Publications

OBJECTIVES: Extended validation of an index predicting mortality among community-dwelling US older adults.

DESIGN/SETTING: Examination of the performance of a previously developed index in predicting 10- and 14-year mortality among respondents to the 1997-2000 National Health Interview Surveys (NHIS) using the original development and validation cohorts. Follow-up mortality data are now available through 2011.

PARTICIPANTS: 16,063 respondents from the original development cohort and 8,027 respondents from the original validation cohort. All participants were community dwelling and ≥65 years old.

MEASUREMENTS: We calculated risk scores for each respondent based on the presence or absence of 11 factors (function, illnesses, behaviors, demographics) that make up the index. Using the Kaplan Meier method, we computed 10- and 14-year mortality estimates for the development and validation cohorts to examine model calibration. We examined model discrimination using the c-index.

RESULTS: Participants in the development and validation cohorts were similar. Participants with risk scores 0-4 had 23% risk of 14-year mortality whereas respondents with risk scores (13+) had 89% risk of 14-year mortality. The c-index of the model in both cohorts was 0.73 for predicting 10-year mortality and 0.72 for predicting 14-year mortality. Overall, 18.4% of adults 65-74 years and 60.2% of adults ≥75 years have >50% risk of mortality in 10 years.

CONCLUSIONS: Our index demonstrated excellent calibration and discrimination in predicting 10- and 14-year mortality among community-dwelling US adults ≥65 years. Information on long-term prognosis is needed to help clinicians and older adults make more informed person-centered medical decisions and to help older adults plan for the future.

Purpose The benefits of annual surveillance mammography in older breast cancer survivors with limited life expectancy are not known, and there are important risks; however, little is known about mammography use among these women. Materials and Methods We used National Health Interview Study data from 2000, 2005, 2008, 2010, 2013, and 2015 to examine surveillance mammography use among women age ≥ 65 years who reported a history of breast cancer. Using multivariable logistic regression, we assessed the probability of mammography within the last 12 months by 5- and 10-year life expectancy (using the validated Schonberg index), adjusting for survey year, region, age, marital status, insurance, educational attainment, and indicators of access to care. Results Of 1,040 respondents, 33.7% were age ≥ 80 years and 88.6% were white. Approximately 8.6% and 35.1% had an estimated life expectancy of ≤ 5 and ≤ 10 years, respectively. Overall, 78.9% reported having routine surveillance mammography in the last 12 months. Receipt of mammography decreased with decreasing life expectancy ( P < .001), although 56.7% and 65.9% of those with estimated ≤ 5-year and ≤ 10-year life expectancy, respectively, reported mammography in the last year. Conversely, 14.1% of those with life expectancy > 10 years did not report mammography. In adjusted analyses, lower ( v higher) life expectancy was significantly associated with lower odds of mammography (odds ratio, 0.4; 95% CI, 0.3 to 0.8 for ≤ 5-year life expectancy and OR, 0.4; 95% CI, 0.3 to 0.6 for ≤ 10-year life expectancy). Conclusion Many (57%) older breast cancer survivors with an estimated short life expectancy (< 5 years) receive annual surveillance mammography despite unknown benefits, whereas 14% with estimated life expectancy > 10 years did not report mammography. Practice guidelines are needed to optimize and tailor follow-up care for older patients.

OBJECTIVES: To examine over-screening of older Israelis for colon and breast cancer.

DESIGN: Cross sectional.

SETTING: Clalit Health Services (CHS), Israel's largest health maintenance organization (HMO), provides care for more than half of the country's population and operates a national age-based programs for cancer screening.

PARTICIPANTS: All community-dwelling members aged 65 to 79 in 2014 (N = 370,876).

MEASUREMENTS: We used CHS data warehouse to evaluate cancer screening during 2014. Life expectancy (LE) was estimated using the validated Schonberg index.

RESULTS: Almost one-quarter (23.1%; 15.6% of adults aged 65-74, 42.7% of adults aged 75-79) of the study population had an estimated LE of less than 10 years. Annual fecal occult blood test and biannual mammography rates among adults aged 65 to 74 with a LE of 10 years or longer were 37.1% and 70.0%, respectively. Rates dropped after age 75 (4.0%, 19.5%) and to a lesser extent with a LE of less than 10 years (31.6%, 56.4%). Prostate-specific antigen testing is not part of the national screening program, and the proportion of people tested (42.6%), did not vary similarly with age of 75 and older (43.2%) or LE of less than 10 years (38.1%).

CONCLUSION: The cancer screening inclusion criteria of the national referral system have a strong effect on receipt of screening; LE considerations are less influential. Some method of estimating LE could be incorporated into algorithms to improve individualized cancer screening to reduce over- and underscreening of older adults.

There are relatively limited data on outcomes of screening older adults for cancer; therefore, the decision to screen older adults requires balancing the potential harms of screening and follow-up diagnostic tests with the possibility of benefit. Harms of screening can be amplified in older and frail adults and include discomfort from undergoing the test itself, anxiety, potential complications from diagnostic procedures resulting from a false-positive test, false reassurance from a false-negative test, and overdiagnosis of tumors that are of no threat and may result in overtreatment. In this paper, we review the evidence and guidelines on breast, colorectal, lung and prostate cancer as applied to older adults. We also provide a general framework for approaching cancer screening in older adults by incorporating evidence-based guidelines, patient preferences, and patient life expectancy estimates into shared screening decisions.

In November 2013, the U.S. Preventive Services Task Force issued a guideline on medications for risk reduction of primary breast cancer in women. Although mammography can detect early cases, it cannot prevent development of breast cancer. Tamoxifen and raloxifene are selective estrogen receptor modulators that have been shown to reduce the risk for estrogen receptor-positive breast cancer and are approved by the U.S. Food and Drug Administration (FDA) for this indication. However, neither medication reduces the risk for estrogen receptor-negative breast cancer or all-cause mortality. The Task Force concluded that postmenopausal women with an estimated 5-year risk for breast cancer of 3% or greater will probably have more net benefit than harm and recommends that clinicians engage in shared, informed decision making about these medications. The American Society of Clinical Oncology issued a practice guideline on use of pharmacologic interventions for breast cancer in 2013. It recommends that women aged 35 years or older at increased risk, defined as a 5-year absolute risk for breast cancer of 1.66% or greater, discuss breast cancer prevention medications with their primary care practitioner. The Society includes the aromatase inhibitor exemestane in addition to tamoxifen and raloxifene as a breast cancer prevention medication, although exemestane is not FDA approved for this indication. Here, an oncologist and an internist discuss how they would balance these recommendations and what they would suggest for an individual patient.

BACKGROUND: 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.

METHODS: 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.

RESULTS: 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.

CONCLUSIONS: 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.

PURPOSE: Accurate risk assessment is necessary for decision-making around breast cancer prevention. We aimed to develop a breast cancer prediction model for postmenopausal women that would take into account their individualized competing risk of non-breast cancer death.

METHODS: We included 73,066 women who completed the 2004 Nurses' Health Study (NHS) questionnaire (all ≥57 years) and followed participants until May 2014. We considered 17 breast cancer risk factors (health behaviors, demographics, family history, reproductive factors) and 7 risk factors for non-breast cancer death (comorbidities, functional dependency) and mammography use. We used competing risk regression to identify factors independently associated with breast cancer. We validated the final model by examining calibration (expected-to-observed ratio of breast cancer incidence, E/O) and discrimination (c-statistic) using 74,887 subjects from the Women's Health Initiative Extension Study (WHI-ES; all were ≥55 years and followed for 5 years).

RESULTS: Within 5 years, 1.8 % of NHS participants were diagnosed with breast cancer (vs. 2.0 % in WHI-ES, p = 0.02), and 6.6 % experienced non-breast cancer death (vs. 5.2 % in WHI-ES, p < 0.001). Using a model selection procedure which incorporated the Akaike Information Criterion, c-statistic, statistical significance, and clinical judgement, our final model included 9 breast cancer risk factors, 5 comorbidities, functional dependency, and mammography use. The model's c-statistic was 0.61 (95 % CI [0.60-0.63]) in NHS and 0.57 (0.55-0.58) in WHI-ES. On average, our model under predicted breast cancer in WHI-ES (E/O 0.92 [0.88-0.97]).

CONCLUSIONS: We developed a novel prediction model that factors in postmenopausal women's individualized competing risks of non-breast cancer death when estimating breast cancer risk.

The population is aging, and breast cancer incidence increases with age, peaking between the ages of 75 and 79. However, it is not known whether mammography screening helps women aged 75 and older live longer because they have not been included in randomized controlled trials evaluating mammography screening. Guidelines recommend that older women with less than a 10-year life expectancy not be screened because it takes approximately 10 years before a screen-detected breast cancer may affect an older woman's survival. Guidelines recommend that clinicians discuss the benefits and risks of screening with women aged 75 and older with a life expectancy of 10 years or longer to help them elicit their values and preferences. It is estimated that two of 1,000 women who continue to be screened every other year from age 70 to 79 may avoid breast cancer death, but 12% to 27% of these women will experience a false-positive test, and 10% to 20% of women who experience a false-positive test will undergo a breast biopsy. In addition, approximately 30% of screen-detected cancers would not otherwise have shown up in an older woman's lifetime, yet nearly all older women undergo treatment for these breast cancers, and the risks of treatment increase with age. To inform decision-making, tools are available to estimate life expectancy and to educate older women about the benefits and harms of mammography screening. Guides are also available to help clinicians discuss stopping screening with older women with less than a 10-year life expectancy. Ideally, screening decisions would consider an older woman's life expectancy, breast cancer risk, and her values and preferences.