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Performance of the Breast Cancer Risk Assessment Tool Among Women Age 75 Years and Older.

ABSTRACT: The Breast Cancer Risk Assessment Tool (BCRAT, "Gail model") is commonly used for breast cancer prediction; however, it has not been validated for women age 75 years and older. We used Nurses' Health Study (NHS) data beginning in 2004 and Women's Health Initiative (WHI) data beginning in 2005 to compare BCRAT's performance among women age 75 years and older with that in women age 55 to 74 years in predicting five-year breast cancer incidence. BCRAT risk factors include: age, race/ethnicity, age at menarche, age at first birth, family history, history of benign breast biopsy, and atypia. We examined BCRAT's calibration by age by comparing expected/observed (E/O) ratios of breast cancer incidence. We examined discrimination by computing c-statistics for the model by age. All statistical tests were two-sided. Seventy-three thousand seventy-two NHS and 97 081 WHI women participated. NHS participants were more likely to be non-Hispanic white (96.2% vs 84.7% in WHI, P < .001) and were less likely to develop breast cancer (1.8% vs 2.0%, P = .02). E/O ratios by age in NHS were 1.16 (95% confidence interval [CI] = 1.09 to 1.23, age 57-74 years) and 1.31 (95% CI = 1.18 to 1.45, age ≥ 75 years, P = .02), and in WHI 1.03 (95% CI = 0.97 to 1.09, age 55-74 years) and 1.10 (95% CI = 1.00 to 1.21, age ≥ 75 years, P = .21). E/O ratio 95% confidence intervals crossed one among women age 75 years and older when samples were limited to women who underwent mammography and were without significant illness. C-statistics ranged between 0.56 and 0.58 in both cohorts regardless of age. BCRAT accurately predicted breast cancer for women age 75 years and older who underwent mammography and were without significant illness but had modest discrimination. Models that consider individual competing risks of non-breast cancer death may improve breast cancer risk prediction for older women.

SUBMITTER: Schonberg MA

PROVIDER: S-EPMC5072372 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ImportanceBreast density is associated with breast cancer risk in women aged 40 to 65 years, but there is limited evidence of its association with risk of breast cancer among women aged 65 years or older.ObjectiveTo compare the association between breast density and risk of invasive breast cancer among women aged 65 to 74 years vs women aged 75 years or older and to evaluate whether the association is modified by body mass index (BMI).Design, setting, and participantsThis prospective cohort study used data from the Breast Cancer Surveillance Consortium from January 1, 1996, to December 31, 2012, for US women aged 65 years or older who underwent screening mammography. Data were analyzed from January 1, 2018, to December 31, 2020.ExposuresBreast Imaging Reporting and Data System breast density category, age, and BMI.Main outcomes and measuresThe 5-year cumulative incidence of invasive breast cancer by level of breast density (almost entirely fat, scattered fibroglandular densities, or heterogeneous or extreme density) and age (65-74 vs ≥75 years) was calculated using weighted means. Cox proportional hazards models were fit to estimate the association of breast density with invasive breast cancer risk. The likelihood ratio test was used to test the interaction between BMI and breast density.ResultsA total of 221 714 screening mammograms from 193 787 women were included in the study; a total of 38% of the study population was aged 75 years or older. Of the mammograms, most were from women aged 65 to 74 years (64.6%) and non-Hispanic White individuals (81.4%). The 5-year cumulative incidence of invasive breast cancer increased in association with increasing breast density among women aged 65 to 74 years (almost entirely fatty breasts: 11.3 per 1000 women [95% CI, 10.4-12.5 per 1000 women]; scattered fibroglandular densities: 17.2 per 1000 women [95% CI, 16.1-17.9 per 1000 women]; extremely or heterogeneously dense breasts: 23.7 per 1000 women [95% CI, 22.4-25.3 per 1000 women]) and among those aged 75 years or older (fatty breasts: 13.5 per 1000 women [95% CI, 11.6-15.5]; scattered fibroglandular densities: 18.4 per 1000 women [95% CI, 17.0-19.5 per 1000 women]; extremely or heterogeneously dense breasts: 22.5 per 1000 women [95% CI, 20.2-24.2 per 1000 women]). Extreme or heterogeneous breast density was associated with increased risk of breast cancer compared with scattered fibroglandular breast density in both age categories (65-74 years: hazard ratio [HR], 1.39 [95% CI, 1.28-1.50]; ≥75 years: HR, 1.23 [95% CI, 1.10-1.37]). Women with almost entirely fatty breasts had a decrease of approximately 30% (range, 27%-34%) in the risk of invasive breast cancer compared with women with scattered fibroglandular breast density (65-74 years: HR, 0.66 [95% CI, 0.58-0.75]; ≥75 years: HR, 0.73; 95% CI, 0.62-0.86). Associations between breast density and breast cancer risk were not significantly modified by BMI (for age 65-74 years: likelihood ratio test, 2.67; df, 2; P = .26; for age ≥75 years, 2.06; df, 2; P = .36).Conclusions and relevanceThe findings suggest that breast density is associated with increased risk of invasive breast cancer among women aged 65 years or older. Breast density and life expectancy should be considered together when discussing the potential benefits vs harms of continued screening mammography in this population.

Project description:Guidelines recommend that women 75 years and older should be informed of the benefits and risks of mammography before being screened. However, few are adequately informed.To develop and evaluate a mammography screening decision aid (DA) for women 75 years and older.We designed the DA using international standards. Between July 14, 2010, and April 10, 2012, participants completed a pretest survey and read the DA before an appointment with their primary care physician. They completed a posttest survey after their appointment. Medical records were reviewed for follow-up information.Boston, Massachusetts, academic primary care practice. Eligible women were aged 75 to 89 years, English speaking, had not had a mammogram in 9 months but had been screened within the past 3 years, and did not have a history of dementia or invasive or noninvasive breast cancer. Of 84 women approached, 27 declined to participate, 12 were unable to complete the study for logistical reasons, and 45 participated.The DA includes information on breast cancer risk, life expectancy, competing mortality risks, possible outcomes of screening, and a values clarification exercise.Knowledge of the benefits and risks of screening, decisional conflict, and screening intentions; documentation in the medical record of a discussion of the risks and benefits of mammography with a primary care physician within 6 months; and the receipt of screening within 15 months. We used the Wilcoxon signed rank test and McNemar test to compare pretest-posttest information.The median age of participants was 79 years, 69% (31 of 45) were of non-Hispanic white race/ethnicity, and 60% (27 of 45) had attended at least some college. Comparison of posttest results with pretest results demonstrated 2 findings. First, knowledge of the benefits and risks of screening improved (P <?.001). Second, fewer participants intended to be screened (56% [25 of 45] afterward compared with 82% [37 of 45] before, P =?.03). Decisional conflict declined but not significantly (P =?.10). In the following 6 months, 53% (24 of 45) of participants had a primary care physician note that documented the discussion of the risks and benefits of screening compared with 11% (5 of 45) in the previous 5 years (P <?.001). While 84% (36 of 43) had been screened within 2 years of participating, 60% (26 of 43) were screened within 15 months after participating (? 2 years since their last mammogram) (P =?.01). Overall, 93% (42 of 45) found the DA helpful.A DA may improve older women's decision making about mammography screening.

Project description:ImportanceGuidelines recommend that women 75 years and older be informed of the benefits and harms of mammography before screening.ObjectiveTo test the effects of receipt of a paper-based mammography screening decision aid (DA) for women 75 years and older on their screening decisions.Design, setting, and participantsA cluster randomized clinical trial with clinician as the unit of randomization. All analyses were completed on an intent-to-treat basis. The setting was 11 primary care practices in Massachusetts or North Carolina. Of 1247 eligible women reached, 546 aged 75 to 89 years without breast cancer or dementia who had a mammogram within 24 months but not within 6 months and saw 1 of 137 clinicians (herein referred to as PCPs) from November 3, 2014, to January 26, 2017, participated. A research assistant (RA) administered a previsit questionnaire on each participant's health, breast cancer risk factors, sociodemographic characteristics, and screening intentions. After the visit, the RA administered a postvisit questionnaire on screening intentions and knowledge.InterventionsReceipt of the DA (DA arm) or a home safety (HS) pamphlet (control arm) before a PCP visit.Main outcomes and measuresParticipants were followed up for 18 months for receipt of mammography screening (primary outcome). To examine the effects of the DA, marginal logistic regression models were fit using generalized estimating equations to allow for clustering by PCP. Adjusted probabilities and risk differences were estimated to account for clustering by PCP.ResultsOf 546 women in the study, 283 (51.8%) received the DA. Patients in each arm were well matched; their mean (SD) age was 79.8 (3.7) years, 428 (78.4%) were non-Hispanic white, 321 (of 543 [59.1%]) had completed college, and 192 (35.2%) had less than a 10-year life expectancy. After 18 months, 9.1% (95% CI, 1.2%-16.9%) fewer women in the DA arm than in the control arm had undergone mammography screening (51.3% vs 60.4%; adjusted risk ratio, 0.84; 95% CI, 0.75-0.95; P = .006). Women in the DA arm were more likely than those in the control arm to rate their screening intentions lower from previsit to postvisit (69 of 283 [adjusted %, 24.5%] vs 47 of 263 [adjusted %, 15.3%]), to be more knowledgeable about the benefits and harms of screening (86 [adjusted %, 25.5%] vs 32 [adjusted %, 11.7%]), and to have a documented discussion about mammography with their PCP (146 [adjusted %, 47.4%] vs 111 [adjusted %, 38.9%]). Almost all women in the DA arm (94.9%) would recommend the DA.Conclusions and relevanceProviding women 75 years and older with a mammography screening DA before a PCP visit helps them make more informed screening decisions and leads to fewer women choosing to be screened, suggesting that the DA may help reduce overscreening.Trial registrationClinicalTrials.gov Identifier: NCT02198690.

Project description:BACKGROUND:There is a growing interest in delivering more personalised, risk-based breast cancer screening protocols. This requires population-level validation of practical models that can stratify women into breast cancer risk groups. Few studies have evaluated the Gail model (NCI Breast Cancer Risk Assessment Tool) in a population screening setting; we validated this tool in a large, screened population. METHODS:We used data from 40,158 women aged 50-69?years (via the lifepool cohort) participating in Australia's BreastScreen programme. We investigated the association between Gail scores and future invasive breast cancer, comparing observed and expected outcomes by Gail score ranked groups. We also used machine learning to rank Gail model input variables by importance and then assessed the incremental benefit in risk prediction obtained by adding variables in order of diminishing importance. RESULTS:Over a median of 4.3?years, the Gail model predicted 612 invasive breast cancers compared with 564 observed cancers (expected/observed (E/O)?=?1.09, 95% confidence interval (CI) 1.00-1.18). There was good agreement across decile groups of Gail scores (?2?=?7.1, p?=?0.6) although there was some overestimation of cancer risk in the top decile of our study group (E/O?=?1.65, 95% CI 1.33-2.07). Women in the highest quintile (Q5) of Gail scores had a 2.28-fold increased risk of breast cancer (95% CI 1.73-3.02, p?<?0.0001) compared with the lowest quintile (Q1). Compared with the median quintile, women in Q5 had a 34% increased risk (95% CI 1.06-1.70, p?=?0.014) and those in Q1 had a 41% reduced risk (95% CI 0.44-0.79, p?<?0.0001). Similar patterns were observed separately for women aged 50-59 and 60-69?years. The model's overall discrimination was modest (area under the curve (AUC) 0.59, 95% CI 0.56-0.61). A reduced Gail model excluding information on ethnicity and hyperplasia was comparable to the full Gail model in terms of correctly stratifying women into risk groups. CONCLUSIONS:This study confirms that the Gail model (or a reduced model excluding information on hyperplasia and ethnicity) can effectively stratify a screened population aged 50-69 years according to the risk of future invasive breast cancer. This information has the potential to enable more personalised, risk-based screening strategies that aim to improve the balance of the benefits and harms of screening.

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Performance of the Breast Cancer Risk Assessment Tool Among Women Age 75 Years and Older.

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