene, Kamila
    Hall, Per
    [J]. JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2020, 112 (04): : 391 - 399
  • [7] Breast cancer surveillance consortium: A national mammography screening and outcomes database
    BallardBarbash, R
    Taplin, SH
    Yankaskas, BC
    Ernster, VL
    Rosenberg, RD
    Carney, PA
    Barlow, WE
    Geller, BM
    Kerlikowske, K
    Edwards, BK
    Lynch, CF
    Urban, N
    Key, CR
    Poplack, SP
    Worden, JK
    Kessler, LG
    [J]. AMERICAN JOURNAL OF ROENTGENOLOGY, 1997, 169 (04) : 1001 - 1008
  • [8] Boyd N, 2002, CANCER EPIDEM BIOMAR, V11, P1048
  • [9] Mammographic densities as a marker of human breast cancer risk and their use in chemoprevention.
    Boyd N.F.
    Martin L.J.
    Stone J.
    Greenberg C.
    Minkin S.
    Yaffe M.J.
    [J]. Current Oncology Reports, 2001, 3 (4) : 314 - 321
  • [10] The relationship of anthropometric measures to radiological features of the breast in premenopausal women
    Boyd, NF
    Lockwood, GA
    Byng, JW
    Little, LE
    Yaffe, MJ
    Tritchler, DL
    [J]. BRITISH JOURNAL OF CANCER, 1998, 78 (09) : 1233 - 1238