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https://www.selleckchem.com/products/rg108.html Osteoporosis and osteopenia are diagnosed most commonly by evaluating the lowest T-score of BMD measurements, typically taken at three sites the L1-L4 lumbar spine, femoral neck, and total hip. This study aimed to evaluate the effect of using all three BMD measurements and multivariate statistical theory to evaluate how the diagnoses of osteoporosis and osteopenia change in simulation studies and in real data. First, it was found that the T-scores from these three BMD measurements rarely give concordant diagnoses using the same World Health Organization (WHO) and International Society for Clinical Densitometry (ISCD) guidelines, so that the diagnosis strongly depends on the BMD sites measured. Next, strong correlations were found between the BMD measurements at different sites within the same person, which resulted in increased congruence/concordance between the diagnoses obtained from the BMD T-scores. Multivariate statistical theory was used to show that the joint distribution of the BMD T-scores at differeh.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 regressio

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