Pruthi, Sandhya

Abstract Background Breast cancer chemoprevention is underutilized among high-risk women. We examined whether decision support could increase informed decision making. Methods We conducted a cluster randomized controlled trial to evaluate the effect of a patient-facing decision aid (RealRisks) and provider tool (BNAV) compared with standard education on the number of women with high-risk breast lesions making informed choices. Questionnaires were administered at baseline and 6 and 12 months. The primary outcome was chemoprevention informed choice (defined as adequate knowledge and attitudes congruent with decision) at 6 months. Secondary endpoints included breast cancer risk perceptions, worry, chemoprevention knowledge, decision conflict, and chemoprevention decision. Results Across 31 randomized sites, we enrolled 210 providers, who were primarily breast health specialists. Of these, 24 sites (14 intervention, 10 control) enrolled 412 patients. Among 287 patients evaluable for the primary outcome, there were no statistically significant differences in informed choice between the intervention and control arms at 6 months (35% vs 27%, respectively; P = .20) and 12 months (37% vs 25%, respectively; P = .05). At 6 months, women in the intervention compared with control arm were more likely to have accurate breast cancer risk perceptions (31% vs 21%, respectively; P = .03) and adequate chemoprevention knowledge (33% vs 23%, respectively; P = .04). At 12 months, 52% of women in the control and 50% in the intervention arm self-reported initiating chemoprevention. Conclusion Decision support led to modest improvements in accurate risk perceptions and chemoprevention knowledge but not informed choice. Relatively high chemoprevention uptake was achieved among women with high-risk breast lesions managed mainly by breast health specialists. Trial Registration NCT04496739, https://clinicaltrials.gov/study/NCT04496739?cond=NCT04496739&viewType=Card&rank=1

Abstract Background Artificial intelligence (AI)–based, mammography breast cancer risk prediction models show improved discriminatory accuracy relative to clinical risk models. However, data on their calibration are limited. This study compared model performance of 3 clinical breast cancer risk models: Gail, Tyrer–Cuzick v8, and Breast Cancer Surveillance Consortium v3 with the MIRAI AI-risk model. Methods Digital mammograms were ascertained from a screening mammography cohort of 12 308 women within the Mayo Clinic Biobank with 250 incident breast cancers (176 invasive) within 5 years. We predicted 5-year breast cancer risk, estimated discriminatory accuracy (C-index), and calibration (observed-to-expected ratio) of both overall and invasive breast cancer and compared estimates using bootstrapping approaches. Results MIRAI demonstrated similar or improved discriminatory accuracy of overall breast cancer (C-index = 0.71, 95% confidence interval [CI] = 0.68 to 0.74) and invasive breast cancer (C-index = 0.71, 95% CI = 0.67 to 0.75) compared with clinical models (overall breast cancer: C-index = 0.59-0.68; invasive breast cancer: C-index = 0.60-0.68). MIRAI’s calibration for risk of overall breast cancer (observed-to-expected ratio = 0.96, 95% CI = 0.85 to 1.08) was improved compared with Gail (observed-to-expected ratio = 1.22, 95% CI = 1.07 to 1.38) and Breast Cancer Surveillance Consortium (observed-to-expected ratio = 1.38, 95% CI = 1.22 to 1.56) but similar to TC with volumetric percent density and polygenic risk score (observed-to-expected ratio = 0.99, 95% CI = 0.87 to 1.13). However, for low-risk women (approximately 50%), MIRAI overestimated risk of overall breast cancer. MIRAI also overestimated risk of invasive breast cancer across the risk spectrum (observed-to-expected ratio = 0.68, 95% CI = 0.58 to 0.78), whereas clinical models had good calibration (observed-to-expected ratio = 0.86–0.99). Conclusion MIRAI demonstrated stronger discriminatory accuracy than clinical models for 5-year overall and invasive breast cancer risk prediction but overestimated risk for both breast cancer endpoints. AI-based risk models should consider discriminatory accuracy and calibration for invasive cancer before implementation.

Abstract Women at increased risk for breast cancer may benefit from taking risk-reducing medication (RRM) with tamoxifen (tam). Historical uptake of tam in women who qualify has been low. Recent studies have shown low-dose tam to have similar efficacy to standard dosing, with lower risk for adverse events. In this study, we aimed to evaluate uptake, adherence, and tolerability of low-dose tam in women at increased risk for breast cancer and those with ductal carcinoma in situ (DCIS). In this two-site prospective study, women who qualified for breast cancer RRM were offered participation and received consultation with a breast specialist for discussion of RRM rationale, benefits, side effects, and risks. Patients received baseline and 1-year follow-up surveys. A total of 41 patients consented for participation, and 31 completed 1-year follow-up. After initial consultation, 90% (n = 37) reported good/complete understanding of breast cancer risk. Of patients included in 1-year follow-up, 5 had DCIS, 13 had high-risk intraepithelial lesion, and 13 qualified based on Breast Cancer Risk Assessment Tool/International Breast Intervention Study calculation. Furthermore, 74% (n = 23) of patients reported that they took low-dose tam after consultation, with 78.2% (n = 18) of those still taking medication at 1 year. Patients who continued medication had higher estimated breast cancer risk compared with those who discontinued (International Breast Intervention Study 10-year risk, 12.7% vs. 7.6%; P = 0.027). All patients with DCIS initiated low-dose tam, and only one patient with DCIS had discontinued at 1 year. Uptake of low-dose tam after informed discussion is high. Adherence and tolerability at 1-year follow-up improved compared with those with traditional dosing of tam. Prevention Relevance: tam has been used extensively for breast cancer prevention in high-risk women. Historical uptake has been low because of concern for side effects and poor tolerability. Herein, we demonstrate that in the clinical setting, effective patient education and offering of a low-dose option can improve uptake in this high-risk population. See related Spotlight, p. 545

Abstract Refinement of breast cancer risk estimates with a polygenic-risk score (PRS) may improve uptake of risk-reducing endocrine therapy (ET). A previous clinical trial assessed the influence of adding a PRS to traditional risk estimates on ET use. We stratified participants according to PRS-refined breast cancer risk and evaluated ET use and ET-related quality of life (QOL) at 1-year (previously reported) and 2-year follow-ups. Of 151 participants, 58 (38.4%) initiated ET, and 22 (14.6%) discontinued ET by 2 years; 42 (27.8%) and 36 (23.8%) participants were using ET at 1- and 2-year follow-ups, respectively. At the 2-year follow-up, 39% of participants with a lifetime breast cancer risk of 40.1% to 100.0%, 18% with a 20.1% to 40.0% risk, and 16% with a 0.0% to 20.0% risk were taking ET (overall P = 0.01). Moreover, 40% of participants whose breast cancer risk increased by 10% or greater with addition of the PRS to a traditional breast cancer-risk model were taking ET versus 0% whose risk decreased by 10% or greater (P = 0.004). QOL was similar for participants taking or not taking ET at 1- and 2-year follow-ups, although most who discontinued ET did so because of adverse effects. However, these QOL results may have been skewed by the long interval between QOL surveys and lack of baseline QOL data. PRS-informed breast cancer prevention counseling has a lasting, but waning, effect over time. Additional follow-up studies are needed to address the effect of PRS on ET adherence, ET-related QOL, supplemental breast cancer screening, and other risk-reducing behaviors. Prevention Relevance: Risk-reducing medications for breast cancer are considerably underused. Informing women at risk with precise and individualized risk assessment tools may substantially affect the incidence of breast cancer. In our study, a risk assessment tool (IBIS-polygenic-risk score) yielded promising results, with 39% of women at highest risk starting preventive medication.

Few proton magnetic resonance spectroscopy studies have explored chemotherapy-related biochemical changes in brain regions. This observational study aimed to longitudinally assess short-term cognitive changes and brain metabolite concentrations in women undergoing chemotherapy for breast cancer. We analyzed 11 women with newly diagnosed stage 1 to 3 breast cancer. Patients were evaluated via objective cognitive testing, and patient self-report tests. Patients were examined using single voxel proton magnetic resonance spectroscopy in the medial frontal cortex, posterior cingulate gyrus, and left thalamus at baseline and after the completion of chemotherapy on a 1.5 Tesla scanner. At the posttreatment evaluation as compared to baseline, 7 of the 10 (70%) patients reported worsening memory on the MD Anderson symptom inventory (annualized change = 1.82 ± 2.88, P = .08), while the delayed recall raw score of the Rey Osterrieth complex figure test did not change from pre- to post-chemotherapy (mean annualized change = 5.00 ± 14.38, P = .30). The annualized change in the creatine concentration in the posterior cingulate gyrus was statistically significant. The annualized change in the MD Anderson symptom inventory was negatively correlated with the annualized change in the medial frontal N-acetylaspartate (Spearman correlation coefficient [rho] = −0.78, P = .01) and positively correlated with the annualized change in the posterior cingulate gyrus creatine (rho = 0.66, P = .04). Annualized changes in the Rey Osterrieth complex figure test were positively correlated with annualized changes in choline (rho = 0.83, P = .01) in the medial frontal cortex, choline (rho = 0.76, P = .04) in the left thalamus, and creatine (rho = 0.73, P = .02) in the medial frontal cortex. Our data suggest that chemotherapy may lead to the worsening of self-reported memory function, which is associated with alterations in brain metabolites.

Background: Breast cancer diagnosis and treatment affect quality of life and stress and are associated with fatigue. Meditation interventions are effective strategies for patients with breast cancer but are often limited by poor access, high cost, substantial time commitment, and poor adherence. In this feasibility study, we investigated the use of a portable, wearable, electroencephalographic device for guided meditation practices by breast cancer patients during the period from breast cancer diagnosis until 3 months after surgical treatment. Methods: We enrolled women (age = 20-75 years) who had received a recent diagnosis of breast cancer and planned to undergo surgical treatment. Participants were randomly assigned to perform guided meditation with the device (intervention group) or receive CD-based stress-reduction education (control group). Surveys were used to measure stress, quality of life, and fatigue at baseline, within 4 days before surgery, up to 14 days after surgery, and at 3 months after surgery. Results: In the intervention group, 15 of 17 participants (88.2%) completed the study; in the control group, 13 of 13 participants completed the study (100%). Participants in both groups had less fatigue and stress and improved quality of life at 2 weeks and 3 months after surgery compared with baseline, but there were no significant intergroup differences at any time point. Conclusion: The use of this wearable electroencephalographic device for meditation is a feasible strategy for patients with breast cancer.