Adjuvant endocrine therapy effects on bone mineral density and microstructure in women with breast cancer

Aromatase inhibitors, bone microstructure, and estimated bone strength in postmenopausal women with breast cancer: a 5-year prospective study

INTRODUCTION

Aromatase inhibitors (AIs) are the standard treatment for early breast cancer (EBC) and are typical causative agents of cancer treatment-induced bone loss. However, the effects of long-term treatment with these drugs on bone microstructure remain unclear.

MATERIALS AND METHODS

This prospective, single-arm observational study included postmenopausal, non-osteoporotic women with hormone receptor-positive EBC. Patients who underwent dual-energy X-ray absorptiometry (DXA), high-resolution peripheral quantitative computed tomography (HR-pQCT), and tartrate-resistant acid phosphatase-5b (TRACP-5b) or procollagen type I N-terminal propeptide levels were compared at baseline and at 60 months after commencing AI treatment.

RESULTS

Fifteen women were included in the study, with a median age of 58 years and a quartile range of 56.5-62.5 years. At 60 months, HR-pQCT revealed that the cortical area and thickness decreased with increased cortical porosity in the cortical bone. In addition, the number of trabeculae decreased and trabecular separation increased trabecular bones decreases, and trabecular bone separation opens, resulting in a decrease in the trabecular bone volume fraction. Total bone mineral density (BMD), trabecular volumetric BMD, and cortical volumetric BMD, and estimated bone strength significantly decreased. DXA BMD values significantly decreased in the total hip and femoral neck but not the lumbar spine. TRACP-5b values after 5 years of AI treatment showed a significant negative correlation with the rate of change in the total volumetric BMD in the distal tibia.

CONCLUSION

Postmenopausal women who received AIs for 5 years for EBC experienced significant deterioration in the bone microstructure, BMD, and estimated bone strength.

Efficacy of a single 5 mg zoledronic acid infusion in preventing bone loss and fracture in postmenopausal women with breast cancer

INTRODUCTION

Chemotherapy-induced bone loss (CTIBL) is common among breast cancer patients, requiring comprehensive assessment and intervention. Zoledronic acid, a strong inhibitor of bone resorption, is effective in CTIBL management, though information on dosing and intervals, particularly the efficacy of the 5 mg annual dose for osteoporosis in breast cancer patients, is limited.

MATERIALS AND METHODS

In this 12-month prospective observational study, 85 breast cancer patients were divided into three groups: 17 received no treatment, 17 received tamoxifen, and 51 received anastrozole or letrozole (AI). Post-surgery, patients were administered a single 5 mg dose of zoledronic acid and monitored over 12 months for changes in bone mineral density (BMD), fracture rates, and biochemical markers.

RESULTS

Initially, the AI group was the oldest, averaging 59.1 ± 8.7 years. At baseline, no significant differences in variables, except age, were observed. After 12 months, BMD increased in all groups following a single zoledronic acid dose, with the smallest increase in the AI group at the lumbar spine: no treatment (2.4% ± 6.1%), tamoxifen (2.6% ± 3.4%), AI (0.6% ± 14.5%) (p = 0.778). CTx and P1NP levels were consistently suppressed up to 12 months post-treatment, with smaller reductions in the AI group. There were no significant differences in fracture or bone metastasis rates among groups.

CONCLUSION

A single infusion of 5 mg zoledronic acid was effective in increasing bone density in breast cancer patients. However, AI-treated patients showed less improvement in vertebral bone mineral density and biochemical markers. Further long-term studies with larger cohorts are needed.

Chemotherapy effects on bone mineral density and microstructure in women with breast cancer

INTRODUCTION

Chemotherapy involves the administration of steroids to prevent nausea and vomiting; however, its effect on bone microstructure remains unknown. This study aimed to evaluate the changes in bone mineral density (BMD) and bone microstructure associated with chemotherapy using high-resolution peripheral quantitative computed tomography (HR-pQCT) in women with early breast cancer.

MATERIALS AND METHODS

This prospective single-arm observational study included non-osteoporotic, postmenopausal women with breast cancer. The patients underwent dual-energy X-ray absorptiometry (DXA), HR-pQCT, and tartrate-resistant acid phosphatase-5b (TRACP-5b) or procollagen type-I N-terminal propeptide (P1NP) measurements at baseline, end of chemotherapy, and 6 months after chemotherapy. The primary endpoint was the change in total volumetric BMD at the distal tibia and radius.

RESULTS

Eighteen women were included in the study (median age: 57 years; range: 55-62 years). At 6 months after chemotherapy, HR-pQCT indicated a significant decrease in total volumetric BMD (median: distal tibia -4.5%, p < 0.01; distal radius -2.3%, p < 0.01), cortical volumetric BMD (-1.9%, p < 0.01;  -0.8%, p = 0.07, respectively), and trabecular volumetric BMD (-1.1%, p = 0.09;  -3.0%, p < 0.01, respectively). The DXA BMD also showed a significant decrease in the lumbar spine (median: -4.5%, p < 0.01), total hip (-5.5%, p < 0.01), and femoral neck (-4.2%, p < 0.01). TRACP-5b and P1NP levels were significantly increased at the end of chemotherapy compared to baseline.

CONCLUSION

Postmenopausal women undergoing chemotherapy for early breast cancer experienced significant BMD deterioration in weight-bearing bone, which was further reduced 6 months after chemotherapy.

Machine learning predicts the risk of osteoporosis in patients with breast cancer and healthy women

OBJECTIVE

In this study, we investigated the effects of endocrine therapy and related drugs on the body composition and bone metabolism of patients with breast cancer. Additionally, using body composition-related indicators in machine learning algorithms, the risks of osteoporosis in patients with breast cancer and healthy women were predicted.

METHODS

We enrolled postmenopausal patients with breast cancer who were hospitalized in a tertiary hospital and postmenopausal women undergoing health checkups in our hospital between 2019 and 2021. The basic information, body composition, bone density-related indicators, and bone metabolism-related indicators of all the study subjects were recorded. Machine learning models were constructed using cross-validation.

RESULTS

Compared with a healthy population, the body composition of patients with breast cancer was low in bone mass, protein, body fat percentage, muscle, and basal metabolism, whereas total water, intracellular fluid, extracellular fluid, and waist-to-hip ratio were high. In patients with breast cancer, the bone mineral density (BMD), Z value, and T value were low and the proportion of bone loss and osteoporosis was high. BMD in patients with breast cancer was negatively correlated with age, endocrine therapy status, duration of medication, and duration of menopause, and it was positively correlated with body mass index (BMI) and basal metabolism. The parameters including body composition, age, hormone receptor status, and medication type were used for developing the machine learning model to predict osteoporosis risk in patients with breast cancer and healthy populations. The model showed a high accuracy in predicting osteoporosis, reflecting the predictive value of the model.

CONCLUSIONS

Patients with breast cancer may have changed body composition and BMD. Compared with the healthy population, the main indicators of osteoporosis in patients with breast cancer were reduced nonadipose tissue, increased risk of edema, altered fat distribution, and reduced BMD. In addition to age, duration of treatment, and duration of menopause, body composition-related indicators such as BMI and basal metabolism may be considerably associated with BMD of patients with breast cancer, suggesting that BMD status can be monitored in clinical practice by focusing on changes in the aforementioned indexes, which may provide a way to prevent preclinical osteoporosis.

Original Research: Oral Health Concerns of Female Breast Cancer Survivors on Adjuvant Endocrine Therapy

BACKGROUND

Oral complications from cancer treatments are among the adverse effects breast cancer survivors can face. Yet such complications are often overlooked in cancer survivorship care. Many breast cancer survivors are receiving adjuvant endocrine therapy, but there is limited understanding of potential oral complications from this therapy.

PURPOSE

This study aimed to compare aspects of oral health in female breast cancer survivors who were taking adjuvant endocrine therapy with those of survivors not taking such therapy.

METHODS

National Health and Nutrition Examination Survey data collected from January 2009 through March 2020 were used for the analysis. Female adults ages 20 years and older who had been diagnosed with breast cancer were included. Linear regression and χ 2 analyses were conducted to examine aspects of oral health, using IBM SPSS Complex Samples software, version 27.

RESULTS

In our sample of 423 female breast cancer survivors, 7.1% were taking tamoxifen, 7.8% were taking anastrozole, 4.3% were taking letrozole, and 2.9% were taking exemestane. Compared with the survivors not taking such therapy, a greater proportion of those taking it had decayed teeth, gum disease/problems, and were recommended for imminent dental care after oral health examination by dentists. The survivors who were not taking adjuvant endocrine therapy had more coronal cavities.

CONCLUSIONS

Data analysis showed that female breast cancer survivors taking adjuvant endocrine therapy appear more likely to have oral health issues than those not taking such therapy. Improved awareness of these issues is critical. Assessment and management guidelines to address these oral health issues are needed by health care providers.

High-resolution peripheral quantitative computed tomography: research or clinical practice?

High-resolution peripheral quantitative CT (HR-pQCT) is a low-dose three-dimensional imaging technique, originally developed for in vivo assessment of bone microarchitecture at the distal radius and tibia in osteoporosis. HR-pQCT has the ability to discriminate trabecular and cortical bone compartments, providing densitometric and structural parameters. At present, HR-pQCT is mostly used in research settings, despite evidence showing that it may be a valuable tool in osteoporosis and other diseases. This review summarizes the main applications of HR-pQCT and addresses the limitations that currently prevent its integration into routine clinical practice. In particular, the focus is on the use of HR-pQCT in primary and secondary osteoporosis, chronic kidney disease (CKD), endocrine disorders affecting bone, and rare diseases. A section on novel potential applications of HR-pQCT is also present, including assessment of rheumatic diseases, knee osteoarthritis, distal radius/scaphoid fractures, vascular calcifications, effect of medications, and skeletal muscle. The reviewed literature seems to suggest that a more widespread implementation of HR-pQCT in clinical practice would offer notable opportunities. For instance, HR-pQCT can improve the prediction of incident fractures beyond areal bone mineral density provided by dual-energy X-ray absorptiometry. In addition, HR-pQCT may be used for the monitoring of anti-osteoporotic therapy or for the assessment of mineral and bone disorder associated with CKD. Nevertheless, several obstacles currently prevent a broader use of HR-pQCT and would need to be targeted, such as the small number of installed machines worldwide, the uncertain cost-effectiveness, the need for improved reproducibility, and the limited availability of reference normative data sets.

Changes in Vertebral Marrow Fat Fraction Using 3D Fat Analysis & Calculation Technique Imaging Sequence in Aromatase Inhibitor-Treated Breast Cancer Women

Aromatase inhibitor (AI) is a cornerstone drug for postmenopausal women with estrogen receptor-positive early-stage breast cancer. Fat-bone interactions within the bone marrow milieu are growing areas of scientific interest. Although AI treatment could lead to deterioration of the skeleton, the association between AI medication and subsequent marrow adiposity remains elusive. A total of 40 postmenopausal, early-staged, and hormone receptor-positive breast cancer patients who underwent treatment with adjuvant AIs and 40 matched controls were included. Marrow proton density fat fraction (PDFF) at the L1-L4 vertebral bodies using 3D Fat Analysis & Calculation Technique imaging (FACT) sequence at 3.0T, bone mineral density (BMD) by dual-energy X-ray absorptiometry, and serum bone turnover biomarkers were determined at baseline and at 6 and 12 months. We found that, in comparison to baseline, an increase of type I collagen cross-linked telopeptide was detected at 12 months (P <0.05). From baseline to 12 months, the PDFF measured using FACT was greatly increased. At 12 months, the median percent change of PDFF (4.9% vs. 0.9%, P <0.05) was significantly different between the AI treatments and controls. The same trend was observed for the marrow PDFF at 6 months relative to the respective values at baseline. Although BMD values were significantly reduced after 12 months in AI-treated women, changes in BMD vs. baseline condition were not significantly different between the AI-treated and control groups [Δ BMD -1.6% to -1.8% vs. -0.3% to -0.6%, respectively, P > 0.05]. In the AI-treated group, Δ PDFF was associated with Δ BMD at the lumbar spine (r = -0.585, P < 0.001), but not in the controls. Taken together, over a 12-month period, spinal marrow fat content assessed with FACT sequence significantly increased in postmenopausal women with hormone-receptor-positive breast cancer receiving AI treatment.