OBJECTIVES: The purpose of this study was to investigate the influences of interruption and reinitiation of monthly minodronate therapy on the bone mineral density (BMD) and bone metabolism markers in postmenopausal women with osteoporosis. METHODS: Study patients were included if they had been administered monthly minodronate therapy for ≥6 months, interrupted the therapy, and reinitiated the therapy for ≥12 months. The BMD and bone metabolism markers were assessed at 4 time points: initiation, interruption, reinitiation and 1 year after reinitiation of therapy. RESULTS: A total of 23 patients were enrolled. The mean monthly minodronate treatment period was 23.8 ± 12.9 months following a mean interruption period of 11.9 ± 5.4 months. Once increased by monthly minodronate treatment for 2 years on average, the BMD of lumbar spine and radius did not significantly decrease even after an interruption for 1 year on average. However, the BMD of the femoral neck did decrease after interruption. The BMD of the lumbar spine and radius increased further after 1 year of monthly minodronate retreatment. The BMD of the femoral neck did not change. Once decreased after the treatment for an average of 2 years followed by an interruption for 1 year, bone metabolism markers increased gradually but did not recover to baseline levels. A potent suppressive effect on bone resorption was noted. The change rate was greater for the bone formation marker procollagen 1 N-terminal propeptide. CONCLUSIONS: Monthly minodronate treatment increases BMD and reduces bone metabolism markers. The effect lessens after treatment interruptions, and can be restored by retreatment.
Bone Density ; Bone Resorption ; Female ; Femur Neck ; Humans ; Metabolism ; Osteogenesis ; Osteoporosis ; Procollagen ; Radius ; Retreatment ; Spine

Objectives: The relationship between weight-related load and bone mineral density (BMD)/bone microstructure under normal load conditions using high-resolution peripheral quantitative computed tomography (HR-pQCT) remains unconfirmed. The study aims to investigate the differences in effect of body mass index (BMI) on BMD/bone microstructure of loaded and unloaded bones, respectively, in Japanese postmenopausal women. Methods: Fifty-seven postmenopausal women underwent HR-pQCT on the tibia and radius. Correlation analysis, principal component (PC) analysis, and hierarchical multiple regression were performed to examine the relationship between BMI and HR-pQCT parameters. Results: Several microstructural parameters of the tibia and radius correlated with BMI through a simple correlation analysis, and these relationships remained unchanged even with an age-adjusted partial correlation analysis. PC analysis was conducted using seven bone microstructure parameters. The first PC (PC1) reflected all parameters of trabecular and cortical bone microstructures, except for cortical porosity, whereas the second PC (PC2) reflected only cortical bone microstructure. Hierarchical multiple regression analysis indicated that BMI was more strongly related to BMD/bone microstructure in the tibia than in the radius. Furthermore, BMI was associated with trabecular/cortical BMD, and PC1 (not PC2) of the tibia and radius. Thus, BMI was strongly related to the trabecular bone microstructure rather than the cortical bone microstructure. Conclusions Our data confirmed that BMI is associated with volumetric BMD and trabecular bone microstructure parameters in the tibia and radius. However, although BMI may be more related to HRpQCT parameters in the tibia than in the radius, the magnitude of association is modest.

Objectives: The relationship between weight-related load and bone mineral density (BMD)/bone microstructure under normal load conditions using high-resolution peripheral quantitative computed tomography (HR-pQCT) remains unconfirmed. The study aims to investigate the differences in effect of body mass index (BMI) on BMD/bone microstructure of loaded and unloaded bones, respectively, in Japanese postmenopausal women. Methods: Fifty-seven postmenopausal women underwent HR-pQCT on the tibia and radius. Correlation analysis, principal component (PC) analysis, and hierarchical multiple regression were performed to examine the relationship between BMI and HR-pQCT parameters. Results: Several microstructural parameters of the tibia and radius correlated with BMI through a simple correlation analysis, and these relationships remained unchanged even with an age-adjusted partial correlation analysis. PC analysis was conducted using seven bone microstructure parameters. The first PC (PC1) reflected all parameters of trabecular and cortical bone microstructures, except for cortical porosity, whereas the second PC (PC2) reflected only cortical bone microstructure. Hierarchical multiple regression analysis indicated that BMI was more strongly related to BMD/bone microstructure in the tibia than in the radius. Furthermore, BMI was associated with trabecular/cortical BMD, and PC1 (not PC2) of the tibia and radius. Thus, BMI was strongly related to the trabecular bone microstructure rather than the cortical bone microstructure. Conclusions Our data confirmed that BMI is associated with volumetric BMD and trabecular bone microstructure parameters in the tibia and radius. However, although BMI may be more related to HRpQCT parameters in the tibia than in the radius, the magnitude of association is modest.

Objectives: Physical activity to maintain bone mass and strength is important for hip fracture prevention. We aim to investigate the relationship between physical performance/activity status and bone mineral density (BMD)/hip structural analysis (HSA) parameters among postmenopausal women in Japan. Methods: Sixty-two postmenopausal women diagnosed with osteoporosis (mean age: 72.61 ± 7.43 years) were enrolled in this cross-sectional observational study. They were evaluated for BMD and HSA in the proximal femur by dual-energy X-ray absorptiometry and underwent several physical performance tests, the Geriatric Locomotive Function Scale of 25 questions (GLFS-25). Principal component analysis (PCA) was used to summarize data on the BMD/HSA parameters. Partial correlation analysis, multiple regression analysis, and structural equation modeling (SEM) were performed to investigate the relationship between physical performance/activity status and BMD/HSA parameters of the proximal femur. Results: In a partial correlation analysis adjusted for age and body mass index (BMI), GLFS-25 scores were correlated with HSA parameter (|r| = 0.260–0.396, P < 0.05). Principal component 1 (PC1) calculated by PCA was interpreted as more reflective of bone strength based on the value of BMD/HSA parameters. The SEM results showed that the model created by the 3 questions (Q13, brisk walking; Q15, keep walking without rest; Q20, load-bearing tasks and housework) of the GLFS-25 had the best fit and was associated with the PC1 score (β = −0.444, P = 0.001). Conclusions The GLFS-25 score was associated with the BMD/HSA parameter, which may reflect the bone strength of the proximal femur as calculated by PCA.