Baseline Body Mass Index Change Research Articles

Evaluating the impact of GLP-1 receptor agonists on weight management in patients with breast cancer undergoing endocrine therapy: A comparative analysis.

e13063 Background: Obesity has been linked to increased risk of recurrence in postmenopausal patients with history of Hormone Receptor positive + (HR) breast cancer. making weight management very important in this patient population. The use of endocrine therapy with aromatase inhibitor (AI) or selective estrogen modulators (SERM) in this population has been linked to weight gain (PMID: 37831449). This study evaluates the effectiveness of GLP-1 medications (Semaglutide, Liraglutide, Dulaglutide, Tirzepatide) in these patients, comparing weight loss outcomes to those in non-cancer populations. Methods: A retrospective analysis was conducted on breast cancer patients who were receiving endocrine therapy (AI or SERM) in combination with GLP-1 medications. The study primarily focused on evaluating mean baseline Body Mass Index (BMI), the proportion of patients with a BMI ≥30, and the mean percentage change in BMI at the 12-month mark, including 95% confidence intervals (CIs) for these changes. Results: The study found that the mean percentage changes in BMI at 12 months for the GLP-1 medications were as follows: Semaglutide resulted in a -4.34% change (95% CI [-7.66%, -1.02%]), in stark contrast to a -14% change reported in the general population (PMID: 33567185); Liraglutide showed a -3.51% change (95% CI [-8.48%, 1.45%]), compared to -8.4% (PMID: 26132939); Dulaglutide led to a -2.33% change (95% CI [-6.80%, 2.13%]), against -10.0% (PMID: 34189841); and Tirzepatide recorded a 2.31% change (CI [-11.47; 20.54]) relative to -15.0% (PMID: 35658024). These findings indicate a substantially reduced weight loss efficacy in breast cancer patients on endocrine therapy compared to the general population. Conclusions: The study concludes that breast cancer patients on endocrine therapy exhibit less significant weight loss with GLP-1 medication treatment than what has been observed in the general population. This suggests that endocrine therapy may reduce the weight-loss efficacy of GLP-1 medications in this particular patient group. Further prospective research is essential to elucidate the mechanisms behind this attenuated response and to develop effective weight management strategies tailored for breast cancer patients undergoing endocrine therapy.

Risk factors and prediction model for new-onset hypertensive disorders of pregnancy: a retrospective cohort study.

Hypertensive disorders of pregnancy (HDP) is a significant cause of maternal and neonatal mortality. This study aims to identify risk factors for new-onset HDP and to develop a prediction model for assessing the risk of new-onset hypertension during pregnancy. We included 446 pregnant women without baseline hypertension from Liyang People's Hospital at the first inspection, and they were followed up until delivery. We collected maternal clinical parameters and biomarkers between 16th and 20th weeks of gestation. Logistic regression was used to determine the effect of the risk factors on HDP. For model development, a backward selection algorithm was applied to choose pertinent biomarkers, and predictive models were created based on multiple machine learning methods (generalised linear model, multivariate adaptive regression splines, random forest, and k-nearest neighbours). Model performance was evaluated using the area under the curve. Out of the 446 participants, 153 developed new-onset HDP. The HDP group exhibited significantly higher baseline body mass index (BMI), weight change, baseline systolic/diastolic blood pressure, and platelet counts than the control group. The increase in baseline BMI, weight change, and baseline systolic and diastolic blood pressure significantly elevated the risk of HDP, with odds ratios and 95% confidence intervals of 1.10 (1.03-1.17), 1.10 (1.05-1.16), 1.04 (1.01-1.08), and 1.10 (1.05-1.14) respectively. Restricted cubic spline showed a linear dose-dependent association of baseline BMI and weight change with the risk of HDP. The random forest-based prediction model showed robust performance with the area under the curve of 0.85 in the training set. This study establishes a prediction model to evaluate the risk of new-onset HDP, which might facilitate the early diagnosis and management of HDP.

FRI082 Impact Of Setmelanotide On Metabolic Parameters And Vital Signs In Patients With Hypothalamic Obesity

Abstract Disclosure: M.J. Abuzzahab: Advisory Board Member; Self; Pfizer, Inc., Endo Pharmaceuticals, Rhythm Pharmaceuticals, Inc., Consynance. Consulting Fee; Self; Pfizer, Inc., Endo Pharmaceuticals, Consynance, Rhythm Pharmaceuticals, Inc. A. Shoemaker: Advisory Board Member; Self; Rhythm Pharmaceuticals, Saniona. M. Gottschalk: Advisory Board Member; Self; Rhythm Pharmaceuticals, Inc. Consulting Fee; Self; Rhythm Pharmaceuticals, Inc. J. Miller: Other; Self; Study funding from Rhythm Pharmaceuticals, Inc. G. Yuan: Employee; Self; Rhythm Pharmaceuticals, Inc. Stock Owner; Self; Rhythm Pharmaceuticals, Inc. S. Malhotra: Employee; Self; Rhythm Pharmaceuticals, Inc. Stock Owner; Self; Rhythm Pharmaceuticals, Inc. C. Scimia: Employee; Self; Rhythm Pharmaceuticals, Inc. Stock Owner; Self; Rhythm Pharmaceuticals, Inc. C.L. Roth: Other; Self; Study funding from Rhythm Pharmaceuticals, Inc. Background: Hypothalamic obesity (HO) is a severe form of obesity that results from insult to the hypothalamus, primarily from tumors, tumor resections, and radiotherapy treatment, which can impair melanocortin-4 receptor (MC4R) pathway signaling. Treatment with setmelanotide, an MC4R agonist, resulted in weight loss and hunger reduction in a Phase 2 trial of patients with HO. This analysis evaluated the impact of 16 weeks of setmelanotide on metabolic parameters and vital signs in patients with HO. Methods: A Phase 2 open-label trial of setmelanotide enrolled patients aged ≥6 to ≤40 years with obesity resulting from hypothalamic injury who completed tumor-related treatment ≥6 months before enrollment (NCT04725240). The primary endpoint was the proportion of patients with ≥5% reduction in baseline body mass index (BMI) after 16 weeks of setmelanotide. Exploratory endpoints of change from baseline in waist circumference and metabolic parameters, including fasting glucose and glycated hemoglobin, were evaluated. Vital signs, including heart rate and blood pressure, were also assessed. Descriptive statistics including changes at Week 16 from baseline are reported. Results: Eighteen patients were included in the study. At Week 16, most patients met the primary endpoint (88.9% [n/N=16/18]; P<0.0001), and 13 of 18 patients who completed treatment had ≥10% BMI reduction (mean [standard deviation (SD)] percent change, −14.5% [9.5%]). Across all patients, body weight was reduced by a mean (SD) of 12.6% (9.1%), and change in BMI Z score in patients aged ≥6 to <18 years was −1.3 (1.0). Overall, waist circumference was reduced by a mean (SD) of 12.0 (5.8) cm, which was a 10.4% (5.2%) reduction. Weight loss was predominately due to reduction in total fat mass rather than loss of lean mass. Most mean metabolic and vital sign values were within normal ranges at baseline, and given the short duration of the study, no changes in metabolic parameters were noted. Vital signs continued to remain normal during the 16-week study duration. Treatment-related adverse events occurred in all patients. The most frequent adverse events included nausea (61.1%; n=11), vomiting (33.3%; n=6), skin hyperpigmentation (33.3%; n=6), and diarrhea (22.2%; n=4). Conclusions: In a heterogeneous population of patients with HO secondary to treatment of hypothalamic tumors, setmelanotide led to weight loss and reduction in BMI and a favorable change in body composition. Efficacy and safety of setmelanotide will continue to be evaluated in a larger Phase 3 clinical trial. Presentation: Friday, June 16, 2023

Examining differences in long-term weight loss outcomes after bariatric surgery: The role of romantic relationship status.

This study tested for differences based on relationship status at the time of surgery in baseline body mass index (BMI), weight loss outcomes (change in BMI [ΔBMI], percent total weight loss [%TWL], percent excess weight loss [%EWL]), and rates of successful weight loss (defined as ≥ 50%EWL) up to 4-year postbariatric surgery. Data came from a secondary analysis of patients (N = 492) who were up to 4-year postsurgery and completed a presurgical psychological evaluation and postsurgical survey. Sixty-nine percent of participants were patients in committed relationships and 31% were single/divorced/widowed patients. Single patients had higher presurgical BMIs than those who were partnered (t = 2.28, p = .02). There were no differences between those who were partnered and singles regarding ΔBMI and %TWL, although singles had smaller %EWL (t = -2.08, p = .04), which became nonsignificant after controlling for covariates. Most participants had successful weight loss (76.8%); however, this was not related to romantic relationship status. The results suggest those who were partnered undergo surgery at better-starting weights than singles and maintain this advantage in the long term. Providers working with patients considering bariatric surgery could inquire about how their romantic and social relationships play a part in their decision-making process. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Postoperative Early Body Weight Loss Is a Risk Factor for Recurrence in Patients with pStage III Gastric Cancer

Introduction: The goal of this study was to determine whether postoperative early body weight loss (EWL) after radical gastrectomy is a risk factor for recurrence in patients with pathological stage III (pStage III) gastric cancer who received postoperative adjuvant chemotherapy, which included tegafur/gimeracil/oteracil (S-1). Methods: Patients who underwent gastrectomy for gastric cancer were identified from a prospectively managed gastric cancer database. We analyzed 58 consecutive patients who underwent radical gastrectomy with D2 lymph node dissection for confirmed pStage III gastric cancer treated postoperatively with adjuvant chemotherapy including S-1 between 2010 and 2019. Clinical and pathologic characteristics, baseline body mass index (BMI), and postoperative weights were extracted. Weight changes were evaluated from the preoperative period to the start of adjuvant chemotherapy. EWL was defined as % BMI change = (preoperative BMI – postoperative BMI at the start of adjuvant chemotherapy) × 100/preoperative BMI. Results: Of the 58 consecutive patients who underwent radical resection for gastric cancer, 72.4% were male, with a mean age of 65.5 years, and a mean preoperative BMI of 21.2 (range: 15.4–29.1) kg/m². The degree of EWL was found to be closely correlated to compliance with adjuvant chemotherapy. Multivariate analysis by Cox proportional hazard analysis revealed that EWL was an independent factor for relapse-free survival (RFS), and patients with an EWL of 15.9% or more severe had poorer RFS. Conclusion: EWL above a certain rate at the start of adjuvant chemotherapy was a predictor of poor compliance with adjuvant chemotherapy and a high risk of disease recurrence in patients with pStage III gastric cancer.

Association between body mass index change and mortality in critically ill patients: A retrospective observational study

ObjectivePrevious studies have emphasized the association between baseline body mass index (BMI) and mortality in patients during a stay in the intensive care unit (ICU). However, to our knowledge, few studies have focused on BMI change during an ICU stay. The aim of this study was to explore the prognostic value of BMI change during ICU hospitalization. MethodsThis was a multicenter, retrospective cohort study with data extracted from the eICU Collaborative Research Database. Logistic regression models were used to explore the relationship between BMI change and mortality in ICU patients. BMI change was calculated as follows: {[discharge ICU weight (kg) – admission ICU weight (kg)] / height (m)2]}.Interaction and subgroup analyses were conducted for patients grouped with baseline BMI on ICU admission (≥30 versus 25–29.9 versus <25 kg/m2), Acute Physiology and Chronic Health Evaluation (APACHE) IV score (<53 versus ≥53), and ICU length of stay (≥3 versus <3 d). ResultsCompared with those with weight loss (n = 17 134), patients with weight gain during ICU hospitalization (n = 17 436) were associated with higher hospital mortality (odds ratio [OR], 1.251; 95% confidence interval [CI], 1.155–1.356; P < 0.001) and ICU mortality (OR, 1.360; 95% CI, 1.227–1.506; P < 0.001) after multivariable adjustment. The associations remained robust in patients with different baseline BMI levels and were especially remarkable among those with higher APACHE IV score and the longer ICU stay. ConclusionsThe present study exposed the potential hazard of increasing BMI for hospital and ICU mortalities during ICU hospitalization and indicating that patients in the ICU may benefit from a more balanced nutritional strategy.

Abstract P015: Associations Of Physical Activity And Lactation Duration With Cardiometabolic Risk Factors: The Cardia Study

Background: Physical activity (PA) and lactation individually benefit cardiometabolic health. Joint associations of PA and lactation with cardiometabolic risk factors have not been described. Methods: We averaged PA across all attended exams and summed total lactation duration in 1,068 Black and White parous women who attended the Year 30 Coronary Artery Risk Development in Young Adults (CARDIA) examination. Two categories were created for PA (-PA: below median; +PA: ≥median) and lactation duration (-L: &lt;3 months, +L: ≥3months). Participants were assigned to one of four groups based on PA patterns and cumulative lactation duration: -PA/-L, -PA/+L, +PA/-L, +PA/+L (most favorable). Cardiometabolic risk factors measured at Y30 were combined and standardized into a composite cardiometabolic risk score. We used linear regression to evaluate associations of group assignments with individual cardiometabolic risk factors and risk score. Covariates included age, race, study center, parity, education, smoking, medication use, alcohol consumption, baseline body mass index (BMI), and baseline diet quality. Results: Median PA=256 exercise units (IQR: 168-379), and 581 (54%) of participants reported cumulative lactation duration ≥3 months. Of the 1,068 participants, 303 were in the -PA/-L category, 231 in -PA/+L, 184 in +PA/-L, and 350 in +PA/+L. Participants in the +PA/+L category were older, had more years of education, lower BMI, gained less weight during follow-up, and were less likely to be Black versus the -PA/-L category. Mean cardiometabolic risk scores improved across categories and were not significantly different between -PA/+L and +PA/-L: -PA/-L: 0.23±0.04, -PA/+L: 0.08±0.04, +PA/-L: -0.02±0.05, +PA/+L: -0.23±0.03 all p≤0.08. After adjustment, +PA/+L assignment was associated with a lower (better) cardiometabolic risk score (β= -0.15, 95%CI: -0.25, -0.04) with no interactive effect of race, p=0.22. Associations were nonsignificant after accounting for 30-year change in BMI. Conclusions: Attaining above average PA combined with ≥3 months of lactation was associated with the most favorable cardiometabolic risk score in Black and White women. Participants who achieved either one of these behaviors had lower risk scores versus those with neither behavior. Attaining these levels of PA and/or lactation may reduce cardiometabolic risk in parous women due to less weight gain over time.

Abstract P2-11-11: Impact of baseline body mass index (BMI) and weight changes after diagnosis in young women with early breast cancer (BC): A multicenter retrospective study

Abstract Background: Prior studies demonstrated that premenopausal obese women with BC have a poorer prognosis than non-obese patients (pts). We examined time trends in the prevalence of overweight and obesity among young women diagnosed with early BC and assessed the impact of baseline BMI and weight changes in disease outcomes. Patients and methods: Multicenter retrospective cohort study including young women (≤40yrs) diagnosed with stage I-III BC during 2000-2016 treated in two large Belgian hospitals. Data on baseline characteristics, treatment, and survival outcomes were collected. Pts were classified according to baseline BMI into underweight (&amp;lt;18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2) and obese (≥30 kg/m2). Landmark analysis at 2y after diagnosis (+/-6 months) was performed to evaluate the impact of weight changes (≥5% from baseline) on disease outcomes. Univariate hazard ratios were calculated for outcomes of interest (invasive disease-free survival [IDFS], distant recurrence-free interval [DRFI], overall survival [OS]). Multivariable analysis adjusting for factors that differed between groups was performed for the analysis of 2 BMI categories. Results: A total of 1,849 eligible pts were included, of whom 1,371 (74.1%) had a BMI recorded: 84 (6.1%) were underweight, 871 (63.5%) had normal weight, 304 (22.1%) were overweight and 112 (8.1%) were obese. Baseline BMI was similar across age groups. Overweight and obese pts had significantly larger tumor size when compared to underweight and normal weight pts (p=0.002) with similar rates of nodal involvement. The proportion of pts diagnosed with a BMI ≥25 significantly increased over time (OR: 1.03; 1.00-1.05 p=0.024). There was no difference in OS, DRFI and IDFS according to baseline BMI when grouping pts in the 4 BMI categories (underweight vs. normal weight vs. overweight vs. obese) or in the 2 BMI categories (underweight/normal weight vs. overweight/obese). Multivariate analysis with 2 BMI categories also did not demonstrate differences in OS, DRFI and IDFS. 1,023 pts had weight registered at 2y follow-up, of whom 360 (35.1%) were overweight, and 107 (10.4%) obese. Regarding weight changes, 117 (11.4%) presented weight loss, 617 (60.4%) stable weight, and 287 (28.1%) had weight gain. Weight gain was significantly associated with the use of endocrine therapy in general (p=0.029) and ovarian function suppression (p&amp;lt;0.001). In pts with baseline BMI ≥25, 59 (18.5%) lost weight, 185 (58%) maintained a stable weight, and 74 (23.2%) continued to gain weight. There was no statistically significant impact of weight changes at 2y on disease outcomes. Conclusions: Our time trend analysis suggests that the prevalence of overweight and obesity among young women with BC is increasing over time, highlighting the need for preventing overweight/obesity. In this retrospective analysis, BMI had no impact on disease outcomes. Prospective studies and analyzes of body composition can add important information in this regard. Weight gain after BC diagnosis was significantly associated with the use of endocrine therapy and ovarian function suppression and is a prevalent issue among young women, with 23% of overweight/obese pts at diagnosis continuing to gain weight. Further studies evaluating weight changes and interventions to prevent weight gain are needed to better inform survivorship programs. Table 1.- Impact of Baseline BMI and weight changes on disease outcomesOverall survival (OS)4 BMI categories (baseline)Hazard ratio2 BMI categories (baseline)Hazard ratioNormal weightReferenceUnderweight/normal weight (BMI&amp;lt;25)ReferenceUnderweight1.37 (0.8-2.2)Overweight1.01 (0.7-.1.3)Overweight/obese (BMI≥25)1.05 (0.7-1.3)Obese1.28 (0.4-1.2)Distant Recurrence-Free Interval (DRFI)Normal weightReferenceUnderweight/normal weight (BMI&amp;lt;25)ReferenceUnderweight0.86 (0.5-1.3)Overweight0.88 (0.6-1.1)Overweight/obese (BMI≥25)0.91 (0.7-1.1)Obese0.94 (0.6-1.3)Invasive disease-free survival (IDFS)Normal weightReferenceUnderweight/normal weight (BMI&amp;lt;25)ReferenceUnderweight0.88 (0.5-1.3)Overweight0.88 (0.6-1.1)Overweight/obese (BMI≥25)0.92 (0.7-1.1)Obese0.99 (0.6-1.4)Weight changes analysisWeight changes categoryHazard ratio for OSHazard ratio for DRFIHazard ratio for IDFSStable weightReferenceReferenceReferenceWeight Loss1.45 (0.9-2.2)1.11 (0.6-1.8)1.05 (0.6-1.6)Weight Gain0.77 (0.5-1.14)0.92 (0.6-1.3)0.92 (0.6-1.2) Citation Format: Maria Alice Franzoi, Kevin Punie, Annouschka Laenen, Boudewijn Dullens, Celia Fernandes Costa, Patrick Neven, Hans Wildiers, Matteo Lambertini, Evandro de Azambuja. Impact of baseline body mass index (BMI) and weight changes after diagnosis in young women with early breast cancer (BC): A multicenter retrospective study [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-11-11.

Decreasing severity of obesity from early to late adolescence and young adulthood associates with longitudinal metabolomic changes implicated in lower cardiometabolic disease risk.

Obesity in childhood is associated with metabolic dysfunction, adverse subclinical cardiovascular phenotypes and adult cardiovascular disease. Longitudinal studies of youth with obesity investigating changes in severity of obesity with metabolomic profiles are sparse. We investigated associations between (i) baseline body mass index (BMI) and follow-up metabolomic profiles; (ii) change in BMI with follow-up metabolomic profiles; and (iii) change in BMI with change in metabolomic profiles (mean interval 5.5 years). Participants (n = 98, 52% males) were recruited from the Childhood Overweight Biorepository of Australia study. At baseline and follow-up, BMI and the % >95th BMI-centile (percentage above the age-, and sex-specific 95th BMI-centile) indicate severity of obesity, and nuclear magnetic resonance spectroscopy profiling of 72 metabolites/ratios, log-transformed and scaled to standard deviations (SD), was performed in fasting serum. Fully adjusted linear regression analyses were performed. Mean (SD) age and % >95th BMI-centile were 10.3 (SD 3.5) years and 134.6% (19.0) at baseline, 15.8 (3.7) years and 130.7% (26.2) at follow-up. Change in BMI over time, but not baseline BMI, was associated with metabolites at follow-up. Each unit (kg/m2) decrease in sex- and age-adjusted BMI was associated with change (SD; 95% CI; p value) in metabolites of: alanine (-0.07; -0.11 to -0.04; p < 0.001), phenylalanine (-0.07; -0.10 to -0.04; p < 0.001), tyrosine (-0.07; -0.10 to -0.04; p < 0.001), glycoprotein acetyls (-0.06; -0.09 to -0.04; p < 0.001), degree of fatty acid unsaturation (0.06; 0.02 to 0.10; p = 0.003), monounsaturated fatty acids (-0.04; -0.07 to -0.01; p = 0.004), ratio of ApoB/ApoA1 (-0.05; -0.07 to -0.02; p = 0.001), VLDL-cholesterol (-0.04; -0.06 to -0.01; p = 0.01), HDL cholesterol (0.05; 0.08 to 0.1; p = 0.01), pyruvate (-0.08; -0.11 to -0.04; p < 0.001), acetoacetate (0.07; 0.02 to 0.11; p = 0.005) and 3-hydroxybuturate (0.07; 0.02 to 0.11; p = 0.01). Results using the % >95th BMI-centile were largely consistent with age- and sex-adjusted BMI measures. In children and young adults with obesity, decreasing the severity of obesity was associated with changes in metabolomic profiles consistent with lower cardiovascular and metabolic disease risk in adults.

Association between body mass index, its change and cognitive impairment among Chinese older adults: a community-based, 9-year prospective cohort study.

To examine the association of baseline body mass index (BMI) and BMI change with cognitive impairment among older adults in China. The study included data from the Chinese Longitudinal Healthy Longevity Study, a national community-based prospective cohort study from 2002 to 2018. Baseline BMI and BMI change were available for 12,027 adults aged older than 65years. Cognitive impairment was defined as Chinese version of the Mini Mental State Examination score lower than 18. Multivariable Cox proportional hazard model was used.Among 12,027 participants (mean age was 81.23years old and 47.48% were male), the proportion of underweight, normal, overweight and obese at baseline was 33.87%, 51.39%, 11.39% and 3.34%, respectively. During an average of 5.9years' follow-up, 3086 participants (4.35 per 100 person-years) with incident cognitive impairment were identified. Compared with normal weight group, adjusted hazard ratio (AHR) for cognitive impairment was 0.86 (95% CI 0.75-0.99) among overweight group, whereas corresponding AHR was 1.02 (95% CI 0.94-1.10) in underweight and 1.01 (95% CI 0.80-1.28) in obese participants. Large weight loss (< -10%) was significantly associated with an increased risk of cognitive impairment (AHR, 1.42, 95% CI 1.29-1.56), compared to stable weight status group (-5% ~ 5%). In the restricted cubic spline models, BMI change showed a reverse J-shaped association with cognitive impairment.BMI-defined overweight, but not obesity, was associated with a lower risk of cognitive impairment among elderly Chinese adults, while large weight loss was associated with an increased risk. These findings are consistent with weight loss in the prodromal phase of dementia.

Early mortality and cardiovascular disease, varied association with body mass index and its changes in insulin-treated diabetes: a nationwide study.

We investigated the hazards of cardiovascular diseases (CVDs) and all-cause death during follow-up according to baseline body mass index (BMI) and percent change in BMI among adults with insulin-treated diabetes. Using the Korean National Health Insurance Service datasets (2002-2017), the hazards of myocardial infarction (MI), stroke, and all-cause mortality during follow-up were analyzed according to baseline BMI and percent change in BMI among adults with insulin-treated diabetes and without baseline CVD and/or malignancy (N = 44,055). At baseline, 67.3% of total subjects were either obese or overweight. During a mean 3.8 years, 1,081 MI and 1,562 stroke cases developed; 2,847 deaths occurred over a mean 3.9 years. Compared with normal weight, overweight and obesity were associated with lower hazards of outcomes [hazard ratio (95% CI): 0.836 (0.712-0.981), 0.794 (0.687-0.917) for MI; 0.829 (0.726-0.946), 0.772 (0.684-0.870) for stroke; 0.740 (0.672-0.816), 0.666 (0.609-0.728) for death, respectively]. Underweight was associated with a higher hazard of all-cause death during follow-up [hazard ratio (95% CI): 2.035 (1.695-2.443)]. When the group with minimum absolute value for percent change in BMI was set as a reference, the relative reduction in BMI was associated with increased hazards of MI, stroke, and all-cause death, and relative increase in BMI was associated with increased hazards of stroke and all-cause death during follow-up. Among adults with insulin-treated diabetes, a high prevalence of overweight and obesity was observed, and baseline BMI category was inversely associated with CVD incidence and all-cause death during follow-up. Both weight loss and gain were associated with increased CVD incidence and all-cause death during follow-up, showing a U-shaped relationship between weight change and outcome. Stable body weight might be a predictor of a lower risk of CVDs and premature death among individuals with insulin-treated diabetes.

Automated computed tomography (CT)-derived skeletal muscle mass determination as a significant prognostic factor in colorectal cancer patients using deep neural network model.

3534 Background: Although recent evidence suggests skeletal muscle depletion predicts the survival of patients with cancer, the retrieval and manual measurement of the computed tomography (CT) images hinder clinical application in routine clinical practice. The advent of recent deep learning applications enables highly accurate noninvasive longitudinal evaluation of skeletal muscle mass (SMM) changes. Here, we evaluated the prognostic impact of DNN-measured skeletal muscle changes in colorectal cancer (CRC) patients. Methods: A total of 6,196 newly diagnosed CRC patients were analyzed in the Yonsei Cancer Registry Database between Jan 1, 2010, and Sep 30, 2020. SMM is measured by the Skeletal muscle index (SMI). The formula used was: L3 skeletal muscle cross-sectional area (cm2)/height2 (m2). Patients’ SMI patterns were grouped by difference ratio of initial and last SMI. Patients were also classified by BMI pattern with the result of K-means clustering. Association of baseline SMI, baseline body mass index (BMI), SMI changes, BMI changes, and demographic factors with overall survival (OS) were evaluated. Univariate and multivariate analyses were conducted. Concordance (c) statistics were used to test the predictive accuracy of survival models. Results: Fully automated UNet architecture-based deep learning algorithms were applied for the third lumbar transverse CT detection, skeletal muscle segmentation, and skeletal muscle area quantification in CRC patients undergoing abdominal CT between at the time of diagnosis and one year after the diagnosis. Baseline BMI distribution was 28% obese, 26% overweight, 42% normal weight, and 4% underweight. Patients in all SMI categories varied widely in BMI. Changes in SMI were categorized into three groups: SMI increase (33%), steady (45%), and decrease (22%) group. Similarly, BMI changes were categorized into three groups: BMI increase (24%), BMI stable (57%), and BMI decrease (19%) group. Low baseline SMI, low baseline BMI, SMI decrease, and BMI decrease were independently prognostic of survival. Intriguingly, BMI and SMI changes had a different prognostic impact in men and women. For women, the SMI increase group (hazard ratio [HR], 0.4; 95% CI, 0.3-0.7; P= 0.001) was associated with longer OS, while the SMI decrease group (HR, 1.2; 95% CI, 0.6-2.2; P= 0.619) was not associated with shorter OS, both compared with SMI steady group. Conclusions: Automated CT-derived SMM depletion had a negative prognostic impact independent of BMI and age in CRC patients. A noninvasive automatic deep learning algorithm provides a unique opportunity to apply to routine clinical practice and understand how and when cachexia impacts cancer prognosis.

Trends in body mass index before and after diagnosis of hidradenitis suppurativa.

A temporal relationship between hidradenitis suppurativa (HS) and obesity has not been established. To compare baseline body mass index (BMI) and change in BMI for patients with HS and controls before and after diagnosis. We performed a retrospective case-control analysis of 1284 patients with HS and controls matched for age, sex, race and calendar year between 1 January 1999 and 9 September 2019. BMI 7years prior to first HS diagnosis, and rate of BMI change, were compared for patients with HS and controls using linear mixed effects models. Baseline BMI was higher among patients with HS than controls [mean difference 3·03kgm-2 , 95% confidence interval (CI) 2·44-3·62; P<0·001)]. This difference was larger for women [mean difference 3·37kgm-2 (95% CI 2·73-4·01)] than men [mean difference 1·27kgm-2 (95% CI-0·20-2·73; interaction P=0·01)], and for patients with HS diagnosed before age 40years [mean difference 4·10kgm-2 (95% CI 3·15-5·06)] than those diagnosed after age 40years [mean difference 2·38kgm-2 (95% CI 1·63-3·12; interaction P<0·001)]. Prior to diagnosis, average annual increase in BMI among patients with HS was slightly higher than controls. There was no statistically significant change in annual BMI among patients with HS following diagnosis. Baseline BMI and, to a lesser extent, rate of BMI change appear to be risk factors for developing HS. The influence of BMI may play a larger role among female patients and younger patients.

Prior loss of body mass index, low body mass index, and central obesity independently contribute to higher rates of fractures in elderly women and men.

We aimed to comprehensively evaluate the association of body composition with fracture risk using longitudinal data from a Swedish cohort of 44,366 women and men (mean age of 70 years) and a subcohort of 5022 women. We estimated hazard ratios (HRs) of fracture for baseline body mass index (BMI), BMI change during the prior 12 and 18 years, baseline waist-to-height ratio, total and regional distribution of fat and lean mass, with and without areal bone mineral density (BMD) adjustment. During follow-up (median 8.7 years), 7290 individuals sustained a fracture, including 4279 fragility fractures, of which 1813 were hip fractures. Higher baseline BMI and prior gain in BMI were inversely associated with all types of fracture. Lower fracture rate with higher baseline BMI was seen within every category of prior BMI change, whereas higher prior BMI gain conferred a lower rate of fracture within those with normal baseline BMI. Each standard deviation (SD) higher baseline waist-to-height ratio, after adjustment for BMI, was associated with higher rates of hip fracture in both women and men (HR 1.12; 95% CI, 1.05-1.19). In the subcohort (median follow-up 10 years), higher baseline fat mass index (FMI) and appendicular lean mass index (LMI) showed fracture-protective effects. After BMD adjustment, higher baseline BMI, total LMI, FMI, and higher prior BMI gain were associated with higher fracture rate. Baseline fat distribution also was associated with fracture rate; a 1-SD higher android to gynoid fat mass ratio in prior BMI gainers was associated with BMD-adjusted HRs of 1.16 (95% CI, 1.05-1.28) for any fracture and 1.48 (95% CI, 1.16-1.89) for hip fracture. This pattern was not observed among prior BMI losers. These findings indicate that for optimal fracture prevention, low baseline BMI, prior BMI loss and high baseline central obesity should be avoided in both women and men. © 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Baseline prognostic nutritional index and changes in pretreatment body mass index associate with immunotherapy response in patients with advanced cancer

BackgroundRecent research suggests that baseline body mass index (BMI) is associated with response to immunotherapy. In this study, we test the hypothesis that worsening nutritional status prior to the start...

Increasing liver fat is associated with progression of cardiovascular risk factors.

Nonalcoholic fatty liver disease is associated with cardiovascular risk factors in cross-sectional analyses. However, less is known about how changes in liver fat associate with the progression of cardiovascular risk factors. A substudy (n=808) drawn from the Framingham Heart Study underwent serial computed tomography scans 6years apart. We performed multivariable-adjusted regression to determine the association between changes in liver fat and progression of cardiovascular risk factors. Each standard deviation increase in liver fat was associated with adverse progression of systolic blood pressure, diastolic blood pressure, fasting glucose, high-density lipoprotein and log triglycerides. After adjusting for baseline cardiovascular risk, baselinebody mass index (BMI),and change in BMI, increasing liver fat was significantly associated with adverse changes in fasting glucose and triglycerides. In a longitudinal cohort, increasing liver fat over 6years was associated with progression of cardiovascular risk factors, even after accounting for BMI changes.

Abstract PD3-09: Sulindac reduces breast density and alters collagen alignment in patients on aromatase inhibitors

Abstract Background. Preclinical and observational evidence supports cancer prevention activity of non-steroidal anti-inflammatory drugs (NSAIDs) in the breast via suppression of prostaglandin E2 (PGE2) synthesis by cyclooxygenase-2 (COX2). Evidence includes linking of PGE2 to aromatase activity and estrogen synthesis in breast adipose tissue, as well as effects on collagen and breast density (BD). Methods. In an open-label trial, we evaluated the effect of the non-selective NSAID sulindac at 150 mg bid for 12 months on BD in 52 postmenopausal women taking adjuvant aromatase inhibitors (AIs) for breast cancer. BD was measured using a fat-water decomposition MRI based BD measure (MRD) previously shown to be more quantitative than mammographic density. A non-randomized observation cohort of 46 postmenopausal women on AI without NSAID use was conducted in parallel to assess the effect of AI on MRD over 12 months. Eligible participants were recruited at two study sites and included women with an intact, unaffected contralateral breast and BI-RADS ≥ 2. Each subject’s MRI_BD measures at baseline and at 6 and 12 months were included in linear mixed models for longitudinal data. Log-transformation was applied to the outcome of BD. Covariates included log-transformed baseline BD, time on AI, and baseline body mass index (BMI) and change in BMI. Breast tissue collagen fiber alignment for 30 women with paired breast biopsies, before and after 6 months on sulindac, was examined using Second-Harmonic Generation (SHG) microscopy and analysis of the distribution (histogram) of ‘straight’ fibers in three randomly selected areas of breast tissue. Straightness of individual fibers was calculated as the linear length of a fiber divided by the distance along the fiber. Results. Participants on sulindac intervention had a significant change in BD relative to baseline BD at 6 (p=0.05) and 12 months (p&amp;lt;0.001). After adjusting for time on AI, baseline BMI and BMI change, the relative change in BD at 12 months from baseline BD was 10% lower (95% CI; -14.4, -5.4%) for women on sulindac. For the AI only group, no significant change from baseline BD was observed at 6 (p=0.50) or 12 months (p=0.17). The relative change in BD for the AI only group at 12 months was -3.5% (95% CI; -8.3, +1.6%). For women with baseline MRD_BD of ≥ 25%, the relative decrease in BD from baseline in the sulindac group was greater, at -16.3% (95% CI, -25.4, -6.2%). In contrast, there was no evidence for baseline BD effect on change in BD at 12 months in the AI only group whose baseline BD was ≥25% [-3.3% change at 12 mo (95% CI; -12.7, +7.1%)]. Exploratory analyses of collagen fiber alignment in the sulindac group at 6 months showed a significant decrease in straight collagen fibers (p=0.01). The decrease in collagen straightness correlated with a decrease in BD (rho=0.66, p=0.01). Conclusions. Twice daily 150 mg sulindac for 12 months in postmenopausal women on AIs was associated with a significant decrease in BD using MRD that was slightly higher for women with higher baseline BD. At the tissue level, the decrease in BD was associated with change in collagen straightness. No decrease in BD was observed in a non-randomized population of postmenopausal women on AI only therapy. These results suggest that sulindac decreases BD and may do so through effects on collagen alignment. Further investigation of sulindac for effects on BD, including synergy with AIs, for breast cancer prevention is indicated. Citation Format: Patricia Thompson, Chuan Huang, Betsy Wertheim, Christina Preece, Jie Yang, Jessica Martinez, Denise Roe, Pavani Chalasani, Alison Stopeck. Sulindac reduces breast density and alters collagen alignment in patients on aromatase inhibitors [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD3-09.

Effects of metformin in obesity treatment in different populations: a meta-analysis.

Objective:Some studies have shown that metformin can reduce body weight. However, metformin has not been officially approved as a medicine for weight loss because its effect on different populations remains inconsistent. This meta-analysis aimed to summarize the weight loss effect of metformin quantitatively.Method:The randomized controlled and high-quality case-control trials of metformin monotherapy in obesity treatment were eligible. Baseline body mass index (BMI) was chosen as a self-control to compare the changes in BMI of different populations before and after treatment. All changes were calculated as differences between the final and initial BMI values (with negative values indicating a decrease). Results were presented as weighted mean difference (WMD) with a 95% confidence interval (CI 95%). Subgroup analysis was performed based on baseline BMI, age, daily dose, and duration of medication.Results:A total of 21 trials (n = 1004) were included, and the meta-analysis of metformin treatment in different populations showed that metformin has a modest reduction in the BMI of included participants (WMD −0.98; 95% CI, −1.25 to −0.72), and the reduction of BMI was most significant in the simple obesity population (WMD −1.31; 95% CI, −2.07 to −0.54). The subgroup analysis showed that metformin treatment significantly reduced BMI in obesity patients with a BMI >35kg/m2 (WMD −1.12; 95% CI, −1.84 to −0.39) compared with before treatment. BMI in the high dose group decreased by 1.01 units (WMD−1.01; 95% CI, −1.29 to −0.73) and BMI did not continue to decrease significantly after treatment of more than 6 months.Conclusion:Patients treated with metformin experienced about a one-unit reduction in BMI at the end of treatment. But whether this decreased value produced enough weight loss (5% of baseline body weight) to qualify as a “weight loss drug” as current guidelines require, requires larger specific randomized control trials.

Glycemic control of newly-diagnosed type 2 diabetes with different baseline body mass index under the standardized metabolic disease management model

Objective To explore the glycemic control of newly-diagnosed type 2 diabetes with different levels of baseline body mass index (BMI) after 6 months treatment under the standardized metabolic disease management model. Methods (1) 163 patients of newly-diagnosed type 2 diabetes were divided into normal weight (BMI 18.5-23.9 kg/m2), overweight (BMI 24.0-27.9 kg/m2), and obese (BMI≥28 kg/m2) groups according to baseline BMI, the blood glucose and lipids levels were compared among 3 groups. (2) The blood glucose levels were compared among 3 groups after 6 months of standardized management. (3) The overweight and obese patients were divided into group weight loss≥5% and group weight loss<5% or weight gain in 6 months. The blood glucose levels were compared. Results (1) At baseline, overweight and obese groups had higher homeostasis model assessment for insulin resistance and lower high density lipoprotein-cholesterol compared with normal weight group. (2) After 6 months of treatment, HbA1C and HbA1C reduction showed no difference among 3 groups (normal, overweight and obese) after adjusted by baseline HbA1C. The rate of HbA1C 0.05). (3) After 6 months of treatment, 32.28% overweight and obese patients lost weight by ≥ 5%, while HbA1Cand HbA1Creduction showed no difference between 2 groups (weight loss≥5% and weight gain or weight loss 0.05). Group weight loss≥5% had better glucose control (92.68% vs 77.91%, P<0.05). Conclusions As BMI increased, insulin resistance and lipid disorders were more serious in newly-diagnosed type 2 diabetes. After 6 months of standardized metabolic management, newly-diagnosed type 2 diabetes with different baseline BMI and weight changes both achieved good glycemic control. In addition, patients losing weight equal to or more than 5% achieved higher attainment of HbA1C targets. Key words: Newly-diagnosed type 2 diabetes; Body mass index; HbA1C; Weight changes

636-P: Effect of Obesity and Weight Variations on the Decline of Ankle-Brachial Index in Type 2 Diabetes Subjects without Peripheral Artery Disease

Object: There are very few studies that evaluate the influence of obesity and weight variations on change in ankle-brachial index (ABI) in subjects with type 2 diabetes (T2D) but without peripheral artery disease (PAD). Methods: In this case-control study, T2D subjects who were without baseline PAD (0.9 ≤ ABI &amp;lt; 1.4), and received minimum 2-year interval ABI exams were included. Subjects with prior diagnosed or treated PAD were excluded. Baseline body mass index (BMI) of all subjects was categorized as normal weight (&amp;lt; 23 kg/m2), overweight (23∼25 kg/m2), and obesity (≥ 25 kg/m2). Weight changes during follow-up were categorized by the percentage of weight change; weight loss (&amp;lt; -3%), stable (-3∼3%), gain (&amp;gt; 3%). Subjects with ABI decline were defined as one or both legs worsened to the abnormal (ABI &amp;lt; 0.9) at follow-up exam. Results: A total of 575 subjects were analyzed (188 normal, 140 overweight, and 245 obesity). During the median 2.9 years of follow-up period, 122 (21.2%) subjects showed ABI decline. When split by category of BMI and weight change, the incidence rate of ABI decline showed stepwise increasing pattern according to the obesity and weight gain. Multivariable logistic regression analysis showed that baseline obesity (vs. normal) was significantly associated with the risk of developing ABI decline after adjusting for age, sex, smoking, diabetes duration, mean HbA1c, GFR, LDL cholesterol, blood pressure, hypertensive medication, insulin use, statin use, antiplatelet use, and weight change (OR = 2.06, 95% CI = 1.22 - 3.49). On the contrary, weight loss was significantly associated with reduction in risk of developing ABI decline (OR = 0.52, 95% CI = 0.31 - 0.86). Conclusion: Obesity is an independent risk factor for developing ABI decline in T2D subjects without PAD, whereas weight loss is an independent protective factor. Weight loss should be emphasized especially in obese subjects with T2D. Disclosure Y. Yang: None. J. Lim: None. E. Lee: None. K. Yoon: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Merck Sharp &amp; Dohme Corp., Novo Nordisk Inc. Speaker's Bureau; Self; Takeda Pharmaceutical Company Limited. B. Cha: None. S. Lee: None. Y. Cho: None.