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/lp/springer-journals/factors-associated-with-weight-gain-in-pre-and-post-menopausal-women-oLsQCsgNJ2
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- Springer Journals
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- Copyright © The Author(s) 2023
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- 1932-2259
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- 1932-2267
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- 10.1007/s11764-023-01408-y
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Abstract
Purpose Weight gain after breast cancer poses health risks. We aimed to identify factors associated with weight gain during adjuvant endocrine therapy (AET). Methods Women initiating AET enrolled in a prospective cohort. Participants completed FACT-ES plus PROMIS pain interference, depression, anxiety, fatigue, sleep disturbance and physical function measures at baseline, 3, 6, 12, 24, 36, 48 and 60 months. Treatment-emergent symptoms were defined as changes in scores in the direction indicative of worsening symptoms that exceeded the minimal important difference at 3 and/or 6 months compared to baseline. We used logistic regres- sion to evaluate associations of clinicodemographic features and treatment-emergent symptoms with clinically significant weight gain over 60 months (defined as ≥ 5% compared to baseline) in pre- and post-menopausal participants. Results Of 309 participants, 99 (32%) were pre-menopausal. The 60 months cumulative incidence of clinically significant weight gain was greater in pre- than post-menopausal participants (67% vs 43%, p < 0.001). Among pre-menopausal par- ticipants, treatment-emergent pain interference (OR 2.49), aromatase inhibitor receipt (OR 2.8), mastectomy, (OR 2.06) and White race (OR 7.13) were associated with weight gain. Among post-menopausal participants, treatment-emergent endocrine symptoms (OR 2.86), higher stage (OR 2.25) and White race (OR 2.29) were associated with weight gain while treatment- emergent physical function decline (OR 0.30) was associated with lower likelihood of weight gain. Conclusions Weight gain during AET is common, especially for pre-menopausal women. Clinicodemographic features and early treatment-emergent symptoms may identify at risk individuals. Implications for cancer survivors Patients at risk for weight gain can be identified early during AET. Clinical trials.gov identifier NCT01937052, registered September 3, 2013. Keywords Breast cancer · Adjuvant endocrine therapy · Weight gain · Patient-reported outcomes · Obesity * Vered Stearns vstearn1@jhmi.edu Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA Johns Hopkins Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA Division of Cancer Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA Present Address: Hematology/Oncology Fellowship Program, Vanderbilt University Medical Center, Nashville, TN, USA Present Address: Division of Statistics, Collaborative Inc., WCG , Washington, DC, USA Division of Biostatistics and Bioinformatics, Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, Sidney Kimmel Comprehensive Cancer Center, Johns MD, USA Hopkins School of Medicine, Under Armour Breast Health Innovation Center, The Skip Viragh Outpatient Cancer, Johns Hopkins Women’s Malignancies Disease Group, Johns Building 201 North Broadway Viragh 10th floor, Room Hopkins University School of Medicine, Baltimore, MD, USA 10291, Baltimore, MD 21287, USA Department of Health Policy and Management, Johns Hopkins Present Address: AstraZeneca, Gaithersburg, MD, USA Bloomberg School of Public Health, Baltimore, MD, USA Vol.:(0123456789) 1 3 Journal of Cancer Survivorship We report here results of a secondary analysis from a Introduction prospective clinic-based cohort of patients with HR-positive breast cancer receiving AET who completed serial PRO Obesity, defined as body mass index (BMI) > 30 kg/m , symptom assessments over 60 months. Our analysis sheds is common among patients with breast cancer, both at the further light on the association of AET with post-diagnosis time of diagnosis and afterwards [1–3]. Excess weight is an weight gain and on risk factors, including patient-reported established risk factor for developing breast cancer in post- symptoms, for weight gain during AET. We describe weight menopausal women [4, 5]. Weight gain after breast cancer trajectories and evaluate associations between clinicode- diagnosis is reported in up to 90% of women, with many mographic factors and symptoms emerging during the first studies suggesting pre-menopausal patients are at particular 6 months of AET with clinically significant weight gain risk for post-diagnosis weight gain [2, 5–19]. Weight gain throughout the course of AET. Given prior literature sug- after breast cancer can pose serious health consequences gesting patterns of weight gain during AET may vary by and can cause psychological distress and poor quality of menopausal status, known differences in the side effect pro- life [10, 20–29]. Breast cancer survivors with obesity or files of tamoxifen and AIs and differences in prescribing who gain clinically significant weight face higher risks of patterns for these agents according to menopausal status, recurrence and mortality [4, 10, 26–28, 30–36]. we conducted analyses separately for pre- and post-meno- The role of breast cancer therapy in post-diagnosis weight pausal participants[2, 47–50]. For this secondary analysis, gain is poorly defined. Multiple studies suggest receipt of we hypothesized that weight gain during AET is associated adjuvant chemotherapy is associated with weight gain; how- with patient-reported treatment-emergent symptoms and that ever, whether findings with regard to the association of adju- it differs according to menopausal status. Identification of vant endocrine therapy (AET) and weight gain have been factors associated with weight gain early in the course of inconsistent [2, 6–9, 11–15, 17, 18, 28, 37–43]. Over two AET may allow the opportunity for targeted interventions thirds of breast cancers are hormone receptor (HR)-positive to prevent weight gain in at-risk breast cancer survivors. and at least 5 years of AET reduces recurrence and death in patients with HR-positive disease [39, 44–46]. The type of AET administered often differs according to menopausal Methods status, with post-menopausal patients typically receiving an aromatase inhibitor (AI) and pre-menopausal patients receiv- Study population ing either tamoxifen, ovarian function suppression (OFS) with tamoxifen, or OFS with an AI [47–49]. While some stud- Women with HR-positive stage 0-III breast cancer initiat- ies have reported differences in the likelihood of weight gain ing AET with either tamoxifen or an AI were enrolled in an according to type of AET, others have not, and risk factors for IRB-approved prospective observational clinic-based cohort weight gain during AET are not well defined [2 , 6–9, 11–14]. from March 2012 through December 2016 (ClinicalTrials. AET is frequently associated with side effects such as gov Identifier: NCT01937052, registered September 3, 2013). musculoskeletal discomfort, fatigue, sleep disturbance, The cohort was comprised of a convenience sample of female mood changes, anxiety, and endocrine symptoms including patients with breast cancer age ≥ 18 years who were seen in hot flashes and vaginal dryness [29, 47, 50–64]. While each medical oncology clinics at Johns Hopkins clinical sites. of these symptoms may occur with any type of AET, the side Potential participants were identified by provider referral or effect profile differs somewhat by type of AET, as exempli- by screening clinic schedules. The type of AET prescribed fied by more frequent musculoskeletal symptoms with AIs was at the discretion of the treating provider. In addition to compared to tamoxifen [11, 50, 65–68]. Treatment-emergent tamoxifen or an AI, pre-menopausal participants could receive side effects with AET often develop soon after initiation concurrent OFS. Participants could enroll when they first [69–71]. AET and its side effects can affect quality of life, started AET or if they were switching from one AET agent to physical activity, sleep, and mood, all of which have been another. Participants were followed until the final PRO ques- associated with weight gain after breast cancer diagnosis [6, tionnaire or the last clinical encounter prior to the date the 11, 29, 51–58]. Unfortunately, side effects during AET are database was locked (May 15, 2020), whichever was longer. not always detected during routine clinical care. The use of Demographics, cancer characteristics, treatment and meno- patient-reported outcomes (PRO), health assessments from pausal status at diagnosis (classified as pre-menopausal or patients without interpretation by a member of the clinical post-menopausal) were obtained via review of the electronic team, typically collected via questionnaires, enhances symp- health record (EHR). Participants were eligible for inclusion tom detection [72–74]. To date, evaluation of the association in this secondary analysis if baseline weight and at least one between patient-reported symptoms and weight gain during follow-up weight were documented in the EHR. AET has been limited [6, 11, 29, 38, 51–58]. 1 3 Journal of Cancer Survivorship prior studies, we defined clinically significant weight gain as Patient‑reported outcomes weight gain of ≥ 5% compared to baseline, a weight change that has been associated with increased all-cause mortality PRO measures were administered electronically using the online PatientViewpoint interface [75–77]. Questionnaires after breast cancer [10, 11, 27, 28, 42]. were administered at baseline and 3, 6, 12, 24, 36, 48 and 60 months later. Measures included in this analysis are the Statistical analysis Patient-Reported Outcomes Measurement Information Sys- tem (PROMIS) Version 1.0 short forms for pain interfer- Participant demographics, cancer characteristics, cancer treatment, weight, BMI and PRO scores are presented with ence, depression, anxiety, fatigue, sleep disturbance and physical function plus the Endocrine Symptom Subscale descriptive statistics including mean (SD), median (range) and proportions. Clinically significant weight gain status of the Functional Assessment of Cancer Therapy (FACT- ES) [59, 78–80]. We defined treatment-emergent symptoms was treated as a dichotomous variable indicating whether patients experienced ≥ 5% weight gain from baseline at each as changes in PRO scores compared to baseline during the first 6 months of AET (i.e. at the 3 and/or 6-month time time point. Differential changes in weight gain status over time between the pre- and post-menopausal groups were points) that met or exceeded the minimal important differ - ence (MID) for each measure in the direction indicative of assessed with a mixed ee ff cts logistic regression model and corresponding interaction terms. Differences in the propor - worsening symptoms. The MID is the change in score on a PRO measure that represents the smallest difference per - tion of patients with treatment-emergent symptoms according to menopause status were assessed with Fisher’s exact tests. ceived by patients as beneficial or harmful and that would impact clinical management [81]. PROMIS measures are To estimate the incidence of weight gain during follow- up, time to weight gain was calculated as the time from base- scored with a T-score metric for which 50 is the popula- tion mean and 10 is the population standard deviation (SD). line to either the r fi st study time point where patients experi - enced ≥ 5% weight gain or last follow-up visit if they did not A higher score indicates more of the outcome measured. PROMIS measures have been validated in patients with gain ≥ 5% weight. The cumulative incidence of weight gain was estimated using the Kaplan–Meier method. early stage cancer with a MID of 3–5 points [78–80, 82, 83]. We considered the mid-point of this range, 4 points, We evaluated the association of clinicodemographic factors and symptoms emerging during the first 6 months as the MID for the PROMIS questionnaires in this analysis. Scores on the Endocrine Symptom Subscale of the FACT- of AET with clinically significant weight gain using uni- variate and multivariate logistic regression modeling with ES range from 0–76, with lower scores indicative of worse endocrine symptoms. We used 0.5 SD to define a medium generalized estimating equations (GEE) to account for the longitudinal design and correlation of repeated measures effect size as a conservative estimate of the MID for the Endocrine Symptom Subscale of the FACT-ES based on the within a participant. Univariate associations were estimated separately according to menopause status. Factors differen- distribution-based, Effect Size Method of identifying a MID for a PRO measure. In prior studies using the Endocrine tially associated with weight gain by menopause status were explored using interaction terms in the models. Multivariate Symptom Subscale of the FACT-ES in patients with early stage breast cancer, the reported mean (SD) was 59 (9.7), models were estimated separately for pre- and post-meno- pausal participants using a forward and backward stepwise thus we halved the SD and rounded this estimate to 5 points to identify the MID for this analysis [59, 81, 84]. selection approach based on Quasi-likelihood under the Independence model Criterion (QIC)[86]. The models with Weight and body mass index the lowest QIC were selected. Non-time dependent demo- graphic variables included in the models were age at enroll- Weight (in kg) and BMI were obtained from the EHR using ment, race (White versus Black/Other) and neighborhood poverty (NP) level. NP level was defined as the percentage measurements assessed during routine clinic visits. BMI was categorized according to the World Health Organiza- of persons living in a zip code with a family income below the federal poverty line (based on United States 2010 census tion categorization as underweight (< 18.5 kg/m ), normal 2 2 2 weight (18.5 kg/m – 24.9 kg/m ), overweight (25 kg/m data); this was used as a surrogate for socioeconomic status 2 2 (SES) with NP level > 15% considered an indicator of low – 29.9 kg/m ), or obese (> 30 kg/m ) [3, 85]. Per study pro- tocol, the heaviest weight and BMI documented in the medi- SES [87]. Non-time dependent clinical variables included baseline PRO scores, baseline BMI category (overweight/ cal record within ± 30 days of questionnaire collection was used in analysis. If a patient did not have a weight or BMI obese compared to normal/underweight), prior radiation (yes/no), prior chemotherapy (yes/no), mastectomy (yes/no), documented in the medical record within ± 30 days of each questionnaire time point, the weight value was missing for stage (classified as a continuous variable), number of con- comitant medications at baseline (self-reported), and type of that time point. Consistent with the threshold used in many 1 3 Journal of Cancer Survivorship AET (AI or tamoxifen). Since only 4 pre-menopausal par- weight gain by 12 months after AET initiation, and contin- ticipants received an AI, we conducted a sensitivity analysis ued over time, with a cumulative incidence of 52% experi- re-running the model selection for the pre-menopausal par- encing ≥ 5% weight gain by 60 months after AET initiation. ticipants excluding the variable for type of AET. There was The proportions of pre-menopausal and post-menopausal no formal hypothesis testing nor sample size considerations participants who gained ≥ 5% weight compared to baseline for this study. The findings presented here are for descriptive both increased over the course of follow-up (p-values evalu- purposes and no adjustments for multiple comparisons were ating weight gain status over time within pre-menopausal made. Analyses were performed with R version 4.0.3 [88]. and post-menopausal groups both < 0.001). However, com- pared to post-menopausal participants, significantly more pre-menopausal participants gained ≥ 5% weight over Results the course of follow-up (interaction p-value < 0.001). By 60 months, the cumulative incidence of ≥ 5% weight gain Participant characteristics compared to baseline was 67% for pre-menopausal and 43% for post-menopausal participants (Fig. 1). Mean (SD) weight Of the 321 participants in the overall cohort, baseline and at gain by 60 months for pre- and post-menopausal participants least one follow-up weight were available for 309 participants, was 3.5 (10.4) kg and 0.6 (6.5) kg, respectively. The num- who were therefore included in this secondary analysis. The ber of patients with missing weight measurements increased 12 participants excluded from this analysis due to missing over time for both pre- and post-menopausal participants weight were generally similar to the 309 who were included (Supplemental Table 3). (Supplemental Table 1). Among participants included in this analysis, 263 (85.1%) had stage I-II disease, 99 (32%) were Scores on PRO measures pre-menopausal, and 259 (83.8%) were White. Prior to initiat- ing AET, 140 (45.3%) underwent mastectomy, 205 (66.3%) Overall, mean scores on each PRO measure at baseline, 3 received radiation and 86 (28%) received chemotherapy. More and 6 months were within one SD of population means. pre-menopausal participants than post-menopausal partici- The number of completed questionnaires declined through pants received prior chemotherapy (33.7% versus 25.4%). follow-up (Supplemental Table 4). Treatment-emergent Overall, 132 (42.7%) participants initiated tamoxifen and 177 symptoms, defined as changes in PRO scores compared to (57.3%) initiated an AI. The type of AET differed according baseline at the 3 and/or 6-month time points that met or to menopausal status. Ninety-five (96%) and 4 (4%) pre-men- exceeded the MID in the direction indicative of worsening opausal participants initiated tamoxifen and AI, respectively. symptoms, were common, each occurring in 23%-42% of In contrast, 37 (17.6%) and 173 (82.4%) post-menopausal par- the overall study population (Fig. 2). Endocrine symptoms ticipants initiated tamoxifen and AI, respectively. Seventeen (42%) and sleep disturbance (37%) were the most common (17.2%) pre-menopausal participants received OFS. Only 5 treatment-emergent symptoms, followed by fatigue (30%), participants enrolled upon switching form one type of AET to anxiety (28%) and depression (26%). There were no statisti- another. Median follow-up was 56 months (Table 1). cally significant differences in the proportions of pre-men- Mean (SD) BMI at baseline for the entire study popula- opausal and post-menopausal participants who experienced tion included in this analysis was 27.5 kg/m (5.8). Baseline each type of treatment-emergent symptom (Fisher’s exact BMI was in the overweight category for 91 (29.4%) partici- test p-values all > 0.05). pants and in the obese category for 100 (32.2%) participants (Table 1). The distribution of baseline BMI categories dif- Association of treatment‑emergent symptoms fered by menopausal status with 47 (47.4%) pre-menopausal and clinicodemographic factors with weight compared to 144 (68.6%) post-menopausal participants hav- gain in pre‑menopausal and post‑menopausal ing a baseline BMI ≥ 25 kg/m (p < 0.001) (Supplemental participants Table 2). At baseline, 158 (61%) White participants, 24 (75%) Black participants and 9 (50%) participants of other Univariate and multivariate logistic regression analyses race were overweight or obese. of factors associated with ≥ 5% weight gain compared to baseline are shown in Table 2. In univariate analyses Weight gain among pre-menopausal participants, prior mastectomy (Odds Ratio [OR] 2.23, 95% Confidence Interval (CI) Overall, 121 (39.2%) participants experienced ≥ 5% weight 1.00–4.96, p = 0.05) and White race (OR 6.45, 95% CI gain compared to baseline on at least one follow-up assess- 1.18–35.25, p = 0.03) were associated with weight gain ment. Clinically significant weight gain frequently occurred while participants with obesity at baseline were less likely early, with a cumulative incidence of 19% experiencing ≥ 5% to gain ≥ 5% weight compared to baseline than those who 1 3 Journal of Cancer Survivorship Table 1 Baseline Characteristics of Study Population According to Menopausal Status Characteristic Pre-Menopausal Post-Menopausal All Participants N = 309 N = 99 N = 210 Mean Age in years (SD) 50.2 (6.6) 68.3 (7.4) 62.5 (11.1) Race—N (%) Black 9 (9.1) 23 (11) 32 (10.4) White 80 (80.8) 179 (85.2) 259 (83.8) Other 10 (10.1) 8 (3.8) 18 (5.8) Endocrine Therapy—N (%) Tamoxifen ± OFS 95 (96) 37 (17.6) 132 (42.7) AI ± OFS 4 (4) 173 (82.4) 177 (57.3) Enrolled upon switching from one endocrine therapy to another 0 (0) 5 (2.3) 5 (1.6) Stage—N (%) 0 3 (3) 22 (10.5) 25 (8.1) I 61 (61.6) 125 (59.5) 186 (60.2) II 31 (31.3) 46 (21.9) 77 (24.9) III 4 (4) 17 (8.1) 21 (6.8) ER-positive—N (%) 99 (100) 210 (100) 309 (100) PR-Positive—N (%) 93 (94.9) 179 (85.2) 272 (88.3) HER-2-Positive—N (%) 7 (7.3) 18 (9.6) 25 (8.8) Mastectomy—N (%) 59 (59.6) 81 (38.6) 140 (45.3) Radiation—N (%) 130 (69.1) 75 (62) 205 (66.3) Chemotherapy—N (%) 33 (33.7) 53 (25.4) 86 (28) Mean (SD) Baseline BMI (kg/m2) 25.9 (6.0) 28.2 (5.6) 27.5 (5.8) Obese – N (%) 20 (20.2) 80 (38.1) 100 (32.3) Overweight – N (%) 27 (27.2) 64 (30.5) 91 (29.4) Median Number of Concomitant Medications (Range) 3 (0–16) 5 (0–29) 4 (0–29) b,c NP Rate > 15%—N (%) 18 (18.2) 24 (11.5) 42 (13.7) Median Follow-up time in Months (Range) 58.1 (12.2–87.7) 54.7 (6.9–87.3) 56.0 (6.9–87.7) SD = Standard Deviation, OFS = Ovarian Function Suppression, ER = estrogen receptor, PR = progesterone receptor, HER2 = Human Epidermal Growth Factor Receptor-2, BMI = body mass index, NP = neighborhood poverty a. Seventeen pre-menopausal participants received OFS (17.2%). Of these, one received an AI and 16 received tamoxifen. No post-menopausal participants received OFS b. Denominator for percentages was based on the number of known assessments. PR status was missing for one pre-menopausal participant. HER2 status was missing for 3 pre-menopausal and 22 post-menopausal participants. Prior chemotherapy status was missing for one pre-meno- pausal and one post-menopausal participant. NP rate was missing for two post-menopausal participants c. NP rate is the percentage of persons living in a zip code with a family income below the federal poverty line based on United States census data were normal weight or underweight at baseline (OR 0.30, Different variables were selected for the final multi- 95% CI 0.10–0.93, p = 0.04). In univariate analysis among variate models of factors associated with clinically signifi- post-menopausal participants, higher tumor stage (OR cant weight gain among pre-and post-menopausal partici- 1.84, 95% CI 1.27–2.67, p = 0.001) and treatment-emer- pants. In the final pre-menopausal model, receipt of AI as gent endocrine symptoms (OR 2.05, 95% CI 1.10–3.82, opposed to tamoxifen (OR 2.8, 95% CI 0.9–8.77, p = 0.08), p = 0.02) were associated with greater likelihood of ≥ 5% prior mastectomy (OR 2.06, 95% CI 0.89–4.77, p = 0.09), weight gain while treatment-emergent decline in physi- treatment-emergent pain interference (OR 2.49, 95% CI cal function was associated with lower likelihood of ≥ 5% 0.99–6.24, p = 0.05) and White race (OR 7.13, 95% CI weight gain (OR 0.36, 95% CI 0.16–0.83, p = 0.02). The 1.29–39.38, p = 0.02) were associated with greater likeli- associations of treatment-emergent change in physical hood of weight gain ≥ 5% compared to baseline. In the function and treatment-emergent pain interference with final post-menopausal model, treatment-emergent endo- weight gain status differed by menopausal status (interac- crine symptoms (OR 2.86, 95% CI 1.55–5.26, p < 0.001), tion p-values both ≤ 0.05). higher stage (OR 2.25, CI 1.52–3.34, p < 0.001), and 1 3 Journal of Cancer Survivorship Fig. 1 Cumulative Incidence of 70% 67% Clinically Significant Weight Pre−Menopausal Gain at Each Time Point by 60% Post−Menopausal Menopausal Status. Bars indi- 54% Overall cate the cumulative incidence of 52% experiencing ≥ 5% weight gain 50% compared to baseline at each 44% 43% 41% time point. Gray bars indicate P, Change over time (Pre−Menopausal) < 0.0001 40% P, Change over time (Post−Menopausal) < 0.0001 the overall population; blue bars 34% 34% P, Interaction < 0.0001 indicate the post-menopausal 31% 29% 30% participants; and orange bars 26% indicate the pre-menopausal 23% 23% participants. Abbreviations: 19% 20% 17% MOS = Months 11% 10% 9% 10% 5% 5% 4% 0% 3 MOS 6 MOS 12 MOS 24 MOS36 MOS48 MOS60 MOS Fig. 2 Proportions of Partici- pants with Treatment-Emergent 70% Symptoms by Menopausal Sta- Pre−Menopausal tus. Bars indicate the proportion 60% Post−Menopausal of participants who experienced Overall treatment-emergent symptoms, defined as changes in PRO 50% 46% scores compared to baseline 43% 42% 40% at the 3 and/or 6-month time 40% 37% points that met or exceeded the 33% MID in the direction indicative 31% 30% 29% 29% 28% 30% 28% 28% of worsening symptoms; Gray 26% 25% 25% 24% 23% bars indicate the overall popula- 23% 22% tion; blue bars indicate the 20% 17% post-menopausal participants; and orange bars indicate the 10% pre-menopausal participants. Abbreviations: PRO = Patient- Reported Outcome, MID = Min- 0% imal Important Difference PhysicalPain EndocrineFatigue DepressionAnxiety Sleep Function Interference Symptoms Disturbance SYMPTOM DOMAINS White race (OR 2.29, 95% CI 0.82–6.37, p = 0.11) were Discussion associated with greater likelihood of ≥ 5% weight gain compared to baseline while treatment-emergent decline in In this study, we confirmed that clinically significant physical function (OR 0.3, 95% CI 0.13–0.68, p = 0.004) weight gain, defined as ≥ 5% compared to baseline, is an was associated with lower likelihood of ≥ 5% weight gain important problem, with a cumulative incidence by 5 years compared to baseline. In addition, compared to post- after AET initiation of 52% in our study population. While menopausal participants with baseline BMI < 25 kg/m , weight gain began soon after initiation of AET for some those with baseline BMI ≥ 30 kg/m were less likely to participants, it occurred later for others. Although pre- gain ≥ 5% weight compared to baseline (OR 0.56, 95% menopausal participants were less likely than post-men- CI 0.27–1.18, p = 0.13). In our sensitivity analysis, after opausal participants to have BMI ≥ 25 kg/m2 at baseline, excluding the type of AET as a candidate variable for the they were more likely to gain ≥ 5% weight by 60 months model for pre-menopausal participants, the model selected (67% versus 43%). An additional key finding of our study included the same variables with similar effect sizes (Sup- is that early treatment-emergent symptoms, defined as plemental Table 5). changes in PRO scores compared to baseline at the 3 and/ 1 3 Proportion of Participants with Treatment−Emergent Symptoms Cumulative Incidence of ≥ 5% Weight Gain from Baseline Journal of Cancer Survivorship Table 2 Univariate and Multiple Logistic Regression Analyses of Factors Associated with ≥ 5% Weight Gain by Menopausal Status Univariate Logistic Regression Model Variable Odds Ratio (OR) Interac- (95% confidence interval, p-value) tion p-value Pre-menopausal Post-menopausal Age (in years) 0.98 (0.91–1.05, 0.55) 0.98 (0.93–1.02, 0.32) 0.96 Radiation 0.56 (0.26–1.20, 0.14) 1.17 (0.61–2.27, 0.63) 0.15 Chemotherapy 1.63 (0.76–3.49, 0.21) 1.80 (0.92–3.54, 0.09) 0.75 Mastectomy 2.23 (1.00–4.96, 0.05) 1.12 (0.59–2.09, 0.74) 0.21 Higher Stage 1.00 (0.54–1.85, 0.99) 1.84 (1.27–2.67, 0.001) 0.08 AET (AI vs Tam) 4.85 (0.73–32.02, 0.10) 2.09 (0.77–5.64, 0.15) 0.51 Race (White vs Black/Other) 6.45 (1.18–35.25, 0.03) 2.03 (0.76–5.45, 0.16) 0.41 NP rate 0.89 (0.62–1.29, 0.54) 0.89 (0.68–1.17, 0.40) 0.9 b 2 2 Baseline BMI (25–29.9 kg/m vs < 25 kg/m ) 0.74 (0.29–1.85, 0.52) 1.13 (0.53–2.41, 0.75) 0.45 2 2 Baseline BMI (≥ 30 kg/m vs < 25 kg/m ) 0.30 (0.10–0.93, 0.04) 0.70 (0.34–1.46, 0.34) 0.29 Treatment-Emergent Decline in Physical Function 1.39 (0.53–3.62, 0.51) 0.36 (0.16–0.83, 0.02) 0.05 Treatment-Emergent Endocrine Symptoms 0.97 (0.45–2.07, 0.93) 2.05 (1.10–3.82, 0.02) 0.11 Treatment-Emergent Pain Interference 2.33 (0.89–6.09, 0.09) 0.54 (0.23–1.25, 0.15) 0.03 Treatment-Emergent Fatigue 2.08 (0.91–4.78, 0.09) 1.51 (0.79–2.86, 0.21) 0.62 Treatment-Emergent Depression 2.07 (0.90–4.79, 0.09) 1.00 (0.51–1.93, 0.99) 0.32 Treatment-Emergent Anxiety 0.76 (0.32–1.82, 0.54) 1.18 (0.63–2.23, 0.61) 0.47 Treatment-Emergent Sleep Disturbance 0.99 (0.45–2.15, 0.97) 1.16 (0.61–2.22, 0.65) 0.68 Multivariate Logistic Regression Model AET (AI vs Tam) 2.80 (0.90–8.77, 0.08) –– –– Mastectomy 2.06 (0.89–4.77, 0.09) ––- –– Treatment-Emergent Pain Interference 2.49 (0.99–6.24, 0.05) ––- –– Race (White vs Black/Other) 7.13 (1.29–39.4, 0.02) 2.29 (0.82–6.37, 0.11) –– 2 2 Baseline BMI (25–29.9 kg/m vs < 25 kg/m ) –– 0.99 (0.45–2.19, 0.98) –– 2 2 Baseline BMI (≥ 30 kg/m vs < 25 kg/m ) –– 0.56 (0.27–1.18, 0.13) –– Treatment-Emergent Endocrine Symptoms –– 2.86 (1.55–5.26, < 0.001) –– Treatment-Emergent Decline in Physical Function –– 0.30 (0.13–0.68, 0.004) –– Higher Stage –– 2.25 (1.52–3.34, < 0.001) –– Treatment-Emergent symptoms were defined as worsening PRO scores meeting or exceeding the MID at 3 and/or 6 months compared to base- line; AET = Adjuvant Endocrine Therapy, AI = Aromatase Inhibitor, Tam = Tamoxifen, BMI = Body Mass Index, NP = Neighborhood Poverty a. Odds ratios estimated from logistic regression models estimated with GEE with weight gain status as the dependent variable and terms for each variable and time point b. P-value for interaction between menopausal status and the variable on weight gain status, estimated from logistic regression models estimated with GEE with weight gain status as the dependent variable and terms for menopause status, the variable shown, and their interaction c. NP rate is the percentage of persons living in a zip code with a family income below the federal poverty line based on United States census data or 6-month time points that were in the direction indica- weight gain have been variable across prior studies [6, 7, 13, tive of worsening symptoms and that met or exceeded 17, 37, 41–43, 89]. Our study, in which the majority of par- the MID, were frequent, and, in multivariable modeling, ticipants did not receive chemotherapy, confirms that weight were associated with clinically significant weight gain gain during AET itself is a clinically important problem, through 5 years of AET in both pre- and post-menopausal although the observational design precludes determination participants. of causality. The mechanisms behind weight gain during While previous literature has consistently demonstrated adjuvant therapy for breast cancer are not clearly defined, but an association between adjuvant chemotherapy and weight may include factors such as reduced physical activity, dietary gain, findings with regard to whether AET is associated with changes, increased insulin resistance and inflammation [ 4, 1 3 Journal of Cancer Survivorship 41, 89, 90]. Additionally, treatment-induced menopause, a changes in PRO scores that meet or exceed the MID in the transition that may impact physiologic fat accumulation and direction indicative of worsening symptoms may be used to body composition, may explain the greater weight gain we identify patients at risk for weight gain during AET. and others have observed among pre-menopausal compared The mechanisms linking changes in symptoms and to post-menopausal women [2, 7–9, 13, 15, 18, 19, 91–94]. weight gain during AET are uncertain. Reduced physical Furthermore, young women may be at particular risk for activity due to joint pain while receiving AET may explain weight gain during adjuvant therapy because responsibilities the relationship we observed between increased pain inter- like career and family may take time away from exercise and ference and weight gain during AET in pre-menopausal par- healthy eating [11]. ticipants [11, 29, 95]. The relationship we observed between A novel aspect of our study is that we identified early declining physical function and lower likelihood of weight patient-reported treatment-emergent symptoms (defined gain during AET in post-menopausal participants may be as changes in PRO scores compared to baseline at the 3 attributable to loss of muscle mass in the setting of frailty. and/or 6-month time points that met or exceeded the MID Disrupted sleep due to vasomotor symptoms may lead to in the direction indicative of worsening symptomatology), fatigue, reduced exercise, and weight gain, explaining the that, in combination with baseline clinicodemographic fac- relationship we observed between endocrine symptoms and tors, were associated with clinically significant weight gain weight gain in post-menopausal participants. Additionally, over 5 years of AET. Among participants who were pre- other endocrine symptoms such as breast tenderness, mood menopausal at diagnosis, patient-reported treatment-emer- swings and irritability might lead to decreased physical gent pain interference was associated with ~ 2.5-fold higher activity and, in turn, to weight gain. likelihood of clinically significant weight gain. Although A difference in likelihood of clinically significant weight associated with weight gain in univariate analysis in the gain according to race was seen in both pre-menopausal and pre-menopausal participants, treatment-emergent fatigue post-menopausal participants, with > 5% weight gain from and depression were not selected for the final model. In baseline more frequent in White participants. Racial differ - post-menopausal participants, patient-reported treatment- ences in weight gain after breast cancer have been mixed in emergent endocrine symptoms were associated with 2.86 prior studies. [8, 100–103]. It is possible that differences in times higher likelihood of ≥ 5% weight gain while patient- weight gain during AET by race are attributable to differ - reported treatment-emergent decline in physical function ences in diet, activity or baseline BMI. While statistically was associated with a 70% lower likelihood of clinically significant, interpretation of differences according to race in significant weight gain. this analysis should be made with caution since the majority Few prior studies have evaluated associations between of participants were White. patient-reported symptoms during AET and weight gain. Among pre-menopausal participants in our study, prior Available data suggest worsening sexual function, physi- mastectomy and receipt of AI compared to tamoxifen were cal activity, endocrine symptoms, sleep disturbance, pain, also associated with weight gain. Weight gain after mastec- fatigue and anxiety are associated with weight gain [11, 29, tomy has previously been reported and may be attributable 52, 58, 95–98]. Weight gain is also associated with changes to post-operative upper extremity and chest wall pain, numb- in patient-reported function [11, 51]. Additionally, avoid- ness, and decreased range of motion leading to decreased ance of weight gain and maintenance of physical activity ability to exercise [9, 104]. While pain interference was are associated with reduced patient-reported symptoms, associated with weight gain in pre-menopausal women, improved function and improved quality of life [55, 99]. AI receipt was also independently associated with weight Our study builds on this limited data by comprehensively gain potentially due to other side effects not captured on evaluating multiple common AET-associated symptoms in the PROMIS pain interference measure, a tool not specific one cohort and demonstrating that early treatment-emergent to joint pain, that may lead to reduced physical activity and symptoms during AET are associated with weight gain over weight gain [95]. Additionally, in pre-menopausal women, 5 years of AET. Moreoever, our study demonstrates that AI therapy requires induction of menopause via either OFS the relationship of specific treatment-emergent symptoms or ablation which can alter metabolism and lead to weight with weight gain varies by menopausal status and that MIDs gain [45, 47, 94, 105]. on PRO measures can detect clinically relevant changes in Among the post-menopausal participants in our study, symptom severity early during AET that are associated with lower BMI at baseline and higher stage were also associated weight gain throughout the course of AET. While further with weight gain. Lower baseline BMI is a known risk fac- research is needed to confirm these associations between tor for weight gain since 5% body weight in a person with early treatment-emergent symptoms and weight gain dur- a lower BMI is less absolute weight than in someone with ing AET in pre- and post-menopausal women, our study a higher BMI [15, 102, 106]. Our study is consistent with suggests that treatment-emergent symptoms identified using other literature showing patients with higher stage breast 1 3 Journal of Cancer Survivorship cancer are at higher risk of weight gain likely due to differ - for the factors associated with clinically significant weight ent treatment regimens, more intense surgery or radiation gain in pre- and post-menopausal participants and that we treatments which could contribute to the risk of weight gain used the QIC model selection approach to build the multi- [2, 9, 18, 106]. variable models are other strengths of this study. The QIC Several recent trials have evaluated weight gain preven- model selection strategy is optimal for use with longitudinal tion and weight loss interventions for patients receiving data with repeated measures in individual participants and treatment for breast cancer and for breast cancer survivors, results in models with overall good correlation structure and with early data supporting efficacy with regard to weight fit. It must be stated, however, that the QIC model selec - endpoints [107–117]. Longer term follow-up of these studies tion approach is based on model likelihood, thus selection and ongoing trials such as the Breast Cancer Weight Loss of variables for inclusion in a multivariable model is not (BWEL) Study (NCT02750826) will determine if weight driven by a p-value threshold. As such, the QIC model selec- loss interventions translate into improvements in breast tion approach can yield final models in which variables with cancer survival outcomes also. Examples of interventions p > 0.05 are included as occurred in this study [86]. How- evaluated to date include face-to-face dietary counseling, ever, the directionality of the odds ratios in the final models telephone dietary counseling, physical exercise regimens we present supports the relationships between the selected and cooking classes, with combined dietary and physical variables and clinically significant weight gain despite some exercise interventions exhibiting the most promising results p-values exceeding 0.05. [107–115]. Given the association between treatment-emer- Our study also has weaknesses. Given that it was per- gent symptoms and weight gain during AET, it is conceiv- formed at a single institution in the United States with a pre- able that symptom management using evidence- based strat- dominantly White population and that few pre-menopausal egies to manage AET-associated symptoms could mitigate participants received OFS and/or an AI, generalizability may weight gain also [50]. However, to successfully implement be limited. In addition, missing PRO data due to incomplete weight gain prevention strategies during AET, it is critical surveys, reasons for which are unknown, and missing weight to identify at risk patients in whom the interventions may be data, due to the fact that weight assessments were only avail- most impactful. Our study indicates that treatment-emergent able if a participant had a routine clinical visit within the des- symptoms, as reported by patients soon after AET initia- ignated windows around PRO time points, are limitations. tion, and baseline clinicodemographic variables can identify Furthermore, we did not have information about specific patients at particular risk for clinically significant weight concomitant medications, such as anti-depressants, which can gain during AET. In the future, this finding may translate influence weight and may potentially confound the relation- into a strategy to identify patients to whom early interven- ship between the variables evaluated and weight gain. We tions to prevent weight gain could be targeted. Additionally, also did not have information about diet, physical activity this study and our prior publication, in which we reported or other comorbid health conditions, all of which may also symptoms over the 5-year course of AET in this cohort, be associated with weight gain. Nor did we collect data on demonstrate that PRO measures can identify clinically other body anthropometrics beyond weight and BMI, such meaningful treatment-emergent symptoms during AET, as weight circumference or body fat. Additionally, while the potentially offering the opportunity for enhanced symptom fact that we performed analyses separately according to meno- management strategies that may, secondarily, lead to lower pausal status is a strength of our study, it must be noted that likelihood of weight gain [118]. we assessed menopausal status at diagnosis and did not cap- Strengths of our study include use of clinically obtained ture changes in menopausal status over time and differences weight and height assessments (as opposed to patient- in patterns of treatment-emergent symptoms by menopausal reported measures), frequent weight assessment time points, status may have largely been driven by differences in receipt use of a defined threshold for clinically significant weight of AIs versus tamoxifen in pre- and post-menopausal par- gain that is supported by prior literature, and longer follow- ticipants. Further, although a change in a PRO score meeting up than many prior studies that focused on short-term weight or exceeding the MID is considered clinically meaningful, it gain during AET [2, 9, 11, 12, 15, 17–19, 93]. The large is not certain that a change of this extent is necessarily the sample size and contemporary real-world population are minimal significant change and MID thresholds may vary in also strengths of this study supporting generalizability of our different clinical scenarios [81]. It is possible that, if anchored findings. Additionally, our use of validated PRO measures to weight gain, different MID thresholds on the PRO measures assessing common symptoms during AET at baseline and could be identified, strengthening or weakening the associa- early during the course of AET plus our use of MID values tions between early treatment-emergent symptoms and clini- to define PRO score changes that represent clinically mean- cally significant weight gain during AET that we identified. ingful treatment-emergent symptoms are strengths of this Finally, all analyses presented are exploratory and were not study. Furthermore, the fact that we built separate models pre-specified in the study protocol. 1 3 Journal of Cancer Survivorship toring board for AstraZeneca and received non-financial support from In conclusion, this study confirms that weight gain during Foundation Medicine for study assays. AET for early breast cancer is an important clinical problem, Karen Lisa Smith MD MPH has received research support (to institu- especially in pre-menopausal patients. There are almost 4 mil- tion) from Pfizer. Karen Lisa Smith’s spouse has stock ownership in lion breast cancer survivors in the United States and those who ABT Labs and Abbvie. The following authors declare that they have no conflicts of interest: are overweight or obese face inferior outcomes with regard to Anna-Carson Rimer Uhelski MD. breast cancer, mental health and cardiovascular health [4, 10, Amanda L. Blackford ScM. 20–28, 30, 31, 34–36, 119]. Strategies to prevent weight gain Jennifer Y. Sheng MD in breast cancer survivors are an unmet need. We demonstrated Jennifer Lehman BS David Lim MS that patient-reported treatment-emergent symptoms early dur- ing AET and clinicodemographic factors present at AET initia- Ethics approval This study was approved by the Johns Hopkins Insti- tion are associated with weight gain over the course of AET, tutional Review Board. indicating that patients at risk for clinically significant weight Consent to participate All participants provided informed consent. gain can be identified and potentially targeted for weight gain prevention interventions. Future studies should evaluate use of Open Access This article is licensed under a Creative Commons Attri- the factors associated with weight gain identified in this study to bution 4.0 International License, which permits use, sharing, adapta- select pre- and post-menopausal breast cancer patients receiv- tion, distribution and reproduction in any medium or format, as long ing AET for weight gain prevention interventions, with the ulti- as you give appropriate credit to the original author(s) and the source, mate goal of preventing the adverse health effects associated provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are with weight gain and obesity after breast cancer. included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in Supplementary information The online version contains supplemen- the article's Creative Commons licence and your intended use is not tary material available at https://doi. or g/10. 1007/ s11764- 023- 01408-y . permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a Acknowledgements The views expressed do not necessarily reflect the copy of this licence, visit http://cr eativ ecommons. or g/licen ses/ b y/4.0/ . official policies of the Department of Health and Human Services, nor does the mention of trade names, commercial practices, or organiza- tions endorsed by the U.S. Government. Author contributions Conceptualization: Karen Smith. References Methodology: Karen Smith, Vered Stearns, Claire Snyder. Formal analysis and investigation: Amanda Blackford, Jennifer 1. Nyrop KA, Damone EM, Deal AM, Carey LA, Lorentsen M, Lehman. Shachar SS, et al. 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Journal
Journal of Cancer Survivorship: Research and Practice – Springer Journals
Published: Jun 1, 2023
Keywords: Breast cancer; Adjuvant endocrine therapy; Weight gain; Patient-reported outcomes; Obesity