Screening for the primary prevention of fragility fractures among adults aged 40 years and older in primary care: systematic reviews of the effects and acceptability of screening and treatment, and the accuracy of risk prediction tools

Bone-active drugs in premenopausal women with breast cancer under hormone-deprivation therapies

BACKGROUND

Bone health management in premenopausal women with breast cancer (BC) under hormone-deprivation therapies (HDTs) is often challenging, and the effectiveness of bone-active drugs is still unknown.

METHODS

This retrospective multicenter study included 306 premenopausal women with early BC undergoing HDTs. Bone mineral density (BMD) and morphometric vertebral fractures (VFs) were assessed 12 months after HDT initiation and then after at least 24 months.

RESULTS

After initial assessment, bone-active drugs were prescribed in 77.5% of women (151 denosumab 60 mg/6 months, 86 bisphosphonates). After 47.0 ± 20.1 months, new VFs were found in 16 women (5.2%). Vertebral fracture risk was significantly associated with obesity (odds ratio [OR] 3.87, P = .028), family history of hip fractures or VFs (OR 3.21, P = .040], chemotherapy-induced menopause (OR 6.48, P < .001), preexisting VFs (OR 25.36, P < .001), baseline T-score less than or equal to -2.5 standard deviation (SD) at any skeletal site (OR 4.14, P = .036), and changes at lumbar and total hip BMD (OR 0.94, P = .038 and OR 0.88, P < .001, respectively). New VFs occurred more frequently in women untreated compared to those treated with bone-active drugs (14/69, 20.8% vs 2/237, 0.8%; P < .001) and the anti-fracture effectiveness remained significant after correction for BMI (OR 0.03; P < .001), family history of fractures (OR 0.03; P < .001), chemotherapy-induced menopause (OR 0.04; P < .001), and preexisting VFs (OR 0.01; P < .001).

CONCLUSIONS

Premenopausal women under HDTs are at high risk of VFs in relationship with high BMI, densitometric diagnosis of osteoporosis, preexisting VFs, and family history of osteoporotic fractures. Vertebral fractures in this setting might be effectively prevented by bisphosphonates or denosumab.

Comprehensive Evidence-Based Health Maintenance

The potential of primary prevention to prevent, delay, or ameliorate disease is immense. However, the total spending on preventive services in the United States remains astoundingly small and represents a meager 3.5% of total health care spending. Moreover, training focused on prevention in medical schools is often neglected, and time-constrained primary providers frequently omit effective preventive and early detection measures, or perform them perfunctorily. Indeed, preventable conditions of serious consequences including "premature" mortality, cardiovascular events, and major organ failure are ubiquitous with the global obesity and diabetes epidemics, and the ongoing high prevalence of noxious habits and drug abuse. Although each aspect has been the subject of extensive research, a succinct evidence-based summary is scarce. We have conducted a review of high-quality evidence (systematic reviews, meta-analyses, and practice guidelines) over the last 20 years to extract the best updated recommendations on comprehensive disease prevention and approved screening, briefly citing significant risk reductions by lifestyle interventions, pharmacological prevention, cancer screening, other endorsed screening, immunizations, and issues in the patient-provider interface.

The potential role for artificial intelligence in fracture risk prediction

Osteoporotic fractures are a major health challenge in older adults. Despite the availability of safe and effective therapies for osteoporosis, these therapies are underused in individuals at high risk for fracture, calling for better case-finding and fracture risk assessment strategies. Artificial intelligence (AI) and machine learning (ML) hold promise for enhancing identification of individuals at high risk for fracture by distilling useful features from high-dimensional data derived from medical records, imaging, and wearable devices. AI-ML could enable automated opportunistic screening for vertebral fractures and osteoporosis, home-based monitoring and intervention targeting lifestyle factors, and integration of multimodal features to leverage fracture prediction, ultimately aiding improved fracture risk assessment and individualised treatment. Optimism must be balanced with consideration for the explainability of AI-ML models, biases (including information inequity in numerically under-represented populations), model limitations, and net clinical benefit and workload impact. Clinical integration of AI-ML algorithms has the potential to transform osteoporosis management, offering a more personalised approach to reduce the burden of osteoporotic fractures.

Prediction of Osteoporotic Hip Fracture Outcome: Comparative Accuracy of 27 Immune-Inflammatory-Metabolic Markers and Related Conceptual Issues

Objectives: This study, based on the concept of immuno-inflammatory-metabolic (IIM) dysregulation, investigated and compared the prognostic impact of 27 indices at admission for prediction of postoperative myocardial injury (PMI) and/or hospital death in hip fracture (HF) patients. Methods: In consecutive HF patient (n = 1273, mean age 82.9 ± 8.7 years, 73.5% females) demographics, medical history, laboratory parameters, and outcomes were recorded prospectively. Multiple logistic regression and receiver-operating characteristic analyses (the area under the curve, AUC) were used to establish the predictive role for each biomarker. Results: Among 27 IIM biomarkers, 10 indices were significantly associated with development of PMI and 16 were indicative of a fatal outcome; in the subset of patients aged >80 years with ischaemic heart disease (IHD, the highest risk group: 90.2% of all deaths), the corresponding figures were 26 and 20. In the latter group, the five strongest preoperative predictors for PMI were anaemia (AUC 0.7879), monocyte/eosinophil ratio > 13.0 (AUC 0.7814), neutrophil/lymphocyte ratio > 7.5 (AUC 0.7784), eosinophil count < 1.1 × 109/L (AUC 0.7780), and neutrophil/albumin × 10 > 2.4 (AUC 0.7732); additionally, sensitivity was 83.1-75.4% and specificity was 82.1-75.0%. The highest predictors of in-hospital death were platelet/lymphocyte ratio > 280.0 (AUC 0.8390), lymphocyte/monocyte ratio < 1.1 (AUC 0.8375), albumin < 33 g/L (AUC 0.7889), red cell distribution width > 14.5% (AUC 0.7739), and anaemia (AUC 0.7604), sensitivity 88.2% and above, and specificity 85.1-79.3%. Internal validation confirmed the predictive value of the models. Conclusions: Comparison of 27 IIM indices in HF patients identified several simple, widely available, and inexpensive parameters highly predictive for PMI and/or in-hospital death. The applicability of IIM biomarkers to diagnose and predict risks for chronic diseases, including OP/OF, in the preclinical stages is discussed.

Proteomic Insights into Osteoporosis: Unraveling Diagnostic Markers of and Therapeutic Targets for the Metabolic Bone Disease

Osteoporosis (OP), a prevalent skeletal disorder characterized by compromised bone strength and increased susceptibility to fractures, poses a significant public health concern. This review aims to provide a comprehensive analysis of the current state of research in the field, focusing on the application of proteomic techniques to elucidate diagnostic markers and therapeutic targets for OP. The integration of cutting-edge proteomic technologies has enabled the identification and quantification of proteins associated with bone metabolism, leading to a deeper understanding of the molecular mechanisms underlying OP. In this review, we systematically examine recent advancements in proteomic studies related to OP, emphasizing the identification of potential biomarkers for OP diagnosis and the discovery of novel therapeutic targets. Additionally, we discuss the challenges and future directions in the field, highlighting the potential impact of proteomic research in transforming the landscape of OP diagnosis and treatment.

Investigating the impact of Wnt pathway-related genes on biomarker and diagnostic model development for osteoporosis in postmenopausal females

The Wnt signaling pathway is essential for bone development and maintaining skeletal homeostasis, making it particularly relevant in osteoporosis patients. Our study aimed to identify distinct molecular clusters associated with the Wnt pathway and develop a diagnostic model for osteoporosis in postmenopausal Caucasian women. We downloaded three datasets (GSE56814, GSE56815 and GSE2208) related to osteoporosis from the GEO database. Our analysis identified a total of 371 differentially expressed genes (DEGs) between low and high bone mineral density (BMD) groups, with 12 genes associated with the Wnt signaling pathway, referred to as osteoporosis-associated Wnt pathway-related genes. Employing four independent machine learning models, we established a diagnostic model using the 12 osteoporosis-associated Wnt pathway-related genes in the training set. The XGB model showed the most promising discriminative potential. We further validate the predictive capability of our diagnostic model by applying it to three external datasets specifically related to osteoporosis. Subsequently, we constructed a diagnostic nomogram based on the five crucial genes identified from the XGB model. In addition, through the utilization of DGIdb, we identified a total of 30 molecular compounds or medications that exhibit potential as promising therapeutic targets for osteoporosis. In summary, our comprehensive analysis provides valuable insights into the relationship between the osteoporosis and Wnt signaling pathway.

Denosumab improves trabecular bone score in relationship with decrease in fracture risk of women exposed to aromatase inhibitors

PURPOSE

Trabecular bone score (TBS) is a gray-level textural metric that has shown to correlate with risk of fractures in several forms of osteoporosis. The value of TBS in predicting fractures and the effects of bone-active drugs on TBS in aromatase inhibitors (AIs)-induced osteoporosis are still largely unknown. The primary objective of this retrospective study was to assess the effects of denosumab and bisphosphonates (BPs) on TBS and vertebral fractures (VFs) in women exposed to AIs.

METHODS

241 consecutive women (median age 58 years) with early breast cancer undergoing treatment with AIs were evaluated for TBS, bone mineral density (BMD) and morphometric VFs at baseline and after 18-24 months of follow-up. During the study period, 139 women (57.7%) received denosumab 60 mg every 6 months, 53 (22.0%) BPs, whereas 49 women (20.3%) were not treated with bone-active drugs.

RESULTS

Denosumab significantly increased TBS values (from 1.270 to 1.323; P < 0.001) accompanied by a significant decrease in risk of VFs (odds ratio 0.282; P = 0.021). During treatment with BPs, TBS did not significantly change (P = 0.849) and incidence of VFs was not significantly different from women untreated with bone-active drugs (P = 0.427). In the whole population, women with incident VFs showed higher decrease in TBS vs. non-fractured women (P = 0.003), without significant differences in changes of BMD at any skeletal site.

CONCLUSIONS

TBS variation predicts fracture risk in AIs treated women. Denosumab is effective to induce early increase of TBS and reduction in risk of VFs.

Recommendations on screening for primary prevention of fragility fractures

BACKGROUND

Fragility fractures are a major health concern for older adults and can result in disability, admission to hospital and long-term care, and reduced quality of life. This Canadian Task Force on Preventive Health Care (task force) guideline provides evidence-based recommendations on screening to prevent fragility fractures in community-dwelling individuals aged 40 years and older who are not currently on preventive pharmacotherapy.

METHODS

We commissioned systematic reviews on benefits and harms of screening, predictive accuracy of risk assessment tools, patient acceptability and benefits of treatment. We analyzed treatment harms via a rapid overview of reviews. We further examined patient values and preferences via focus groups and engaged stakeholders at key points throughout the project. We used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach to determine the certainty of evidence for each outcome and strength of recommendations, and adhered to Appraisal of Guidelines for Research and Evaluation (AGREE), Guidelines International Network and Guidance for Reporting Involvement of Patients and the Public (GRIPP-2) reporting guidance.

RECOMMENDATIONS

We recommend "risk assessment-first" screening for prevention of fragility fractures in females aged 65 years and older, with initial application of the Canadian clinical Fracture Risk Assessment Tool (FRAX) without bone mineral density (BMD). The FRAX result should be used to facilitate shared decision-making about the possible benefits and harms of preventive pharmacotherapy. After this discussion, if preventive pharmacotherapy is being considered, clinicians should request BMD measurement using dual-energy x-ray absorptiometry (DXA) of the femoral neck, and re-estimate fracture risk by adding the BMD T-score into FRAX (conditional recommendation, low-certainty evidence). We recommend against screening females aged 40-64 years and males aged 40 years and older (strong recommendation, very low-certainty evidence). These recommendations apply to community-dwelling individuals who are not currently on pharmacotherapy to prevent fragility fractures.

INTERPRETATION

Risk assessment-first screening for females aged 65 years and older facilitates shared decision-making and allows patients to consider preventive pharmacotherapy within their individual risk context (before BMD). Recommendations against screening males and younger females emphasize the importance of good clinical practice, where clinicians are alert to changes in health that may indicate the patient has experienced or is at higher risk of fragility fracture.