Brian L. Sprague

A Sustained Decline in Postmenopausal Hormone Use: Results From the National Health and Nutrition Examination Survey, 1999–2010

OBJECTIVE: Short-term declines in postmenopausal hormone use were observed after the Womens Health Initiative trial results in 2002. Although concerns about the trials generalizability have been expressed, long-term trends in hormone use in a nationally representative sample have not been reported. We sought to evaluate national trends in the prevalence of hormone use and to assess variation by type of formulation and patient characteristics. METHODS: We examined postmenopausal hormone use during 1999–2010 using cross-sectional data from 10,107 women aged 40 years and older in the National Health and Nutrition Examination Survey. RESULTS: In 1999–2000, the prevalence of oral postmenopausal hormone use was 22.4% (95% confidence interval [CI] 19.0–25.8) overall, 13.3% (95% CI 11.0–15.5) for estrogen only, and 8.3% (95% CI 6.2–10.4) for estrogen plus progestin. A sharp decline in use of all formulations occurred in 2003–2004, when the overall prevalence decreased to 11.9% (95% CI 9.6–14.2). This decline was initially limited to non-Hispanic whites; use among non-Hispanic blacks and Hispanics did not decline substantially until 2005–2006. Hormone use continued to decline through 2009–2010 across all patient demographic groups, with the current prevalence now at 4.7% (95% CI 3.3–6.1) overall, 2.7% (95% CI 1.9–3.4) for estrogen only, and 1.7% (95% CI 0.7–2.7) for estrogen plus progestin. Patient characteristics currently associated with hormone use include history of hysterectomy, non-Hispanic white race or ethnicity, and income. CONCLUSION: Postmenopausal hormone use in the United States has declined in a sustained fashion to low levels across a wide variety of patient subgroups. LEVEL OF EVIDENCE: II

Collaborative Modeling of the Benefits and Harms Associated With Different U.S. Breast Cancer Screening Strategies.

Context Multiple alternative mammography screening strategies exist. Contribution This modeling study estimated outcomes of 8 strategies that differed by starting age and interval. Biennial screening from age 50 to 74 years avoided a median of 7 breast cancer deaths; in contrast, annual screening from age 40 to 74 years avoided an additional 3 deaths but yielded 1988 more false-positive results and 11 more overdiagnoses per 1000 women screened. Annual screening from age 40 years for high-risk women had similar outcomes as screening average-risk women biennially from 50 to 74 years of age. Caution Imaging technologies other than mammography and nonadherence were not modeled. Implication Biennial mammography screening for breast cancer is efficient for average-risk women. Despite decades of mammography screening for early detection of breast cancer, there is no consensus on optimal strategies, target populations, or the magnitude of harms and benefits (111). The 2009 US Preventive Services Task Force (USPSTF) recommended biennial film mammography from age 50 to 74 years and suggested shared decision making about screening for women in their 40s (12). Since that recommendation was formulated, new data on the benefits of screening have emerged (2, 6, 8, 9, 11, 13, 14), digital mammography has essentially replaced plain film (15), and increasingly effective systemic treatment regimens for breast cancer have become standard (16). There has also been growing interest in consumer preferences and personalized screening approaches (1720). These factors could each affect the outcomes of breast cancer screening programs or alter policy decisions about population screening strategies (17). Modeling can inform screening policy decisions because it uses the best available evidence to evaluate a wide range of strategies while holding selected conditions (such as treatment effects) constant, facilitating strategy comparisons (21, 22). Modeling also provides a quantitative summary of outcomes in different groups and assesses how preferences affect results. Collaboration of several models provides a range of plausible effects and illustrates the effects of differences in model assumptions on results (1, 7, 23). We used 6 well-established simulation models to synthesize current data and examine the outcomes of digital mammography screening at various starting ages and intervals among average-risk women. We also examined how breast density, risk, or comorbidity levels affect results and whether preferences for health states related to screening and its downstream consequences affected conclusions. Methods Strategies We evaluated 8 strategies that varied by starting age (40, 45, or 50 years) and interval (annual, biennial, and hybrid [annual for women in their 40s and biennial thereafter]); all strategies stop screening at age 74 years. We included no screening as a baseline. Model Descriptions The models used to evaluate the screening strategies were developed within the Cancer Intervention and Surveillance Modeling Network (CISNET) (2430), and the research was institutional review boardapproved. They were named model D (Dana-Farber Cancer Institute, Boston, Massachusetts), model E (Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands), model GE (Georgetown University Medical Center, Washington, DC, and Albert Einstein College of Medicine, Bronx, New York), model M (MD Anderson Cancer Center, Houston, Texas), model S (Stanford University, Stanford, California), and model W (University of Wisconsin, Madison, Wisconsin, and Harvard Medical School, Boston, Massachusetts). The Appendix provides information on model validation. Since earlier analyses (1), the models have undergone substantial revision to reflect advances in breast cancer control, including portrayal of molecular subtypes based on estrogen receptor (ER) and human epidermal growth factor-2 receptor (HER2) status (23); current population incidence (31) and competing nonbreast cancer mortality; digital screening; and the most current therapies (32). All models except model S include ductal carcinoma in situ (DCIS). The general modeling approach is summarized in this article; full details, including approach, construction, data sources, assumptions, and implementation, are available at https://resources.cisnet.cancer.gov/registry and reference 33. Additional information is available on request, and the models are available for use via collaboration. The models begin with estimates of breast cancer incidence (31) and ER/HER2-specific survival trends without screening or adjuvant treatment, and then overlay data on screening and molecular subtypespecific adjuvant treatment to generate observed incidence and breast cancerspecific mortality trends in the U.S. population (1, 7, 17, 23, 33, 34). Breast cancer has a distribution of preclinical screen-detectable periods (sojourn time) and clinical detection points. Performance characteristics of digital mammography depend on age, first versus subsequent screen, time since last mammogram, and breast density. ER/HER2 status is assigned at diagnosis on the basis of stage and age. Molecular subtype and stage-specific treatment reduces the hazard of breast cancer death (models D, GE, M, and S) or results in a cure for some cases (models E and W). Women can die of breast cancer or other causes. Screen detection of cancer during the preclinical screen-detectable period can result in the identification and treatment of earlier-stage or smaller tumors than might occur via clinical detection, with a corresponding reduction in breast cancer mortality. We used a cohort of women born in 1970 with average-risk and average breast density and followed them from age 25 years (because breast cancer is rare before this age [0.08% of cases]) until death or age 100 years. Model Input Parameters The models used a common set of age-specific variables for breast cancer incidence, performance of digital mammography, treatment effects, and average and comorbidity-specific nonbreast cancer causes of death (20, 35). The parameter values are available at www.uspreventiveservicestaskforce.org/Page/Document/modeling-report-collaborative-modeling-of-us-breast-cancer-1/breast-cancer-screening1 (33). In addition, each group included model-specific inputs (or intermediate outputs) to represent preclinical detectable times, lead time, and age- and ER/HER2-specific stage distribution in screen- versus nonscreen-detected women on the basis of their specific model structure (1, 7, 2330). These model-specific parameters were based on assumptions about combinations of values that reproduced U.S. trends in incidence and breast cancerspecific mortality, including proportions of DCIS that were nonprogressive and would not be detected without screening. Models M and W also assumed some small nonprogressive invasive cancers. The models adopted an ageperiodcohort modeling approach to project incidence rates of breast cancer in the absence of screening (31, 36); model M used 19751979 rates from the Surveillance, Epidemiology, and End Results program. The models assumed 100% adherence to screening and receipt of the most effective treatment to isolate the effect of varying screening strategies. Four models used age-specific sensitivity values for digital mammography that were observed in the Breast Cancer Surveillance Consortium (BCSC) for detection of invasive and DCIS cancers combined (model S uses data for invasive cancers only). Separate values were used for initial and subsequent mammography by screening interval, using standard BCSC definitions: Annual includes data from screens occurring within 9 to 18 months of the prior screen, and biennial includes data on screens within 19 to 30 months (37, 38). Model D used these data as input variables (28), and models GE, S, and W used the data for calibration (24, 25, 27). Models E and M fit estimates from the BCSC and other data (26, 29). Women with ER-positive tumors received 5 years of hormone therapy and an anthracycline-based regimen accompanied by a taxane. Women with ER-negative invasive tumors received anthracycline-based regimens with a taxane. Those with HER2-positive tumors also received trastuzumab. Women with ER-positive DCIS received hormonal therapy (16). Treatment effectiveness was based on clinical trials and was modeled as a reduction in breast cancerspecific mortality risk or increase in the proportion cured compared with ER/HER2-specific survival in the absence of adjuvant treatment (32). Benefits Screening benefits (vs. no screening or incremental to other strategies) included percentage of reduction in breast cancer mortality, breast cancer deaths averted, and life-years and quality-adjusted life-years (QALYs) gained because of averted or delayed breast cancer death. Benefits (and harms) were accumulated from age 40 to 100 years to capture the lifetime effect of screening. We considered preferences, or utilities, to account for morbidity from screening and treatment. A disutility for age- and sex-specific general population health was first applied to quality-adjust the life-years (39). These were further adjusted to account for additional decrements in life-years related to undergoing screening (0.006 for 1 week, or 1 hour), evaluating a positive screen (0.105 for 5 weeks, or 3.7 days), undergoing initial treatment by stage (for the first 2 years after diagnosis), and having distant disease (for the last year of life for all women who die of breast cancer) (Appendix Table 1) (33, 40, 41). Appendix Table 1. Utility Input Parameter Values Use and Harms Use of services focused on the number of mammograms required for the screening strategy. Harms included false-positive mammograms, benign biopsies, and overdiagnosis. Rates of false-positive mammograms were calculated as mammograms read as abnormal or needing further work-up in women without cancer divided by the total number of screening

Benefits, harms, and cost-effectiveness of supplemental ultrasonography screening for women with dense breasts

Background At least nineteen states have laws that require telling women with dense breasts and a negative screening mammogram to consider supplemental screening. The most readily available supplemental screening modality is ultrasound, yet little is known about its effectiveness.

Identifying Women With Dense Breasts at High Risk for Interval Cancer: A Cohort Study

BACKGROUND Twenty-one states have laws requiring that women be notified if they have dense breasts and that they be advised to discuss supplemental imaging with their provider. OBJECTIVE To better direct discussions of supplemental imaging by determining which combinations of breast cancer risk and Breast Imaging Reporting and Data System (BI-RADS) breast density categories are associated with high interval cancer rates. DESIGN Prospective cohort. SETTING Breast Cancer Surveillance Consortium (BCSC) breast imaging facilities. PATIENTS 365,426 women aged 40 to 74 years who had 831,455 digital screening mammography examinations. MEASUREMENTS BI-RADS breast density, BCSC 5-year breast cancer risk, and interval cancer rate (invasive cancer ≤12 months after a normal mammography result) per 1000 mammography examinations. High interval cancer rate was defined as more than 1 case per 1000 examinations. RESULTS High interval cancer rates were observed for women with 5-year risk of 1.67% or greater and extremely dense breasts or 5-year risk of 2.50% or greater and heterogeneously dense breasts (24% of all women with dense breasts). The interval rate of advanced-stage disease was highest (>0.4 case per 1000 examinations) among women with 5-year risk of 2.50% or greater and heterogeneously or extremely dense breasts (21% of all women with dense breasts). Five-year risk was low to average (0% to 1.66%) for 51.0% of women with heterogeneously dense breasts and 52.5% with extremely dense breasts, with interval cancer rates of 0.58 to 0.63 and 0.72 to 0.89 case per 1000 examinations, respectively. LIMITATION The benefit of supplemental imaging was not assessed. CONCLUSION Breast density should not be the sole criterion for deciding whether supplemental imaging is justified because not all women with dense breasts have high interval cancer rates. BCSC 5-year risk combined with BI-RADS breast density can identify women at high risk for interval cancer to inform patient-provider discussions about alternative screening strategies. PRIMARY FUNDING SOURCE National Cancer Institute.

Barriers and Facilitators to Implementing Cancer Survivorship Care Plans

PURPOSE/OBJECTIVES To evaluate the process of survivorship care plan (SCP) completion and to survey oncology staff and primary care physicians (PCPs) regarding challenges of implementing SCPs. DESIGN Descriptive pilot study. SETTING Two facilities in Vermont, an urban academic medical center and a rural community academic cancer center. SAMPLE 17 oncology clinical staff created SCPs, 39 PCPs completed surveys, and 58 patients (breast or colorectal cancer) participated in a telephone survey. METHODS Using Journey Forward tools, SCPs were created and presented to patients. PCPs received the SCP with a survey assessing its usefulness and barriers to delivery. Oncology staff were interviewed to assess perceived challenges and benefits of SCPs. Qualitative and quantitative data were used to identify challenges to the development and implementation process as well as patient perceptions of the SCP visit. MAIN RESEARCH VARIABLES SCP, healthcare provider perception of barriers to completion and implementation, and patient perception of SCP visit. FINDINGS Oncology staff cited the time required to obtain information for SCPs as a challenge. Completing SCPs 3-6 months after treatment ended was optimal. All participants felt advanced practice professionals should complete and review SCPs with patients. The most common challenge for PCPs to implement SCP recommendations was insufficient knowledge of cancer survivor issues. Most patients found the care plan visit very useful, particularly within six months of diagnosis. CONCLUSIONS Creation time may be a barrier to widespread SCP implementation. Cancer survivors find SCPs useful, but PCPs feel insufficient knowledge of cancer survivor issues is a barrier to providing best follow-up care. Incorporating SCPs in electronic medical records may facilitate patient identification, appropriate staff scheduling, and timely SCP creation. IMPLICATIONS FOR NURSING Oncology nurse practitioners are well positioned to create and deliver SCPs, transitioning patients from oncology care to a PCP in a shared-care model of optimal wellness. Institution support for the time needed for SCP creation and review is imperative for sustaining this initiative. KNOWLEDGE TRANSLATION Accessing complete medical records is an obstacle for completing SCPs. A 3-6 month window to develop and deliver SCPs may be ideal. PCPs perceive insufficient knowledge of cancer survivor issues as a barrier to providing appropriate follow-up care.

Comparative effectiveness of combined digital mammography and tomosynthesis screening for women with dense breasts

PURPOSE To evaluate the effectiveness of combined biennial digital mammography and tomosynthesis screening, compared with biennial digital mammography screening alone, among women with dense breasts. MATERIALS AND METHODS An established, discrete-event breast cancer simulation model was used to estimate the comparative clinical effectiveness and cost-effectiveness of biennial screening with both digital mammography and tomosynthesis versus digital mammography alone among U.S. women aged 50-74 years with dense breasts from a federal payer perspective and a lifetime horizon. Input values were estimated for test performance, costs, and health state utilities from the National Cancer Institute Breast Cancer Surveillance Consortium, Medicare reimbursement rates, and medical literature. Sensitivity analyses were performed to determine the implications of varying key model parameters, including combined screening sensitivity and specificity, transient utility decrement of diagnostic work-up, and additional cost of tomosynthesis. RESULTS For the base-case analysis, the incremental cost per quality-adjusted life year gained by adding tomosynthesis to digital mammography screening was

Breast cancer screening in an era of personalized regimens: A conceptual model and National Cancer Institute initiative for risk-based and preference-based approaches at a population level

53 893. An additional 0.5 deaths were averted and 405 false-positive findings avoided per 1000 women after 12 rounds of screening. Combined screening remained cost-effective (less than

National Performance Benchmarks for Modern Screening Digital Mammography: Update from the Breast Cancer Surveillance Consortium

100 000 per quality-adjusted life year gained) over a wide range of incremental improvements in test performance. Overall, cost-effectiveness was most sensitive to the additional cost of tomosynthesis. CONCLUSION Biennial combined digital mammography and tomosynthesis screening for U.S. women aged 50-74 years with dense breasts is likely to be cost-effective if priced appropriately (up to

Screening Ultrasound as an Adjunct to Mammography in Women with Mammographically Dense Breasts

226 for combined examinations vs

Physical Activity, White Blood Cell Count, and Lung Cancer Risk in a Prospective Cohort Study

139 for digital mammography alone) and if reported interpretive performance metrics of improved specificity with tomosynthesis are met in routine practice.