Fracture Risk Assessment: An Update

Mijiao formula regulates NAT10-mediated Runx2 mRNA ac4C modification to promote bone marrow mesenchymal stem cell osteogenic differentiation and improve osteoporosis in ovariectomized rats

ETHNOPHARMACOLOGICAL RELEVANCE

The Mijiao (MJ) formula, a traditional herbal remedy, incorporates antlers as its primary constituent. It can effectively treat osteoporosis (OP), anti-aging, enhance immune activity, and change depression-like behavior. In this study, we investigated that MJ formula is a comprehensive treatment strategy, and may provide a potential approach for the clinical treatment of postmenopausal osteoporosis.

AIM OF THE STUDY

The purpose of this study was to determine whether MJ formula promoted osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) and improved osteoporosis in ovariectomized rats by regulating the NAT10-mediated Runx2 mRNA ac4C modification.

MATERIALS AND METHODS

Female Sprague-Dawley (SD) rats were used to investigate the potential therapeutic effect of MJ formula on OP by creating an ovariectomized (OVX) rat model. The expression of osteogenic differentiation related proteins in BMSCs was detected in vivo, indicating their role in promoting bone formation. In addition, the potential mechanism of its bone protective effect was explored via in vitro experiments.

RESULTS

Our study showed that MJ formula significantly mitigated bone mass loss in the OVX rat model, highlighting its potential as an OP therapeutic agent. We found that the possible mechanism of action was the ability of this formulation to stabilize Runx2 mRNA through NAT10-mediated ac4C acetylation, which promoted osteogenic differentiation of BMSCs and contributed to the enhancement of bone formation.

CONCLUSIONS

MJ formula can treat estrogen deficiency OP by stabilizing Runx2 mRNA, promoting osteogenic differentiation and protecting bone mass. Conceivably, MJ formulation could be a safe and promising strategy for the treatment of osteoporosis.

Predicting Osteoporotic Fracture in Patients With Early-Stage Diabetic Kidney Disease Using a Radiomic Model: A Longitudinal Cohort Study

OBJECTIVE

There is an urgent need for effective predictive strategies to accurately evaluate the risk of fragility fractures in elderly patients in the early stages of diabetic kidney disease (DKD).

METHODS

This longitudinal cohort study included 715 older patients in the early stages of DKD diagnosed between January 2015 and August 2019. Patients were randomly allocated to a training cohort (n = 499) and a validation cohort (n = 216). The least absolute shrinkage and selection operator method was used to select key features for dual-energy x-ray absorptiometry-based radiomic analysis. A radiomic model was constructed using Cox proportional hazards regression. The performance of the radiomic model was compared with that of traditional fracture assessment tools through a receiver operating characteristic curve, calibration curve, and decision curve analysis.

RESULTS

Over a mean follow-up period of 4.72 ± 1.60 years, 65 participants (9.09%) experienced incident fragility fractures. Seventeen features were ultimately selected to create the radiomic model. The calibration plots of this model demonstrated satisfactory agreement between the observed and predicted outcomes. Moreover, the radiomic model outperformed traditional fracture assessment tools in both the training and validation cohorts according to the area under the receiver operating characteristic curve and decision curve analysis.

CONCLUSIONS

The novel radiomic model has demonstrated a more effective prediction of fragility fracture in elderly patients in the early stages of DKDcompared to traditional fracture assessment tools.

The risk of fractures after entering long-term care facilities

BACKGROUND

Stratifying residents at increased risk for fractures in long-term care facilities (LTCFs) can potentially improve awareness and facilitate the delivery of targeted interventions to reduce risk. Although several fracture risk assessment tools exist, most are not suitable for individuals entering LTCF. Moreover, existing tools do not examine risk profiles of individuals at key periods in their aged care journey, specifically at entry into LTCFs.

PURPOSE

Our objectives were to identify fracture predictors, develop a fracture risk prognostic model for new LTCF residents and compare its performance to the Fracture Risk Assessment in Long term care (FRAiL) model using the Registry of Senior Australians (ROSA) Historical National Cohort, which contains integrated health and aged care information for individuals receiving long term care services.

METHODS

Individuals aged ≥65 years old who entered 2079 facilities in three Australian states between 01/01/2009 and 31/12/2016 were examined. Fractures (any) within 365 days of LTCF entry were the outcome of interest. Individual, medication, health care, facility and system-related factors were examined as predictors. A fracture prognostic model was developed using elastic nets penalised regression and Fine-Gray models. Model discrimination was examined using area under the receiver operating characteristics curve (AUC) from the 20 % testing dataset. Model performance was compared to an existing risk model (i.e., FRAiL model).

RESULTS

Of the 238,782 individuals studied, 62.3 % (N = 148,838) were women, 49.7 % (N = 118,598) had dementia and the median age was 84 (interquartile range 79-89). Within 365 days of LTCF entry, 7.2 % (N = 17,110) of individuals experienced a fracture. The strongest fracture predictors included: complex health care rating (no vs high care needs, sub-distribution hazard ratio (sHR) = 1.52, 95 % confidence interval (CI) 1.39-1.67), nutrition rating (moderate vs worst, sHR = 1.48, 95%CI 1.38-1.59), prior fractures (sHR ranging from 1.24 to 1.41 depending on fracture site/type), one year history of general practitioner attendances (≥16 attendances vs none, sHR = 1.35, 95%CI 1.18-1.54), use of dopa and dopa derivative antiparkinsonian medications (sHR = 1.28, 95%CI 1.19-1.38), history of osteoporosis (sHR = 1.22, 95%CI 1.16-1.27), dementia (sHR = 1.22, 95%CI 1.17-1.28) and falls (sHR = 1.21, 95%CI 1.17-1.25). The model AUC in the testing cohort was 0.62 (95%CI 0.61-0.63) and performed similar to the FRAiL model (AUC = 0.61, 95%CI 0.60-0.62).

CONCLUSIONS

Critical information captured during transition into LTCF can be effectively leveraged to inform fracture risk profiling. New fracture predictors including complex health care needs, recent emergency department encounters, general practitioner and consultant physician attendances, were identified.

Can TBS reference values be a valid indicator for clinical vertebral fracture? A cross-sectional study

INTRODUCTION

Trabecular bone score (TBS) is partially independent of fracture risk. Reference values for TBS have not been established in official guidelines, and thus clinicians often have difficulty interpreting TBS results. This study aimed to investigate whether reference values for TBS could be a valid indicator for clinical vertebral fracture (CVF).

MATERIALS AND METHODS

This cross-sectional study involved 231 women with CVF and 563 women without CVF aged 60-90 years who underwent dual-energy X-ray absorptiometry during 2019-2023. They were divided into osteoporosis, osteopenia, and normal groups according to bone mineral density of the lumbar spine. Reference values for TBS were defined as low (≤ 1.23), intermediate (1.23-1.31), and high (≥ 1.31).

RESULTS

Among patients without anti-osteoporosis treatment (n = 476), the proportion with low TBS was 36.7% in the CVF group and 10.7% in the control group. The proportion with CVF was higher in the low TBS group than in the intermediate and high TBS groups, especially in the osteoporosis group (p < 0.001). The odds ratio for CVF was higher in the low TBS group than in the intermediate and high especially in patients with normal BMD and osteoporosis. The TBS cut-off values for incidence of CVF in the osteoporosis, osteopenia, and normal groups were 1.224, 1.319, and 1.322, respectively.

CONCLUSIONS

The reference value for low TBS (≤ 1.23) was useful as an indicator for CVF, especially in patients with osteoporosis. It is expected that reference values for TBS will be established in official guidelines in the future.

The correlation between osteoporotic vertebrae fracture risk and bone mineral density measured by quantitative computed tomography and dual energy X-ray absorptiometry: a systematic review and meta-analysis

This paper presents a comparison of quantitative computed tomography (QCT) and dual-energy X-ray absorptiometry (DXA) in osteoporosis with vertebral fracture and osteoporosis without fracture. It has been proved that the volumetric bone mineral density (vBMD) measured by QCT exhibits a stronger correlation with fracture risk than areal bone mineral density (aBMD) measured by DXA.

PURPOSE

This study aims to systematically evaluate the ability of QCT and DXA to distinguish between osteoporosis with vertebral fracture and osteoporosis without fracture according to vBMD and aBMD.

METHODS

We conducted a primary literature search of the online databases up to 3 July, 2022, in both English and Chinese publications, combining synonyms for "QCT", "DXA" and "osteoporosis". The Newcastle-Ottawa scale (NOS) was employed to evaluate the quality of the selected articles. vBMD obtained through QCT and aBMD obtained through DXA were extracted, and were analyzed by Review Manager 5.4 and RStudio.

RESULTS

Six studies with 610 individuals aged 45 to 90, of which 179 had vertebral fractures, were included in the final analysis. The weighted mean difference (WMD) between osteoporosis with vertebral fracture and osteoporosis without fracture for vBMD was - 27.08 (95% CI  - 31.24 to  - 22.92), while for aBMD was - 0.05 (95% CI - 0.08 to - 0.03).

CONCLUSIONS

Both vBMD detected by QCT and aBMD detected by DXA could discriminate fracture status in the spine, and vBMD performed a stronger correlation with fracture risk.

TRIAL REGISTRATION

PROSPERO 2022 CRD42022349185.

3D Finite Element Models Reconstructed From 2D Dual-Energy X-Ray Absorptiometry (DXA) Images Improve Hip Fracture Prediction Compared to Areal BMD in Osteoporotic Fractures in Men (MrOS) Sweden Cohort

Bone strength is an important contributor to fracture risk. Areal bone mineral density (aBMD) derived from dual-energy X-ray absorptiometry (DXA) is used as a surrogate for bone strength in fracture risk prediction tools. 3D finite element (FE) models predict bone strength better than aBMD, but their clinical use is limited by the need for 3D computed tomography and lack of automation. We have earlier developed a method to reconstruct the 3D hip anatomy from a 2D DXA image, followed by subject-specific FE-based prediction of proximal femoral strength. In the current study, we aim to evaluate the method's ability to predict incident hip fractures in a population-based cohort (Osteoporotic Fractures in Men [MrOS] Sweden). We defined two subcohorts: (i) hip fracture cases and controls cohort: 120 men with a hip fracture (<10 years from baseline) and two controls to each hip fracture case, matched by age, height, and body mass index; and (ii) fallers cohort: 86 men who had fallen the year before their hip DXA scan was acquired, 15 of which sustained a hip fracture during the following 10 years. For each participant, we reconstructed the 3D hip anatomy and predicted proximal femoral strength in 10 sideways fall configurations using FE analysis. The FE-predicted proximal femoral strength was a better predictor of incident hip fractures than aBMD for both hip fracture cases and controls (difference in area under the receiver operating characteristics curve, ΔAUROC = 0.06) and fallers (ΔAUROC = 0.22) cohorts. This is the first time that FE models outperformed aBMD in predicting incident hip fractures in a population-based prospectively followed cohort based on 3D FE models obtained from a 2D DXA scan. Our approach has potential to notably improve the accuracy of fracture risk predictions in a clinically feasible manner (only one single DXA image is needed) and without additional costs compared to the current clinical approach. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

A Fracture Risk Assessment Tool for High Resolution Peripheral Quantitative Computed Tomography

Most fracture risk assessment tools use clinical risk factors combined with bone mineral density (BMD) to improve assessment of osteoporosis; however, stratifying fracture risk remains challenging. This study developed a fracture risk assessment tool that uses information about volumetric bone density and three-dimensional structure, obtained using high-resolution peripheral quantitative compute tomography (HR-pQCT), to provide an alternative approach for patient-specific assessment of fracture risk. Using an international prospective cohort of older adults (n = 6802) we developed a tool to predict osteoporotic fracture risk, called μFRAC. The model was constructed using random survival forests, and input predictors included HR-pQCT parameters summarizing BMD and microarchitecture alongside clinical risk factors (sex, age, height, weight, and prior adulthood fracture) and femoral neck areal BMD (FN aBMD). The performance of μFRAC was compared to the Fracture Risk Assessment Tool (FRAX) and a reference model built using FN aBMD and clinical covariates. μFRAC was predictive of osteoporotic fracture (c-index = 0.673, p < 0.001), modestly outperforming FRAX and FN aBMD models (c-index = 0.617 and 0.636, respectively). Removal of FN aBMD and all clinical risk factors, except age, from μFRAC did not significantly impact its performance when estimating 5-year and 10-year fracture risk. The performance of μFRAC improved when only major osteoporotic fractures were considered (c-index = 0.733, p < 0.001). We developed a personalized fracture risk assessment tool based on HR-pQCT that may provide an alternative approach to current clinical methods by leveraging direct measures of bone density and structure. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Improved fracture risk prediction by adding VFA-identified vertebral fracture data to BMD by DXA and clinical risk factors used in FRAX

Vertebral fracture (VF) is a strong predictor of subsequent fracture. In this study of older women, VF, identified by dual-energy X-ray absorptiometry (DXA) vertebral fracture assessment (VFA), were associated with an increased risk of incident fractures and had a substantial impact on fracture probability, supporting the utility of VFA in clinical practice.

PURPOSE

Clinical and occult VF can be identified using VFA with dual-energy X-ray absorptiometry (DXA). The aim of this study was to investigate to what extent VFA-identified VF improve fracture risk prediction, independently of bone mineral density (BMD) and clinical risk factors used in FRAX.

METHODS

A total of 2852 women, 75-80 years old, from the prospective population-based study SUPERB cohort, were included in this study. At baseline, BMD was measured by DXA, VF diagnosed by VFA, and questionnaires used to collect data on risk factors for fractures. Incident fractures were captured by X-ray records or by diagnosis codes. An extension of Poisson regression was used to estimate the association between VFA-identified VF and the risk of fracture and the 5- and 10-year probability of major osteoporotic fracture (MOF) was calculated from the hazard functions for fracture and death.

RESULTS

During a median follow-up of 5.15 years (IQR 4.3-5.9 years), the number of women who died or suffered a MOF, clinical VF, or hip fracture was 229, 422, 160, and 124, respectively. A VFA-identified VF was associated with an increased risk of incident MOF (hazard ratio [HR] = 1.78; 95% confidence interval [CI] 1.46-2.18), clinical VF (HR = 2.88; 95% [CI] 2.11-3.93), and hip fracture (HR = 1.67; 95% [CI] 1.15-2.42), adjusted for age, height, and weight. For women at age 75 years, a VFA-identified VF was associated with 1.2-1.4-fold greater 10-year MOF probability compared with not taking VFA into account, depending on BMD.

CONCLUSION

Identifying an occult VF using VFA has a substantial impact on fracture probability, indicating that VFA is an efficient method to improve fracture prediction in older women.

The progress in quantitative evaluation of callus during distraction osteogenesis

The manual monitoring of callus with digital radiography (X-ray) is the primary bone healing evaluation, assessing the number of bridged callus formations. However, this method is subjective and nonquantitative. Recently, several quantitative monitoring methods, which could assess the recovery of the structure and biomechanical properties of the callus at different stages and the process of bone healing, have been extensively investigated. These methods could reflect the bone mineral content (BMC), bone mineral density (BMD), stiffness, callus and bone metabolism at the site of bone lengthening. In this review, we comprehensively summarized the latest techniques for evaluating bone healing during distraction osteogenesis (DO): 1) digital radiography; 2) dual-energy X-ray scanning; 3) ultrasound; 4) quantitative computed tomography; 5) biomechanical evaluation; and 6) biochemical markers. This evidence will provide novel and significant information for evaluating bone healing during DO in the future.

Evaluation and Treatment in Urology for Nocturia Caused by Nonurological Mechanisms: Guidance from the PLANET Study

Patients with nocturia are commonly referred to urology clinics, including many for whom a nonurological medical condition is responsible for their symptoms. The PLanning Appropriate Nocturia Evaluation and Treatment (PLANET) study was established to develop practical approaches to equip healthcare practitioners to deal with the diverse causes of nocturia, based on systematic reviews and expert consensus. Initial assessment and therapy need to consider the possibility of one or more medical conditions falling into the "SCREeN" areas of Sleep medicine (insomnia, periodic limb movements of sleep, parasomnias, and obstructive sleep apnoea), Cardiovascular (hypertension and congestive heart failure), Renal (chronic kidney disease), Endocrine (diabetes mellitus, thyroid disease, pregnancy/menopause, and diabetes insipidus), and Neurology. Medical and medication causes of xerostomia should also be considered. Some key indicators for these conditions can be identified in urology clinics, working in partnership with the primary care provider. Therapy of the medical condition in some circumstances lessens the severity of nocturia. However, in many cases there is a conflict between the two, in which case the medical condition generally takes priority on safety grounds. It is important to provide patients with a realistic expectation of therapy and awareness of limitations of current therapeutic options for nocturia. PATIENT SUMMARY: Nocturia is the symptom of waking at night to pass urine. Commonly, this problem is referred to urology clinics. However, in some cases, the patient does not have a urological condition but actually a condition from a different speciality of medicine. This article describes how best the urologist and the primary care doctor can work together to assess the situation and make sensible and safe treatment suggestions. Unfortunately, there is sometimes no safe or effective treatment choice for nocturia, and treatment needs to focus instead on supportive management of symptoms.

Development of an open-source measurement system to assess the areal bone mineral density of the proximal femur from clinical CT images

Commercial software is generally needed to measure the areal bone mineral density (aBMD) of the proximal femur from clinical computed tomography (CT) images. This study developed and verified an open-source reproducible system to quantify CT-aBMD to screen osteoporosis using clinical CT images.

PURPOSE

For existing CT images acquired for various reasons other than osteoporosis, it might be beneficial to estimate areal BMD as assessed by dual-energy X-ray absorptiometry (DXA-based BMD) to ascertain the bone status based on DXA. In this study, we aimed to (1) develop an open-source reproducible measurement system to quantify DXA-based BMD from CT images and (2) validate its accuracy.

METHODS

This study analyzed 75 pairs of hip CT and DXA images of women that were acquired for the preoperative assessment of total hip arthroplasty. From the CT images, the femur and a calibration phantom were automatically segmented using pre-trained codes/models available at https://github.com/keisuke-uemura . The proximal femoral region was isolated by manually selected landmarks and was projected onto the coronal plane to measure the areal density (CT-aHU). The calibration phantom was employed to convert the CT-aHU into CT-aBMD. Each parameter was correlated with DXA-based BMD, and the residual errors of CT images to estimate the T-scores in DXA were calculated using the standard error of estimate (SEE).

RESULTS

The correlation coefficients of DXA-based BMD with CT-aHU and CT-aBMD were 0.947 and 0.950, respectively (both p < 0.001). The SEE for quantifying the T-scores in DXA were 0.51 and 0.50 for CT-aHU and CT-aBMD, respectively.

CONCLUSION

With the method developed herein, CT permits estimation of the DXA-based BMD of the proximal femur within the standard DXA total hip region of interest with an SEE of 0.5 in T-scores. The radiation dose for CT acquisition needs consideration; therefore, our data do not provide a rationale for performing CT for screening osteoporosis. However, on CT images already acquired for clinical indications other than osteoporosis, researchers may use this open-source system to investigate osteoporosis status through the estimated DXA-based BMD of the proximal femur.