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Characteristics predicting recommendation for familial breast cancer referral in a cohort of women from primary care

Lee, Siang Ing; Kai, Joe; Qureshi, Nadeem; Dutton, Brittany; Weng, Stephen

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Authors

Siang Ing Lee

Stephen Weng



Abstract

© 2020, The Author(s). Family history of breast and related cancers can indicate increased breast cancer (BC) risk. In national familial breast cancer (FBC) guidelines, the risk is stratified to guide referral decisions. We aimed to identify characteristics associated with the recommendation for referral in a large cohort of women undergoing FBC risk assessment in a recent primary care study. Demographic, family history, psychological and behavioural factors were collected with family history questionnaires, psychological questionnaires and manual data extraction from general practice electronic health records. Participants were women aged 30–60 with no previous history of breast or ovarian cancer. Data from 1127 women were analysed with stepwise logistic regression. Two multivariable logistic models were developed to predict recommendations for referral: using the entire cohort (n = 1127) and in a subgroup with uncertain risks (n = 168). Model performance was assessed by the area under the receiver operating curve (AUC). In all 1127 women, a multivariable model incorporating five family history components (BC aged < 40, bilateral BC, prostate cancer, first degree relative with ovarian cancer, paternal family history of BC) and having a mammogram in the last 3years, performed well (AUC = 0.86). For the 168 uncertain risk women, only paternal family history of BC remained significant (AUC = 0.71). Clinicians should pay particular attention to these five family history components when assessing FBC risk, especially prostate cancer which is not in the current national guidelines.

Citation

Lee, S. I., Kai, J., Qureshi, N., Dutton, B., & Weng, S. (2020). Characteristics predicting recommendation for familial breast cancer referral in a cohort of women from primary care. Journal of Community Genetics, 11, 331–338. https://doi.org/10.1007/s12687-020-00452-w

Journal Article Type Article
Acceptance Date Jan 14, 2020
Online Publication Date Jan 22, 2020
Publication Date 2020-07
Deposit Date Jan 16, 2020
Publicly Available Date Jan 24, 2020
Journal Journal of Community Genetics
Print ISSN 1868-310X
Electronic ISSN 1868-6001
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 11
Pages 331–338
DOI https://doi.org/10.1007/s12687-020-00452-w
Keywords Genetics(clinical); Public Health, Environmental and Occupational Health; Epidemiology
Public URL https://nottingham-repository.worktribe.com/output/3736350
Publisher URL https://link.springer.com/article/10.1007%2Fs12687-020-00452-w
Additional Information Received: 8 July 2019; Accepted: 14 January 2020; First Online: 22 January 2020; : ; : SW is a member of the Clinical Practice Research Datalink (CPRD) Independent Scientific Advisory Committee at the UK MHRA, academic advisor to Quealth Ltd., and has received independent research grants from AMGEN Ltd. NQ is a member of the NICE Guideline Development Group for Familial Breast Cancer and the advisory board for Journal of Community Genetics. SIL, BD, JK declare no potential conflict of interest.; : The study was granted ethics approval by Nottingham 2 Medical Research and Ethics Committee, reference number 14/EM/0009, and was performed in accordance with the Declaration of Helsinki.; : The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

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