Skip to main content
AACR Open Access logoLink to AACR Open Access
. 2026 Aug 4;32(20):4633–4642. doi: 10.1158/1078-0432.CCR-26-0270

Weight Loss Responses to Pharmacotherapy in Breast Cancer Survivors: Results from the Adaptive Nutrition and Exercise Weight Loss (A-NEW) Study

Jennifer Y Sheng 1,*, Marianna L Zahurak 1, Faith Too 1, Amanda Montanari 1, Jennifer Trost 2, Mengyang Lu 2, Young Lee 3, Sheetal Parida 1, Amanda L Blackford 1, Dipali Sharma 1, Marci Laudenslager 1, Claire Snyder 1,4, Janelle W Coughlin 5, Vered Stearns 1,*
PMCID: PMC13669726  PMID: 42550849

Abstract

Purpose:

Behavioral weight loss (BWL) interventions consisting of remote coaching and self-monitoring have limited effectiveness in breast cancer survivors. We conducted a single-arm phase II study evaluating the addition of Contrave for <5% weight loss (%WL) after 2 months of BWL.

Patients and Methods:

Women with prior stage 0 to III breast cancer and a body mass index ≥27 kg/m2 were eligible and initiated BWL. We collected weight, patient-reported outcomes, and labs at baseline, 2 months, and 6 months. At 2 months, participants with ≥5% WL (FAST-BWL) continued BWL, whereas those with <5% WL (SLOW-BWL) received BWL + Contrave. The primary endpoint was the proportion of SLOW-BWL with ≥5% WL at 6 months, with 30 participants providing 80% power with 5% type I error. Paired t tests, Kruskal–Wallis tests, and mixed-effects models were utilized.

Results:

Of 55 participants, 2 withdrew prior to 2 months. At 2 months, 15 (28.3%) were FAST-BWL with mean% WL [standard deviation (SD)] of 7.2% (1.5) and 38 (71.7%) were SLOW-BWL with mean% WL (SD) of 1.2% (2.2). Mean% WL between 2 and 6 months was similar in SLOW-BWL (3.8% ± 3.6) and FAST-BWL (3.6% ± 2.6). At 6 months, mean% WL (SD) was 5.1% (2.9) for SLOW-BWL and 10.8% (3.5) for FAST-BWL; 13 of 15 (86.7%) FAST-BWL and 16 of 38 (42%) SLOW-BWL had ≥5% WL. Physical function and pain improved with ≥5% WL (P = 0.03 and P = 0.02, respectively). SLOW-BWL had improved HbA1c (P = 0.003) and triglycerides (P = 0.04). Gastrointestinal symptoms were reported in 74% of SLOW-BWL. Of 6 withdrawals on Contrave, 1 was due to adverse events.

Conclusions:

Adding Contrave for breast cancer survivors with minimal initial benefit from BWL results in clinically meaningful WL (≥5%) in 42% following 6 months of treatment, which also improves selective cardiometabolic risk factors.


Translational Relevance.

Breast cancer survivors with obesity experience poor outcomes, and behavioral weight loss (BWL) interventions yield limited efficacy. Adaptive Nutrition and Exercise Weight loss (A-NEW) is a phase II single-arm study with an adaptive design utilizing weight loss (WL) at 2 months to identify those likely to lose ≥5% weight at 6 months with BWL intervention alone. This study evaluated the WL achieved when the addition of the Food and Drug Administration (FDA)–approved anti-obesity medication Contrave was added to a BWL intervention. After 2 months of BWL intervention, 71.7% of participants had <5% WL; they were more often Black/African American, premenopausal, or had a lower Eastern Cooperative Oncology Group performance status. For those that received the addition of Contrave, 42.1% achieved ≥5% WL by 6 months, and their mean (±standard deviation) % weight change was –5.1 ± 2.9, with positive modulation of biomarkers. Future studies should evaluate biomarkers for those who may benefit most from the addition of pharmacotherapy to BWL interventions.

Introduction

Obesity is prevalent in breast cancer survivors and is associated with inferior survival outcomes compared with those with normal weight (1). At diagnosis, overweight and obesity are present in 31% to 69% of women <65 years and 69% to 82% of women ≥65 years (2). Among 4 million breast cancer survivors (3), more than half gain weight following diagnosis because of decreased activity, lower resting metabolism, altered eating habits with chemotherapy, and hormonal changes (4). Obesity is associated with poor quality of life and risk of treatment-related adverse effects (5). Compared with breast cancer survivors without obesity, those with obesity have an 18% higher recurrence risk and a 21% to 22% higher mortality risk (6, 7). The ≥5% weight loss (WL) threshold is considered clinically meaningful in breast cancer survivors because it is the benchmark associated with improvements in metabolic health, quality of life, physical functioning (PF), and potentially reduced risk of recurrence and mortality in patients with excess weight (8, 9). Guidelines from the American Cancer Society, American Society of Clinical Oncology, and National Comprehensive Cancer Network (NCCN) recommend 5% to 10% WL for breast cancer survivors with body mass index (BMI) ≥25 kg/m2 as a target for health optimization (10).

In the Practice-based Opportunities for Weight Reduction (POWER) trial, investigators demonstrated the equivalence of remote (POWER-r) and in-person behavioral weight loss (BWL) interventions in promoting WL in individuals with cardiovascular risk (11). POWER included 2 interventions: in-person WL support during group and individual sessions or remotely with 3 remote means of support (telephone, study-specific website, and email) and a control group in which WL was self-directed. In the 2 behavioral interventions, participants achieved and sustained clinically significant WL over a period of 24 months. We adapted the POWER-r intervention and conducted a series of studies in breast cancer survivors. Our results and those of others demonstrate that BWL is associated with a WL ≥5% in only approximately half of the participants, highlighting the need for more effective strategies (12, 13). Early WL response (1–3 months) is significantly associated with long-term (6 months and beyond) WL success from lifestyle interventions, and individuals who achieve early response demonstrate distinct baseline characteristics and behavioral patterns (14, 15). In the Look AHEAD trial, those with 3% to 6% WL at 2 months had higher odds of ≥5% WL after 1 year and 45% loss ≥5% after 2 months (14). Lifestyle modifications alone will yield significant WL in these individuals. As this population will have a unique trajectory and outcome, they should not be compared with those without early response. Thus, our primary goal is to evaluate the proportion of those without early response who attain at least 5% WL with the augmentation of behavioral intervention with pharmacotherapy.

The Food and Drug Administration (FDA)–approved obesity management medications have not been prospectively studied in breast cancer survivors. Approved by the FDA in 2014, Contrave is an oral sustained-release combination of the dopamine and norepinephrine reuptake antagonist bupropion and the opioid antagonist naltrexone (16). The proposed mechanism of action involves complementary stimulation of central melanocortin pathways, resulting in increased energy expenditure and reduced appetite (17). Effects may result from the regulation of food intake via the hypothalamus (appetite regulatory center) and the mesolimbic dopamine circuit (reward system). Contrave offers specific advantages in patients with comorbid psychiatric conditions (e.g., depression) and patients who prefer oral therapy or require a lower-cost option, although it produces less WL than GLP1 receptor agonists and phentermine–topiramate (16). At the time of study design, only 1 subcutaneous GLP1 agonist (liraglutide) was approved for chronic weight management in adults, and phentermine–topamax was associated with concerning adverse effects, including cognitive impairment and lack of cardiovascular outcome trial data. The safety and efficacy of Contrave were assessed in 4 randomized, double-blind, placebo-controlled phase III trials involving 4,536 subjects following up to 52 weeks of treatment compared with placebo (18). In all studies, significantly more participants taking Contrave achieved ≥5% WL at 1 year than those taking placebo [66.4% vs. 42.5% among patients without diabetes undergoing intensive behavioral treatment (19)]. Additionally, improved PF was associated with weight reduction and was achieved in more subjects treated with Contrave than placebo (20). The most common adverse reactions (≥10%) reported with Contrave include nausea, constipation, and headache.

We conducted the Adaptive Nutrition and Exercise Weight loss (A-NEW) study (trial registration ID: NCT04499950), a multicenter, investigator-initiated, phase II, prospective, single-arm trial, to evaluate the proportion of breast cancer survivors who achieved ≥5% WL by 6 months with the addition of Contrave and to understand the effect of the intervention on cardiometabolic parameters and patient-reported outcomes (PRO).

Patients and Methods

Study population

Eligible women had stage 0 to III breast cancer, were at least 3 months after completion of the recommended local therapy and chemotherapy, and had a BMI ≥30 kg/m2 or a BMI of 27.0 to 29.9 kg/m2 with hypertension, diabetes, or dyslipidemia; these BMI cutoffs are consistent with the FDA-approved drug label for Contrave. Patients were eligible if they had an Eastern Cooperative Oncology Group (ECOG) performance status score of 0 (fully active and able to carry all activities without restriction) or 1 (some symptoms and restricted in physically strenuous activity but able to carry out light work and adhere to activity recommendations from a coach; ref. 21). Additionally, eligibility required ability to read and write the English language unassisted and daily access to email and/or smartphone. Patients were excluded if they were pregnant or nursing within the past 6 months, planned to become pregnant in the following year, enrolled in a WL program, planned to take a WL medication, or were taking tamoxifen, monoamine oxidase (MAO) inhibitors, bupropion-containing products, or opiate agonists. Concomitant aromatase inhibitor and HER2 therapy were administered. Participants were recruited from 3 Johns Hopkins Sidney Kimmel Comprehensive Cancer Center clinics and from the Anne Arundel Medical Center. The study was approved by the Johns Hopkins Institutional Review Board (IRB00223131) and conducted in accordance with the principles of the Declaration of Helsinki. All participants provided written informed consent.

Study design

We used an adaptive design (a Simon two-stage design) to focus on the attainment of WL in SLOW-BWL with the addition of pharmacotherapy. All participants with evaluable data at 2 months are representative of response to BWL alone, which is critical to the identification of the SLOW-BWL group. The pharmacotherapy intervention (Contrave) was only applied to those with <5% WL at 2 months (SLOW-BWL). Participants who withdrew between 2 and 6 months were classified as not having achieved ≥5% WL at 6 months. The minimal time to evaluation of response to Contrave requires 16 weeks (4 weeks for titration and 12 weeks of maintenance dose). As assessment of initial WL for predicting long-term WL could be performed between 1 and 3 months (14, 15), 2 months was selected to allow for a total study duration of 6 months. Participants with and without ≥5% WL at 2 months were stratified as FAST-BWL and SLOW-BWL, respectively. FAST-BWL continued BWL alone for 4 months, whereas SLOW-BWL received Contrave in addition to BWL. Within the SLOW-BWL group, the trial continued with a Simon two-stage minimax design, with the proportion of SLOW-BWL attaining ≥5% WL at 6 months as the primary endpoint. Following the Simon two-stage design, the study would be stopped early for futility if there were 1 or fewer woman who attained ≥5% WL in the first 15 SLOW-BWL women.

Intervention

Participants initiated a 6-month BWL program based on the POWER-r intervention (11, 22). The POWER-r consisted of remote coaching, web-based educational materials from a lifestyle curriculum, and self-monitoring of diet, physical activity, and weight. The curriculum focused on self-monitoring, behavioral strategies for modifying eating behavior and increasing physical activity, stimulus control, social support, problem-solving, and cognitive restructuring. As the goal is ≥ 5% reduction in body weight (with goals tailored to the individual), calorie intake is adjusted based on starting weight. Individuals followed a Dietary Approaches to Stop Hypertension (DASH)-style diet (high in fruits, vegetables, and low-fat dairy, with low sodium and limited fat) or a Mediterranean-style diet (focused on plant-based foods, healthy fats, and limited red meat). Additional recommendations included a gradual increase in physical activity to at least 180 minutes per week of moderate-intensity exercise, weekly weight checks, and daily tracking of calories and physical activity. Participants were given a physical activity monitor (Fitbit) to encourage activity. Fitbit was used to track diet and activity with app-based food logging to manage a daily calorie goal. Users could set weight goals and monitor their calorie deficit by logging meals and scanning barcodes. Coaches were trained in BWL principles and components of motivational interviewing and had access to self-monitoring data, allowing them to provide feedback on dietary and physical activity behaviors, and WL progress. Contacts occurred weekly during the first 3 months (12 phone sessions) and monthly for the remaining 3 months (3 phone sessions).

At 2 months, those who lost >5% of their baseline body weight (FAST-BWL) continued BWL alone, whereas those who lost <5% (SLOW-BWL) received Contrave in addition to BWL. Contrave dosing was one 8-mg naltrexone/90-mg bupropion tablet per day, increased over 3 weeks to the maintenance dosage of two 8-mg/90-mg tablets twice daily, for a total daily dose of 32 mg/360 mg. Contrave was purchased from Currax Pharmaceuticals and was provided to the participants by the study team. Participants were asked to take Contrave with meals and to avoid high-fat meals (as they could result in a significant increase in systemic exposure). Questionnaires were administered via a secure web-based tool, REDCap (RRID: SCR_003445). A weekly questionnaire assessed intervention-related adverse effects in all the participants. New symptoms were evaluated by the study team, and Contrave dosing was modified by the principal investigator and a board-certified obesity medicine co-investigator if needed.

Data collection

Participants completed demographic questionnaires at baseline. At baseline, 2 months, and 6 months, the participants were weighed in the clinic, and blood was drawn to evaluate the fasting lipid profile [consisting of triglycerides (TG), total cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL)] and HbA1c. Participants completed the following PRO measures at baseline and at 2 and 6 months: Patient-Reported Outcomes Measurement Information System (PROMIS) version 1.0, measures of PF, pain interference, fatigue, depression, and anxiety (23); Functional Assessment of Cancer Therapy–Endocrine Symptoms (FACT-ES) subscale (24); Medical Outcomes Study-Sexual Problems (MOS-SP; ref. 25); and Pittsburgh Sleep Quality Index (PSQI; ref. 26).

PROMIS measures use T scores, with 50 representing the US population average and a standard deviation (SD) of 10. Higher scores for function were better, whereas lower scores for symptoms were better. FACT-ES scores range from 0 to 76, with higher scores indicating lower symptom burden. Estimates of the mean (SD) on the FACT-ES in women with early-stage breast cancer were 59 (SD = 9.7; ref. 24). The MOS-SP scores ranged from 0 to 100, with higher scores indicating more sexual problems. Reported mean MOS-SP scores for women with early-stage breast cancer range from 20 to 36 (SD = 27-31; ref. 27). PSQI scores range from 0 to 21, with higher scores indicating poorer sleep quality. A score ≥5 was considered indicative of poor sleep (28).

Outcomes, sample size, and power

The primary statistical endpoint was the proportion of participants with SLOW-BWL who achieved ≥5% WL from baseline to 6 months after the addition of Contrave to BWL. Secondary and exploratory endpoints included (i) cardiometabolic biomarkers (HbA1c and fasting lipid panel) at 2 and 6 months compared with baseline levels in SLOW-BWL and FAST-BWL and (ii) PROs at 2 and 6 months compared with baseline levels in SLOW-BWL and FAST-BWL, as well as all participants who attained ≥5% WL at 6 months compared with those who did not attain ≥5% WL.

The projected sample size of 30 SLOW-BWL participants had 80% power at a type I error rate of 5% if the true rate of attaining the primary endpoint by 6 months was 29%. The study was considered successful if 7 or more SLOW-BWL participants achieved more than 5% WL compared with their baseline weight, implying that the success rate of achieving ≥5% WL was significantly higher than 10.9%.

Statistical methods

Data were summarized using descriptive statistics (continuous data) or contingency tables (categorical data) for demographics, baseline characteristics, laboratory values, and PROs. Summary statistics are presented for the SLOW-BWL and FAST-BWL groups, as well as for the overall percentage of WL. All changes were calculated by subtracting the pre-intervention values. Within-patient changes in weight and laboratory values between timepoints were analyzed using paired t tests. Independent sample comparisons were performed using two-sample t tests or Kruskal–Wallis tests, as appropriate. Toxicities by type and grade according to the revised Common Terminology Criteria for Adverse Events 4.0 were reported. For each participant and adverse event type, the earliest instances of the event with the highest grade and attribution combination were reported. Statistical analyses were performed using R version 4.4.0 (R Project for Statistical Computing; RRID: SCR_001905).

Logistic regression was used to evaluate the association of baseline weight, age, and PRO scores with ≥5% WL at 2 months and to evaluate the effect of the same baseline characteristics, as well as the change in weight at 2 months, on attaining ≥5% WL at 6 months for participants in SLOW-BWL. Baseline PRO scores were calculated by subtracting the mean and dividing by the SD. With this parameterization, the odds ratios (OR) for successful WL represented the odds of success for a 1 SD increase in the PRO score. The proportion of participants in the SLOW-BWL group achieving the minimally important difference (MID), the smallest change in a participant’s health score that the participant perceives as important and meaningful, was reported for each PRO with 95% confidence intervals (CI). PROMIS measures have been validated in patients with early-stage cancer with an MID of 3 to 5 points (29). For analyses in this study, a change of 4 points was considered the MID: +4 for PF and −4 for symptoms. The empirical rule effect size method was used to determine MIDs for FACTS-ES scores and MOS-SP. This yielded +5 points for FACTS-ES scores and −8 points for the MOS-SP scores. The proportion of participants achieving an MID was calculated based on complete-case analyses (denominator is the number with complete data) and intent-to-treat analysis (denominator is the total number of participants, including those with missing data as nonresponders). When all patients are considered in the denominator, we assume that those with missing values were unlikely to have achieved benefit between 2 and 6 months. The details of the individual measures, score interpretation, and MID are provided in Supplementary Table S1. Graphical representations of PRO scores in the 2 groups over time were generated using a mixed-effects model.

Results

Participant characteristics

From February 2021 to July 2023, a total of 55 participants enrolled in the study. The overall representativeness of study participation was similar to that of the US population (Supplementary Table S2). One participant withdrew after the baseline visit, and 1 withdrew before the 2-month study visit. Thus, 53 participants were included in the analysis [Consolidated Standards of Reporting Trials (CONSORT) diagram, Fig. 1]: 15 (28.3%) achieved ≥5% WL at 2 months and were designated FAST-BWL, whereas the other 38 (71.7%) were designated SLOW-BWL. A total of 6 of 38 participants in SLOW-BWL withdrew from the study. Thus, of 53 evaluable at 2 months, 15 of 15 in FAST-BWL and 32 of 38 in SLOW-BWL completed the study. Although there were no statistically significant differences in baseline characteristics between the FAST-BWL and SLOW-BWL groups, participants in SLOW-BWL were more often Black or African American (31.6% vs. 6.7%), premenopausal (21.1% vs. 6.7%), had an ECOG performance status score of 1 (26.3% vs. 13.3%), and employed (71.1% vs. 60%; Table 1). The median (range) age (in years) was 61 (40–73) for FAST-BWL and 56.5 (30–73) for SLOW-BWL. Approximately two thirds of the participants in both groups had stage 0 to I breast cancer. In FAST-BWL, 46.7% of patients received prior chemotherapy (vs. 55.3% in SLOW-BWL) and 66.7% received concomitant endocrine therapy (vs. 78.9% in SLOW-BWL).

Figure 1.

Figure 1.

CONSORT diagram.

Table 1.

Baseline characteristics by the BWL group (N = 53).

Characteristic FAST-BWL (n = 15) SLOW-BWL (n = 38) P
Site, n (%) ​ ​ 0.31
 Anne Arundel Medical Center 0 (0) 5 (13.2) ​
 Johns Hopkins 15 (100) 33 (86.8) ​
Age (years), median (min, max) 61 (40, 73) 56.5 (30, 73) 0.33
Time since diagnosis (years), median (min, max) 3.27 (1.52, 7.30) 2.89 (0.24, 10.63) 0.48
Hispanic or Latino, n (%) 1 (6.7) 2 (5.3) >0.99
Race, n (%) ​ ​ 0.11
 Black or African American 1 (6.7) 12 (31.6) ​
 Other 1 (6.7) 2 (5.3) ​
 White/Caucasian 13 (86.7) 24 (63.2) ​
Weight (kg), median (min, max) 92.1 (73.5, 117) 93.6 (73.5, 129.7) 0.73
BMI (kg/m2), median (min, max) 33.3 (27.5, 42.3) 34.7 (30.4, 50.7) 0.36
ECOG, n (%) ​ ​ 0.47
 0 13 (86.7) 28 (73.7) ​
 1 2 (13.3) 10 (26.3) ​
Stage, n (%) ​ ​ 0.19
 DCIS 3 (20) 2 (5.3) ​
 Stage 1 6 (40) 23 (60.5) ​
 Stage 2 2 (13.3) 8 (21.1) ​
 Stage 3 4 (26.7) 5 (13.2) ​
Postmenopause, n (%) 14 (93.3) 30 (78.9) 0.42
Working, n (%) 9 (60) 27 (71.1) 0.52
Tobacco (current), n (%) ​ ​ >0.99
 No 15 (100) 38 (100) ​
Alcohol, n (%) ​ ​ >0.99
 Never or up to 3 per month 9 (60) 21 (55.3) ​
 1–6 per week 4 (26.7) 12 (31.6) ​
 1–3 per day 2 (13.3) 5 (13.2) ​
Local treatment ​ ​ ​
 Lumpectomy, n (%) 10 (66.7) 22 (57.9) 0.56
 Mastectomy, n (%) 7 (46.7) 21 (55.3) 0.89
 Radiation, n (%) 10 (66.7) 29 (76.3) 0.50
Systemic treatment ​ ​ ​
 Chemotherapy (all completed), n (%) 7 (46.7) 21 (55.3) 0.57
 Anti-HER2 therapy (all completed), n (%) 2 (13.3) 5 (13.2) >0.99
 Endocrine therapy (all concomitant), n (%) 10 (66.7) 30 (78.9) 0.48
HbA1c, median (min, max) 5.6 (4.7, 6) 5.7 (4.2, 6.7) 0.22
Cholesterol, median (min, max) 202 (169, 292) 201 (156, 286) 0.96
LDL, median (min, max) 119 (78, 191) 117 (15, 169) 0.63
TG, median (min, max) 114 (61, 332) 117 (50, 303) 0.90
PROs, median (lower quartile, upper quartile)
 PF 48 (45, 53) 46 (41, 50) 0.2
 Endocrine function 67 (54, 71) 56 (49, 63) 0.05
 Depression 43 (37, 51) 50 (39, 55) 0.3
 Anxiety 53 (48, 53) 54 (48, 58) 0.5
 Pain 51 (41, 58) 55 (43, 58) 0.2
 Fatigue 48 (41, 51) 48 (46, 54) 0.1
 Sleep 8 (6, 8) 9 (6, 10) 0.2
 Sexual function 4 (0, 42) 25 (0, 68) 0.4

Abbreviation: DCIS, ductal carcinoma in situ; LDL, low-density lipoprotein.

Efficacy

In the intent-to-treat analysis of 38 participants who initiated Contrave, 16 (42.1%) achieved ≥5% WL by 6 months and 22 (57.9%) did not (Table 2A). The per-protocol analysis set included 15 FAST-BWL and 32 SLOW-BWL participants who completed the study (Fig. 2). At 6 months, 13 of 15 (86.7%) FAST-BWL participants achieved ≥5% WL compared with 16 of 32 (50%) SLOW-BWL participants. Inference following studies with Simon two-stage designs involves adjusting estimates for the interim analysis as well as adjusting for deviations from the planned sample size (30). In the SLOW-BWL group on Contrave, this adjusted estimate of success is 43.5% (95% CI, 24.4, 64; P = 0.0005).

Table 2.

WL outcomes.

(A) Percentage of participants with WL success
​Time point of success n/N (%)
Success at 2 months ​
 Yes: FAST-BWL 15/53 (28.3%)
 No: SLOW-BWL 38/53 (71.7%)
Success at 6 months in FAST-BWL
 Yes 13/15 (86.7%)
 No 2/15 (13.3%)
Success at 6 months in SLOW-BWL
 Yes 16/38 (42.1%)
 No 22/38 (57.9%)
Success: (≥5% WL)
(B) Weight and percentage changes at baseline, 2 months, and 6 months
Group N Baseline, mean in kg (SD) 2 months, mean in kg (SD) 6 months, mean in kg (SD) %Change: (2 months − baseline), mean (95% CI) %Change: (6 months − 2 months), mean (95% CI) %Change: (6 months − BL), mean (95% CI)
FAST-BWL 15 95.4 (13.4) 88.5 (12.9) 85.2 (14) −7.3 (−8.1 to −6.4) −3.9 (−5.8 to −2) −10.8 (−12.8 to −8.9)
SLOW-BWL 38 97.2 (14.2) 96.1 (14.2) 92.3 (15) −1.2 (−1.9 to −0.5) −3.8 (−4.8 to −2.8) −5.1 (−6.2 to −4.1)

Figure 2.

Figure 2.

Waterfall plot of weight change at 6 months (per-protocol set n = 47). Of 53 participants, 15 (28.3%) were in the FAST-BWL group and 38 (71.7%) were in the SLOW-BWL group and initiated on Contrave. Among the 32 SLOW-BWL patients that completed the study per-protocol, 16 (50%) achieved ≥5% WL by 6 months. Among the 15 FAST-BWL participants in this analysis set, 13 (86.7%) maintained ≥5% WL at 6 months.

The mean and median baseline weights were similar between the groups (Fig. 3; Table 2B). After 2 months of BWL, the SLOW-BWL and FAST-BWL groups had a mean %WL of 1.2% (2.2) and 7.2% (1.5), respectively. The mean WL from baseline to 2 months was 1.1 kg (2.1) in SLOW-BWL and 6.9 kg (1.5) in FAST-BWL. Between 2 and 6 months, the mean %WL values in the SLOW-BWL and FAST-BWL groups were 3.8% (3.6) and 3.9% (2.6), respectively. The mean WL in SLOW-BWL and FAST-BWL between 2 and 6 months was 1.1 kg (2.1) and 3.3 kg (3), respectively. Of the 38 SLOW-BWL participants, 32 were evaluable at 6 months and experienced a mean %WL of 5.1% (2.9). The total mean WL for the SLOW-BWL from baseline to 6 months was 4.9 kg (2.7) and ranged from a 0.5 kg gain to a 9.5 kg loss. Of the 15 participants in FAST-BWL, the mean %WL at 6 months was 10.8% (3.5), and the total mean WL was 10.1 kg (3.1), ranging from a 4.5 kg loss to a 14 kg loss.

Figure 3.

Figure 3.

Box plots of baseline weight and % weight change by the BWL group. A, Weight (in kg) at baseline. B, % Weight change after 2 months of BWL intervention. C, % Weight change from 2 to 6 months. D, Total % weight change after 6 months. The length of the box is the interquartile range (IQR) of the data and depicts the spread of the middle 50% of the observations. The median is represented by a line within the box, and the mean is represented by a square. The lines extending from the box extend from the upper and lower quartiles to adjacent values. The adjacent values are defined as the upper quartile plus 1.5 × IQR and the lower quartile minus 1.5 × IQR.

Adverse events

Among the FAST-BWL groups, arthralgia and constipation were reported in ≥10% of the participants from months 2 to 6 (Supplementary Fig. S1). Gastrointestinal (GI) symptoms were the most commonly reported adverse effects in SLOW-BWL participants from months 2 to 6: constipation (52.6%), nausea (42.1%), dry mouth (36.8%), and abdominal pain (18.4%). Other side effects (reported in >15%) included insomnia (31.6%), headache (23.7%), fatigue (21.1%), and anxiety (15.8%). Of the 38 SLOW-BWL participants, at least 1 dose reduction was advised for 9 participants. The drug was interrupted and then resumed for 4 participants (2 of whom had advised dose reduction) because of adverse events. There were no serious adverse events (grade 3 and higher) reported during the study. In SLOW-BWL, there were a total of 21 grade 2 adverse events reported, with the most commonly reported being nausea (14.2%), fatigue (9.5%), anxiety (9.5%), and tremor (9.5%). Only 1 participant discontinued pharmacotherapy because of adverse events. Of the 6 participants who withdrew from the study, only 1 reported adverse events related to pharmacotherapy as a reason for discontinuation.

PRO measures

Baseline PRO scores are presented in Table 1. Endocrine symptom scores were higher at baseline in the FAST-BWL group compared with the SLOW-BWL group [62 (11.8) vs. 56 (9.1); P = 0.05]. The mean PF score for all participants in the study was 46 (7), which was slightly worse than the average in the general population. Those with ECOG scores of 1 had significantly lower PF scores of 41.7 versus 47.7 for those with ECOG scores of 0 (t test, P = 0.007). The mean baseline PF score for participants with ≥5% WL at 2 months was similar to that of those with <5% WL [48 (7) vs. 46 (7); P = 0.24]. The mean baseline PROMIS symptom scores for pain, depression, anxiety, and fatigue were all within 5 points of the US average (31), overall, and within the 2 groups of the study. Reported sleep symptoms (PSQI) were high in both groups, with mean scores of 8 and 5, indicating poor sleep. Baseline sexual symptoms ranged widely (0–100) but were not significantly different between the 2 groups, with 47% of participants at baseline in both groups reporting no sexual symptoms. The baseline and the 2- and 6-month PROs for both groups are shown in Supplementary Fig. S2. Across all participants in the FAST-BWL and SLOW-BWL groups, scores for PF, endocrine function, depression, and sleep improved at 6 months compared with baseline. Anxiety scores also improved in the SLOW-BWL group. Regardless of group, PF improved, and pain was reduced in those with ≥5% WL (P = 0.03 and P = 0.02, respectively). Pain significantly (P = 0.03) improved in those who achieved ≥5% WL in the SLOW-BWL group (Supplementary Fig. S3).

Minimally important changes

In the intent-to-treat analysis, which considered all participants (N = 53), at least 20% attained a minimally important improvement in endocrine symptoms (24.53%), depression (24.53%), pain (26.42%), fatigue (22.64%), and sexual symptoms (26.42%) after the first 2 months of BWL intervention (Supplementary Table S1). In the intent-to-treat analysis of FAST-BWL at 6 months, ≥20% attained a minimally important improvement in all domains except sleep, with 66.67% experiencing a minimally important improvement in PF. In the SLOW-BWL groups, there were no domains with ≥20% of participants achieving a minimally important improvement while on Contrave.

Percentage changes in cardiometabolic markers (HbA1c and fasting lipid panel)

Participants in the FAST-BWL group showed substantial improvement in the TG levels of the fasting lipid panel from baseline to 2 months of −20.1% (32) and from baseline to 6 months [−22.6% (24.9); Supplementary Table S3]. The SLOW-BWL group showed a modest TG change of −8.3% (24.9) at 2 months and −8.4% (23.3) at 6 months. Participants in the FAST-BWL group had a reduction in HbA1c from baseline to 2 months of −0.6 (3.7) and from baseline to 6 months of −1.7 (4.1). SLOW-BWL showed an HbA1c increase of 0.1 (3.9) at 2 months and a substantial reduction of −1.9 (3.4) at 6 months. Participants in the SLOW-BWL group had a significant improvement in HbA1c [mean difference of −0.11 (95% CI, −0.18 to −0.04); P = 0.003] and TG [mean difference of −14.30 (95% CI, −27.58 to −1.02); P = 0.04; Supplementary Table S4] between baseline and 6 months.

Other exploratory analyses

For 38 participants in SLOW-BWL, those with an average amount of WL at 2 months (−1.14 kg) had a 46.6% probability of achieving success at 6 months. In contrast, participants whose weight increased at 2 months (1 SD above the average change), the odds of success were lower (OR, 0.30; 95% CI, 0.10–0.88; P = 0.03; Supplementary Table S5). There were 12 of 38 (31.6%) Black participants in the SLOW-BWL group. Of the 12 Black participants in the SLOW-BWL group, 4 (33%) were ultimately successful in achieving ≥5% WL. Of the 26 non-Latino White women in the SLOW-BWL group, 12 (46%) were successful in attaining ≥5% WL.

Discussion

Although obesity is considered a treatable disease, approaches have focused on behavioral interventions in breast cancer survivors, and outcomes have been modest (32). To the best of our knowledge, A-NEW is the only completed WL study in breast cancer survivors using initial WL to guide the addition of an FDA-approved obesity management medication. We demonstrated that early WL results can guide WL interventions. Specifically, 42.1% of breast cancer survivors with overweight or obesity were unable to lose ≥5% of their weight after 2 months of BWL and lost ≥5% of their weight after 4 months of continued BWL with the addition of Contrave.

Medication for obesity management, via reduction of hunger and food cravings and enhancement of satiety, helps patients limit the amount of food they eat, thereby increasing their adherence to the prescribed diet (33). Although a multitarget approach that includes BWL and pharmacotherapy may provide greater benefits than BWL monotherapy, selecting the optimal WL medication requires consideration of differences in efficacy, side effects, and cautions for chronic management of obesity (34). Combination products approved by the FDA to treat obesity, such as Contrave, have a moderate WL effect but less severe adverse effects (16). In the A-NEW study, Contrave was well tolerated, with GI symptoms being the most reported adverse event. Unlike other centrally acting medications, it has no potential for abuse.

Across all participants enrolled in the A-NEW study, approximately 74% (28 of 38) lost ≥5% weight, a larger proportion than that demonstrated in prior studies conducted in breast cancer survivors (13, 22). Assessment of initial BWL response provides an early opportunity to adapt obesity treatment. Unlike the non-cancer population, almost three quarters of breast cancer survivors were unable to attain ≥5% WL after 2 months of lifestyle change. Most women who lost ≥5% of their weight at 2 months (FAST-BWL) continued to lose weight. Although 42% of SLOW-BWL participants achieved ≥5% WL at 6 months, the overall benefit was still lower than the 88% of FAST-BWL who attained ≥5% WL.

Consistent with other experiences, premenopausal women and those who are Black or African American may struggle to lose weight with BWL alone (35). Premenopausal women, particularly those who have been on endocrine therapy for 5 years, tend to have more weight gain (36). In the Breast Cancer Weight Loss (BWEL) trial randomizing patients with breast cancer with a BMI ≥27 kg/m2 to a WL intervention versus control, the intervention yielded less WL in premenopausal women, especially in those who identified as Black or Hispanic (37). Our results, with data from BWEL, highlight the need for tailored interventions to augment WL in Black and younger patients.

The PROs collected at baseline, 2 months, and 6 months aid in our understanding of the implications of WL at the individual level to improve symptoms. Our study confirmed the benefits of a 5% WL in improving PF and pain. Reviews of meta-analyses have shown that behavioral interventions improve quality of life, mental health, and PF (38). Our findings confirm that PF was worse in breast cancer survivors than in the general population in the United States and that targeting at least 5% WL can improve it. Across the 4 phase III studies of Contrave, there were significant improvements in PF in Contrave-treated participants versus placebo-treated participants in PF (18). Additionally, even without the impact of the degree of WL, 6 months of BWL was shown to improve anxiety, pain, fatigue, sleep disturbance, and sexual function in one fifth of those in SLOW-BWL.

Across all the participants in the A-NEW group, many had poor sleep quality. Insomnia is associated with weight gain (39–41), as deficient sleep may reduce activity and alter hormones, leading to greater consumption of calorie-dense foods. Although baseline sleep does not seem to be a predictor of outcome in the A-NEW study, in our post hoc analysis of POWER-r, those who reported poor baseline sleep had lower 6-month WL than those with better sleep (42). These findings led to the development of an ongoing NIH-funded trial (NCT05780814) in which breast cancer survivors with overweight or obesity are randomized to either sleep education or treatment of insomnia prior to BWL, based on preliminary evidence that those receiving cognitive behavioral therapy prior to BWL lost more weight than those receiving sleep education (43). Sleep quality and quantity may contribute to the degree of WL in breast cancer survivors participating in BWL and may be leveraged to individualize and increase the effectiveness of obesity treatment.

Breast cancer survivors are at a heightened risk of cardiovascular disease, as many have overweight or obesity, which is a strong risk factor for cardiovascular disease. Cancer treatment can further increase the risk of adverse cardiac effects (44). WL may be an underaddressed strategy for reducing cardiovascular risk factors such as dyslipidemia. In the A-NEW study, we observe a striking reduction in TG, which correspond to dramatic weight responses in the FAST-BWL group from baseline to 2 and 6 months and in the SLOW-BWL group from baseline to 6 months. The benefits of WL in breast cancer survivors extend beyond real-time improvements in PF and pain to beneficial metabolic outcomes, which may ultimately improve cardiovascular mortality.

Approximately 60% (9/15) of the participants in the FAST-BWL group experienced ≥10% WL at 6 months. Studies on survivors have focused on ≥5% WL, given the significant reduction in diabetes and cardiovascular diseases at this threshold (45, 46). Studies have shown that loss of ≥10% improves β-cell function and insulin sensitivity in muscles, causes favorable changes in adipose tissue, and reduces inflammatory cytokines (47). This may be especially beneficial for breast cancer survivors, as many have elevated cytokines following therapy, which can persist for years (48). Additionally, WL of ≥10% has been associated with greater improvement in PF (49). The use of obesity strategies to target higher thresholds of WL may be critical if the modulation of serum biomarkers is needed. As the A-NEW trial was started in 2021, there have been several new FDA-approved WL medications, some of which are associated with greater WL than anticipated with Contrave. This should be further evaluated, particularly among cancer survivors.

The limitations of our study include the relatively small number of participants and nonrandomized design. Although the data seem compelling, a larger randomized study is needed to establish the superiority of the addition of obesity management drugs to behavioral intervention alone. We were unable to include breast cancer survivors receiving tamoxifen because of drug interactions with bupropion, as chronic co-administration of potent or moderate CYP450 2D6 inhibitors (such as bupropion) may reduce the effectiveness of tamoxifen. The participants were primarily postmenopausal or high-risk premenopausal women with ovarian function suppression and use of an aromatase inhibitor. Thus, these results may not be applicable to premenopausal women with a lower risk of receiving tamoxifen. Nonetheless, the postmenopausal population still requires aggressive obesity management, as the risk of obesity increases with age and hormonal changes during menopause can affect metabolism and lead to weight gain (31).

In conclusion, the initial weight response can inform populations that would benefit from multimodal obesity treatments involving pharmacotherapy and lifestyle interventions. The combination of Contrave with behavioral intervention yielded significant WL in nearly half of breast cancer survivors who did not have significant WL after 2 months of intensive lifestyle intervention. The benefits of 5% WL on PF and pain are also clinically meaningful. An adaptive WL approach may meet the major unmet needs of many breast cancer survivors, and the BWL–Contrave combination strategy should be considered for patients not receiving tamoxifen with insignificant weight change with modifications of diet and physical activity.

Supplementary Material

Supplementary Data 1

includes 5 tables and 3 figures

Acknowledgments

This study was funded by the NCCN Foundation (J.Y. Sheng, 90088495), American Institute for Cancer Research as part of the American Institute for Cancer Research (AICR) Investigator-Initiated Grant Program (V. Stearns, 586453), Breast Cancer Research Foundation (V. Stearns, BCRF-23-154), Maryland Cigarette Restitution Fund (J.Y. Sheng, PHPA-1896), National Capital Cancer Research Fund (J.Y. Sheng), NIH P30 CA006973, Conquer Cancer Foundation of ASCO (J.Y. Sheng, Young Investigator Award), and Under Armour (V. Stearns).

Footnotes

Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

Contributor Information

Jennifer Y. Sheng, Email: Jsheng7@jhmi.edu.

Vered Stearns, Email: Ves4007@med.cornell.edu.

Data Availability

The data that support the findings of this study are available from the corresponding author upon reasonable request. The data are not publicly available, as they are housed in REDCap, a secure web-based software tool that complies with the Health Insurance Portability and Accountability Act standards and is required by the Johns Hopkins Institutional Review Board. Please note that all requests must be reviewed and approved by the Johns Hopkins Institutional Review Board prior to fulfillment.

Authors’ Disclosures

C. Snyder reports grants from Pfizer and Johnson & Johnson and personal fees from Pfizer, Shionogi, and Movember outside the submitted work. J.W. Coughlin reports grants from NCCN outside the submitted work. V. Stearns reports personal fees from AstraZeneca and Astellas Pharma outside the submitted work. No disclosures were reported by the other authors.

Disclaimer

This study was funded, in part, by the NCCN Foundation. Any opinions, findings, and conclusions expressed in this material are those of the authors (s) and do not necessarily reflect those of the NCCN or the NCCN Foundation.

Authors’ Contributions

J.Y. Sheng: Conceptualization, supervision, funding acquisition, investigation, methodology, writing–original draft, writing–review and editing. M.L. Zahurak: Software, formal analysis, visualization, writing–original draft, writing–review and editing. F. Too: Resources, data curation, project administration, writing–review and editing. A. Montanari: Investigation, writing–review and editing. J. Trost: Investigation, writing–review and editing. M. Lu: Investigation, writing–review and editing. Y. Lee: Supervision, writing–review and editing. S. Parida: Resources, writing–review and editing. A.L. Blackford: Formal analysis, writing–review and editing. D. Sharma: Resources, methodology, writing–review and editing. M. Laudenslager: Supervision, writing–review and editing. C. Snyder: Methodology, writing–review and editing. J.W. Coughlin: Supervision, investigation, writing–review and editing. V. Stearns: Conceptualization, funding acquisition, methodology, writing–original draft, writing–review and editing.

References

  • 1. Chlebowski RT, Aragaki AK, Pan K, Simon MS, Neuhouser ML, Haque R, et al. Breast cancer incidence and mortality by metabolic syndrome and obesity: the Women’s Health Initiative. Cancer 2024;130:3147–56. 10.1002/cncr.35318. [DOI] [PubMed] [Google Scholar]
  • 2. Maliniak ML, Patel AV, McCullough ML, Campbell PT, Leach CR, Gapstur SM, et al. Obesity, physical activity, and breast cancer survival among older breast cancer survivors in the Cancer Prevention Study-II Nutrition Cohort. Breast Cancer Res Treat 2018;167:133–45. 10.1007/s10549-017-4470-7. [DOI] [PubMed] [Google Scholar]
  • 3. Giaquinto AN, Sung H, Newman LA, Freedman RA, Smith RA, Star J, et al. Breast cancer statistics 2024. CA Cancer J Clin 2024;74:477–95. 10.3322/caac.21863. [DOI] [PubMed] [Google Scholar]
  • 4. Cathcart-Rake EJ, Sanft T, Tevaarwerk AJ. Weight gain after breast cancer diagnosis: it’s complicated. Cancer 2022;128:3152–4. 10.1002/cncr.34343. [DOI] [PubMed] [Google Scholar]
  • 5. LeVee A, Mortimer J. The challenges of treating patients with breast cancer and obesity. Cancers (Basel) 2023;15:2526. 10.3390/cancers15092526. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Pang Y, Wei Y, Kartsonaki C. Associations of adiposity and weight change with recurrence and survival in breast cancer patients: a systematic review and meta-analysis. Breast Cancer 2022;29:575–88. 10.1007/s12282-022-01355-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Harborg S, Cronin-Fenton D, Jensen M-BR, Ahern TP, Ewertz M, Borgquist S. Obesity and risk of recurrence in patients with breast cancer treated with aromatase inhibitors. JAMA Netw Open 2023;6:e2337780. 10.1001/jamanetworkopen.2023.37780. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Dieli-Conwright CM, Courneya KS, Demark-Wahnefried W, Sami N, Lee K, Buchanan TA, et al. Effects of aerobic and resistance exercise on metabolic syndrome, sarcopenic obesity, and circulating biomarkers in overweight or obese survivors of breast cancer: a randomized controlled trial. J Clin Oncol 2018;36:875–83. 10.1200/JCO.2017.75.7526. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Ligibel JA, Bohlke K, May AM, Clinton SK, Demark-Wahnefried W, Gilchrist SC, et al. Exercise, diet, and weight management during cancer treatment: ASCO guideline. J Clin Oncol 2022;40:2491–507. 10.1200/JCO.22.00687. [DOI] [PubMed] [Google Scholar]
  • 10. Runowicz CD, Leach CR, Henry NL, Henry KS, Mackey HT, Cowens-Alvarado RL, et al. American Cancer Society/American Society of Clinical Oncology breast cancer survivorship care guideline. J Clin Oncol 2016;34:611–35. 10.1200/JCO.2015.64.3809. [DOI] [PubMed] [Google Scholar]
  • 11. Appel LJ, Clark JM, Yeh H-C, Wang N-Y, Coughlin JW, Daumit G, et al. Comparative effectiveness of weight-loss interventions in clinical practice. N Engl J Med 2011;365:1959–68. 10.1056/NEJMoa1108660. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Sheng J, Sharma D, Jerome G, Santa-Maria CA. Obese breast cancer patients and survivors: management considerations. Oncology 2018;32:410–7. [PMC free article] [PubMed] [Google Scholar]
  • 13. Wang S, Yang T, Qiang W, Zhao Z, Shen A, Zhang F. Benefits of weight loss programs for breast cancer survivors: a systematic reviews and meta-analysis of randomized controlled trials. Support Care Cancer 2022;30:3745–60. 10.1007/s00520-021-06739-z. [DOI] [PubMed] [Google Scholar]
  • 14. Unick JL, Hogan PE, Neiberg RH, Cheskin LJ, Dutton GR, Evans-Hudnall G, et al. Evaluation of early weight loss thresholds for identifying non-responders to an intensive lifestyle intervention. Obesity 2014;22:1608–16. 10.1002/oby.20777. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Zhou B, Roberts SB, Das SK, Naumova EN. Weight loss trajectories and short-term prediction in an online weight management program. Nutrients 2024;16:1224. 10.3390/nu16081224. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Gudzune KA, Kushner RF. Medications for obesity: a review. JAMA 2024;332:571–84. 10.1001/jama.2024.10816. [DOI] [PubMed] [Google Scholar]
  • 17. Preskorn SH. Contrave, lybalvi, auvelity, and cobenfy: what do they have in common? J Psychiatr Pract 2025;31:214–6. 10.1097/PRA.0000000000000863. [DOI] [PubMed] [Google Scholar]
  • 18. Apovian CM. Naltrexone/bupropion for the treatment of obesity and obesity with Type 2 diabetes. Future Cardiol 2016;12:129–38. 10.2217/fca.15.79. [DOI] [PubMed] [Google Scholar]
  • 19. Yanovski SZ, Yanovski JA. Naltrexone extended-release plus bupropion extended-release for treatment of obesity. JAMA 2015;313:1213–4. 10.1001/jama.2015.1617. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Kolotkin RL, Chen S, Klassen P, Gilder K, Greenway FL. Patient-reported quality of life in a randomized placebo-controlled trial of naltrexone/bupropion for obesity. Clin Obes 2015;5:237–44. 10.1111/cob.12108. [DOI] [PubMed] [Google Scholar]
  • 21. Fillipo R, Leblanc TW, Plyler KE, Arizmendi C, Henke DM, Coles T. How do patients interpret and respond to a novel patient-reported eastern cooperative oncology group performance status (ECOG)? Qual Life Res 2024;33:2375–85. 10.1007/s11136-024-03715-y. [DOI] [PubMed] [Google Scholar]
  • 22. Santa-Maria CA, Coughlin JW, Sharma D, Armanios M, Blackford AL, Schreyer C, et al. The effects of a remote-based weight loss program on adipocytokines, metabolic markers, and telomere length in breast cancer survivors: the POWER-remote trial. Clin Cancer Res 2020;26:3024–34. 10.1158/1078-0432.CCR-19-2935. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Jensen RE, Moinpour CM, Potosky AL, Lobo T, Hahn EA, Hays RD, et al. Responsiveness of 8 Patient-Reported Outcomes Measurement Information System (PROMIS) measures in a large, community-based cancer study cohort. Cancer 2017;123:327–35. 10.1002/cncr.30354. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Fallowfield LJ, Leaity SK, Howell A, Benson S, Cella D. Assessment of quality of life in women undergoing hormonal therapy for breast cancer: validation of an endocrine symptom subscale for the FACT-B. Breast Cancer Res Treat 1999;55:189–99. 10.1023/a:1006263818115. [DOI] [PubMed] [Google Scholar]
  • 25. Ware JE, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care 1992;30:473–83. 10.1097/00005650-199206000-00002. [DOI] [PubMed] [Google Scholar]
  • 26. Backhaus J, Junghanns K, Broocks A, Riemann D, Hohagen F. Test-retest reliability and validity of the Pittsburgh Sleep Quality Index in primary insomnia. J Psychosom Res 2002;53:737–40. 10.1016/s0022-3999(02)00330-6. [DOI] [PubMed] [Google Scholar]
  • 27. Ribi K, Luo W, Walley BA, Burstein HJ, Chirgwin J, Ansari RH, et al. Treatment-induced symptoms, depression and age as predictors of sexual problems in premenopausal women with early breast cancer receiving adjuvant endocrine therapy. Breast Cancer Res Treat 2020;181:347–59. 10.1007/s10549-020-05622-5. [DOI] [PubMed] [Google Scholar]
  • 28. Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res 1989;28:193–213. 10.1016/0165-1781(89)90047-4. [DOI] [PubMed] [Google Scholar]
  • 29. Yost KJ, Eton DT, Garcia SF, Cella D. Minimally important differences were estimated for six Patient-Reported Outcomes Measurement Information System-Cancer scales in advanced-stage cancer patients. J Clin Epidemiol 2011;64:507–16. 10.1016/j.jclinepi.2010.11.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Koyama T, Chen H. Proper inference from Simon’s two-stage designs. Stat Med 2008;27:3145–54. 10.1002/sim.3123. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Palacios S, Chedraui P, Sánchez-Borrego R, Coronado P, Nappi RE. Obesity and menopause. Gynecol Endocrinol 2024;40:2312885. 10.1080/09513590.2024.2312885. [DOI] [PubMed] [Google Scholar]
  • 32. Shaikh H, Bradhurst P, Ma LX, Tan SYC, Egger SJ, Vardy JL. Body weight management in overweight and obese breast cancer survivors. Cochrane Database Syst Rev 2020;12:CD012110. 10.1002/14651858.CD012110.pub2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Elmaleh-Sachs A, Schwartz JL, Bramante CT, Nicklas JM, Gudzune KA, Jay M. Obesity management in adults: a review. JAMA 2023;330:2000–15. 10.1001/jama.2023.19897. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34. Lingvay I, Cohen RV, Roux CWle, Sumithran P. Obesity in adults. Lancet 2024;404:972–87. 10.1016/S0140-6736(24)01210-8. [DOI] [PubMed] [Google Scholar]
  • 35. Pumpa KL, Dalton J, Mara JK, Zhang Y, Yip D. Identifying women at risk of weight gain after a breast cancer diagnosis: results from a cohort of Australian women. Health Promot J Austr 2022;33:138–47. 10.1002/hpja.474. [DOI] [PubMed] [Google Scholar]
  • 36. Uhelski A-CR, Blackford AL, Sheng JY, Snyder C, Lehman J, Visvanathan K, et al. Factors associated with weight gain in pre- and post-menopausal women receiving adjuvant endocrine therapy for breast cancer. J Cancer Surviv 2024;18:1683–96. 10.1007/s11764-023-01408-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Ligibel JA, Ballman KV, McCall LM, Goodwin PJ, Weiss A, Delahanty L, et al. Effect of a telephone-based weight loss intervention (WLI) on weight at 12-months in women with early breast cancer: results from the Breast Cancer Weight Loss (BWEL) trial. J Clin Oncol 2023;41:12001. 10.1200/jco.2023.41.16_suppl.12001. [DOI] [Google Scholar]
  • 38. Aune D, Markozannes G, Abar L, Balducci K, Cariolou M, Nanu N, et al. Physical activity and health-related quality of life in women with breast cancer: a meta-analysis. JNCI Cancer Spectr 2022;6:pkac072. 10.1093/jncics/pkac072. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Cooper CB, Neufeld EV, Dolezal BA, Martin JL. Sleep deprivation and obesity in adults: a brief narrative review. BMJ Open Sport Exerc Med 2018;4:e000392. 10.1136/bmjsem-2018-000392. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Mamalaki E, Tsapanou A, Anastasiou CA, Kosmidis MH, Dardiotis E, Hadjigeorgiou GM, et al. Associations between sleep and obesity indices in older adults: results from the HELIAD study. Aging Clin Exp Res 2019;31:1645–50. 10.1007/s40520-018-01113-2. [DOI] [PubMed] [Google Scholar]
  • 41. Häusler N, Heinzer R, Haba-Rubio J, Marques-Vidal P. Does sleep affect weight gain? Assessing subjective sleep and polysomnography measures in a population-based cohort study (CoLaus/HypnoLaus). Sleep 2019;42:zsz077. 10.1093/sleep/zsz077. [DOI] [PubMed] [Google Scholar]
  • 42. Sheng JY, Chen R, Rosner GL, Snyder CF, Appel LJ, Stearns V, et al. The impact of baseline sleep as a potential moderator of weight loss intervention in breast cancer survivors: results from the POWER-remote trial. Obesity (Silver Spring) 2025;34:334–43. 10.1002/oby.70096. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43. Montanari A, Smith M, Hunt C, Sheng JY, Stearns V, Coughlin JW. Cognitive-behavioral treatment for insomnia prior to behavioral weight loss in female breast cancer survivors: a preliminary study [Internet]. 2021. In: American Institute of Cancer Research Conference, Virtual. [Google Scholar]
  • 44. Valiyaveettil D, Joseph D, Malik M. Cardiotoxicity in breast cancer treatment: causes and mitigation. Cancer Treat Res Commun 2023;37:100760. 10.1016/j.ctarc.2023.100760. [DOI] [PubMed] [Google Scholar]
  • 45. Magkos F, Fraterrigo G, Yoshino J, Luecking C, Kirbach K, Kelly SC, et al. Effects of moderate and subsequent progressive weight loss on metabolic function and adipose tissue biology in humans with obesity. Cell Metab 2016;23:591–601. 10.1016/j.cmet.2016.02.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Ma C, Avenell A, Bolland M, Hudson J, Stewart F, Robertson C, et al. Effects of weight loss interventions for adults who are obese on mortality, cardiovascular disease, and cancer: systematic review and meta-analysis. BMJ 2017;359:j4849. 10.1136/bmj.j4849. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. Dauccia C, Agostinetto E, Arecco L, Lobo-Martins S, Gitto M, Lyon AR, et al. Cardiovascular toxicity of breast cancer treatments: from understanding to enhancing survivorship care. ESMO Open 2025;10:105128. 10.1016/j.esmoop.2025.105128. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48. Cho HJ, Song S, Kim Z, Youn HJ, Cho J, Min JW, et al. Associations of body mass index and weight change with circulating levels of high-sensitivity C-reactive protein, proinflammatory cytokines, and adiponectin among breast cancer survivors. Asia Pac J Clin Oncol 2023;19:113–25. 10.1111/ajco.13779. [DOI] [PubMed] [Google Scholar]
  • 49. Ryan DH, Yockey SR. Weight loss and improvement in comorbidity: differences at 5%, 10%, 15%, and over. Curr Obes Rep 2017;6:187–94. 10.1007/s13679-017-0262-y. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Data 1

includes 5 tables and 3 figures

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request. The data are not publicly available, as they are housed in REDCap, a secure web-based software tool that complies with the Health Insurance Portability and Accountability Act standards and is required by the Johns Hopkins Institutional Review Board. Please note that all requests must be reviewed and approved by the Johns Hopkins Institutional Review Board prior to fulfillment.


Articles from Clinical Cancer Research are provided here courtesy of American Association for Cancer Research

RESOURCES