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Background Sedative-hypnotic medications are used to treat chemotherapy-related nausea, anxiety, and insomnia. However, prolonged sedative-hypnotic use can lead to dependence, misuse, and increased health-care use. We aimed to estimate the rates at which patients who receive adjuvant chemotherapy for breast cancer become new persistent users of sedative-hypnotic medications, specifically benzodiazepines and nonbenzodiazepine sedative-hypnotics (Z-drugs). Methods Using the MarketScan health-care claims database, we identified sedative-hypnotic–naïve patients who received adjuvant chemotherapy for breast cancer. Patients who filled 1 and more prescriptions during chemotherapy and 2 and more prescriptions up to 1 year after chemotherapy were classified as new persistent users. Univariate and multivariable logistic regression analyses were used to estimate odds of new persistent use and associated characteristics. Results We identified 22 039 benzodiazepine-naïve patients and 23 816 Z-drug–naïve patients who received adjuvant chemotherapy from 2008 to 2017. Among benzodiazepine-naïve patients, 6159 (27.9%) filled 1 and more benzodiazepine prescriptions during chemotherapy, and 963 of those (15.6%) went on to become new persistent users. Among Z-drug–naïve patients, 1769 (7.4%) filled 1 and more prescriptions during chemotherapy, and 483 (27.3%) became new persistent users. In both groups, shorter durations of chemotherapy and receipt of opioid prescriptions were associated with new persistent use. Medicaid insurance was associated with new persistent benzodiazepine use (odds ratio = 1.88, 95% confidence interval = 1.43 to 2.47) compared with commercial or Medicare insurance. Conclusions Patients who receive sedative-hypnotic medications during adjuvant chemotherapy for breast cancer are at risk of becoming new persistent users of these medications after chemotherapy. Providers should ensure appropriate sedative-hypnotic use through tapering dosages and encouraging nonpharmacologic strategies when appropriate. [ABSTRACT FROM AUTHOR]

Contrary to clinical guidelines, there has been a decrease over time in estrogen therapy use in premenopausal women undergoing bilateral oophorectomy for benign indications. This study aimed to estimate the excess morbidity and mortality associated with current patterns of estrogen therapy use in women who undergo bilateral oophorectomy with hysterectomy for benign indications. We developed 2 Bayesian sampling Markov state-transition models to estimate the excess disease incidence (incidence model) and mortality (mortality model). The starting cohort for both models were women who had undergone bilateral oophorectomy with hysterectomy for benign indications at the age of 45 to 49 years. The models tracked outcomes in 5-year intervals for 25 years. The incidence model estimated excess incidence of breast cancer, lung cancer, colorectal cancer, coronary heart disease, and stroke, whereas the mortality model estimated excess mortality due to breast cancer, lung cancer, coronary heart disease, and all-other-cause mortality. The models compared current rates of estrogen therapy use with optimal (100%) use and calculated the mean difference in each simulated outcome to determine excess disease incidence and death. By 25 years after bilateral oophorectomy with hysterectomy, there were an estimated 94 (95% confidence interval, −158 to −23) fewer colorectal cancer cases, 658 (95% confidence interval, 339–1025) more coronary heart disease cases, and 881 (95% confidence interval, 402–1483) more stroke cases. By 25 years after bilateral oophorectomy with hysterectomy, there were an estimated 189 (95% confidence interval, 59–387) more breast cancer deaths, 380 (95% confidence interval, 114–792) more coronary heart disease deaths, and 759 (95% confidence interval, 307–1527) more all-other-cause deaths. In sensitivity analyses where we defined estrogen therapy use as a duration of >2 years of use, these differences increased >2-fold. Underuse of estrogen therapy in premenopausal women who undergo oophorectomy is associated with substantial excess morbidity and mortality. [ABSTRACT FROM AUTHOR]

Background: Expert groups and national guidelines recommend individualized decision making about screening mammography for women in their 40s at low-to-average risk of breast cancer. We created Breast Screening Decisions (BSD), a personalized, web-based decision aid, to help women decide when to start and how often to have routine screening mammograms. We evaluated BSD in a large, prospective pilot trial of women and their clinicians.Methods: Women ages 40-49 were invited to use BSD before a scheduled preventive care visit. One month post-visit, users were asked about decisional conflict, knowledge, perceptions and worry about breast cancer and screening. They were also asked whether they had a screening mammogram since their visit, scheduled an appointment for a screening mammogram, or if they were planning to schedule an appointment within the next six months. Women who responded "no" to each of these successive questions were considered to have no plan for a screening mammogram within the next 6 months, unless they explicitly stated that they were unsure about screening mammography. Clinicians were surveyed regarding mammography discussions and perceived patient knowledge and anxiety.Results: Of 1,100 women invited to use BSD, 253 accessed the website, and 168 were eligible to participate in the pilot study. One-fifth had a family history of breast cancer, and at least 76% had any prior mammogram. At follow-up, 88% of BSD users reported discussing mammography at their visit, and 77% said they had a screening mammogram since the visit or that they made or were planning to make a screening mammogram appointment. The average decisional conflict score was 22.5, within the threshold for implementing decisions. Decisional conflict scores were lowest in women who said that they had or planned to have a mammogram (mean 21.4, 95% CI 18.3-24.6), higher in those who did not (mean 24.8, 95% CI 19.2-30.5), and highest in those who were unsure (mean 31.5, 95% CI 13.9-49.1). Most BSD users expressed accurate perceptions of their breast cancer risk and the benefits and limitations of screening.Conclusions: A web-based decision aid may support informed, individualized decisions about screening mammography and facilitate discussions about screening between women in their 40s and their clinicians. [ABSTRACT FROM AUTHOR]

BACKGROUND Rates of screening mammography have plateaued, and the number of mammography facilities has declined in the past decade. The objective of this study was to assess changes over time and geographic disparities in the availability of mammography services. METHODS Using information from the US Food and Drug Administration and the US Census, county-level mammography capacity was defined as the number of mammography machines per 10,000 women aged ≥ 40 years. Cross-sectional variation and longitudinal changes in capacity were examined in relation to county characteristics. RESULTS Between 2000 and 2010, the number of mammography facilities declined 10% from 9434 to 8469, the number of mammography machines declined 10% from 13,100 to 11,762, and the median county mammography capacity decreased nearly 20% from 1.77 to 1.42 machines per 10,000 women aged ≥ 40 years. In cross-sectional analysis, counties with greater percentages of uninsured residents, less educated residents, greater population density, and higher managed care penetration had lower mammography capacity. Conversely, counties with more hospital beds per 100,000 population had higher capacity. High initial mammography capacity, growth in both the percentage of the population aged ≥ 65 years and the percentage living in poverty, and increased managed care penetration were all associated with a decrease in mammography capacity between 2000 and 2010. Only the percentage of rural residents was associated with an increase in capacity. CONCLUSIONS Geographic variation in mammography capacity and declines in capacity over time are associated with demographic, socioeconomic, and health care market characteristics. Maldistribution of mammography resources may explain geographic disparities in breast cancer screening rates. Cancer 2013;119:3847-3853. © 2013 American Cancer Society. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the utilization and cost effectiveness of human epidermal growth receptor 2 (HER2) testing strategies in clinical practice in the U.S. It notes that HER2 testing aims to determine which breast cancer patients overexpress HER2 gene and to prove whether trastuzumab treatment to 20-30% patients is highly effective. It emphasizes on the importance of understanding the use of HER2 testing in cancer care because of its critical role in targeting therapy.

Purpose. Women with localized breast cancer face difficult decisions about adjuvant therapy. Several decision aids are available to help women choose between treatment options. Decision aids are known to affect treatment choices and may therefore affect patient survival. The authors aimed to model the effects of the Adjuvant! decision aid on expected survival in women with early stage breast cancer. Patients and Methods. Data were obtained from a randomized trial of Adjuvant! (n=395). To calculate the effects of the decision aid on survival, the authors used the Adjuvant! survival predictions as a surrogate endpoint. Data from each arm were entered separately into statistical models to estimate change in survival associated with receiving the Adjuvant! decision aid. Results. Most women (∼85%) chose a treatment option that maximized predicted survival. The effects of the decision aid on outcome could not be modeled because a small number of women (n=12, 3%) chose treatment options associated with a large (5%-14%) loss in survival. These women--most typically estrogen receptor positive but refusing hormonal therapy--were equally divided between Adjuvant! and control groups and were not distinguished by medical or demographic factors. Conclusions. Expected benefit from treatment is a key variable in understanding patient behavior. A small number of women refuse adjuvant treatment associated with large increases in predicted survival, even when they are explicitly informed about the degree of benefit they would forgo. Investigation of the effects of decision aids on cancer survival is unlikely to be fruitful due to power considerations. [ABSTRACT FROM AUTHOR]

A reply by Kathryn A. Phillips, Elena B. Elkin and Jennifer S. Hass to a comment by Fitzgibbons et al. about their article on the clinical practice patterns and cost-effectiveness of human epidermal growth receptor-2 (HER-2) testing strategies in patients with breast cancer, is presented.