Inpatient Screening Mammography for Non-adherent and High Risk Women

51 Background: Screening women at high risk with MRI has been shown to detect breast cancer at an early stage. Therefore, MRI screening has been recommended in the UK and USA for women who are at a high risk of developing breast cancer. However, there is no information available in the province of British Columbia (BC) about the number of women who have a high risk of developing breast cancer. Therefore, we carried out a study to estimate the breast cancer risk distribution in three sample populations in BC using Tyrer-Cuzick (TC) risk prediction model so that additional resource requirement for MRI breast screening can be calculated. Methods: A survey questionnaire was designed based on the TC model, which includes family history, hormonal factors, and benign breast disease. Additional questions also include factors that are used in other models (Gail, Claus, and BCRAPRO) as well as factors that may be included in the future. Women were recruited by staff and volunteers at three screening mammography clinics: Kelowna, Victoria General Hospital, and BC Women’s Health Centre in Vancouver. The survey was available to women to complete on the web, by phone, or on paper. An online database was constructed to store and query the data. The 10-year risk of developing breast cancer for each woman was calculated using the Tyrer-Cuzick IBIS Risk Evaluator software and the risk distribution of the survey population was analyzed. Results: Data from 3,200 women recruited from three sites, gives a risk distribution showing 2.6% are at high risk of developing breast cancer, 31.2% are at moderate risk, and 66.2% are at low risk. Based on NICE guidelines (UK), high risk is defined as having a 10-year risk of greater than 8%, moderate risk as 3-8%, and low risk as less than 3%. Extrapolating this to the approximately 500,000 women who are eligible to attend for screening mammography in BC, 13,000 women are considered at high risk. Conclusions: Our results indicate that 2.6% of women ages 40-79 attending screening mammography in BC may have a very high risk of developing breast cancer based on personal and family history. Based on a 14-hour work day, three additional MRI scanners would be required to implement MRI screening for these high-risk women in BC.

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Identifying women at high-risk for breast cancer using data from the electronic health record compared to self-report.

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.e13044 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. e13044-e13044 ◽

Cited By ~ 1

Author(s):

Xinyi Li ◽

Julia E. McGuinness ◽

Alejandro Vanegas ◽

Hilary Colbeth ◽

Jennifer Vargas ◽

...

Keyword(s):

Breast Cancer ◽

Family History ◽

High Risk ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Screening Mammography ◽

Self Report ◽

High Risk Women ◽

Race Ethnicity ◽

Self Report Data

e13044 Background: One of the barriers to chemoprevention uptake among high-risk women is the lack of routine breast cancer risk assessment in the primary care setting. We calculated breast cancer risk using the Breast Cancer Surveillance Consortium (BCSC) model, which accounts for age, race/ethnicity, first-degree family history of breast cancer, benign breast disease, and mammographic density, using data collected from the electronic health record (EHR) compared to self-report. Methods: Among women undergoing screening mammography, we collected breast cancer risk information from the EHR and a self-administered survey. Eligibility criteria for calculating 5-year invasive breast cancer risk using the BCSC model included age 35-74, no prior history of breast cancer, mastectomy, or breast augmentation. We extracted data on demographics, structured first-degree family history, breast radiology and pathology reports from the EHR. We assessed agreement in breast cancer risk information between the EHR and self-report data. Results: Among 13,735 women with EHR data for BCSC risk calculation, 2708 women (20%) met high-risk criteria, based upon a 5-year breast cancer risk ≥1.67%. Among high-risk women, 2% were age 40-49, 23% age 50-59, 48% age 60-69, and 26% age 70-74. From the EHR, data was missing on 31% for race/ethnicity and 85% for family history. Among 2320 women with both EHR and self-report data, more complete information was available for race/ethnicity, family history, and breast biopsies in the surveys. More first-degree family history (14% vs. 3%) and prior breast biopsies (18% vs. 11%) were identified by self-report vs. EHR, respectively. However, more women with atypia and lobular carcinoma in situwere identified from the EHR. More high-risk women (20% vs. 16%) were identified with EHR vs. survey data, respectively, with correlation of 0.82. Conclusions: Among women undergoing screening mammography, we identified 20% who met high-risk criteria according to the BCSC model based upon EHR data, despite missing information on race/ethnicity, family history, and prior breast biopsies. This may serve as an initial screen for identifying women eligible for breast cancer chemoprevention.

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Identifying Women at High Risk for Breast Cancer Using Data From the Electronic Health Record Compared With Self-Report

JCO Clinical Cancer Informatics ◽

10.1200/cci.18.00072 ◽

2019 ◽

pp. 1-8 ◽

Cited By ~ 3

Author(s):

Xinyi Jiang ◽

Julia E. McGuinness ◽

Margaret Sin ◽

Thomas Silverman ◽

Rita Kukafka ◽

...

Keyword(s):

Breast Cancer ◽

Family History ◽

High Risk ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Screening Mammography ◽

Self Report ◽

High Risk Women ◽

History Of ◽

Using Data

PURPOSE A barrier to chemoprevention uptake among high-risk women is the lack of routine breast cancer risk assessment in the primary care setting. We calculated breast cancer risk using the Breast Cancer Surveillance Consortium (BCSC) model, accounting for age, race/ethnicity, first-degree family history of breast cancer, benign breast disease, and mammographic density, using data collected from the electronic health records (EHRs) and self-reports. PATIENTS AND METHODS Among women undergoing screening mammography, we enrolled those age 35 to 74 years without a prior history of breast cancer. Data on demographics, first-degree family history, breast radiology, and pathology reports were extracted from the EHR. We assessed agreement between the EHR and self-report on information about breast cancer risk. RESULTS Among 9,514 women with known race/ethnicity, 1,443 women (15.2%) met high-risk criteria based upon a 5-year invasive breast cancer risk of 1.67% or greater according to the BCSC model. Among 1,495 women with both self-report and EHR data, more women with a first-degree family history of breast cancer (14.6% v 4.4%) and previous breast biopsies (21.3% v 11.3%) were identified by self-report versus EHR, respectively. However, more women with atypia and lobular carcinoma in situ were identified from the EHR. There was moderate agreement in identification of high-risk women between EHR and self-report data (κ, 0.48; 95% CI, 0.42-0.54). CONCLUSION By using EHR data, we determined that 15% of women undergoing screening mammography had a high risk for breast cancer according to the BCSC model. There was moderate agreement between information on breast cancer risk derived from the EHR and self-report. Examining EHR data may serve as an initial screen for identifying women eligible for breast cancer chemoprevention.

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