Predicting Fragility Fractures Research Articles

P043 The different roles of FRAX risk factors as predictors of fragility fractures in peri-menopausal vs post-menopausal patients: results from a large population-based cohort study

Abstract Background/Aims The marked rise in the prevalence of fragility fractures affecting both women undergoing the transition to menopause (i.e. peri-menopause), and post-menopausal women, confers a significant burden on patients’ health and quality of life. The risk factors for fractures in post-menopausal women have been previously well-explored, and tend to align with the FRAX variables. However, there is less consensus regarding the fracture risk factors in peri-menopausal women. We compare the association between FRAX risk factors and fractures across peri-menopausal and post-menopausal women, selected from the same large population-based cohort. Methods Female patients referred for a DXA scan at the Royal Lancaster Infirmary between 2004-2011 provided information relating to any previous fragility fracture(s), FRAX risk factors, and menopause status (i.e. not post-menopausal vs post-menopausal) through a questionnaire. Patients aged 41 to 51 (median menopause age in UK) who had not undergone the menopause, as per their questionnaire response, were categorised as ‘peri-menopausal’. Logistic regression modelling, which included adjustment for potential confounders, was performed using r(version 4.3.1). Results Our study included 23388 patients, including 3785 peri-menopausal patients and 20774 post-menopausal patients, with a mean age of 47.5 (SD:3.0) and 66.1 (SD:10.4) respectively. The prevalence of fragility fractures was greater in the post-menopausal than peri-menopausal cohort (42.8% vs 25.5% respectively; p < 0.001). Across post-menopausal patients, following adjustment for the other FRAX risk factors, significant predictors of increased fracture risk were age (odds ratio (OR): 1.04 (95% CI:1.03-1.04, p < 0.001), smoking (OR:1.16 (CI:1.09-1.23, p < 0.001), alcohol (OR:1.54, CI:1.36-1.74, p < 0.001), and a family history of fracture(s) (OR:1.21 (CI:1.13-1.29, p < 0.001). Comparatively, across peri-menopausal patients, only alcohol (OR:1.57, CI:1.08-2.26, p = 0.016) and smoking (OR:1.22 (CI:1.00-1.48, p = 0.045) positively predicted fracture risk. Corticosteroid use was associated with a reduced fracture risk across both post-menopausal (OR:0.84, CI:0.79-0.90, p < 0.001) and peri-menopausal (OR:0.79, CI: 0.64-0.97, p = 0.024) cohorts. Conclusion Different FRAX risk factors predict fracture occurrence across post-menopausal and peri-menopausal patients; notably, only smoking and alcohol consumption predict an increased fracture risk in the latter group. Interestingly, corticosteroids were associated with a reduced risk of fractures across both groups. This finding may be elucidated by the fact that low-dose corticosteroids can exert an anti-inflammatory effect, and may protect bone cells. However, our finding is limited by the fact that the indication, dose and duration of corticosteroids were unknown. More generally, our study is limited by the fact that patients’ peri-menopausal status was not clinically confirmed, but inferred based on patients’ age and self-reported menopause status. Our results suggest that the FRAX risk factors, which were derived from analysis of predominantly 50-80 year old patients, may require adjustment for peri-menopausal patients (many of whom are aged <50). Future studies should assess whether our conclusions apply to specific fracture sites, and are replicated across more demographically diverse patient populations. Disclosure K. Song: None. M. Bukhari: None.

Reference-Class Problems Are Real: Health-Adjusted Reference Classes and Low Bone Mineral Density.

Elselijn Kingma argues that Christopher Boorse's biostatistical theory (the BST) does not show how the reference classes it uses are objective and naturalistic. Recently, philosophers of medicine have attempted to rebut Kingma's concerns. I argue that these rebuttals are theoretically unconvincing, and that there are clear examples of physicians adjusting their reference classes according to their prior knowledge of health and disease. I focus on the use of age-adjusted reference classes to diagnose low bone mineral density in children. In addition to using the BST's age, sex, and species, physicians also choose to use other factors to define reference classes, such as pubertal status, bone age, body size, and muscle mass. I show that physicians calibrate the reference classes they use according to their prior knowledge of health and disease. Reference classes are also chosen for pragmatic reasons, such as to predict fragility fractures.

Limited utility of salivary mineral content in prediction of fragility fractures among postmenopausal women.

Osteoporosis is a metabolic disease characterized by increased bone fragility. As it is characterized as a general skeletal disease, changes can also be seen in the stomatognathic system (edentulism, wrong fitting of dentures, etc.). The question is whether early changes in the salivary mineral content and acid-base balance may reflect skeletal status and risk of bone fracture. The objective of the study was to evaluate whether minerals in the saliva were associated with skeletal fractures in a population of postmenopausal women. In this observational study, dental examinations along with the collection of saliva were conducted in 117 randomly recruited women (mean age 64.6 ±5.9 years). The study group included 23 study participants with fractures, of which 10 had a history of osteoporotic fractures. Saliva samples for mineral content including copper (Cu), zinc (Zn), calcium (Ca), and phosphorus (P), as well as salivary pH were collected and analyzed to determine associations between salivary mineral content and fracture risk. As a result, the median pH value was 6.8, and the median levels for Cu (0.35 μmol/L), Zn (0.61 μmol/L), Ca (0.7 mmol/L), and P (6.64 mmol/L) were observed. No differences were noted in salivary mineral content and acid-basic balance between the fractured and non-fractured participants. The results of our study suggest that salivary mineral content has limited usability in predicting skeletal fragility in postmenopausal women when used alone.

Comparison of the predictive values of MRI-based vertebral bone quality scores for the determination of osteoporosis in different diseases.

The study aimed to examine the consistency of vertebral bone quality (VBQ) scores for assessing osteoporosis across different etiologies and explore the predictive value of various VBQ scores for fragility vertebral fractures. Patients with fragility fractures were matched by age and sex to patients with lumbar degeneration. VBQ scores were calculated in T1- and T2-weighted magnetic resonance imaging. Differential analysis of bone quality was performed based on etiology. A total of 96 inpatients were retrospectively enrolled. VBQT1 scores were only sensitive to osteoporotic bone in degenerative group (p < 0.01), failing to identify osteoporosis in fractured group (p > 0.05). For the degenerative group, the area under the curve (AUC) using the VBQT1 scores to differentiate osteoporosis was 0.72. After controlling the confounding variables, only VBQT2 scores were significantly higher in fractured group than degenerative group, with a greater AUC of 0.82 predicting fragility fractures. VBQT1 scores moderately correlated with femoral neck T-scores in degenerative group (r = -0.45, p < 0.01) but not in fractured group (r = -0.24, p > 0.05). VBQT2 scores were not associated with femoral neck T-scores (p > 0.05). This study is the first to evaluate the effectiveness of VBQs scores in assessing osteoporosis post-fracture. Only non-fractured patients' bone quality is fully susceptible to VBQT1 scores. While VBQT1 scores may not correlate with fragility fractures, VBQT2 scores present a viable alternative.

Prediction of fragility fractures in men with prostate cancer under androgen deprivation therapy: the importance of a multidisciplinary approach using a mini-invasive diagnostic tool.

Bone fragility in men who are treated with androgen deprivation therapy (ADT) has a complex pathophysiology that differs from that of primary and post-menopausal osteoporosis. Fracture risk assessment based on bone mineral density (BMD) and Fracture Risk Assessment Tool (FRAX) score might not be effective in this patient setting, since high frequency of fragility fractures has been reported even in subjects with low FRAX risk and normal BMD. In this paper we want to emphasize the importance in the individual assessment of bone fragility and prediction of fractures by measuring parameters of bone quality, assessing morphometric vertebral fractures and evaluating body composition that in subjects under hormone-deprivation therapies can play a crucial role. Noteworthy, a single mini-invasive diagnostic tool, i.e., the dual energy x-ray absorptiometry (DXA) scan, offers the opportunity to evaluate reliably parameters of bone quality (e.g., trabecular bone score) and body composition, besides measurement of BMD and assessment of vertebral fractures by a morphometric approach. This article highlights the values and cost-effectiveness of this mini-invasive tool in the context of multidisciplinary approach to subjects with prostate cancer under ADTs.

Partial body fat percentage as a predictor of fragility fractures in a large cohort: a cross-sectional study.

BMI is a component of fracture risk calculators; however, it may be too simplistic to predict fracture risk. There is emerging evidence for the role that fat plays as a predictor of fracture. Partial body fat percentage (PBF%) may be a novel way to predict both hip and non-hip fractures. The aim of this study is to evaluate PBF% as a predictor of fragility fractures. A multivariate logistic regression analysis was conducted looking at PBF% as a predicter of both non-hip and hip fractures in an observational cohort. Our results were adjusted for age, biological sex, gender, smoking status, excess alcohol consumption (>3 units/day), current steroid therapy and the T-scores in both femurs. To allow for comparison, the same model was used with BMI, height and weight as the primary predictor of fracture. A subgroup analysis was conducted stratified by fracture site. A sensitivity analysis using a negative binomial regression was conducted. A total of 31 447 patients were included in our analysis [mean age 64.9 years (s.d. 12.9)]. PBF% was shown to predict all non-hip fractures after adjustment [odds ratio (OR) 22.14 (95% CI 15.08, 32.50)]. Hip fractures were not predicted by our model [OR 4.19 (95% CI 0.43, 41.46)]. Sensitivity analysis demonstrated a lack of predictive capability for hip fracture but not non-hip fractures. PBF% may be a suitable predictor for all non-hip fractures, independent of confounding variables. More research is needed on whether it can predict hip fractures.

Influence of hand grip strength test and short physical performance battery on FRAX in post-menopausal women: a machine learning cross-sectional study.

Impaired physical performance and muscle strength are recognized risk factors for fragility fractures, frequently associated with osteoporosis and sarcopenia. However, the integration of muscle strength and physical performance in the comprehensive assessment of fracture risk is still debated. Therefore, this cross-sectional study aimed to assess the potential role of hand grip strength (HGS) and short physical performance battery (SPPB) for predicting fragility fractures and their correlation with Fracture Risk Assessment Tool (FRAX) with a machine learning approach. In this cross-sectional study, a group of postmenopausal women underwent assessment of their strength, with the outcome measured using the HSG, their physical performance evaluated using the SPPB, and the predictive algorithm for fragility fractures known as FRAX. The statistical analysis included correlation analysis using Pearson's r and a decision tree model to compare different variables and their relationship with the FRAX Index. This machine learning approach allowed to create a visual decision boundaries plot, providing a dynamic representation of variables interactions in predicting fracture risk. Thirty-four patients (mean age 63.8±10.7 years) were included. Both HGS and SPPB negatively correlate with FRAX major (r=-0.381, P=0.034; and r=-0.407, P=0.023 respectively), whereas only SPPB significantly correlated with an inverse proportionality to FRAX hip (r=-0.492, P=0.001). According to a machine learning approach, FRAX major ≥20 and/or hip ≥3 might be reported for an SPPB<6. Concurrently, HGS<17.5 kg correlated with FRAX major ≥20 and/or hip ≥3. In light of the major findings, this cross-sectional study using a machine learning model related SPPB and HGS to FRAX. Therefore, a precise assessment including muscle strength and physical performance might be considered in the multidisciplinary assessment of fracture risk in post-menopausal women.

A risk assessment tool for predicting fragility fractures in people with HIV: derivation and internal validation of the FRESIA model.

People with HIV have a higher risk of fracture than the general population. Because of the low performance of the existing prediction tools, there is controversy surrounding fracture risk estimation in this population. The aim of the study was to develop a model for predicting the long-term risk of fragility fractures in people with HIV. We included 11,899 individuals aged ≥ 30 years from the Spanish HIV/AIDS research network cohort. We identified incident fragility fractures from medical records, defined as those non-traumatic or occurring after a casual fall, at major osteoporotic sites (hip, clinical spine, forearm, proximal humerus). Our model accounted for the competing risk of death and included 12 candidate predictors to estimate the time to first fragility fracture. We assessed the discrimination and calibration of the model and compared it with the FRAX tool. The incidence rate of fragility fractures was 4.34 (95% CI 3.61-5.22) per 1,000 person-years. The final prediction model included age, chronic kidney disease, and chronic obstructive pulmonary disease as significant predictors. The model accurately predicted the five-year and ten-year risk of fragility fractures, with an area under the receiving operator characteristic curve of 0.768 (95% CI 0.722-0.814), and agreement between the observed and expected probabilities. Furthermore, it demonstrated better discrimination and calibration than the FRAX tool, improving the classification of over 35% of individuals with fragility fractures compared to FRAX. Our prediction model demonstrated accuracy in predicting the long-term risk of fragility fractures. It can assist in making personalized intervention decisions for individuals with HIV and may potentially replace the current tools recommended for fracture risk assessment in this population. This article is protected by copyright. All rights reserved.

Coexistence of Low Muscle Mass and Osteoporosis as a Predictor of Fragility Fractures in Long-Term Kidney Transplant Recipients

Introduction: Sarcopenia and osteoporosis are highly prevalent among kidney transplant recipients (KTRs). Although osteoporosis is known to increase fracture risk in KTRs, it is unclear whether sarcopenia or osteosarcopenia is associated with this increased risk. Thus, we aimed to investigate the association of the coexistence of low muscle mass (LMM) and osteoporosis with the risk of fracture in long-term KTRs. Methods: Exactly 342 stable KTRs underwent dual-energy X-ray absorptiometry and skeletal muscle mass index (SMI) measurement using bioelectrical impedance analysis. Results: LMM and osteoporosis were observed in 109 (31.9%) and 93 patients (27.2%), respectively. During a follow-up period of 5.1 years, 48 (14.0%) fractures occurred. KTRs with LMM had a higher fracture risk, but this was not significant (adjusted hazard ratio [aHR] 1.82, 95% confidence interval [CI] 0.94–3.50, p = 0.073). Similar results were obtained in KTRs with osteoporosis (aHR 1.84, 95% CI 0.96–3.47, p = 0.063). We divided the KTRs into four groups according to the presence of LMM and/or osteoporosis. The cumulative incidence rates of fractures were 13.0%, 11.1%, 10.5%, and 31.3% in the KTRs without both LMM and osteoporosis, those with LMM alone, those with osteoporosis alone, and those with both, respectively. The KTRs with both LMM and osteoporosis had a 2.92fold higher risk of fractures (95% CI 1.29–6.49; p = 0.010) than those without both LMM and osteoporosis. Conclusion: Long-term KTRs with the coexistence of LMM and osteoporosis had an independently higher risk of fragility fractures than those without both LMM and osteoporosis. The combination of SMI and osteoporosis definitions can be used to identify KTRs with a high fracture risk.

What is the role of CT-based Hounsfield unit assessment in the evaluation of bone mineral density in patients undergoing 1- or 2-level lumbar spinal fusion for degenerative spinal pathologies? A prospective study

Computed tomography-based vertebral attenuation values (CT-based HU) have been shown to correlate with T-scores on DEXA scan; and have been acknowledged as an independent factor for predicting fragility fractures. Most patients undergoing lumbar surgeries require CT as part of their preoperative evaluation. The current study was thus planned to evaluate the role of lumbar CT as an opportunistic investigation in determining BMD preoperatively in patients undergoing lumbar fusion. Prospective cohort study. Patients older than 45 years, who underwent one- to two-level lumbar (L3-S1 levels) fusions. Comparison of the quantitative assessment of osteoporosis using Hounsfield Units (HU) on CT (L1-L5) and mean lumbar T-scores on DEXA (Dual Energy X-ray Absorptiometry). HU on CT is comparable to T-score on DEXA as a suitable modality for the assessment of osteoporosis in patients undergoing one- to two-level lumbar fusion. A prospective cohort study was conducted between January and December 2021. Patients older than 45 years, who underwent one- to two-level lumbar (L3-S1 levels) fusions and had complete clinico-radiological records, were prospectively enrolled. A comparison was drawn between the HU (measured by placing an oval region of interest [ROI] over axial, sagittal and coronal images of lumbar vertebrae) on CT and T-scores on DEXA, and analyzed statistically. The HU values correlating best with normal (group A), osteopenia (B) and osteoporosis (C) categories (classified based on T-scores of lumbar spines) were determined statistically. Overall, 87 patients (mean age of 60.56±11.63 years; 63 [72.4%] female patients) were prospectively studied. There was a statistically significant difference in the mean age (p=.01) and sex distribution (predominantly female patients; p=.03) of patients belonging to groups B (osteopenic) and C (osteoporotic patients), as compared with group A. The greatest correlation between T-score (on DEXA) and HU (on CT) for differentiating osteopenia (group B) from group A was observed at levels L1 (p<.001), L2 (p<.001) and L3 (p<.001). Based on receiver-operating characteristic (ROC) curve analysis, the cut-off values for HU for identifying osteopenia were 159 (at L1; sensitivity 81.6 and specificity 80) and 162 (at L2; sensitivity 80 and specificity 71.1). In addition, there was statistically significant correlation between T-score (on DEXA) and HU at all the lumbar levels for distinguishing osteoporosis (group C), although the difference was most evident at the upper lumbar (L1 and L2) levels (p<.001). Based on ROC analysis, cut-off HU values for defining osteoporosis were 127 (at L1; sensitivity 71.3 and specificity 70) and 117 (at L2; sensitivity 65.5 and specificity 90). Based on our study, the measurement of HU on CT at upper lumbar levels can be considered as "surrogate marker" for BMD in the diagnosis of osteopenia (cut-off: 159 at L1, 162 at L2) and osteoporosis (cut-off: 127 at L1, 117 at L2) in patients undergoing lumbar fusion surgeries. The HU measurements on CT at the lower lumbar levels (L4 and L5) are less reliable in this preoperative scenario.

Characteristics of MRI‑based vertebral bone quality scores in elderly patients with vertebral fragility fractures.

To explore the characteristics of vertebral bone quality (VBQ) scores in patients with vertebral fragility fractures, including VBQ score and single-level VBQ score, and evaluate their effectiveness as predictors. The VBQ scores were measured using T1-weighted MRI images. VBQ scores were compared in patients with different times of previous fragility fractures. In addition, patients with fractures were matched for age and sex with patients without fractures, and VBQ scores were compared between the two groups. Finally, the predictive efficiency of VBQ scores for vertebral fragility fractures was analyzed by the receiver-operator curve (ROC). The average VBQ score and single-level VBQ score in patients with fractures were 3.48 ± 0.56 and 3.60 ± 0.60 and no difference among patients with different times of previous fractures. As for the age- and sex-matched patients, fracture patients had higher VBQ scores (VBQ score: 3.48 ± 0.56 vs. 2.88 ± 0.40, p < 0.001; single-level VBQ score: 3.60 ± 0.60 vs. 2.95 ± 0.44, p < 0.001). The AUCs using the VBQ score and single-level VBQ score to predict fragility fractures were 0.815 and 0.817, respectively. The optimal thresholds of the VBQ score and single-level VBQ score for predicting fragility fractures were 3.22 and 3.16, respectively. MRI‑based VBQ scores are important predictors of vertebral fragility fracture but have no predictive value for the recurrence of fractures in patients with a history of fragility fractures. The VBQ score of 3.22 and single-level VBQ score of 3.16 are optimal thresholds that can be used when using lumbar MRI scans to identify individuals at high risk for fragility fractures.

Trabecular bone score, bone marrow fat and vertebral fractures in cushing syndrome.

Prediction of fragility fractures in Cushing syndrome (CS) is a challenge since dual energy X-ray absorptiometry (DXA) measurement of bone mineral density (BMD) does not capture all the alterations in bone microstructure induced by glucocorticoid excess. In this study we investigated the relationship between trabecular bone score (TBS), bone marrow fat (BMF) and vertebral fractures (VFs) in endogenous CS. Cross-sectional. Thirty subjects (7 M and 23 F, mean age 44.8 ± 13.4 yrs, range: 25-71) with active hypercortisolism were evaluated for VFs by quantitative morphometry, BMD and TBS by lumbar spine DXA and BMF by single-voxel magnetic resonance spectroscopy of vertebral body of L3. Subjects with VFs (17 cases; 56.7%) had higher BMF (P = 0.014) and lower BMD T-score (P = 0.012) and TBS (P = 0.004) as compared to those without VFs. Prevalence of VFs resulted to be significantly higher in individuals with impaired TBS as compared to those with normal TBS (77.8% vs. 25.0%; P = 0.008). Among patients with VFs, only 6 (35.3%) had either osteoporosis or "low BMD for age". In logistic regression analysis, impaired TBS maintained the significant association with VFs [odds ratio (OR) 6.60, 95% C.I. 1.07-40.61; P = 0.042] independently of BMF (OR 1.03, 95% C.I. 0.99-1.08; P = 0.152). TBS might be more accurate than BMF in identifying subjects with active CS and skeletal fragility at risk of VFs. Excess in glucocorticoids is associated with alterations in bone remodeling and metabolism, leading to fragility fractures regardless of bone mineral density, making more challenging for the clinician the identification of high-risk population and the definition of preventing strategies. In this context, instrumental parameters suggestive of bone quality alterations and predictive of increased fracture risk are needed. In this study, we found CS patients to have bone quality alterations as indicated by the decreased trabecular bone score and increased bone marrow fat, as measured by DEXA and MRI respectively. Both parameters were associated with high risk of VFs, and were inversely correlated, although TBS seems to be more accurate than BMF in fractures prediction in this clinical setting.

CFracture, an alternative to QFracture that accounts for mortality to better predict fragility fracture risk

One in two women and one in five men over the age of 50 years are estimated to sustain one or more fragility fractures—a low-trauma fracture sustained from a fall, slip, or trip from standing height or less—in their lifetime.1 In the UK, this estimate translates to approximately 549 000 fragility fracture per year,2 costing the National Health Service more than £4·7 billion.3 Similarly, across Europe, an estimated 4·3 million fragility fractures per year result in health-care costs in excess of €56·9 billion annually.

Patient physiology influences the MRI-based vertebral bone quality score

BACKGROUND CONTEXTOsteoporosis is a critical issue affecting postmenopausal women and the aging population. A novel magnetic resonance imaging (MRI)-based vertebral bone quality (VBQ) score has been proposed as a method to identify poor bone quality and predict fragility fractures. The diagnostic accuracy of this tool is not well understood. PURPOSETo examine the ability of VBQ to predict osteoporosis and osteopenia, its correlation with dual-energy x-ray absorptiometry (DEXA), and the influence of patient-specific factors upon the score. STUDY DESIGNRetrospective cohort study. PATIENT SAMPLEPatients over the age of 18 with a DEXA scan and noncontrast, T1-weighted MRI of the lumbar spine completed within a 2-year period. OUTCOME MEASURESArea-under-curve (AUC) values of the VBQ score predicting osteopenia and osteoporosis when controlling for patient characteristics. METHODSPatients with noncontrast, T1-weighted MRIs of the lumbar spine and DEXA scans completed within a 2-year time frame were retrospectively reviewed. Patient demographics and medical risk factors for osteoporosis were identified and compared. VBQ scores were measured by two trained researchers and interrater reliability was calculated. Patients were separated into three groups defined by lowest DEXA T-score: Healthy Bone, Osteopenia, and Osteoporosis. analysis of variance, Kruskal-Wallis test, chi-square, t tests, Mann-Whitney U tests, and multivariate linear regression were performed to examine the relationship between patient characteristics, DEXA t-scores, and VBQ scores. Receiver operating characteristic analysis and AUC values were generated for the prediction of osteopenia and osteoporosis. RESULTSA total of 156 patients were included for analysis. Sufficient inter-rater reliability was determined for VBQ measures (intraclass correlation coefficient: 0.81). Most patients were female (83%), postmenopausal (81%), and had hyperlipidemia (64%). Patients with hyperlipidemia and healthy bone density by DEXA had elevated baseline VBQ scores (p<.001) reflective of values seen in osteopenia and osteoporosis. The AUC of the VBQ score predicting osteopenia and osteoporosis changed to be more concordant with DEXA results after controlling for hyperlipidemia (AUC=0.72, 0.70 vs. AUC=0.88, 0.89; p<.001). Sub-analysis of hyperlipidemia subtypes revealed that elevated high-density lipoprotein is associated with elevated VBQ scores. CONCLUSIONSHyperlipidemia increased the MRI-based VBQ score in our healthy bone population. The high signal intensities resembled values seen in osteopenia and osteoporosis, suggesting that physiologic variables which impact bone composition may influence the VBQ score. Specifically, elevated high-density lipoprotein may contribute to this. The microarchitectural changes and the clinical implications of these factors need further exploration.

Normative Data and Reproducibility for Vertebral Bone Quality Score in Serial Lumbar Spine Magnetic Resonance Imaging

The vertebral bone quality (VBQ) score can independently predict fragility fractures and is useful for osteoporosis screening. It is derived by taking the ratio of the median L1-L4 signal intensity (SI) and L3 cerebral spinal fluid SI on opportunistic T1 weighted (fat sensitive) magnetic resonance imaging (MRI) scans. Higher VBQ score indicates more fat and less bone suggesting osteoporosis. Normative data has not been described. The purpose of this study was to determine whether VBQ score increased with age and remained consistent across serial MRI studies. This retrospective study evaluated 107 lumbar spine patients, age 20-69, who received two T1-weighted MRI within three months of each other between January 2011 and December 2021. Patients were divided into cohorts by decade of life. Patients with prior vertebral fracture, spinal metastasis, instrumentation at two or more levels, and MRI scans with spin sequences outside the optimal range for bone marrow analysis (TR=400-850, TE=8-20) were excluded. Regression analysis was performed to determine correlation of VBQ score with age. Interclass correlation (ICC) was calculated to determine reproducibility between VBQ scores derived from separate MRI scans. 53 males and 54 females were included in the study. 90% were Caucasian. The mean VBQ scores for the first and second set of MRI scans were 2.39±0.74 and 2.30±0.88, 2.68±0.57 and 2.54±0.74, 2.56±0.63 and 2.70±0.69, 2.99±0.72 and 2.77±0.89, 3.27±0.57 and 3.21±0.60 for the age ranges of 20-29, 30-39, 40-49, 50-59, 60-69, respectively. Among males, age positively correlated with VBQ scores measured from the first (r=0.361, p=0.008) and second (r=0.286, p=0.038) MRI scans. Among females, age likewise positively correlated with VBQ scores measured from the first (r=0.395, p=0.003) and second (r=0.398, p=0.003) MRI scans. For the entire cohort, the ICC=0.749. VBQ score is positively correlated with age. The majority of patients age > 50 had VBQ > 3.00, further supporting this threshold as a diagnostic cutoff for potential osteoporosis and additional bone health evaluation. Reproducibility of the VBQ score across serial MRI is good, which supports the possible usefulness of the VBQ score in the pre-operative evaluation of spine surgical patients.

Incidence and predictors of fragility fracture in postmenopausal rheumatoid arthritis patients receiving oral bisphosphonates: a longitudinal observational study

BackgroundAlthough many studies have reported the predictors of fractures in patients with rheumatoid arthritis (RA) who are not receiving anti-osteoporotic treatments or who are receiving unspecified treatments, studies focusing on the predictors of fracture in patients with RA who are currently being treated with oral bisphosphonates (BP) are quite scarce. This study aims to investigate the incidence and predictors of fragility fracture in postmenopausal patients with RA receiving oral BP.MethodsThis retrospective longitudinal observational study comprised 98 postmenopausal RA patients receiving oral BP for a minimum of 6 months between April 2015 and December 2020. The cumulative incidence of fragility fractures including vertebral and nonvertebral fractures was investigated using the Kaplan–Meier method. Cox proportional hazards analysis was used to analyze baseline predictors of future fragility fractures. To determine a cutoff value of continuous predictors, the receiver-operating characteristic curve was applied.ResultsTwenty patients developed fractures during the study period, with a cumulative incidence of 6.1% at 12 months, 10.5% at a median follow-up of 28 months, and 14.4% at 36 months. Multivariable Cox hazards analysis showed a history of prior vertebral fracture (hazard ratio [HR] 6.26, 95% confidence interval [CI] 1.99‒19.68, P = 0.001) and dose of methotrexate (HR 0.87, 95% CI 0.76‒0.99, P = 0.041) to be independent predictors. The cutoff value for methotrexate dose was 4 mg/week.ConclusionsWe found a cumulative incidence of any fractures of 10.5% at 28 months in patients with RA currently being treated with oral BP. A history of prior vertebral fractures and methotrexate dose were positive and negative predictors for fractures, respectively. Practitioners should consider selecting another anti-osteoporotic drug in patients with RA who remain at risk despite receiving oral BP.

Beyond bone mineral density: new developments in dual X-ray absorptiometry assessment of bone quality

Bone mineral density, bone texture, bone geometry and bone strength are all elements necessary for a proper osteoporotic fragility fracture prediction assessment. Data regarding bone quantity (density) and, in part, bone quality (structure and geometry) are obtained by the gold standard method of dual X-ray absorptiometry (DXA), while data about bone strength are obtained by means of a new DXA index called the bone strain index (BSI). The BSI evaluates bone resistance by means of average strain calculation, and it is based on finite element analysis applied to DXA spine and femoral scans. The BSI includes local information on bone density distribution, bone geometry and, unlike variables of bone mineral density and bone quality such as the trabecular bone score, it represents the status of the bone in a particular loading condition. This review illustrates the methodology for calculating the BSI and discusses findings on its reproducibility and data about its capability to predict fragility fractures and monitor pharmacological treatment for osteoporosis.

Bone Strain Index predicts fragility fracture in osteoporotic women: an artificial intelligence-based study

BackgroundWe applied an artificial intelligence-based model to predict fragility fractures in postmenopausal women, using different dual-energy x-ray absorptiometry (DXA) parameters.MethodsOne hundred seventy-four postmenopausal women without vertebral fractures (VFs) at baseline (mean age 66.3 ± 9.8) were retrospectively evaluated. Data has been collected from September 2010 to August 2018. All subjects performed a spine x-ray to assess VFs, together with lumbar and femoral DXA for bone mineral density (BMD) and the bone strain index (BSI) evaluation. Follow-up exams were performed after 3.34 ± 1.91 years. Considering the occurrence of new VFs at follow-up, two groups were created: fractured versus not-fractured. We applied an artificial neural network (ANN) analysis with a predictive tool (TWIST system) to select relevant input data from a list of 13 variables including BMD and BSI. A semantic connectivity map was built to analyse the connections among variables within the groups. For group comparisons, an independent-samples t-test was used; variables were expressed as mean ± standard deviation.ResultsFor each patient, we evaluated a total of n = 6 exams. At follow-up, n = 69 (39.6%) women developed a VF. ANNs reached a predictive accuracy of 79.56% within the training testing procedure, with a sensitivity of 80.93% and a specificity of 78.18%. The semantic connectivity map showed that a low BSI at the total femur is connected to the absence of VFs.ConclusionWe found a high performance of ANN analysis in predicting the occurrence of VFs. Femoral BSI appears as a useful DXA index to identify patients at lower risk for lumbar VFs.

65 Comparison of Frax and Qfracture in Predicting Fragility Fractures in Patients Presenting with Falls

Abstract Introduction Falls are a major risk factor for fragility fractures and patients should be appropriately assessed to reduce future fragility fracture risk. National guidelines provide recommendations on assessing fracture risk using calculators to guide therapy initiation. FRAX and QFracture are the two main calculators used, however they differ considerably in their inputs. The aim of this study was to compare the risk estimation and performance between these two frequently used calculators to help determine their appropriate utility. Methods Data from patients aged ≥70 years admitted with a fall to the Acute Medical Units at Charing Cross Hospital between 1st Dec 2018–31st March 2019 were retrospectively collected, covering all inputs required for the two risk calculators. The 10-year major osteoporotic and hip fracture risks were calculated using FRAX and QFracture and compared. The one-year major osteoporotic and hip fracture risks from QFracture were assessed against actual one-year fracture rates. Results Conclusions Risk calculators are effective tools to aid the decision of bone therapy initiation. Here we demonstrate that there is a strong correlation between the two commonly used calculators. However, in terms of absolute risk values there is a mean 8.9% difference with QFracture providing higher risks in this “fallers” group. As absolute treatment thresholds are frequently used to guide bone therapy initiation, opposing recommendations may result. Therefore, there is a need to further explore calculator performance and determine which would more accurately serve different patient groups.

Beyond Bone Mineral Density: A New Dual X-Ray Absorptiometry Index of Bone Strength to Predict Fragility Fractures, the Bone Strain Index.

For a proper assessment of osteoporotic fragility fracture prediction, all aspects regarding bone mineral density, bone texture, geometry and information about strength are necessary, particularly in endocrinological and rheumatological diseases, where bone quality impairment is relevant. Data regarding bone quantity (density) and, partially, bone quality (structure and geometry) are obtained by the gold standard method of dual X-ray absorptiometry (DXA). Data about bone strength are not yet readily available. To evaluate bone resistance to strain, a new DXA-derived index based on the Finite Element Analysis (FEA) of a greyscale of density distribution measured on spine and femoral scan, namely Bone Strain Index (BSI), has recently been developed. Bone Strain Index includes local information on density distribution, bone geometry and loadings and it differs from bone mineral density (BMD) and other variables of bone quality like trabecular bone score (TBS), which are all based on the quantification of bone mass and distribution averaged over the scanned region. This state of the art review illustrates the methodology of BSI calculation, the findings of its in reproducibility and the preliminary data about its capability to predict fragility fracture and to monitor the follow up of the pharmacological treatment for osteoporosis.