Dataset Information

The Interaction of Lean Body Mass With Fat Body Mass Is Associated With Vertebral Fracture Prevalence in Women With Early Breast Cancer Undergoing Aromatase Inhibitor Therapy.

ABSTRACT: Aromatase inhibitors (AIs) induce depletion of estrogen levels, causing bone loss and increased fracture risk in women with breast cancer. High-fat body mass (FBM) emerged as an independent factor associated with the prevalence of morphometric vertebral fractures (VFs) in patients undergoing AIs. We explored the role of lean body mass (LBM) and the interaction of LBM with FBM in predicting the occurrence of VFs in postmenopausal women who were either AI-naïve or AI-treated. A total of 684 consecutive breast cancer patients were enrolled in this cross-sectional study. Each woman underwent a dual-energy X-ray absorptiometry (DXA) scan, measuring bone mineral density (BMD), LBM, and FBM; VFs were assessed using a quantitative morphometric analysis of DXA images. After propensity score matching, the study population was restricted to 480 women, 240 AI-naïve and 240 AI-treated. We used multivariable logistic regression models to explore the associations between baseline characteristics, VF prevalence and the interaction between LBM, FBM and AI therapy. No interaction between LBM and AI therapy on VF prevalence was shown. Conversely, we reported a significant interaction between LBM, FBM and AI therapy (p = .0311). Among AI-treated women having LBM below and FBM above or equal the median value, VF prevalence was numerically higher (15/31; 48.4%) than in other subgroups (VF prevalence: 35.7% in high-LBM and low-FBM group, 23.2% in high-LBM and high-FBM group, and 19.8% in low-LBM and low-FBM group). Among AI-naïve women, the greatest VF proportion was observed in the subgroup with LBM and FBM below median value (25/92; 27.2%). This study suggests a synergism between LBM and FBM in predicting the morphometric VF in women with early breast cancer undergoing AIs. This observation is new and deserves further investigation. The assessment of body composition by DXA might be useful when estimating fracture risk in this population. © 2020 American Society for Bone and Mineral Research © 2020 The Authors. JBMR Plus published by Wiley Periodicals LLC. on behalf of American Society for Bone and Mineral Research.

SUBMITTER: Monteverdi S

PROVIDER: S-EPMC7872339 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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The Interaction of Lean Body Mass With Fat Body Mass Is Associated With Vertebral Fracture Prevalence in Women With Early Breast Cancer Undergoing Aromatase Inhibitor Therapy.

Monteverdi Sara S Pedersini Rebecca R Gallo Fabio F Maffezzoni Filippo F Dalla Volta Alberto A Di Mauro Pierluigi P Turla Antonella A Vassalli Lucia L Ardine Mara M Formenti Anna Maria AM Simoncini Edda Lucia EL Giustina Andrea A Maroldi Roberto R Amoroso Vito V Berruti Alfredo A

JBMR plus 20201221 2

Aromatase inhibitors (AIs) induce depletion of estrogen levels, causing bone loss and increased fracture risk in women with breast cancer. High-fat body mass (FBM) emerged as an independent factor associated with the prevalence of morphometric vertebral fractures (VFs) in patients undergoing AIs. We explored the role of lean body mass (LBM) and the interaction of LBM with FBM in predicting the occurrence of VFs in postmenopausal women who were either AI-naïve or AI-treated. A total of 684 consec ...[more]

PMID: 33615109

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Project description:ImportanceAromatase inhibitors induce a profound depletion in serum estrogen levels. Postmenopausal obese women receiving aromatase inhibitor therapy may be at increased risk of bone fractures owing to the detrimental association of adiposity with bone quality and the loss of the protective effect of estrogens on bone mineral density.ObjectiveTo determine whether fat body mass (FBM), as measured by dual-energy x-ray absorptiometry, is associated with vertebral fracture prevalence in postmenopausal women undergoing adjuvant aromatase inhibitor therapy for breast cancer.Design, setting, and participantsIn this single-center, cross-sectional study, 556 postmenopausal women with early-stage breast cancer were consecutively enrolled from October 15, 2013, to June 30, 2018, and stratified according to whether they were aromatase inhibitor-naive or aromatase inhibitor-treated for at least 2 years. The database was locked on December 31, 2018, and data analysis was completed on February 28, 2019. Eligible patients in both groups had normal renal function, no metabolic diseases, and no previous or current treatment with antiosteoporotic drugs or glucocorticoids. Previous chemotherapy, but not tamoxifen, was permitted. Data were gathered once, at baseline.Main outcomes and measuresVertebral fracture prevalence associated with FBM in aromatase inhibitor-naive and aromatase inhibitor-treated patients.ResultsOf the 556 women enrolled, the mean age was 63.0 years (95% CI, 62.2-63.8 years). The 195 aromatase inhibitor-treated patients were older than the 361 aromatase inhibitor-naive patients (mean age, 66.1 vs 61.3 years; P < .001), had a higher body mass index (mean, 26.4 vs 25.3; P = .009), were less likely to engage in physical activity (65.3% vs 73.7%; P = .03), and were less likely to consume alcoholic beverages (68.4% vs 80.9%; P = .001). Among the aromatase inhibitor-naive patients, the vertebral fracture prevalence was higher in the subgroup with FBM below the median value than in those with high FBM, but the difference was not statistically significant (19.2% vs 13.3%; P = .13). Conversely, the proportion of vertebral fractures in the aromatase inhibitor-treated group was 20.0% in patients with low FBM vs 33.3% in patients with high FBM (P = .04). An opposite trend in the association of FBM with vertebral fracture prevalence according to aromatase inhibitor group was shown by multivariable analysis in the propensity score-matched sample: odds ratio, 0.38 (95% CI, 0.12-1.19) and 1.94 (95% CI, 0.67-5.64) in the aromatase inhibitor-naive and aromatase inhibitor-treated groups, respectively (odds ratio for the interaction, 5.77 [95% CI, 1.08-30.81]; P for interaction term = .03).Conclusions and relevanceFat body mass may be associated with fragility-related fractures in patients with breast cancer who undergo aromatase inhibitor therapy. If these data are confirmed, obesity could be included in the algorithm for assessing fracture risk and selecting patients to receive bone resorption inhibitors.

Project description:ImportanceWomen with early breast cancer (EBC) exposed to aromatase inhibitors (AIs) may experience fragility fractures despite treatment with bone-active drugs. Risk factors for fractures in patients receiving AIs and denosumab have not been explored to date.ObjectivesTo evaluate whether an association exists between dual x-ray absorptiometry (DXA)-measured fat body mass (FBM) and vertebral fracture (VF) progression in postmenopausal women with EBC undergoing adjuvant therapy with AIs in combination with denosumab and to examine whether VF was associated with common risk factors for bone fracture and parameters of body composition other than FBM.Design, setting, and participantsFor this prospective, single-center, cohort study, 237 patients with EBC who were undergoing adjuvant treatment with AIs and denosumab (60 mg every 6 months) were enrolled at the Breast Unit of the ASST Spedali Civili of Brescia from September 2014 to June 2018. Data analysis was conducted in June 2022.ExposureBody composition parameters, bone mineral density, and morphometric VFs were assessed by DXA at study entry and after 18 months of therapy.Main outcomes and measuresVF progression, defined as either new or worsening of preexisting VFs, between the 2 time points.ResultsOf the 237 patients enrolled (median [range] age, 61 [28-84] years), 17 (4.4%) reported VF progression. Univariable analysis found an association between VF progression and a history of clinical fractures (odds ratio [OR], 3.22; 95% CI, 1.19-8.74; P = .02), Fracture Risk Assessment Tool (FRAX) score for major fractures (OR, 4.42; 95% CI, 1.23-13.79; P = .04), percentage of FBM (OR, 6.04; 95% CI, 1.69-21.63; P = .006), and android fat (OR, 9.58; 95% CI, 1.17-78.21; P = .04) and an inverse association with appendicular lean mass index-FBM ratio (OR, 0.25, 95% CI, 0.08-0.82; P = .02). Multivariable analysis revealed percentage of FBM (OR, 5.41; 95% CI, 1.49-19.59; P = .01) and FRAX score (OR, 3.95; 95% CI, 1.09-14.39; P = .04) as independent variables associated with VF progression.Conclusions and relevanceThe findings of this study suggest that baseline FBM is an independent factor for VF progression in patients with EBC treated with adjuvant AIs and denosumab. This observation is new and indicates that diet and exercise may synergize with denosumab in the management of bone health in this patient setting.

Project description:BackgroundLittle is known about the association of changes in two body components, muscle and fat mass, with the risk of cardiovascular disease (CVD) among young adults. We investigated the association of changes in predicted lean body mass index (LBMI), appendicular skeletal muscle mass index (ASMI), and body fat mass index (BFMI) with the development of CVD among young adults.MethodsThis nationwide, population-based cohort study included 3 727 738 young adults [2 406 046 (64.5%) men and 1 321 692 (35.5%) women] aged 20-39 years without a previous history of CVD who underwent two health screening examinations during 2009-2010 and 2011-2012. Using validated and robust prediction equations, we calculated the changes in predicted LBMI, ASMI, and BFMI from the first to the second examinations.ResultsThe mean (SD) age was 32.2 (4.9) years, and 2 406 046 (64.5%) of the participants were men. A total of 23 344 CVD events were detected during 22 257 632 person-years of follow-up. Each 1 kg/m2 increase in predicted LBMI and ASMI change was associated with a reduced risk of CVD among men [adjusted hazard ratio (aHR): 0.86, 95% confidence interval (CI) 0.82-0.91; aHR: 0.76, 95% CI 0.69-0.82, respectively] and women (aHR: 0.77, 95% CI 0.63-0.95; aHR: 0.75, 95% CI 0.59-0.96). Each 1 kg/m2 increase in predicted BFMI change was associated with an increased risk of CVD among men (aHR: 1.16, 95% CI 1.10-1.22) and women (aHR: 1.32, 95% CI 1.06-1.65). In both sexes, decreases in predicted LBMI and ASMI were associated with greater CVD risk, and decreased predicted BFMI was associated with a reduced CVD risk. Those who maintained their BMI between -1 and +1 kg/m2 also had a decreased risk of CVD per 1 kg/m2 increase in predicted LBMI and ASMI change among men (aHR: 0.86, 95% CI 0.80-0.92; aHR: 0.85, 95% CI 0.76-0.95) and women (aHR: 0.62, 95% CI 0.47-0.83; aHR: 0.59, 95% CI 0.44-0.80) and had a greater risk of CVD per 1 kg/m2 increase in predicted BFMI change among men (aHR: 1.17, 95% CI 1.10-1.25) and women (aHR: 1.64, 95% CI 1.20-2.23). Regardless of changes in weight, such as from normal to obese or vice versa, these results were consistent.ConclusionsAmong young adults, increased predicted muscle mass or decreased predicted fat mass were associated with a reduced risk of development of CVD. Decreased predicted muscle mass or increased predicted fat mass were associated with an elevated risk of development of CVD.

Project description:During median follow-up 6.0 years in 9622 individuals, prior loss in estimated total body lean mass (TBLM), but not total body fat mass loss (TBFM), was associated with increased fracture risk, particularly for hip fracture.IntroductionWeight loss, and especially muscle loss, adversely affects skeletal health. The FRAX® tool considers baseline body mass index, but not body composition nor changes in its components over time. Our aim was to compare the independent associations between prior loss in DXA-estimated TBLM and TBFM and subsequent fracture risk.MethodsWe identified women and men age 40 years or older with two DXA assessments at least 1 year apart (median interval 3.3 years). TBLM and TBFM were estimated from weight, sex, and DXA of the spine and hip. Incident fractures and deaths were ascertained from linked population-based health service data after the date of the second DXA. Hazard ratios (HRs) from Cox regression models were used to study time to fracture from prior loss in TBLM and TBFM adjusted for FRAX-related covariates.ResultsThe study population consisted of 9622 individuals (mean age 67 [SD 10] years, 95% female). We identified 692 subjects with incident major osteoporotic fracture [MOF] and 194 with hip fracture. Mean TBLM loss was significantly greater in those with incident MOF and hip fracture (P < 0.001) while TBFM loss was only significantly greater in those with incident hip fracture (P < 0.001). Each SD greater TBLM loss was associated with 10-13% increased MOF risk and 29-38% increased hip fracture risk, adjusted for TBFM loss and other covariates. Prior TBFM loss was not associated with fractures when adjusted for TBLM loss.ConclusionsPrior loss in total body lean mass, but not in fat mass, is associated with increased fracture risk, particularly hip fracture, independent of other risk factors. This is consistent with the hypothesis that muscle loss (sarcopenia) adversely impacts skeletal health and fracture risk.

Project description:BackgroundAccurate obesity classification is important so that appropriate intervention can be instituted to modify metabolic risk factors. Commonly utilized body mass index (BMI) and percentage body fat (PBF) are influenced by lean mass whereas fat mass index (FMI) measures only body fat. This study compares the prevalence of obesity and metabolic risk factors with FMI, BMI and PBF using DXA (dual-energy x-ray absorptiometry).Methods489 women randomly recruited from the electoral roll were stratified into 4 age groups; 40-49, 50-59, 60-69 and 70-79 years from 2000 to 2001. Clinical data and DXA body composition were obtained. Statistical analyses were performed using Medcalc v15 (Ostend, Belgium) with significance level at p = 0.05 (two-tailed).ResultsThere was higher prevalence of obesity using PBF compared to BMI and FMI (p<0.001). This difference was greater from age 50-59 (p<0.05) which may be explained by age-related lean mass loss. PBF over-classified obesity in over 35% of normal and 95% of overweight categories compared to FMI and BMI. BMI has a sensitivity of 78.9% and specificity of 98.3% for obesity using FMI as the standard. BMI under-classified obesity in the overweight category by 14.9% compared to FMI. There was no difference in diabetes, dyslipidemia, hypertension and metabolic syndrome prevalence within the BMI-obesity and FMI-obesity categories (p>0.05).ConclusionPBF classified more obesity than BMI and FMI because of its low pre-determined threshold. The greater difference with PBF compared to BMI and FMI from the 50-59 decade onwards can be attributed to age-related lean mass loss. BMI had the lowest sensitivity for obesity diagnosis. BMI under-classified obesity in the overweight category compared to FMI due to its inability to differentiate lean mass. However, there was no significant difference in the prevalence of metabolic risk factors between BMI and FMI-obesity categories indicating that fat location may influence metabolic dysregulation.

Dataset Information

The Interaction of Lean Body Mass With Fat Body Mass Is Associated With Vertebral Fracture Prevalence in Women With Early Breast Cancer Undergoing Aromatase Inhibitor Therapy.

Publications

The Interaction of Lean Body Mass With Fat Body Mass Is Associated With Vertebral Fracture Prevalence in Women With Early Breast Cancer Undergoing Aromatase Inhibitor Therapy.

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