The Effects of a Remote-Based Weight Loss Program on Adipocytokines, Metabolic

Author Manuscript Published OnlineFirst on February 18, 2020; DOI: 10.1158/1078-0432.CCR-19-2935 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Markers, and Telomere Length in Breast Cancer Survivors: the POWER-Remote Trial

Cesar A. Santa-Maria1, Janelle W. Coughlin2, Dipali Sharma1, Mary Armanios1, Amanda L.

Blackford1, Colleen Schreyer2, Arlene Dalcin3,4, Ashley Carpenter1, Gerald J. Jerome4,5, Deborah

Armstrong1, Madhu Chaudhry6, Gary Cohen6, Roisin M. Connolly1, John Fetting1, Robert

Miller1*, Karen L. Smith1, Claire Snyder1,4, Andrew Wolfe1, Antonio C. Wolff1, Chiung-Yu

Huang1*, Lawrence J. Appel2,4, Vered Stearns1

From the Departments of Oncology1 and Psychiatry2; the Welch Center for Prevention,

Epidemiology, and Clinical Research3; and Division of General Internal Medicine4 at the Johns

Hopkins University School of Medicine; Department of Kinesiology Towson University5; and

Greater Baltimore Medical Center6

*Current Address:

Robert S. Miller, MD, FACP, FASCO

American Society of Clinical Oncology

e-mail: [email protected]

Chiung-Yu Huang, PhD

University of California, San Francisco

e-mail: [email protected]

Andrew Wolfe, PhD

National Institute of Health

e-mails: [email protected]

Downloaded from clincancerres.aacrjournals.org on October 1, 2021. © 2020 American Association for Cancer Research. Author Manuscript Published OnlineFirst on February 18, 2020; DOI: 10.1158/1078-0432.CCR-19-2935 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Acknowledgements: We thank Dr. Robert Donegan and Dr. Ben Park for patient referral,

Brandon Luber for assistance in study design, and David Lim for assistance with data

analysis.

Corresponding Author:

Vered Stearns, M.D.

Professor of Oncology

Co-Director, Breast and Ovarian Cancer Program

Breast Cancer Research Chair in Oncology

The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins

The Skip Viragh Outpatient Cancer Building

Under Armour Breast Health Innovation Center, Room 10291

201 North Broadway

Baltimore, MD 21287

Phone: 443-287-6489

Fax: 410-614-9421 e-mail: [email protected]

Key words: breast cancer, obesity, weight loss intervention, biomarkers, cytokines, telomere length

Running head: POWER-remote for Breast Cancer Survivors

Presented at: SABCS 2016

Funding: Breast Cancer Research Foundation, Cigarette Restitution Fund, National Institutes of Health [P30 CA006973], and Commonwealth Foundation Johns Hopkins Precision Medicine

Initiative (MA).

Conflict of interest: Healthways, Inc. developed the website for the original POWER trial in collaboration with Johns Hopkins investigators (Appel, Coughin, Dalcin, Jerome). On the basis of POWER trial results, Healthways developed and commercialized a weight-loss intervention program called Innergy. This project used the Innergy website to deliver the weight loss intervention. Under an agreement with Healthways, Johns Hopkins faculty (Appel, Coughlin,

Dalcin, Gerome) monitored the Innergy program’s content and process (staffing, training, and counseling) and outcomes (engagement and weight loss) to ensure consistency with the original

POWER Trial. Johns Hopkins received fees for these services and faculty members (Appel,

Coughlin, Dalcin, Gerome) who participated in the consulting services receive a portion of these fees. Johns Hopkins receives royalty on sales of the Innergy program. After completion of this project, Healthways sold the Innergy platform to Sharecare, which ended the relationship with

Hopkins.

CAS (Santa-Maria) received research funding from Tesaro, Medimmune, and Pfizer; ad board for Polyphor, Genomic Health, and Halozyme.

KS received research funding from Pfizer; family member with stock in Abbvie and Abbott

Laboratories.

VS received research funding from Abbvie, Medimmune, Novartis, Pfizer, and PUMA, serves as a member of the data safety monitoring board for Immunomedics, and served as a consultant to

Iridium Therapeutics.

CS (Snyder) receives research funding from Genentech.

All other authors otherwise have no conflict of interest to declare.

Author Contributions: Drs. Stearns and Santa-Maria had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

All authors were responsible for preparation, review and approval of the manuscript.

Study concept and design: Stearns, Appel, Santa-Maria, Coughlin, Blackford.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: All authors.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Blackford, Huang, Sharma, Armanios.

Administrative, technical, or material support: Carpenter, Schreyer.

Study supervision: Stearns, Santa-Maria.

Word count:

Abstract: 249/250

Manuscript: 3887/5000

Tables: 2 (1 supplemental)

Figures: 4 (2 supplemental)

References: 44/50

STATEMENT OF TRANSLATIONAL RELEVANCE

Patients with breast cancer who are obese experience inferior outcomes, biologically related to metabolic and inflammatory pathways, and other molecular changes. While ongoing studies are evaluating the effects of weight loss on recurrence rates, translating weight loss interventions in clinic has been limited. We present here an effective remote-supported weight loss intervention that is potentially scalable and exportable. We demonstrate that weight loss is associated with decreases in leptin and other inflammatory markers, which may have anti-oncogenic effects.

ABSTRACT

Purpose: We initiated a clinical trial to determine the proportion of breast cancer survivors achieving ≥5% weight loss using a remotely-delivered weight loss intervention

(POWER-remote) or a self-directed approach, and to determine the effects of the intervention on biomarkers of cancer risk including metabolism, inflammation, and telomere length.

Experimental Design: Women with stage 0-III breast cancer, who completed local therapy and chemotherapy, with a body mass index ≥25 kg/m2 were randomized to a 12-month intervention (POWER-remote) versus a self-directed approach. The primary objective was to determine the number of women who achieved at least 5% weight loss at six-months. We assessed baseline and six-month change in a panel of adipocytokines (adiponectin, leptin, resistin, HGF, NGF, PAI1, TNFα, MCP1, IL1β, IL6, and IL8), metabolic factors (insulin, glucose, lipids, hs-CRP), and telomere length in peripheral blood mononuclear cells.

Results: From 2013-2015, 96 women were enrolled, and 87 were evaluable for the primary analysis; 45 to POWER-remote and 42 to self-directed. At six-months 51% of women randomized to POWER-remote lost ≥5% of their baseline body weight, compared to 12% in the self-directed arm (OR=7.9, 95% CI 2.6-23.9, p=0.0003); proportion were similar at 12-months

(51% versus 17%, respectively, p=0.003). Weight loss correlated with significant decreases in leptin, and favorable modulation of inflammatory cytokines and lipid profiles. There was no significant change in telomere length at six-months.

Conclusions: A remotely-delivered weight loss intervention resulted in significant weight loss in breast cancer survivors, and favorable effects on several biomarkers.

Trial registration: ClinicalTrials.gov Identifier: NCT01871116

INTRODUCTION

Excess body weight is a major risk factor for many malignancies, including breast cancer

(1,2). Once diagnosed with breast cancer, women who are overweight or obese experience inferior survival outcomes (3,4). Furthermore, most women gain weight following a diagnosis of breast cancer, which is associated with a 1.5 fold increased risk of breast cancer recurrence and death (4,5).

Preliminary studies suggest that weight loss in breast cancer survivors leads to improvements in cancer outcomes; however, data have been inconsistent. In the Women’s

Intervention Nutrition Study (WINS), women with early breast cancer who received a dietary intervention experienced modest weight loss and had reduced risk of breast cancer recurrence

(6). Conversely, in the Women’s Healthy Eating and Living (WHEL) study, a different dietary intervention did not lead to significant weight loss and did not reduce the risk of breast cancer recurrence (7). Results from WINS and WHEL suggest that weight loss may be required to demonstrate a reduction in breast cancer recurrence (8). Furthermore, obesity is associated with quality-of-life factors, including neuropathy, cardiotoxicity, chronic fatigue, and lymphedema

(9). Studies have demonstrated that weight loss in breast cancer survivors is feasible; however, most interventions have not been validated in other cohorts or used in-person counseling, which limit scalability into clinical practice (10-13). There is an urgent need to develop scalable weight loss interventions that can be readily integrated into clinical practice.

The Practice-based Opportunities for Weight Reduction (POWER) study, a randomized controlled comparative effectiveness trial, demonstrated that among a general medicine cohort of obese adults with at least one cardiovascular risk factor, 38% of participants randomized to a remote-support intervention achieved and sustained a ≥5% weight loss over 24 months, with a maximum weight loss observed at six-months (14). In the present study, we adapted the remote-support arm of the POWER study, designated POWER-remote, for breast cancer survivors.

Obesity is associated with specific biological changes in various metabolic and inflammatory factors, as well as factors related to cancer risk. Obesity is also associated with high concentrations of inflammatory cytokines, which drive pro-proliferative pathways (15).

Recent data demonstrate that both breast cancer and energy excess states are associated with shorter telomere length, and a healthy lifestyle may favorably modulate telomerase and telomere length (16-18), but several methodologic concerns have been raised about the measurement tools used in these studies (19,20).

The primary objective of this study was to compare the proportion of breast cancer survivors who could achieve at least 5% weight loss between those randomized to the adapted

POWER-remote program versus a control arm of self-directed weight loss. Translational objectives were to characterize alterations in circulating concentrations of adipocytokines, and a clinically validated measurement of telomere length at six-months.

METHODS

Study design

We designed a randomized clinical trial to assess the effects of POWER-remote versus self-directed weight loss in overweight/obese women who completed local and systemic chemotherapy for early stage breast cancer. Eligible participants had stage 0-III breast cancer and, completed recommended primary breast surgery, radiation, and/or chemotherapy prior to enrolling into the trial. Endocrine therapy was allowed if started at least three months prior to randomization and if expected to continue for the duration of the study. Concurrent anti-human epidermal growth factor receptor 2-neu (HER2) therapy was permitted. Women had to have a body mass index (BMI) ≥25 kg/m2, weigh ≤400 lbs, and be willing to lose at least 5% of their body weight. The study protocol conducted in accordance with the Declaration of Helsinki, was approved by the Institutional Review Board, and enrolled subjects provided signed written informed consent.

Experimental and control arm protocols

POWER-remote arm. The infrastructure of the adapted POWER-remote intervention was similar to that of the original POWER trial; however, educational materials included oncology-relevant information such as lymph edema prevention exercises and general information about breast cancer. In addition, instead of engaging the primary care provider as in the original POWER study, each patient’s treating oncologist was involved and received information regarding the patient’s weight loss. Participants randomized to POWER-remote received a 12-month behavioral weight loss intervention based on the original POWER study including telephone-based behavioral weight loss coaching and use of a web-based self- monitoring and learning platform developed by Healthways Inc (14). Participants could record dietary intake, exercise, and weight on a web-based platform (Innergy™). Dietary recommendations included a reduced calorie, high vegetable and fruit diet based on the Dietary

Approaches to Stop Hypertension (DASH) diet (21). Weight goals and behavioral and self- monitoring recommendations are described in Supplemental Table 1. Coaches trained in both behavioral weight loss principles and motivational interviewing reviewed self-monitoring data through the Innergy™ website and provided behavioral weight loss counseling during telephonic coaching sessions. The website and an accompanying smart phone application allowed participants to track their weight, food and beverage intake and exercise; the website provided access to the weight loss educational materials for review during coaching calls. Additional platform features included a Message Center to communicate with the study health Coach and a Group wall for weight loss support from other participants in the study. Participants were offered in 21 phone calls over the one-year study period (weekly for three months, monthly for an additional nine months). The approximately 20-minutes calls were with a designated Coach and included review of self-monitoring, problem solving and identification of barriers and strategies for overcoming these barriers and goal setting. The theoretical framework for the

active intervention draws upon behavior change theory related to weight loss, specifically social cognitive theory and utilized a Motivational Interviewing approach. The health coach had a background in delivering weight loss interventions (including the original POWER trial) and was trained by experienced Co-Investigators.

Self-directed arm. This arm served as the comparison group. It reflected standard medical care, where oncologists encourage participants to achieve and maintain ideal BMI (9).

The same Coach as in the POWER-remote arm delivered the one-time coaching session to self-directed participants. The content of this call included the importance of gradual weight loss, promoted lifestyle change related to diet and exercise, and encouraged self -monitoring.

Participants in this arm were provided the National Heart, Lung, and Blood Institute (NHLBI) publication “Aim for A Healthy Weight,” and met with a weight-loss coach one time during the baseline visit (22).

Collection of anthropomorphic measurements.

Weight and height were collected at baseline, six, and 12 months by trained and certified staff using a high-quality, calibrated digital scale. Outcome assessment staff were masked to randomization assignment. Each weight measurement was collected twice; if the difference between the two measurements was more than 0.1 kg, the measurements were repeated until the difference between two measurements was less than 0.1 kg. BMI was calculated as the

Quetelet index (kg/m2).

Waist circumference was measured in centimeters and collected by trained, certified staff using a measuring tape at a horizontal plane one cm above the navel. Measurements were repeated once; if difference between the two measurements was more than 0.5 cm, measurement were repeated until difference between two measurements was less than 0.5 cm.

Collection and analysis of biomarkers

Adipocytokines and inflammatory markers. Serum samples from study participants were collected at baseline and six-months. Samples were examined using HADCYMAG-61K |

MILLIPLEX MAP Human Adipocyte Magnetic Bead Panel - Endocrine Multiplex Assay (EMD

Millipore, Billerica, MA) following manufacturer’s instructions. The analytes included in this multiplex assay were adiponectin, leptin, resistin, HGF, NGF, PAI1, TNFα, MCP1, IL1β, IL6, and

IL8.

Metabolic panel. Fasting levels of insulin, glucose, hs-CRP, total cholesterol, high- density lipoprotein cholesterol (HDL), low density lipoprotein (LDL), and triglycerides were analyzed by standardized enzymatic methodology at Clinical Laboratory Improvement

Amendments (CLIA) certified laboratories. Total cholesterol ratio was calculated by the total cholesterol number divided by HDL.

Telomere length. Telomere length was measured on lymphocytes and granulocytes which were cryopreserved from ficoll-separated blood samples, using a CLIA-approved flow cytometry and fluorescence in situ hybridization (FISH) assay as described previously (23,24).

Cells were preserved in freezing media at the time of isolation and preserved in liquid nitrogen until thawing at the time of analysis. There is high inter-lab concordance for measurement of leukocyte telomere length by flowFISH (23). The data for each subject and timepoint were plotted relative to a validated nomogram derived from (192 controls) from across the age spectrum(23,25). The deviation from the age-adjusted range was calculated as the difference in telomere length from the median value for age (delta telomere length, deltaTL) (23). The effect of the intervention was tested by comparing the deltaTL differences in lymphocytes at six- months versus baseline. The age at the time of draw was used for the median control value.

Statistical approach

Sample size. The original POWER study demonstrated that 53% participants in the remote-support intervention group and 14.2% participants in the self-directed group had at least

a 5% weight loss at six-months, and 38% participants in the intervention group and 19% in the self-directed group maintained this weight loss at 24 months (14). Though our primary endpoint was the proportion of participants achieving at least 5% of weight loss at six-months, given that individuals with breast cancer may undergo treatments that affect weight and because we enrolled persons who were both overweight and obese compared to obese only individuals in the original POWER trial, we powered our study to detect the smaller difference of 38.2% versus 18.8%. We estimated that a sample size of 80 participants was required to yield approximately 88% power to detect a differential weight loss response of 19% in the self- directed arm and 38% in the POWER-remote arm with a one-sided type I error of 10%. Women were randomized 1:1, stratifying by use of hormonal therapy and menopausal status.

Endpoint analysis. Analyses were by intention-to-treat. The proportion of women who achieved at least 5% weight loss at six-months was estimated with an exact 95% CI. The primary analysis would conclude a significant benefit for the POWER-remote versus the self- directed arm if the one-sided Fisher’s exact test p-value was <0.10 for the difference in the proportion of women who lost 5% or more weight at six months. Rejection of the null hypothesis in this phase 2 randomized study would suggest that POWER-remote is an effective intervention in overweight/obese breast cancer survivors, and justify further investigation in future trials. The odds ratio for the association between 5% or more weight loss and study arm was estimated using logistic regression that included the randomization stratification variables as covariates. This analysis was also performed for response as measured at 12-months, to describe differences in weight loss maintenance between arms. Changes in weight at six and 12 months were measured continuously. Differential changes in weight between groups across time points were assessed with a mixed effects regression model, with a random intercept for each patient and terms for time point, treatment group and their interaction. Changes in waist circumference were analyzed similarly. Exploratory analyses were performed to evaluate weight loss in specific subgroups using interaction analysis.

Correlative analysis. We summarized biomarkers at baseline and six-months with descriptive statistics. We calculated within-patient changes in biomarkers from baseline to six- months and compared the differences according to treatment arm with Wilcoxon rank sum tests.

We explored the differences in biomarkers according to weight loss. These analyses separating weight loss from treatment arm were of interest because the likely mechanism to biomarker changes is weight loss rather than the randomized group. The telomere length comparisons were made using the deltaTL values to adjust for age-related changes and the data and the statistics were plotted and calculated using GraphPad Prism. Changes in TL according to exposure to chemotherapy versus no chemotherapy were assessed by the Mann-Whitney test.

Two-sided p values <0.05 were considered statistically significant for all analyses except for the primary analysis, which used a one-sided p<0.10. Due to the exploratory nature of the secondary and correlative analyses, we did not adjust for multiple comparisons in reporting the results of the correlatives. Analyses were completed using R version 3.4.2.

RESULTS

Patient Characteristics

From July 2013 to December 2015, 458 women were assessed for eligibility, and a total of 96 signed a written informed consent and were randomized; 87 participants were eligible for the primary analysis (Figure 1). Of the 362 who were excluded, 305 did not meet eligibility criteria, only 12 declines, and 45 had other reasons. The most common reasons for not meeting eligibility criteria were 1) no correspondence after first contact (n=105), 2) medical exclusion (i.e. second malignancy, excluded medication, uncontrolled comorbidity) (n=59), 3) BMI less than

25kg/m2 (n=35); the most common “other” reasons were 1) travel (n=18), 2) no breast cancer

(n=4), 3) limited access to computer/internet (n=3), and 4) on another trial (n=3). Characteristics were balanced between study arms, 74% of participants were postmenopausal, with an average

BMI of 32 kg/m2, more than half had received chemotherapy (52% POWER-remote, 59% self-

directed), and the majority of women had estrogen receptor-positive disease and were on endocrine therapy (Table 1). At six-months 45 participants (90%) had measured weights in

POWER-remote arm, and 42 (91%) in the self-directed; at 12-months 41 (82%) had measured weights in POWER-remote, and 36 (78%) in the self-directed.

Weight Loss Program Endpoints

Those randomized to the POWER-remote had high participation rates. Median call completion was 14/15 calls in the first six months and 7/7 calls from months seven to 12. There was a median of 24 weekly logins during the first six months and 22.5 weekly logins during months seven to 12.

At six-months, 51% of women in the POWER-remote and 12% in the self-directed arm had lost at least 5% of their baseline body weight (one-sided Fisher’s p<0.0001, adjusted

OR=7.9, 95% CI 2.6-23.9, p=0.0003). Significant differences between groups were observed at

12-months, with 51% of women in the POWER-remote arm exhibiting at least 5% loss of their baseline body weight compared to 17% in the self-directed arm (adjusted OR=5.2, 95% CI 1.8-

14.2, p=0.003). Significant differences between study arms were also noted in the proportion of women losing at least 10% of their baseline body weight at six (22% versus 0, p<0.001) and 12- months (32% versus 5.6%, p=0.004).Patients enrolled in POWER-remote were more likely to achieve weight loss than those in the self-directed arm (Figure 2A). In the POWER-remote group, mean weight loss at six-months was 4.6 kg (SD=4.8 kg), which was sustained at 12- months (mean weight loss 4.7, SD 6.3), compared to mean weight loss of 0.5 kg (SD=3.3) at six-months, and 0.4 kg (SD=4.7) at 12-months in the self-directed arm (Figure 2B). In subgroup analyses, weight loss did not differ by age, race, prior chemotherapy, endocrine therapy, or baseline BMI category (each p-interaction >0.05; Supplemental Figure 1).

At six-months, patients in both study arms had reductions in waist circumference

(POWER-remote arm: -5.4cm [-10.3cm, -0.55cm], Self-Directed: -1.7cm [-3.8cm, 0.37cm]), but

the decreases were not different between groups (interaction p=0.26). By 12-months, however, the change in the POWER-remote arm was -6.6cm [-11.5cm, -1.7cm], which was significantly lower compared to the Self-Directed group (increase by 0.3cm [-2.0cm, 2.1cm], interaction p=0.003; Supplemental Figure 2).

Correlative Endpoints

Adipocytokines and inflammatory markers. Compared to the self-directed arm, we observed reduction in leptin concentrations at six-months in women randomized to the POWER- remote arm. We did not observe a significant effect on resistin, adiponectin, HGF, NGF, IL1β,

IL8, IL6, MCP1, PAI1 and TNFα (Table 2). Leptin concentration in the POWER-remote arm decreased by 918.8 pg/mL (SD 2127) compared to an increase by 395.1 pg/mL (SD 1596) in the self-directed arm (p<0.01). Participants who achieved 5% or greater weight loss, versus not, had a significant decrease in leptin by 1615 pg/mL (SD 2388, p<0.01). Those achieving 5% weight loss, compared to those who did not, had favorable improvements in inflammatory cytokines including lower HGF, IL1β, and hs-CRP, and a smaller increase in MCP1 (Table 2).

Metabolic panel. Those who achieved at least 5% weight loss had lower triglycerides and total cholesterol ratio at six-months (Table 2). When percent weight change was assessed as a continuous variable, percent weight loss was again associated with decreases in leptin and triglyceride concentrations, and, decreases in insulin were also observed (Figure 3).

Differences between study arm and insulin, glucose, and lipid panels were not observed.

Telomere length. A total of 84 participants with available samples underwent telomere length testing by flowFISH (41 self-directed, and 43 POWER-remote, Figure 4A). The following analyses are listed for lymphocytes but similar patterns were seen for granulocyte telomere length. While there was no difference between the two groups in telomere length at baseline, the overall telomere length in this cohort and in each of the groups was slightly but significantly shorter than the historic controls from a validated nomogram based on healthy age-matched

controls (mean deltaTL -0.8 (95%CI -1.1 to -0.5) vs. -0.8kb (-1.0 to -0.5), respectively) (23). This effect was not related to a history of chemotherapy exposure as we detected no difference in telomere length between treated and untreated cases (p=0.21, Mann-Whitney test, Figure 4B).

When we examined differences in telomere length at six-months we found no difference compared to baseline (mean +0.1 vs. +0.1, p=0.7, Mann-Whitney test). These changes are also within the assay variability of the flowFISH telomere length measurement (23). Indeed, there was no change in lymphocyte or granulocyte telomere length detected when we compared those who lost 5% or 10% of baseline body weight versus with those who did not (p=0.67,

Wilcoxon rank sum test), or when assessed continuously by percentage weight loss (p=0.09,

Pearson correlation test) (Table 2, Figure 4C).

DISCUSSION

In this prospective study, we demonstrate that breast cancer survivors randomized to a remotely-supported scalable weight loss intervention can experience clinically significant weight loss known to improve cardiovascular risk factors, irrespective of chemotherapy or use of endocrine therapies (26,27). Participants in this study who were randomized to the POWER- remote arm had near perfect adherence as demonstrated by the high call completion and login rates, and only one patient randomized to POWER-remote who participated was lost to follow up.

POWER-remote is inherent scalability, cost-effective relative to in-person interventions and thus may be implemented in clinical practice (28). This is particularly relevant as more definitive studies that assess the benefits of weight loss are ongoing, in particular the Breast

Cancer Weight Loss (BWEL) study (NCT02750826) (29). Indeed, in a recent interim analysis of the SUCCESS-C trial, patients who completed a two-year lifestyle intervention program had better DFS than non-completers (HR 0.35, 95%CI 0.27 to 0.45, p<0.001), however only 48.2% of patients originally randomized to the lifestyle intervention group completed the entire program

(30). The American Society of Clinical Oncology (ASCO) recommends counselling breast cancer survivors to achieve and maintain an ideal weight, limit consumption of high-calorie foods and beverages, and increase physical activity; however, there is no specific intervention or program to help patients accomplish this goal (31).

Weight loss in patients with breast cancer is feasible, as demonstrated by several studies. The Lifestyle Intervention in Adjuvant Treatment of Early Breast Cancer (LISA) Study, which evaluated a mail-based general health information with or without a telephone-based lifestyle intervention on postmenopausal breast cancer survivors on letrozole found that participants lost a mean 5.3% versus 0.7% of their baseline body weight at 6 months (32). The

Lifestyle, Exercise, And Nutrition (LEAN) Study evaluated an in-person, versus remote, versus usual care intervention, and found an average of 6.4%, 5.4%, and 2.0% weight loss respectively at 6 months (33). The Enhance Recovery and Good Health for You (ENERGY) Trial, which compared a group-based versus a less intensive intervention in breast cancer survivors found that at 12-months mean weight loss favored the group intervention (6.0% versus 1.5%) (34).

Another intervention, which evaluated the addition of metformin to a weight loss intervention found similar percent weight loss at six-months in the weight loss group (5.5% versus 2.7%)

(35). While these mean changes in weight loss are comparable to our study (Figure 2B), the proportion of patients who achieved at least 5% weight loss in these other studies is not reported, a metric that identifies the percentage of the population that may benefit from the intervention. Our intervention included premenopausal women, did not have an in-person component, nor included pharmacotherapy; thus, builds upon existing literature. Furthermore, we demonstrate that by the end of the intervention, there was a significant decrease in waist circumference in those who underwent the POWER-remote intervention. Waist circumference is associated with increase breast cancer risk in both pre-and post-menopausal women, and may be a better marker than BMI in determining risk of metabolic syndrome (36,37).

We consistently observed that weight loss and study arm correlated with decreases in leptin. This is particularly noteworthy as leptin has been demonstrated to increase breast cancer cell proliferation, invasion and migration by activation of pro-survival pathways (38-41). Weight loss was associated with relatively lower concentrations of MCP1, HGF, and IL1β, which are inflammatory markers that may have pro-oncogenic properties (39). While in this small study the variability in these markers was high, the general trend suggests a favorable effect from weight loss.

We observed a clinically significant decrease in triglycerides, and small decreases in total cholesterol ratio in patients who met the primary endpoint of 5% weight loss. High triglycerides and total cholesterol ratio are associated with increased cardiovascular risk (42,43).

This is particularly relevant since cancer treatment in obese patients can further increase risk for adverse cardiac effects, especially in those treated with anthracyclines or trastuzumab (44,45).

We did not demonstrate differences in leukocyte telomere length by randomized group or by weight loss. Our data are in contrast to studies in prostate cancer suggesting that a dietary intervention was associated with an increase in telomerase activity in peripheral blood mononuclear cells, and results from the LEAN study which found an association with randomization to a weight loss intervention with telomere lengthening after 6-months by measuring relative telomere length by quantitative-polymerase chain reaction done on buffy coat-extracted genomic DNA (16,17,46). We chose to evaluate telomere length since it is a primary mediator of cellular and clinical phenotypes; whereas telomerase activity is only detectable in cycline lymphoctyes, and assays are semi-quantitative. Furthermore, we utilized a more robust and clinically validated telomere length measurement technique (flowFISH) (19,20).

Similar to our findings, a recent retrospective study found that assignment to a weight loss intervention did not result in a significant change in telomere length compared to the control group (3% versus 5% shortening, respectively, p=0.12) (46). Thus, there is insufficient evidence to suggest short term weight loss is associated with changes in telomere length.

The major strength of POWER-remote, compared to other weight loss interventions in breast cancer populations, is that it is based on an intervention demonstrated to be effective in a general medicine population, where a remote-supported intervention was equal in efficacy to an in-person intervention (14). Given its scalability and exportability the POWER-remote arm serves as a control arm for next-generation studies evaluating relationships of weight loss and sleep interventions in patients with insomnia (NCT03542604), biomarker modulation

(NCT02431676), and pharmacologic weight loss management. Our randomized design used a standard of care approach as a control arm, further validating our findings. Our comprehensive biomarker analysis, although exploratory due to small sample size, further validates biological changes observed with weight loss. Limitations of this study include a short follow up period of

12-months. Notably, the original POWER study had 24-month follow up and weight loss was sustained (14).

With increasing data demonstrating the benefits of weight loss in breast cancer survivors, practical integration of weight loss programs that offer guidance to patients will be of paramount importance. The POWER-remote intervention is a scalable and effective weight loss program that can significantly reduce weight in breast cancer survivors.

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Table 1. Baseline participant characteristics. Omnibus Chi-square test failed to reject the null hypothesis that baseline characteristics are the same between study groups (P = 0.76).

POWER-Remote (n=50), n (%) Self-Directed (n=46), n (%)

Age - median (range) 53 (33, 71) 55 (30, 73) Menopausal Status Postmenopausal 37 (74) 34 (74) Premenopausal 13 (26) 12 (26) Weight (kg), mean 85.7 (62.9-121.9) 85.0 (68.5-114.8) (range)Mean (SD) BMI (kg/m2), mean 32.0 (26.9-49.2) 32.0 (29.8-45.3) (range)Mean (SD) Race Caucasian 41 (82) 33 (72) African American 9 (18) 10 (22) Other 0 (0) 3 (6) Ethnicity Non-Hispanic 48 (100) 45 (98) Hispanic 0 (0) 1 (2) Estrogen receptor status Positive 43 (88) 36 (84) Negative 7 (12) 10 (16) Breast Surgery Lumpectomy 22 (49) 26 (61) Mastectomy, unilateral 12 (27) 6 (14) Mastectomy, bilateral 11 (24) 11 (26) Received radiation therapy 35 (70) 31 (67) Received Chemotherapy 26 (52) 27 (59) Concurrent Endocrine Therapy Aromatase inhibitors 19 (38) 19 (41) Tamoxifen 20 (40) 18 (39) None 11 (22) 9 (20)

Abbreviations. Number (n), kilogram (kg), standard deviation (SD), body mass index (BMI)

Table 2. Changes in candidate biomarkers following six-months according to randomized assignment and the primary outcome of whether the participant lost 5% weight at six-months.

Change in those Change in who did Change in Change in those who not Baseline 6-month POWER- P- Biomarker Self-directed, achieved achieve P-value* Mean (SD) Mean (SD) remote, Mean value* Mean (SD), n >5% weight >5% (SD), n loss (SD), n weight loss (SD), n Adipocytokines

(pg/mL) 0.06 (0.6), NGF 0.5 (0.6) 0.5 (0.6) 0.06 (0.6), 44 -0.03 (0.3), 41 0.2 0 (0.4), 58 0.6 27 2609 18295 19793 2138 (10685), 812.8 (6584), -887.3 PA1 0.3 (10068), 0.1 (12836) (15015) 44 41 (5102), 27 58 327.9 33.72 (156.2), 37.07( 232.4), 5.2 (129.5), 49.4 MCP1 292.5 (144.1) 0.9 0.04 (215.9) 44 41 27 (219.2), 58 327.5 70.76 (302.3), -35.6 97.7 HGF 272.2 (158.8) 41(196.6), 44 0.60 0.02 (305.4) 41 (102.1), 27 (288.3), 58 0.2 (3.06), 0.6 (6.55), TNFα 3 (2.7) 3.4 (5.2) 0.62(2.63), 44 0.31(7.73), 41 0.4 0.46 27 58 10.1 (62.4), -0.3 (1.25), 10.4 IL1β 0.8 (25) 7. 8 (45.9) 4.1 (22.4), 44 0.1 <0.01 41 27 (55.52), 58 49.5 IL6 4.6 (12.8) 38.6 (259.9) 9.7 (57), 44 60 (370.8), 41 0.6 0.7 (5.6), 27 0.5 (314.8), 58 25

206.2 222.9 (905.2), 121.3 (601.6), 25.2 (221.1), 243.1 IL8 32.3 (158.2) 0.4 0.97 (760.3) 44 41 27 (915.6), 58 3326 35819 36672 -7889 10235 -4458 Resistin 0.6 (43796), 0.27 (66427) (67715) (71407), 44 (40535), 41 (83552), 27 58 -918.8 (2127), 395.1 (1596), -1615 334 Leptin 3582 (3761) 3297 (3879) <0.01 <0.01 44 41 (2388), 27 (1419), 58 2334 18304 19211 2662 (36375), -976.9 -2159 Adiponectin 0.7 (37450), 0.3 (32062) (27163) 44 (36502), 41 (34057), 27 58 Metabolic panel (mg/dL) -2.5 (5.2), 0.1 (10.3), Insulin 13 (7.9) 12.4 (11.8) -1.1 (10), 43 -0.4 (7.8), 40 0.69 0.18 27 56 -1.6 (18.4), -12.8 Glucose 90.1 (18) 81.0 (29.4) -9.6 (26.8), 43 -8.8 (28.3), 40 0.43 0.24 27 (30.3), 56 -0.7 (1.6), 2.5 (9.1), hs-CRP 3.1 (3.2) 4.6 (8.9) 0.1 (2.6), 43 2.9 (10.6), 40 0.07 <0.001 27 56 2.3 (23.8), Total cholesterol 200.8 (35.6) 200.4 (37.5) -3.9 (18.2), 43 3.3 (25.5), 40 0.16 -6 (17.5), 27 0.12 56 -11.1 (47.7), -24.3 (33.8), 1 (54.6), Triglycerides 127.4 (75.3) 120.2 (68.8) -3.1 (52.7), 40 0.77 0.02 43 27 56 HDL 61.7 (14.2) 62.2 (13.7) 1.3 (7.6), 43 -0.3 (6.9), 40 0.42 1.5 (7.2), 27 0 (7.3), 56 0.41 -2.4 (17.3), 2 (20.7), LDL 113.7 (31.7) 114.2 (31.7) -2.8 (18.1), 43 4.2 (20.8), 40 0.14 0.51 27 56 Total -0.2 (0.4), Cholesterol 3.4 (1.1) 3.4 (1.0) -0.2 (0.5), 43 0.1 (0.5), 40 0.08 0 (0.5), 56 0.03 27 Ratio

Telomere 0.1 (0.8), -0.8 (0.8) -0.7 (1.0) 0.1 (0.7), 42 0.1 (0.7), 41 0.76 0 (0.5), 26 0.66 length 57 *P values for Wilcoxon rank sum tests, comparing changes in biomarkers according to study arm and whether patients achieved the primary outcome for weight loss, are not adjusted for multiple comparisons and are included for descriptive purposes only.

Figure 1. Consort diagram.

Figure 2. Weight changes in patients assigned to POWER-remote and self-directed arms. (A)

Proportion of patients who lost weight between study arms, and (B) mean weight change by study arms.

Figure 3. Association of metabolic factors with percent weight loss (continuously). Weight loss is associated with decreases in insulin, hsCRP, and triglycerides. Weight loss is not associated with changes in other metabolic factors.

Figure 4. (A) Telomere length at baseline according to age. (B) Chemotherapy versus no chemotherapy was not associated with changes in telomere length. (C) Weight loss is not associated with changes in telomere length. Patients allocated to POWER-remote in yellow, self-directed in blue.

Assessed for eligibility Figure 1 (n=458)

Excluded (n=362) - not eligible (n=305) - declined (n=12) - other reasons (n=45)

Randomized (n=96)

POWER-remote (n=50) Self-directed (n=46)

Excluded from primary analysis (n=5) Excluded from primary analysis - withdrew consent (n=3) (n=4) - lost to follow up (n=1) - withdrew consent (n=4) - 6m weight not collected (n=1)

Included in analysis (n=45) Included in analysis (n=42)

Figure 2a

Per cent Weight Change from Baseline to 6 months

Self?Directed POWER?remote Lost 15% or More (N=42) (N=45)

Lost 10?14% 12% Lost 5% 51% Lost 5% Lost 5?9% or More or More

Lost 1?4%

No Weight Change

Gained 1?4%

88% Gained Weight 49% Gained Weight Gained 5% or More or Lost < 5% or Lost < 5%

60 50 40 30 20 10 0 10 20 30 40 50 60

Percent of Patients

Figure 2b

-1

-2 POWER-remote -3 Self directed

-4 Weight Weight change (kg)

-5

-6 Baseline 6-month 12-month

Figure 3

Figure 4a

Figure 4b

Figure 4c

The Effects of a Remote-Based Weight Loss Program on Adipocytokines, Metabolic Markers, and Telomere Length in Breast Cancer Survivors: the POWER-Remote Trial

Cesar A Santa-Maria, Janelle W. Coughlin, Dipali Sharma, et al.

Clin Cancer Res Published OnlineFirst February 18, 2020.

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