Transdisciplinary Research in Energetics and Cancer early career investigator training program: first year results.

Energy imbalance increases cancer burden by increasing cancer risk and mortality. Training early career investigators on conducting impactful energy balance and cancer research is needed. We developed a Transdisciplinary Research in Energetics and Cancer (TREC) Training Program for early career investigators. This analysis examined program satisfaction, knowledge gained, publications, and awards among Year 1 participants (i.e., fellows). The program consists of an in-person course, followed by 1 year of mentorship. Faculty and fellows completed precourse and postcourse surveys. Following the mentorship period, we surveyed fellows for TREC-related research productivity, including publications and grant funding attributed to the program. Twenty fellows were accepted into the program: 3 basic, 7 clinical, and 10 population scientists. Sixteen fellows were junior faculty and four were postdoctoral fellows. The course included ~50 lectures, small group sessions, and faculty-fellow sessions. 96.7% of attendees rated the course in the highest categories of "good/very good." Knowledge significantly improved in 37 of 39 research competencies (94.8%). In the 18 months following the course, fellows published 25 manuscripts, with 3 published in journals with impact factor ≥10. Nineteen grants were funded to TREC fellows (i.e., 7 National Institutes of Health awards, 2 American Cancer Society [ACS] awards, and 10 foundation/pilot awards), and 7 fellows received career promotions. The program's impact will be defined by the degree to which TREC fellows produce discoveries that could improve the health of populations at risk for and/or surviving cancer. Upon the conclusion of our fifth year in 2021, we will publicly disseminate the program material.

Total Sitting Time and Sitting Pattern in Postmenopausal Women Differ by Hispanic Ethnicity and are Associated With Cardiometabolic Risk Biomarkers.

Background Sedentary behavior is pervasive, especially in older adults, and is associated with cardiometabolic disease and mortality. Relationships between cardiometabolic biomarkers and sitting time are unexplored in older women, as are possible ethnic differences. Methods and Results Ethnic differences in sitting behavior and associations with cardiometabolic risk were explored in overweight/obese postmenopausal women (n=518; mean±SD age 63±6 years; mean body mass index 31.4±4.8 kg/m2). Accelerometer data were processed using validated machine-learned algorithms to measure total daily sitting time and mean sitting bout duration (an indicator of sitting behavior pattern). Multivariable linear regression was used to compare sitting among Hispanic women (n=102) and non-Hispanic women (n=416) and tested associations with cardiometabolic risk biomarkers. Hispanic women sat, on average, 50.3 minutes less/day than non-Hispanic women (P<0.001) and had shorter (3.6 minutes less, P=0.02) mean sitting bout duration. Among all women, longer total sitting time was deleteriously associated with fasting insulin and triglyceride concentrations, insulin resistance, body mass index and waist circumference; longer mean sitting bout duration was deleteriously associated with fasting glucose and insulin concentrations, insulin resistance, body mass index and waist circumference. Exploratory interaction analysis showed that the association between mean sitting bout duration and fasting glucose concentration was significantly stronger among Hispanic women than non-Hispanic women (P-interaction=0.03). Conclusions Ethnic differences in 2 objectively measured parameters of sitting behavior, as well as detrimental associations between parameters and cardiometabolic biomarkers were observed in overweight/obese older women. The detrimental association between mean sitting bout duration and fasting glucose may be greater in Hispanic women than in non-Hispanic women. Corroboration in larger studies is warranted.

Using Isotemporal Analyses to Examine the Relationships Between Daytime Activities and Cancer Recurrence Biomarkers in Breast Cancer Survivors.

BACKGROUND: For breast cancer survivors, moderate to vigorous physical activity (MVPA) is associated with improved survival. Less is known about the interrelationships of daytime activities (sedentary behavior [SB], light-intensity physical activity, and MVPA) and associations with survivors' health outcomes. This study will use isotemporal substitution to explore reallocations of time spent in daytime activities and associations with cancer recurrence biomarkers. METHODS: Breast cancer survivors (N = 333; mean age 63 y) wore accelerometers and provided fasting blood samples. Linear regression models estimated the associations between daytime activities and cancer recurrence biomarkers. Isotemporal substitution models estimated cross-sectional associations with biomarkers when time was reallocated from of one activity to another. Models were adjusted for wear time, demographics, lifestyle factors, and medical conditions. RESULTS: MVPA was significantly associated with lower insulin, C-reactive protein, homeostatic model assessment of insulin resistance, and glucose, and higher sex hormone-binding globulin (all P < .05). Light-intensity physical activity and SB were associated with insulin and homeostatic model assessment of insulin resistance (both P < .05). Reallocating 18 minutes of SB to MVPA resulted in significant beneficial associations with insulin (-9.3%), homeostatic model assessment of insulin resistance (-10.8%), glucose (-1.7%), and sex hormone-binding globulin (7.7%). There were no significant associations when 79 minutes of SB were shifted to light-intensity physical activity. CONCLUSIONS: Results illuminate the possible benefits for breast cancer survivors of replacing time spent in SB with MVPA.

Continuous, objective measurement of physical activity during chemotherapy for breast cancer: the Activity in Treatment pilot study.

Despite many potential benefits of physical activity during and after breast cancer treatment, activity levels typically decline from pre- to posttreatment. Most previous research has relied on self-reported activity. The purpose of this study were to assess patterns of daily, to objectively measured physical activity throughout chemotherapy for breast cancer, and to identify predictors of physical activity patterns. Participants were given a Fitbit before starting chemotherapy and asked to wear it throughout chemotherapy. Restricted cubic splines assessed nonlinear patterns of Fitbit measured total physical activity (TPA) and moderate-to-vigorous physical activity (MVPA) throughout the duration of chemotherapy (mean = 17 weeks, standard deviation [SD] = 6.3). Mixed-effects regression models assessed the rate of physical activity decline. Regressions of subject-level random slope assessed predictors of the rate of physical activity decline on participant and cancer characteristics and self-reported physical and cognitive functioning. Participants (n = 32) were on average 50 years old; the majority had stage II breast cancer. MVPA declined linearly at a mean rate of 1.4 min/day (p = .002) for every 10% of chemotherapy completed, whereas TPA declined linearly at an average rate of 13.4 min/day (p = .0007) for every 10% of chemotherapy completed, until around halfway through chemotherapy, when activity rates leveled off. HER+ receptor status was associated with a greater rate of MVPA decline, ß = 13.3, p = .04. This novel study of objectively measured daily MVPA throughout chemotherapy showed that most reductions in activity occurred during the first half of a course of chemotherapy. Targeting this early period of chemotherapy may be important for preventing declines in activity levels throughout chemotherapy.

Mediators of a Physical Activity Intervention on Cognition in Breast Cancer Survivors: Evidence From a Randomized Controlled Trial.

BACKGROUND: Emerging research suggests that increasing physical activity can help improve cognition among breast cancer survivors. However, little is known about the mechanism through which physical activity impacts cancer survivors' cognition. OBJECTIVE: The objective of this secondary analysis examined physical and psychological function potentially linking physical activity with changes in cognition among breast cancer survivors in a randomized controlled trial where the exercise arm had greater improvements in cognition than the control arm. METHODS: A total of 87 sedentary breast cancer survivors were randomized to a 12-week physical activity intervention (n=43) or control condition (n=44). Objectively measured processing speed (National Institutes of Health Toolbox Oral Symbol Digit), self-reported cognition (patient-reported outcomes measurement information system [PROMIS] cognitive abilities), PROMIS measures of physical and psychological function (depression, anxiety, fatigue, and physical functioning), and plasma biomarkers (brain-derived neurotrophic factor, homeostatic model assessment 2 of insulin resistance, and C-reactive protein [CRP]) were collected at baseline and 12 weeks. Linear mixed-effects models tested intervention effects on changes in physical and psychological function variables and biomarkers. Bootstrapping was used to assess mediation. Exploratory analyses examined self-reported cognitive abilities and processing speed as mediators of the intervention effect on physical functioning. RESULTS: Participants in the exercise arm had significantly greater improvements in physical functioning (beta=1.23; 95% CI 2.42 to 0.03; P=.049) and reductions in anxiety (beta=-1.50; 95% CI -0.07 to -2.94; P=.04) than those in the control arm. Anxiety significantly mediated the intervention effect on cognitive abilities (bootstrap 95% CI -1.96 to -0.06), whereas physical functioning did not (bootstrap 95% CI -1.12 to 0.10). Neither anxiety (bootstrap 95% CI -1.18 to 0.74) nor physical functioning (bootstrap 95% CI -2.34 to 0.15) mediated the intervention effect on processing speed. Of the biomarkers, only CRP had greater changes in the exercise arm than the control arm (beta=.253; 95% CI -0.04 to 0.57; P=.09), but CRP was not associated with cognition; therefore, none of the biomarker measures mediated the intervention effect on cognition. Neither cognitive abilities (bootstrap 95% CI -0.06 to 0.68) nor processing speed (bootstrap 95% CI -0.15 to 0.63) mediated the intervention effect on physical function. CONCLUSIONS: Physical activity interventions may improve self-reported cognition by decreasing anxiety. If supported by larger studies, reducing anxiety may be an important target for improving self-reported cognition among cancer survivors. TRIAL REGISTRATION: ClinicalTrials.gov NCT02332876; https://clinicaltrials.gov/ct2/show/NCT02332876.

Physical Activity Change in an RCT: Comparison of Measurement Methods.

Objectives: We aimed to quantify the agreement between self-report, standard cut-point accelerometer, and machine learning accelerometer estimates of physical activity (PA), and exam- ine how agreement changes over time among older adults in an intervention setting. Methods: Data were from a randomized weight loss trial that encouraged increased PA among 333 postmenopausal breast cancer survivors. PA was estimated using accelerometry and a validated questionnaire at baseline and 6-months. Accelerometer data were processed using standard cut-points and a validated machine learning algorithm. Agreement of PA at each time-point and change was assessed using mixed effects regression models and concordance correlation. Results: At baseline, self-report and machine learning provided similar PA estimates (mean dif- ference = 11.5 min/day) unlike self-report and standard cut-points (mean difference = 36.3 min/ day). Cut-point and machine learning methods assessed PA change over time more similarly than other comparisons. Specifically, the mean difference of PA change for the cut-point versus machine learning methods was 5.1 min/day for intervention group and 2.9 in controls, whereas it was ≥ 24.7 min/day for other comparisons. Conclusions: Intervention researchers are facing the issue of self-report measures introducing bias and accelerometer cut-points being insensi- tive. Machine learning approaches may bridge this gap.

The effects of weight loss and metformin on cognition among breast cancer survivors: Evidence from the Reach for Health study.

OBJECTIVE: Breast cancer survivors experience problems with cognition that interfere with daily life and can last for years. In the general population, obesity and diabetes are risk factors for cognitive decline, and weight loss can improve cognition; however, the impact of intentional weight loss on cancer survivors' cognition has not been tested. We investigated the impact of weight loss and metformin on changes in cognitive function in a sample of breast cancer survivors. METHODS: Overweight/obese postmenopausal breast cancer survivors (n = 333) were randomized to a weight loss intervention versus control and metformin versus placebo in a 2 × 2 factorial design. Outcomes were changes in five cognitive domains from baseline to 6 months measured by objective neurocognitive tests. RESULTS: There were no statistically significant intervention effects for the metformin or weight loss interventions in five neurocognitive domains. Baseline body mass index (BMI) was a significant effect modifier of the changes in verbal functioning for the weight loss (P = 0.009) and metformin interventions (P = 0.0125). These effect modifications were independent of percent weight loss achieved during the 6-month study period. CONCLUSIONS: This randomized controlled trial of weight loss and metformin interventions that examined changes to cognition among breast cancer survivors suggests that these interventions may not improve cognitive functioning among breast cancer survivors in general. However, weight loss may improve verbal functioning among individuals with a higher BMI.

Modeling interrelationships between health behaviors in overweight breast cancer survivors: Applying Bayesian networks.

Obesity and its impact on health is a multifaceted phenomenon encompassing many factors, including demographics, environment, lifestyle, and psychosocial functioning. A systems science approach, investigating these many influences, is needed to capture the complexity and multidimensionality of obesity prevention to improve health. Leveraging baseline data from a unique clinical cohort comprising 333 postmenopausal overweight or obese breast cancer survivors participating in a weight-loss trial, we applied Bayesian networks, a machine learning approach, to infer interrelationships between lifestyle factors (e.g., sleep, physical activity), body mass index (BMI), and health outcomes (biomarkers and self-reported quality of life metrics). We used bootstrap resampling to assess network stability and accuracy, and Bayesian information criteria (BIC) to compare networks. Our results identified important behavioral subnetworks. BMI was the primary pathway linking behavioral factors to glucose regulation and inflammatory markers; the BMI-biomarker link was reproduced in 100% of resampled networks. Sleep quality was a hub impacting mental quality of life and physical health with > 95% resampling reproducibility. Omission of the BMI or sleep links significantly degraded the fit of the networks. Our findings suggest potential mechanistic pathways and useful intervention targets for future trials. Using our models, we can make quantitative predictions about health impacts that would result from targeted, weight loss and/or sleep improvement interventions. Importantly, this work highlights the utility of Bayesian networks in health behaviors research.

The Effects of Metformin and Weight Loss on Biomarkers Associated With Breast Cancer Outcomes.

Background: This study investigated the effects of metformin and weight loss on biomarkers associated with breast cancer prognosis. Methods: Overweight/obese postmenopausal breast cancer survivors (n = 333) were randomly assigned to metformin vs placebo and to a weight loss intervention vs control (ie, usual care). The 2 × 2 factorial design allows a single randomized trial to investigate the effect of two factors and interactions between them. Outcomes were changes in fasting insulin, glucose, C-reactive protein (CRP), estradiol, testosterone, and sex-hormone binding globulin (SHBG). The trial was powered for a main effects analysis of metformin vs placebo and weight loss vs control. All tests of statistical significance were two-sided. Results: A total of 313 women (94.0%) completed the six-month trial. High prescription adherence (ie, ≥80% of pills taken) ranged from 65.9% of participants in the metformin group to 81.3% of those in the placebo group (P < .002). Mean percent weight loss was statistically significantly higher in the weight loss group (-5.5%, 95% confidence interval [CI] = -6.3% to -4.8%) compared with the control group (-2.7%, 95% CI = -3.5% to -1.9%). Statistically significant group differences (ie, percent change in metformin group minus placebo group) were -7.9% (95% CI = -15.0% to -0.8%) for insulin, -10.0% (95% CI = -18.5% to -1.5%) for estradiol, -9.5% (95% CI = -15.2% to -3.8%) for testosterone, and 7.5% (95% CI = 2.4% to 12.6%) for SHBG. Statistically significant group differences (ie, percent change in weight loss group minus placebo group) were -12.5% (95% CI = -19.6% to -5.3%) for insulin and 5.3% (95% CI = 0.2% to 10.4%) for SHBG. Conclusions: As adjuvant therapy, weight loss and metformin were found to be a safe combination strategy that modestly lowered estrogen levels and advantageously affected other biomarkers thought to be on the pathway for reducing breast cancer recurrence and mortality.

Statistical approaches to account for missing values in accelerometer data: Applications to modeling physical activity.

Physical inactivity is a recognized risk factor for many chronic diseases. Accelerometers are increasingly used as an objective means to measure daily physical activity. One challenge in using these devices is missing data due to device nonwear. We used a well-characterized cohort of 333 overweight postmenopausal breast cancer survivors to examine missing data patterns of accelerometer outputs over the day. Based on these observed missingness patterns, we created psuedo-simulated datasets with realistic missing data patterns. We developed statistical methods to design imputation and variance weighting algorithms to account for missing data effects when fitting regression models. Bias and precision of each method were evaluated and compared. Our results indicated that not accounting for missing data in the analysis yielded unstable estimates in the regression analysis. Incorporating variance weights and/or subject-level imputation improved precision by >50%, compared to ignoring missing data. We recommend that these simple easy-to-implement statistical tools be used to improve analysis of accelerometer data.

Randomized controlled trial of increasing physical activity on objectively measured and self-reported cognitive functioning among breast cancer survivors: The memory & motion study.

BACKGROUND: Increasing physical activity can improve cognition in healthy and cognitively impaired adults; however, the benefits for cancer survivors are unknown. The current study examined a 12-week physical activity intervention, compared with a control condition, on objective and self-reported cognition among breast cancer survivors. METHODS: Sedentary breast cancer survivors were randomized to an exercise arm (n = 43) or a control arm (n = 44). At baseline and at 12 weeks, objective cognition was measured with the National Institutes of Health Cognitive Toolbox, and self-reported cognition using the Patient-Reported Outcomes Measurement Information System scales. Linear mixed-effects regression models tested intervention effects for changes in cognition scores. RESULTS: On average, participants (n = 87) were aged 57 years (standard deviation, 10.4 years) and were 2.5 years (standard deviation, 1.3 years) post surgery. Scores on the Oral Symbol Digit subscale (a measure of processing speed) evidenced differential improvement in the exercise arm versus the control arm (b = 2.01; P < .05). The between-group differences in improvement on self-reported cognition were not statistically significant but were suggestive of potential group differences. Time since surgery moderated the correlation, and participants who were ≤2 years post surgery had a significantly greater improvement in Oral Symbol Digit score (exercise vs control (b = 4.00; P < .01), but no significant improvement was observed in patients who were >2 years postsurgery (b = -1.19; P = .40). A significant dose response was observed with greater increased physical activity associated with objective and self-reported cognition in the exercise arm. CONCLUSIONS: The exercise intervention significantly improved processing speed, but only among those who had been diagnosed with breast cancer within the past 2 years. Slowed processing speed can have substantial implications for independent functioning, supporting the potential importance of early implementation of an exercise intervention among patients with breast cancer. Cancer 2018;124:192-202. © 2017 American Cancer Society.

Sedentary Behaviors and Biomarkers Among Breast Cancer Survivors.

BACKGROUND: Sedentary behavior is associated with increased risk of poor outcomes in breast cancer survivors, but underlying mechanisms are not well understood. This pilot study explored associations between different aspects of sedentary behaviors (sitting, prolonged sitting, sit-to-stand transitions, and standing) and breast cancer risk-related biomarkers in breast cancer survivors (n = 30). METHODS: Sedentary behavior variables were objectively measured with thigh-worn activPALs. Breast cancer risk-related biomarkers assessed were C-reactive protein (CRP), insulin, and homeostatic model assessment of insulin resistance (HOMA-IR) and were measured in fasting plasma samples. Linear regression models were used to investigate associations between sedentary behavior variables and biomarkers (log CRP, insulin, and HOMA-IR). RESULTS: Sit-to-stand transitions were significantly associated with insulin resistance biomarkers (P < .05). Specifically, each 10 additional sit-to-stand transitions per day was associated with a lower fasting insulin concentration (ß = -5.52; 95% CI, -9.79 to -1.24) and a lower HOMA-IR value (ß = -0.22; 95% CI, -0.42 to -0.03). Sit-to-stand transitions were not significantly associated with CRP concentration (P = .08). Total sitting time, long sitting bouts, and standing time were not significantly associated with CRP, insulin, or HOMA-IR (P > .05). CONCLUSIONS: Sit-to-stand transitions may be an intervention target for reducing insulin resistance in breast cancer survivors, which may have favorable downstream effects on cancer prognosis.

Metabolic Effects of Intermittent Fasting.

The objective of this review is to provide an overview of intermittent fasting regimens, summarize the evidence on the health benefits of intermittent fasting, and discuss physiological mechanisms by which intermittent fasting might lead to improved health outcomes. A MEDLINE search was performed using PubMed and the terms "intermittent fasting," "fasting," "time-restricted feeding," and "food timing." Modified fasting regimens appear to promote weight loss and may improve metabolic health. Several lines of evidence also support the hypothesis that eating patterns that reduce or eliminate nighttime eating and prolong nightly fasting intervals may result in sustained improvements in human health. Intermittent fasting regimens are hypothesized to influence metabolic regulation via effects on (a) circadian biology, (b) the gut microbiome, and (c) modifiable lifestyle behaviors, such as sleep. If proven to be efficacious, these eating regimens offer promising nonpharmacological approaches to improving health at the population level, with multiple public health benefits.

Ankyloglossia in Infancy: An Indian Experience.

OBJECTIVE: To study the prevalence, clinical presentation and management of infants with ankyloglossia. METHODS: A retrospective file review of infants less than 6 months of age with a diagnosis of ankyloglossia. RESULTS: Of the 25786 babies born during the assessment period (2007-2015), 134 (0.52%) had ankyloglossia. Sixty-four (47.7%) infants who presented with breastfeeding difficulties were diagnosed significantly earlier than the asymptomatic group (P<0.05). Of the symptomatic group, 85.9% underwent frenotomy with satisfactory results. Seventy asymptomatic infants were managed conservatively with counselling. CONCLUSION: Frenotomy seems to be a safe and effective procedure in infants with symptomatic ankyloglossia.

Kernel Density Estimation as a Measure of Environmental Exposure Related to Insulin Resistance in Breast Cancer Survivors.

Background: Environmental factors may influence breast cancer; however, most studies have measured environmental exposure in neighborhoods around home residences (static exposure). We hypothesize that tracking environmental exposures over time and space (dynamic exposure) is key to assessing total exposure. This study compares breast cancer survivors' exposure to walkable and recreation-promoting environments using dynamic Global Positioning System (GPS) and static home-based measures of exposure in relation to insulin resistance.Methods: GPS data from 249 breast cancer survivors living in San Diego County were collected for one week along with fasting blood draw. Exposure to recreation spaces and walkability was measured for each woman's home address within an 800 m buffer (static), and using a kernel density weight of GPS tracks (dynamic). Participants' exposure estimates were related to insulin resistance (using the homeostatic model assessment of insulin resistance, HOMA-IR) controlled by age and body mass index (BMI) in linear regression models.Results: The dynamic measurement method resulted in greater variability in built environment exposure values than did the static method. Regression results showed no association between HOMA-IR and home-based, static measures of walkability and recreation area exposure. GPS-based dynamic measures of both walkability and recreation area were significantly associated with lower HOMA-IR (P < 0.05).Conclusions: Dynamic exposure measurements may provide important evidence for community- and individual-level interventions that can address cancer risk inequities arising from environments wherein breast cancer survivors live and engage.Impact: This is the first study to compare associations of dynamic versus static built environment exposure measures with insulin outcomes in breast cancer survivors. Cancer Epidemiol Biomarkers Prev; 26(7); 1078-84. ©2017 AACR.

Objectively measured sedentary behavior and quality of life among survivors of early stage breast cancer.

PURPOSE: This study examined relationships between sedentary behavior accumulated in different bout durations and quality of life (QoL) among breast cancer survivors. METHODS: Postmenopausal breast cancer survivors completed the Short Form Health Survey to assess QoL and wore an accelerometer to measure sedentary behavior and physical activity between August 2011 and May 2013. RESULTS: Participants (n = 134) averaged 509.7 min/day in sedentary time with 285.2 min/day in short bouts (<20 min) and 224.5 min/day long bouts (≥20 min). Linear regression models indicated that greater total sedentary time was significantly associated with worse physical QoL (b = -0.70, p = 0.02) but not mental QoL (p = 0.92). Models that examined the accumulation of sedentary time in short bouts and long bouts together showed that time in long sedentary bouts was significantly related to physical QoL (b = -0.72, p = 0.02), while time in short bouts was not (p = 0.63). Moderate-to-vigorous intensity physical activity (MVPA) was a significant effect modifier of the relation between time spent in long sedentary bouts and physical QoL (p = 0.028) such that greater time in long bouts was associated with worse physical QoL only among women with lower levels of MVPA. CONCLUSIONS: Findings indicate that time spent in long sedentary bouts is associated with worse physical QoL among breast cancer survivors who do not engage in high levels of MVPA. Future research should examine reducing sedentary time as a potential strategy to improve physical QoL.

The Association of the C-Reactive Protein Inflammatory Biomarker with Breast Cancer Incidence and Mortality in the Women's Health Initiative.

Purpose: To examine associations of prediagnosis high-sensitivity C-reactive protein (hsCRP) with breast cancer incidence and postdiagnosis survival and to assess whether associations are modified by body mass index (BMI).Methods: A prospective analysis of the Women's Health Initiative was conducted among 17,841 cancer-free postmenopausal women with baseline hsCRP measurements. Cox proportional hazards models were used to examine associations between hsCRP concentrations and (i) breast cancer risk (n cases = 1,114) and (ii) all-cause mortality after breast cancer diagnosis. HRs are per 1 SD in log hsCRP.Results: hsCRP was not associated with breast cancer risk overall [HR = 1.05; 95% confidence interval (CI), 0.98-1.12]; however, an interaction between BMI and hsCRP was observed (Pinteraction = 0.02). A 1 SD increase in log hsCRP was associated with 17% increased breast cancer risk (HR = 1.17; 95% CI, 1.03-1.33) among lean women (BMI < 25), whereas no association was observed among overweight/obese (BMI ≥ 25) women. Prediagnosis hsCRP was not associated with overall mortality (HR, 1.04; 95% CI, 0.88-1.21) after breast cancer diagnosis; however, an increased mortality risk was apparent among leaner women with higher hsCRP levels (HR, 1.39, 95% CI, 1.03-1.88).Conclusions: Prediagnosis hsCRP levels are not associated with postmenopausal breast cancer incidence or survival overall; however, increased risks are suggested among leaner women. The observed effect modification is in the opposite direction of a previous case-control study finding and warrants further investigation.Impact: Associations of higher CRP levels with incident breast cancer and survival after breast cancer may depend on BMI. Cancer Epidemiol Biomarkers Prev; 26(7); 1100-6. ©2017 AACR.

Sleep duration and breast cancer prognosis: perspectives from the Women's Healthy Eating and Living Study.

PURPOSE: To examine whether baseline sleep duration or changes in sleep duration are associated with breast cancer prognosis among early-stage breast cancer survivors in the multi-center Women's Healthy Eating and Living Study. METHODS: Data were collected from 1995 to 2010. Analysis included 3047 women. Sleep duration was self-reported at baseline and follow-up intervals. Cox proportional hazard models were used to investigate whether baseline sleep duration was associated with breast cancer recurrence, breast cancer-specific mortality, and all-cause mortality. Time-varying models investigated whether changes in sleep duration were associated with breast cancer prognosis. RESULTS: Compared to women who slept 7-8 h/night at baseline, sleeping ≥9 h/night was associated with a 48% increased risk of breast cancer recurrence (Hazard ratio [HR] 1.48, 95% Confidence interval [CI] 1.01, 2.00), a 52% increased risk of breast cancer-specific mortality (HR 1.52, 95% CI 1.09, 2.13), and a 43% greater risk of all-cause mortality (HR 1.43, 95% CI 1.07, 1.92). Time-varying models showed analogous increased risk in those who inconsistently slept ≥9 h/night (all P < 0.05), but not in those who consistently slept ≥9 h/night. CONCLUSIONS: Consistent long or short sleep, which may reflect inter-individual variability in the need for sleep, does not appear to influence prognosis among early-stage breast cancer survivors.

Time-restricted feeding improves insulin resistance and hepatic steatosis in a mouse model of postmenopausal obesity.

BACKGROUND: Menopause is associated with significant hormonal changes that result in increased total body fat and abdominal fat, amplifying the risk for metabolic syndrome and diseases such as diabetes, cardiovascular disease and cancer in postmenopausal women. Intermittent fasting regimens hold significant health benefit promise for obese humans, however, regimens that include extreme daytime calorie restriction or daytime fasting are generally associated with hunger and irritability, hampering long-term compliance and adoption in the clinical setting. Time-restricted feeding (TRF), a regimen allowing eating only during a specific period in the normal circadian feeding cycle, without calorie restriction, may increase compliance and provide a more clinically viable method for reducing the detrimental metabolic consequences associated with obesity. METHODS: We tested TRF as an intervention in a mouse model of postmenopausal obesity. Metabolic parameters were measured using Clinical Laboratory Animal Monitoring System (CLAMS) and we carried out glucose tolerance tests. We also stained liver sections with oil red O to examine steatosis and measured gene expression related to gluconeogenesis. RESULTS: Preexisting metabolic disease was significantly attenuated during 7 weeks of TRF. Despite having access to the same high fat diet (HFD) as ad libitum fed (ALF) mice, TRF mice experienced rapid weight loss followed by a delayed improvement in insulin resistance and a reduced severity of hepatic steatosis by having access to the HFD for only 8h during their normal nocturnal feeding period. The lower respiratory exchange ratio in the TRF group compared with the ALF group early in the dark phase suggested that fat was the predominant fuel source in the TRF group and correlated with gene expression analyses that suggested a switch from gluconeogenesis to ketogenesis. In addition, TRF mice were more physically active than ALF fed mice. CONCLUSIONS: Our data support further analysis of TRF as a clinically viable form of intermittent fasting to improve metabolic health due to obesity.

Technology- and Phone-Based Weight Loss Intervention: Pilot RCT in Women at Elevated Breast Cancer Risk.

INTRODUCTION: For women with an increased breast cancer risk, reducing excess weight and increasing physical activity are believed to be important approaches for reducing their risk. This study tested a weight loss intervention that combined commercially available technology-based self-monitoring tools with individualized phone calls. DESIGN: Women were randomized to a weight loss intervention arm (n=36) or a usual care arm (n=18). SETTING/PARTICIPANTS: Participants were women with a BMI ≥ 27.5 kg/m2 and elevated breast cancer risk recruited from the mammography clinic at the Moores Cancer Center at the University of California San Diego. INTERVENTION: Intervention participants used the MyFitnessPal website and phone app to monitor diet and a Fitbit to monitor physical activity. Participants received 12 standardized coaching calls with trained counselors over 6 months. Usual care participants received the U.S. Dietary Guidelines for Americans at baseline and two brief calls over the 6 months. MAIN OUTCOME MEASURES: Weight and accelerometer-measured physical activity were assessed at baseline and 6 months. Data were collected in San Diego, CA, from 2012 to 2014 and analyzed in 2015. RESULTS: Participants (n=54) had a mean age of 59.5 (SD=5.6) years, BMI of 31.9 (SD=3.5), and a mean Gail Model score of 2.5 (SD=1.4). At 6 months, intervention participants had lost significantly more weight (4.4 kg vs 0.8 kg, p=0.004) and a greater percentage of starting weight (5.3% vs 1.0%, p=0.005) than usual care participants. Across arms, greater increases in moderate-to-vigorous physical activity resulted in greater weight loss (p=0.01). CONCLUSIONS: Combining technology-based self-monitoring tools with phone counseling supported weight loss over 6 months in women at increased risk for breast cancer.