Miglioretti, Diana L

Abstract Small pulmonary nodules are most often managed by surveillance imaging with computed tomography (CT) of the chest, but the optimal frequency and duration of surveillance are unknown. The Watch the Spot Trial is a multicenter, pragmatic, comparative-effectiveness trial with cluster randomization by hospital or health system that compares more- versus less-intensive strategies for active surveillance of small pulmonary nodules. The study plans to enroll approximately 35,200 patients with a small pulmonary nodule that is newly detected on chest CT imaging, either incidentally or by screening. Study protocols for more- and less-intensive surveillance were adapted from published guidelines. The primary outcome is the percentage of cancerous nodules that progress beyond American Joint Committee on Cancer seventh edition stage T1a. Secondary outcomes include patient-reported anxiety and emotional distress, nodule-related health care use, radiation exposure, and adherence with the assigned surveillance protocol. Distinctive aspects of the trial include: 1) the pragmatic integration of study procedures into existing clinical workflow; 2) the use of cluster randomization by hospital or health system; 3) the implementation and evaluation of a system-level intervention for protocol-based care; 4) the use of highly efficient, technology-enabled methods to identify and (passively) enroll participants; 5) reliance on data collected as part of routine clinical care, including data from electronic health records and state cancer registries; 6) linkage with state cancer registries for complete ascertainment of the primary study outcome; and 7) intensive engagement with a diverse group of patient and nonpatient stakeholders in the design and execution of the study.

Abstract Background: Mammographic breast density declines during menopause. We assessed changes in volumetric breast density across the menopausal transition and factors that influence these changes. Methods: Women without a history of breast cancer, who had full field digital mammograms during both pre- and postmenopausal periods, at least 2 years apart, were sampled from four facilities within the San Francisco Mammography Registry from 2007 to 2013. Dense breast volume (DV) was assessed using Volpara on mammograms across the time period. Annualized change in DV from pre- to postmenopause was estimated using linear mixed models adjusted for covariates and per-woman random effects. Multiplicative interactions were evaluated between premenopausal risk factors and time to determine whether these covariates modified the annualized changes. Results: Among the 2,586 eligible women, 1,802 had one premenopausal and one postmenopausal mammogram, 628 had an additional perimenopausal mammogram, and 156 had two perimenopausal mammograms. Women experienced an annualized decrease in DV [−2.2 cm3 (95% confidence interval, −2.7 to −1.7)] over the menopausal transition. Declines were greater among women with a premenopausal DV above the median (54 cm3) versus below (DV, −3.5 cm3 vs. −1.0 cm3; P < 0.0001). Other breast cancer risk factors, including race, body mass index, family history, alcohol, and postmenopausal hormone therapy, had no effect on change in DV over the menopausal transition. Conclusions: High premenopausal DV was a strong predictor of greater reductions in DV across the menopausal transition. Impact: We found that few factors other than premenopausal density influence changes in DV across the menopausal transition, limiting targeted prevention efforts.

Abstract Background: Reductions in breast density with tamoxifen and aromatase inhibitors may be an intermediate marker of treatment response. We compare changes in volumetric breast density among breast cancer cases using tamoxifen or aromatase inhibitors (AI) to untreated women without breast cancer. Methods: Breast cancer cases with a digital mammogram prior to diagnosis and after initiation of tamoxifen (n = 366) or AI (n = 403) and a sample of controls (n = 2170) were identified from the Mayo Clinic Mammography Practice and San Francisco Mammography Registry. Volumetric percent density (VPD) and dense breast volume (DV) were measured using Volpara (Matakina Technology) and Quantra (Hologic) software. Linear regression estimated the effect of treatment on annualized changes in density. Results: Premenopausal women using tamoxifen experienced annualized declines in VPD of 1.17% to 1.70% compared with 0.30% to 0.56% for controls and declines in DV of 7.43 to 15.13 cm3 compared with 0.28 to 0.63 cm3 in controls, for Volpara and Quantra, respectively. The greatest reductions were observed among women with ≥10% baseline density. Postmenopausal AI users had greater declines in VPD than controls (Volpara P = 0.02; Quantra P = 0.03), and reductions were greatest among women with ≥10% baseline density. Declines in VPD among postmenopausal women using tamoxifen were only statistically greater than controls when measured with Quantra. Conclusions: Automated software can detect volumetric breast density changes among women on tamoxifen and AI. Impact: If declines in volumetric density predict breast cancer outcomes, these measures may be used as interim prognostic indicators. Cancer Epidemiol Biomarkers Prev; 26(6); 930–7. ©2017 AACR.

Purpose Women with proliferative breast lesions are candidates for primary prevention, but few risk models incorporate benign findings to assess breast cancer risk. We incorporated benign breast disease (BBD) diagnoses into the Breast Cancer Surveillance Consortium (BCSC) risk model, the only breast cancer risk assessment tool that uses breast density. Methods We developed and validated a competing-risk model using 2000 to 2010 SEER data for breast cancer incidence and 2010 vital statistics to adjust for the competing risk of death. We used Cox proportional hazards regression to estimate the relative hazards for age, race/ethnicity, family history of breast cancer, history of breast biopsy, BBD diagnoses, and breast density in the BCSC. Results We included 1,135,977 women age 35 to 74 years undergoing mammography with no history of breast cancer; 17% of the women had a prior breast biopsy. During a mean follow-up of 6.9 years, 17,908 women were diagnosed with invasive breast cancer. The BCSC BBD model slightly overpredicted risk (expected-to-observed ratio, 1.04; 95% CI, 1.03 to 1.06) and had modest discriminatory accuracy (area under the receiver operator characteristic curve, 0.665). Among women with proliferative findings, adding BBD to the model increased the proportion of women with an estimated 5-year risk of 3% or higher from 9.3% to 27.8% (P < .001). Conclusion The BCSC BBD model accurately estimates women's risk for breast cancer using breast density and BBD diagnoses. Greater numbers of high-risk women eligible for primary prevention after BBD diagnosis are identified using the BCSC BBD model.

Purpose We determined whether the association between breast density and breast cancer risk and cancer severity differs according to menopausal status and postmenopausal hormone therapy (HT) use. Methods We collected data on 587,369 women who underwent 1,349,027 screening mammography examinations; 14,090 women were diagnosed with breast cancer. We calculated 5-year breast cancer risk from a survival model for subgroups of women classified by their Breast Imaging Reporting and Data System (BIRADS) breast density, age, menopausal status, and current HT use, assuming a body mass index of 25 kg/m 2 . Odds of advanced (ie, IIb, III, IV) versus early (ie, I, IIa) stage invasive cancer was calculated according to BIRADS density. Results Breast cancer risk was low among women with low density (BIRADS-1): women age 55 to 59 years, 5-year risk was 0.8% (95% CI, 0.6 to 0.9%) for non-HT users and 0.9% (95% CI, 0.7% to 1.1%) for estrogen and estrogen plus progestin users. Breast cancer risk was high among women with very high density (BIRADS-4), particularly estrogen plus progestin users: women age 55 to 59 years, 5-year risk was 2.4% (95% CI, 2.0% to 2.8%) for non-HT users, 3.0% (95% CI, 2.6% to 3.5%) for estrogen users, and 4.2% (95% CI, 3.7% to 4.6%) for estrogen plus progestin users. Advanced-stage breast cancer risk was increased 1.7-fold for postmenopausal HT users who had very high density (BIRADS-4) compared to those with average density (BIRADS-2). Conclusion Postmenopausal women with high breast density are at increased risk of breast cancer and should be aware of the added risk of taking HT, especially estrogen plus progestin.

AbstractGenetic counseling may turn risk information into cancer prevention behavior by modifying health beliefs and cancer‐related distress. We assessed the effect of genetic counseling on these factors in 101 adult first‐degree‐relatives of colorectal cancer patients from families with known or suspected hereditary nonpolyposis colorectal cancer. Before counseling and once afterward, subjects completed self‐report measures of perceived lifetime risk and cancer‐distress. Most persons overestimated their cancer risk, and higher perceived risk was associated with believing that colorectal cancer cannot be prevented. Individual perceived risk changed after counseling, although mean perceived risk was unchanged. After adjusting for baseline risk, older persons and those with higher estimated objective cancer risk had larger postcounseling decreases. Distress after counseling was positively correlated with baseline distress and anxiety symptoms, and inversely correlated with tolerance for ambiguity. The findings suggest counseling interventions that should increase the likelihood of screening and offer hypotheses for future research.