Vertebral Fracture Assessment Increases Use of Pharmacologic Therapy for Fracture Prevention in Clinical Practice

Association between a history of major osteoporotic fractures and subsequent hip fracture: a systematic review and meta-analysis

PURPOSE

A history of fractures involving the distal radius, proximal humerus, spine, and hip may be associated with the incidence of subsequent hip fractures in older people. However, a comprehensive summary of this association using a rigorous methodology is lacking. Our objective was to systematically review the literature and examine the association between four major osteoporotic fractures and subsequent hip fractures in individuals aged ≥ 50 years.

METHODS

We searched MEDLINE, Embase, CENTRAL, ICTRP, and ClinicalTrials.gov on February 15, 2023. The search included cohort or case-control studies investigating the association between these four types of osteoporotic fractures and subsequent hip fractures. We pooled the hazard ratios (HRs) with 95% confidence intervals (CI) using the random-effects model. We used the Quality In Prognosis Studies tool to assess the risk of bias in the included studies, and the grading of recommendations assessment, development, and evaluation approach to determine the certainty of evidence.

RESULTS

The selection process identified 48 studies for qualitative synthesis and 23 studies (2,239,217 participants) for meta-analysis. The overall methodological quality had a low risk of bias in 65% of the included studies. The association between a history of major osteoporotic fractures and subsequent hip fracture varied, with a high certainty of evidence for a history of proximal humerus and hip fractures (HR 2.02, 95% CI 1.75-2.33 and 2.86, 95% CI 1.92-4.25, respectively), moderate certainty for distal radius fractures (HR 1.66, 95% CI 1.53-1.81), and low certainty for spine fractures (HR 1.53, 95% CI 1.38-1.69).

CONCLUSIONS

In conclusion, a history of major osteoporotic fractures, particularly distal radius, proximal humerus, and hip fractures, is associated with subsequent hip fractures in older adults. Further research is needed to verify the association between a history of spine fracture and subsequent hip fractures.

PROTOCOL REGISTRATION

Open Science Framework ( https://osf.io/7fjuc ).

Quality improvement initiative: implementing routine vertebral fracture assessments into an Australian Fracture Liaison Service

Osteoporosis is a global health concern and a major contributor to worldwide mortality rates. Vertebral fractures due to osteoporosis are common and often undetected. Since vertebral fractures are often missed, evidence and guidelines suggest that vertebral fracture assessment (VFA) may optimise current approaches to bone density tests. We aimed to integrate VFA into an Australian Fracture Liaison Service (FLS) and measure the impact it had on osteoporosis treatment initiation.A retrospective case note review was undertaken to determine the number of clinic patients receiving VFA before the change in practice. Proctor's seven domains of implementation strategy were used to facilitate quality improvement outcomes.The percentage of eligible patients receiving a routine VFA at the FLS imaging centre increased from 0% to 90%. The remaining 10% of patients did not receive a scan due to the patient not being able to assume the correct position, skilled staff being unavailable to perform the scan, or the patient declining. Post implementation, almost half (41%) of patients who underwent a VFA displayed abnormalities and 16 (4%) of these recorded a normal bone measure density score but abnormal VFA. Despite the successful adoption of the new screening protocol, there was no statistically significant increase in treatment initiation rates for patients with normal bone mass density scores.The FLS successfully integrated routine VFA into the osteoporosis care pathway. However, the introduction of VFA did not significantly increase treatment initiation. It may be more effective to offer VFAs to a proportion of patients based on a tailored approach rather than offering them routinely to all patients who access the FLS.

Machine learning for abdominal aortic calcification assessment from bone density machine-derived lateral spine images

BACKGROUND

Lateral spine images for vertebral fracture assessment can be easily obtained on modern bone density machines. Abdominal aortic calcification (AAC) can be scored on these images by trained imaging specialists to assess cardiovascular disease risk. However, this process is laborious and requires careful training.

METHODS

Training and testing of model performance of the convolutional neural network (CNN) algorithm for automated AAC-24 scoring utilised 5012 lateral spine images (2 manufacturers, 4 models of bone density machines), with trained imaging specialist AAC scores. Validation occurred in a registry-based cohort study of 8565 older men and women with images captured as part of routine clinical practice for fracture risk assessment. Cox proportional hazards models were used to estimate the association between machine-learning AAC (ML-AAC-24) scores with future incident Major Adverse Cardiovascular Events (MACE) that including death, hospitalised acute myocardial infarction or ischemic cerebrovascular disease ascertained from linked healthcare data.

FINDINGS

The average intraclass correlation coefficient between imaging specialist and ML-AAC-24 scores for 5012 images was 0.84 (95% CI 0.83, 0.84) with classification accuracy of 80% for established AAC groups. During a mean follow-up 4 years in the registry-based cohort, MACE outcomes were reported in 1177 people (13.7%). With increasing ML-AAC-24 scores there was an increasing proportion of people with MACE (low 7.9%, moderate 14.5%, high 21.2%), as well as individual MACE components (all p-trend <0.001). After multivariable adjustment, moderate and high ML-AAC-24 groups remained significantly associated with MACE (HR 1.54, 95% CI 1.31-1.80 & HR 2.06, 95% CI 1.75-2.42, respectively), compared to those with low ML-AAC-24.

INTERPRETATION

The ML-AAC-24 scores had substantial levels of agreement with trained imaging specialists, and was associated with a substantial gradient of risk for cardiovascular events in a real-world setting. This approach could be readily implemented into these clinical settings to improve identification of people at high CVD risk.

FUNDING

The study was supported by a National Health and Medical Research Council of Australia Ideas grant and the Rady Innovation Fund, Rady Faculty of Health Sciences, University of Manitoba.

Should vertebral fracture assessment be performed in Fracture Liaison Service patients with non-vertebral fracture?

Prior non-vertebral fractures, except of the ankle, are associated with increased likelihood of vertebral fracture. As knowledge of vertebral fracture presence may alter care, vertebral fracture assessment (VFA) is indicated in patients with prior fracture.

INTRODUCTION

Vertebral fractures are often unappreciated. It was recently advocated that all Fracture Liaison Service (FLS) patients have densitometric VFA performed. We evaluated the likelihood of vertebral fracture identification with VFA in patients with prior fracture using the Manitoba Bone Density database. METHODS : VFA was performed in patients with T-scores below - 1.5 and age 70 + (or younger with height loss or glucocorticoid use) obtaining bone densitometry in Manitoba from 2010 to 2018. Those with prior clinical vertebral fracture, pathologic fracture, or uninterpretable VFA were excluded. Vertebral fractures were identified using the modified ABQ method. Health records were assessed for non-vertebral fracture (excluding head, neck, hand, foot) diagnosis codes unassociated with trauma prior to DXA. Multivariable odds ratios (ORs) for vertebral fracture were estimated without and with adjustment for age, sex, body mass index, ethnicity, area of residence, income level, comorbidity score, diabetes mellitus, falls in the last year, glucocorticoid use, and lowest BMD T-score.

RESULTS

The study cohort consisted of 12,756 patients (94.4% women) with mean (SD) age 75.9 (6.8) years. Vertebral fractures were identified in 1925 (15.1%) overall. Vertebral fractures were significantly more likely (descending order) in those with prior pelvis, hip, humerus, other sites, and forearm, but not ankle fracture. There was modest attenuation with covariate adjustment but statistical significance was maintained.

CONCLUSIONS

Prior hip, humerus, pelvis, forearm, and other fractures are associated with an increased likelihood of previously undiagnosed vertebral fracture, information useful for risk stratification and monitoring. These data support recommending VFA in FLS patients who are age 70 + with low BMD.

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.

Post-fracture care programs for prevention of subsequent fragility fractures: a literature assessment of current trends

Post-fracture care (PFC) programs evaluate and manage patients with a minimal trauma or fragility fracture to prevent subsequent fractures. We conducted a literature review to understand current trends in PFC publications, evaluate key characteristics of PFC programs, and assess their clinical effectiveness, geographic variations, and cost-effectiveness. We performed a search for peer-reviewed articles published between January 2003 and December 2020 listed in PubMed or Google Scholar. We categorized identified articles into 4 non-mutually exclusive PFC subtopics based on keywords and abstract content: PFC Types, PFC Effectiveness/Success, PFC Geography, and PFC Economics. The literature search identified 784 eligible articles. Most articles fit into multiple PFC subtopics (PFC Types, 597; PFC Effectiveness/Success, 579; PFC Geography, 255; and PFC Economics, 98). The number of publications describing how PFC programs can improve osteoporosis treatment rates has markedly increased since 2003; however, publication gaps remain, including low numbers of publications from some countries with reported high rates of osteoporosis and/or hip fractures. Fracture liaison services and geriatric/orthogeriatric services were the most common models of PFC programs, and both were shown to be cost-effective. We identified a need to expand and refine PFC programs and to standardize patient identification and reporting on quality improvement measures. Although there is an increasing awareness of the importance of PFC programs, publication gaps remain in most countries. Improvements in established PFC programs and implementation of new PFC programs are still needed to enhance equitable patient care to prevent occurrence of subsequent fractures.

Development of a manufacturer-independent convolutional neural network for the automated identification of vertebral compression fractures in vertebral fracture assessment images using active learning

BACKGROUND

Convolutional neural networks (CNNs) can identify vertebral compression fractures in GE vertebral fracture assessment (VFA) images with high balanced accuracy, but performance against Hologic VFAs is unknown. To obtain good classification performance, supervised machine learning requires balanced and labeled training data. Active learning is an iterative data annotation process with the ability to reduce the cost of labeling medical image data and reduce class imbalance.

PURPOSE

To train CNNs to identify vertebral fractures in Hologic VFAs using an active learning approach, and evaluate the ability of CNNs to generalize to both Hologic and GE VFA images.

METHODS

VFAs were obtained from the OsteoLaus Study (labeled Hologic Discovery A, n = 2726), the Manitoba Bone Mineral Density Program (labeled GE Prodigy and iDXA, n = 12,742), and the Canadian Longitudinal Study on Aging (CLSA, unlabeled Hologic Discovery A, n = 17,190). Unlabeled CLSA VFAs were split into five equal-sized partitions (n = 3438) and reviewed sequentially using active learning. Based on predicted fracture probability, 17.6% (n = 3032) of the unlabeled VFAs were selected for expert review using the modified algorithm-based qualitative (mABQ) method. CNNs were simultaneously trained on Hologic, GE dual-energy and GE single-energy VFAs. Two ensemble CNNs were constructed using the maximum and mean predicted probability from six separately trained CNNs that differed due to stochastic variation. CNNs were evaluated against the OsteoLaus validation set (n = 408) during the active learning process; ensemble performance was measured against the OsteoLaus test set (n = 819).

RESULTS

The baseline CNN, prior to active learning, achieved 55.0% sensitivity, 97.9% specificity, 57.9% positive predictive value (PPV), F1-score 56.4%. Through active learning, 2942 CLSA Hologic VFAs (492 fractures) were added to the training data-increasing the proportion of Hologic VFAs with fractures from 4.2% to 12.5%. With active learning, CNN performance improved to 80.0% sensitivity, 99.7% specificity, 94.1% PPV, F1-score 86.5%. The CNN maximum ensemble achieved 91.9% sensitivity (100% for grade 3 and 95.5% for grade 2 fractures), 99.0% specificity, 81.0% PPV, F1-score 86.1%.

CONCLUSION

Simultaneously training on a composite dataset consisting of both Hologic and GE VFAs allowed for the development of a single manufacturer-independent CNN that generalized to both scanner types with good classification performance. Active learning can reduce class imbalance and produce an effective medical image classifier while only labeling a subset of available unlabeled image data-thereby reducing the time and cost required to train a machine learning model.

High prevalence of vertebral fractures in seizure patients with normal bone density receiving chronic anti-epileptic drugs

People with epilepsy who take certain medications are at risk for developing osteoporosis and fractures of the vertebrae that commonly go undiagnosed. By using technology available in a bone density scan, we observed at least one fracture in many subjects with bone density in the normal and osteopenic range.

PURPOSE/INTRODUCTION

Chronic use of antiepileptic drugs (AEDs), both enzyme-inducing (phenytoin, phenobarbital, carbamazepine, and primidone) and non-enzyme-inducing (i.e., valproate), is recognized as a cause of secondary osteoporosis. Vertebral compression fractures (VF) are the most common type of osteoporotic fractures and may confer an increased risk of future hip, wrist, and vertebral fractures. Vertebral compression fractures in the general population are frequently asymptomatic, and under-diagnosed. The purpose of this study is to describe the prevalence of VF in a cohort of male veterans with epilepsy on chronic AEDs.

METHODS

The cohort for this study consisted of 146 male veterans who carried a diagnosis of epilepsy and were chronic users of AEDs known to cause osteoporosis (phenobarbital, phenytoin, carbamazepine, primidone, and valproate). Chronic AED use was defined as receiving an AED for at least 2 years. Subjects were previously seen in the osteoporosis clinic and had been evaluated by a dual-energy X-Ray absormetry (DXA) instrument including morphometric studies following a standard vertebral fracture assessment (VFA) protocol during the same DXA imaging acquisition session.

RESULTS

The mean age was 63 years. Low bone mineral density defined as osteoporosis or osteopenia was observed in 29% and 43% respectively. We observed at least one VF in 41 % of the subjects who had normal BMD, 54% in the osteopenic range, and 75% in the osteoporotic range.

CONCLUSIONS

By performing a VFA in addition to standard bone densitometric studies, we disclosed a large prevalence of compression fractures in individuals with epilepsy chronically treated with AEDs who had BMDs in the normal and osteopenic ranges. The addition of VFA or other imaging methods to evaluate VF should be included in the evaluation of bone health in individuals with epilepsy receiving AEDs since it may modify treatment recommendations to prevent future osteoporotic fractures.

Feasibility of a generalized convolutional neural network for automated identification of vertebral compression fractures: The Manitoba Bone Mineral Density Registry

BACKGROUND

Vertebral fracture assessment (VFA) images are acquired in dual-energy (DE) or single-energy (SE) scan modes. Automated identification of vertebral compression fractures, from VFA images acquired using GE Healthcare scanners in DE mode, has achieved high accuracy through the use of convolutional neural networks (CNNs). Due to differences between DE and SE images, it is uncertain whether CNNs trained on one scan mode will generalize to the other.

PURPOSE

To evaluate the ability of CNNs to generalize between GE DE and GE SE VFA scan modes.

METHODS

12,742 GE VFA images from the Manitoba Bone Mineral Density Program, obtained between 2010 and 2017, were exported in both DE and SE modes. VFAs were classified by imaging specialists as fracture present or absent using the modified algorithm-based qualitative (mABQ) method. VFA scans were randomly divided into independent training (60%), validation (10%), and test (30%) sets. Three CNN models were constructed by training separately on DE only, SE only, and a composite dataset comprised of both SE and DE VFAs. All three trained CNN models were separately evaluated against both SE and DE test datasets.

RESULTS

Good performance was seen for CNNs trained and evaluated on the same scan mode. DE scans used for both training and evaluation (DE/DE) achieved 87.9% sensitivity, 87.4% specificity, and an area under the receiver operating characteristic curve (AUC) of 0.94. SE scans used for both training and evaluation (SE/SE) achieved 78.6% sensitivity, 90.6% specificity, AUC = 0.92. Conversely, CNNs performed poorly when evaluated on scan modes that differed from their training sets (AUC = 0.58). However, a composite CNN trained simultaneously on both SE and DE VFAs gave performance comparable to DE/DE (82.4% sensitivity, 94.3% specificity, AUC = 0.95); and provided improved performance over SE/SE (82.2% sensitivity, 92.3% specificity, AUC = 0.94). Positive predictive value was higher with the composite CNN compared with models trained solely on DE (74.5% vs. 58.7%) or SE VFAs (68.6% vs. 62.9%).

CONCLUSION

CNNs for vertebral fracture identification are highly sensitive to scan mode. Training CNNs on a composite dataset, comprised of both GE DE and GE SE VFAs, allows CNNs to generalize to both scan modes and may facilitate the development of manufacturer-independent machine learning models for vertebral fracture detection.

Vertebral Fracture Assessment in Postmenopausal Women With Postsurgical Hypoparathyroidism

CONTEXT

Hypoparathyroidism is a rare endocrine disorder whose skeletal features include suppression of bone turnover and greater volume and width of the trabecular compartment. Few and inconsistent data are available on the prevalence of vertebral fractures (VF).

OBJECTIVE

To evaluate the prevalence of VF assessed by vertebral fracture assessment (VFA) in postmenopausal women with chronic postsurgical hypoparathyroidism.

DESIGN

Cross-sectional study.

SETTING

Ambulatory referral center.

PATIENTS OR OTHER PARTICIPANTS

Fifty postmenopausal women (mean age 65.4 ± 9 years) with chronic postsurgical hypoparathyroidism and 40 age-matched healthy postmenopausal women (mean age 64.2 ± 8.6).

MAIN OUTCOME MEASURES

Lumbar spine, femoral neck, and total hip bone mineral density were measured by dual X-ray absorptiometry (Hologic Inc., USA) in all subjects. Site-matched spine trabecular bone score was calculated by TBS iNsight (Medimaps, Switzerland). Assessment of VF was made by VFA (iDXA, Lunar GE, USA) using the semiquantitative method and the algorithm-based qualitative assessment.

RESULTS

All-site BMD values were higher in the hypoparathyroid vs the control group. By VFA, we observed a 16% prevalence of VF in hypoparathyroid women vs 7.5% in control subjects. Among those with hypoparathyroidism who fractured, 5 (62.5%) had grade 1 wedge, 2 (25%) had grade 2 wedge, and 1 (12.5%) had grade 2 wedge and grade 2 biconcave VF. In the hypoparathyroid group, 57% with VFs and 32% without VFs had symptoms of hypoparathyroidism.

CONCLUSION

We demonstrate for the first time that in postmenopausal women with chronic postsurgical hypoparathyroidism, VFs are demonstrable by VFA despite normal BMD.

Vertebral fracture: epidemiology, impact and use of DXA vertebral fracture assessment in fracture liaison services

Vertebral fractures are independent risk factors for vertebral and nonvertebral fractures. Since vertebral fractures are often missed, the relatively new introduction of vertebral fracture assessment (VFA) for imaging of the lateral spine during DXA-measurement of the spine and hips may contribute to detect vertebral fractures. We advocate performing a VFA in all patients with a recent fracture visiting a fracture liaison service (FLS). Fracture liaison services (FLS) are important service models for delivering secondary fracture prevention for older adults presenting with a fragility fracture. While commonly age, clinical risk factors (including fracture site and number of prior fracture) and BMD play a crucial role in determining fracture risk and indications for treatment with antiosteoporosis medications, prevalent vertebral fractures usually remain undetected. However, vertebral fractures are important independent risk factors for future vertebral and nonvertebral fractures. A development of the DXA technology, vertebral fracture assessment (VFA), allows for assessment of the lateral spine during the regular DXA bone mineral density measurement of the lumbar spine and hips. Recent approaches to the stratification of antiosteoporosis medication type according to baseline fracture risk, and differences by age in the indication for treatment by prior fracture mean that additional information from VFA may influence initiation and type of treatment. Furthermore, knowledge of baseline vertebral fractures allows reliable definition of incident vertebral fracture events during treatment, which may modify the approach to therapy. In this manuscript, we will discuss the epidemiology and clinical significance of vertebral fractures, the different methods of detecting vertebral fractures, and the rationale for, and implications of, use of VFA routinely in FLS. • Vertebral fracture assessment is a tool available on modern DXA instruments and has proven ability to detect vertebral fractures, the majority of which occur without a fall and without the signs and symptoms of an acute fracture. • Most osteoporosis guidelines internationally suggest that treatment with antiosteoporosis medications should be considered for older individuals (e.g., 65 years +) with a recent low trauma fracture without the need for DXA. • Younger individuals postfracture may be risk-assessed on the basis of FRAX® probability including DXA and associated treatment thresholds. • Future fracture risk is markedly influenced by both site, number, severity, and recency of prior fracture; awareness of baseline vertebral fractures facilitates definition of true incident vertebral fracture events occurring during antiosteoporosis treatment. • Detection of previously clinically silent vertebral fractures, defining site of prior fracture, might alter treatment decisions in younger or older FLS patients, consistent with recent IOF-ESCEO guidance on baseline-risk-stratified therapy, and provides a reliable baseline from which to define new, potentially therapy-altering, vertebral fracture events.

Vertebral fracture assessment (VFA) for osteoporosis screening in US postmenopausal women: is it cost-effective?

Vertebral fracture assessment (VFA) is cost-effective when it was incorporated in the routine screening for osteoporosis in community-dwelling women aged ≥ 65 years, which support guidelines, such as the National Osteoporosis Foundation (NOF) for the diagnostic use of VFA as an important addition to fracture risk assessment.

INTRODUCTION

To evaluate the cost-effectiveness of VFA as a screening tool to reduce future fracture risk in US community-dwelling women aged ≥ 65 years.

METHODS

An individual-level state-transition cost-effectiveness model from a healthcare perspective was constructed using derived data from published literature. The time horizon was lifetime. Five screening strategies were compared, including no screening at all, central dual-energy X-ray absorptiometry (DXA) only, VFA only, central DXA followed by VFA if the femoral neck T-score (FN-T) ≤ - 1.5, or if the FN-T ≤ - 1.0. Various initiation ages and rescreening intervals were evaluated. Oral bisphosphonate treatment for 5-year periods was assumed. Incremental cost-effectiveness ratios (2017 US dollars per quality-adjusted life-year (QALY) gained) were used as the outcome measure.

RESULTS

The incorporation of VFA slightly increased life expectancy by 0.1 years and reduced the number of subsequent osteoporotic fractures by 3.7% and 7.7% compared with using DXA alone and no screening, respectively, leading to approximately 30 billion dollars saved. Regardless of initiation ages and rescreening intervals, central DXA followed by VFA if the FN-T ≤ - 1.0 was most cost-effective ($40,792 per QALY when the screening is initiated at age 65 years and with rescreening every 5 years). Results were robust to change in VF incidence and medication costs.

CONCLUSION

In women aged ≥ 65 years, VFA is cost-effective when it was incorporated in routine screening for osteoporosis. Our findings support the National Osteoporosis Foundation (NOF) guidelines for the diagnostic use of VFA as an important addition to fracture risk assessment.

A Risk Assessment Tool for Predicting Fragility Fractures and Mortality in the Elderly

Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current undermanagement of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and its consequences. The study involved 8965 people aged ≥60 years from the Dubbo Osteoporosis Epidemiology Study and the Canadian Multicentre Osteoporosis Study. Incident fracture was identified from X-ray reports and questionnaires, and death was ascertained though contact with a family member or obituary review. We used a multistate model to quantify the effects of the predictors on the transition risks to an initial and subsequent incident fracture and mortality, accounting for their complex interrelationships, confounding effects, and death as a competing risk. There were 2364 initial fractures, 755 subsequent fractures, and 3300 deaths during a median follow-up of 13 years (interquartile range [IQR] 7-15). The prediction model included sex, age, bone mineral density, history of falls within 12 previous months, prior fracture after the age of 50 years, cardiovascular diseases, diabetes mellitus, chronic pulmonary diseases, hypertension, and cancer. The model accurately predicted fragility fractures up to 11 years of follow-up and post-fracture mortality up to 9 years, ranging from 7 years after hip fractures to 15 years after non-hip fractures. For example, a 70-year-old woman with a T-score of -1.5 and without other risk factors would have 10% chance of sustaining a fracture and an 8% risk of dying in 5 years. However, after an initial fracture, her risk of sustaining another fracture or dying doubles to 33%, ranging from 26% after a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction model for individualization of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. © 2020 American Society for Bone and Mineral Research.

Vertebral fracture assessment (VFA) in patients over 50 years of age with a non-severe peripheral fracture

The prevalence of unknown vertebral fractures evaluated by systematic vertebral fracture assessment (VFA) was 21% in patients over 50 years of age who suffered from a recent low-trauma non-severe peripheral fracture. The outcome of VFA resulted in changes in the management of osteoporosis.

INTRODUCTION

The aim of this study was to evaluate the utility of VFA in detecting vertebral fractures (VFs) in patients over 50 years of age, who suffered from a recent low-trauma non-severe peripheral fracture.

METHODS

This was an observational, single-center, cross-sectional study conducted in patients over 50 years of age, who presented a recent low-trauma non-severe peripheral fracture and were identified by the Fracture Liaison Service (FLS) of Amiens University Hospital between December 2017 and March 2019. VFA was interpreted by two trained rheumatologists providing a consensual reading using Genant semi-quantitative assessment.

RESULTS

Of the 359 eligible patients, 114 patients (31.8%) were included (mean age 65.6 ± 8.4 years; 89.5% female). Twenty-four patients (21%) had one or more VF diagnosed by VFA. The total number of VF diagnosed by VFA was 30: 20 VF (66.7%) grade 1, 7 VF (23.3%) grade 2, and 3 VF (10%) grade 3. Among the 24 patients with at least one prevalent VF diagnosed by VFA, 18 patients had an osteoporosis medication adaptation after the VFA results (16 osteoporosis medication initiation and 2 treatment intensification), and 6 patients would have had an osteoporosis medication even without the VFA results (66.7% versus 33.3% respectively, p < 0.001). Of the 51 patients receiving an osteoporosis medication after DXA and VFA, 18 patients (35.3%) had a change in the management of osteoporosis after knowing the outcome of VFA. All the VFs diagnosed by VFA were unknown before. We did not evidence any threshold (age, T-score, height loss) below which no VF was detected.

CONCLUSIONS

Our study demonstrates the usefulness of systematic VFA to detect prevalent VF in patients over 50 years of age who suffer from a recent non-severe peripheral fracture.

New Developments in Fracture Risk Assessment for Current Osteoporosis Reports

PURPOSE OF REVIEW

Identifying individuals at high fracture risk can be used to target those likely to derive the greatest benefit from treatment. This narrative review examines recent developments in using specific risk factors used to assess fracture risk, with a focus on publications in the last 3 years.

RECENT FINDINGS

There is expanding evidence for the recognition of individual clinical risk factors and clinical use of composite scores in the general population. Unfortunately, enthusiasm is dampened by three pragmatic randomized trials that raise questions about the effectiveness of widespread population screening using clinical fracture prediction tools given suboptimal participation and adherence. There have been refinements in risk assessment in special populations: men, patients with diabetes, and secondary causes of osteoporosis. New evidence supports the value of vertebral fracture assessment (VFA), high resolution peripheral quantitative CT (HR-pQCT), opportunistic screening using CT, skeletal strength assessment with finite element analysis (FEA), and trabecular bone score (TBS). The last 3 years have seen important developments in the area of fracture risk assessment, both in the research setting and translation to clinical practice. The next challenge will be incorporating these advances into routine work flows that can improve the identification of high risk individuals at the population level and meaningfully impact the ongoing crisis in osteoporosis management.

The Belgian Bone Club 2020 guidelines for the management of osteoporosis in postmenopausal women

PURPOSE

To provide updated evidence-based guidelines for the management of osteoporosis in postmenopausal women in Belgium.

METHODS

The Belgian Bone Club (BBC) gathered a guideline developer group. Nine "Population, Intervention, Comparator, Outcome" (PICO) questions covering screening, diagnosis, non-pharmacological and pharmacological treatments, and monitoring were formulated. A systematic search of MEDLINE, the Cochrane Database of Systematic Reviews, and Scopus was performed to find network meta-analyses, meta-analyses, systematic reviews, guidelines, and recommendations from scientific societies published in the last 10 years. Manual searches were also performed. Summaries of evidence were provided, and recommendations were further validated by the BBC board members and other national scientific societies' experts.

RESULTS

Of the 3840 references in the search, 333 full texts were assessed for eligibility, and 129 met the inclusion criteria. Osteoporosis screening using clinical risk factors should be considered. Patients with a recent (<2 years) major osteoporotic fracture were considered at very high and imminent risk of future fracture. The combination of bone mineral density measured by dual-energy X-ray absorptiometry and 10-year fracture risk was used to categorize patients as low or high risk. Patient education, the combination of weight-bearing and resistance training, and optimal calcium intake and vitamin D status were recommended. Antiresorptive and anabolic osteoporosis treatment should be considered for patients at high and very high fracture risk, respectively. Follow-up should focus on compliance, and patient-tailored monitoring should be considered.

CONCLUSION

BBC guidelines and 25 guideline recommendations bridge the gap between research and clinical practice for the screening, diagnosis, and management of osteoporosis.