Literature DB >> 32154920

Familial risk of breast cancer by dynamic, accumulative, and static definitions of family history.

Trasias Mukama1,2,3, Elham Kharazmi1,4, Kristina Sundquist4,5,6, Jan Sundquist4,5,6, Hermann Brenner1,7,8, Mahdi Fallah1,4.   

Abstract

BACKGROUND: Familial breast cancer risk studies usually overlook the dynamic nature of family history.
METHODS: The authors assessed the effect of incorporating the timing of cancer diagnosis events into the assessment of familial risks of breast cancer in first-degree and second-degree relatives in a nationwide cohort study of 5,099,172 women (follow-up was between 1958-2015). Family history was assessed using 3 approaches: 1) as a static variable (ever having a relative with breast cancer); 2) as accumulative history; and 3) as a dynamic variable (time-dependent variable).
RESULTS: For women aged <50 years, familial risk was mostly higher when family history was assessed as a dynamic variable compared with using a static or accumulative family history. For example, the cumulative risk of receiving a breast cancer diagnosis until age 50 years for women with a history of breast cancer in 1 first-degree relative was 2.6% (95% CI, 2.5%-2.7%) using the static method, 2.4% (95% CI, 2.3%-2.4%) using the accumulative method, and 3.1% (95% CI, 3.0%-3.2%) using the dynamic method. Relative risk in women aged <50 years with a breast cancer diagnosis in a sister was 1.40-fold (95% CI, 1.31-fold to 1.48-fold) using the static method, 1.66-fold (95% CI, 1.57-fold to 1.76-fold) using the accumulative method, and 2.28-fold (95% CI, 2.07-fold to 2.51-fold) using the dynamic method.
CONCLUSIONS: The results of the current study demonstrated that assessing family history as static, accumulative, or dynamic results in different familial risk estimates. The answer as to which method to use for family history assessment depends on the implications of the study, with the dynamic method appearing to be better suited for risk stratification studies, the accumulative method being the most convenient in practice and the least favored for risk prediction, and the static method being suitable for etiological impact and risk attribution studies.
© 2020 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

Entities:  

Keywords:  breast cancer; familial risk; family history; prospective study; time-dependent

Mesh:

Year:  2020        PMID: 32154920     DOI: 10.1002/cncr.32815

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  6 in total

1.  Breast cancer screening: in the era of personalized medicine, age is just a number.

Authors:  Andrea Cozzi; Simone Schiaffino; Paolo Giorgi Rossi; Francesco Sardanelli
Journal:  Quant Imaging Med Surg       Date:  2020-12

2.  Risk of colorectal cancer in patients with diabetes mellitus: A Swedish nationwide cohort study.

Authors:  Uzair Ali Khan; Mahdi Fallah; Kristina Sundquist; Jan Sundquist; Hermann Brenner; Elham Kharazmi
Journal:  PLoS Med       Date:  2020-11-13       Impact factor: 11.069

3.  Correlation between family history and characteristics of breast cancer.

Authors:  Lei Liu; Xiaomeng Hao; Zian Song; Xiangcheng Zhi; Sheng Zhang; Jin Zhang
Journal:  Sci Rep       Date:  2021-03-18       Impact factor: 4.379

4.  Family history of breast cancer as a second primary malignancy in relatives: a nationwide cohort study.

Authors:  Guoqiao Zheng; Jan Sundquist; Kristina Sundquist; Jianguang Ji
Journal:  BMC Cancer       Date:  2021-11-12       Impact factor: 4.430

5.  Age at initiation of screening mammography by family history of breast cancer in the breast cancer surveillance consortium.

Authors:  Danielle D Durham; Megan C Roberts; Carly P Khan; Linn A Abraham; Robert A Smith; Karla Kerlikowske; Diana L Miglioretti
Journal:  Cancer Causes Control       Date:  2020-10-24       Impact factor: 2.506

6.  Association of Family History with the Development of Breast Cancer: A Cohort Study of 129,374 Women in KoGES Data.

Authors:  Hyo Geun Choi; Jung Ho Park; Yeon Ju Choi; Yong Joon Suh
Journal:  Int J Environ Res Public Health       Date:  2021-06-13       Impact factor: 3.390

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.