Bone and muscle diseases are both highly prevalent in aging adults, but results from previous studies examining the relationship between sarcopenia and its components with osteoporosis are inconsistent. This study aimed to investigate the associations between sarcopenia, its components, and osteoporosis in older women from the Fracture RISk Brussels Epidemiological Enquiry (FRISBEE) cohort. Additionally, it explored the relationship between sarcopenia components and trabecular bone score (TBS). This study is based on cross-sectional data from the FRISBEE cohort, involving 3560 community-dwelling postmenopausal women initially included between 2007 and 2013. Consecutively included participants were reassessed 10 years after inclusion, with evaluations including body composition by dual-energy X-ray absorptiometry (DXA), a medical questionnaire, and a comprehensive geriatric assessment. The diagnostic criteria for sarcopenia were: low muscle mass (appendicular skeletal muscle index [ASMi] < 5.5 kg/m2), low muscle strength (< 16 kg), and low gait speed (≤ 0.8 m/s), according to the European Working Group on Sarcopenia in Older People (EWGSOP2). Osteoporosis was defined using the extended criteria proposed by the National Bone Health Alliance Working Group. Among the 500 women included, with a median age of 77.4 years (74.7–81.8), 178 (35.6

We assessed the associations between osteosarcopenia, sarcopenia (according to seven definitions), and the presence of radiologically validated recent osteoporotic fractures in community-dwelling older women from the Fracture Risk Brussels Epidemiological Enquiry (FRISBEE2) study. Retrospective cohort design. The FRISBEE2 study includes 907 community-dwelling women aged 77 (75–81) years. Sarcopenia (according to six consensual definitions: EWGSOP2 “probable” and “confirmed”; IWGS; SCWD; SDOC; FNIH, and as seventh, an exploratory, potential framework for the GLIS), osteoporosis (T-score ≤ − 2.5SD), and osteosarcopenia (osteoporosis plus each of the 7 sarcopenia definitions) were assessed at baseline. We recorded and radiologically validated recent (i.e., within 2 years before baseline) central or major osteoporotic fractures (MOFs). Multivariate regression models adjusted for age, BMI, sedentary lifestyle, and comorbidities, were used to evaluate associations between osteosarcopenia and sarcopenia at baseline with the presence of recent fractures. As expected, the prevalence of osteosarcopenia and sarcopenia varied widely depending on the definitions used. Out of the 907 included women, 47 (5.2

Our imminent model was less sensitive but more selective than FRAX® in the choice of treatment to prevent imminent fractures. This new model decreased NNT by 30%, which could reduce the treatment costs. In the Belgian FRISBEE cohort, the effect of recency further decreased the selectivity of FRAX®. We analyzed the selection for treatment of patients at high risk of fracture by the Belgian FRISBEE imminent model and the FRAX® tool. We identified in the FRISBEE cohort subjects who sustained an incident MOF (mean age 76.5 ± 6.8 years). We calculated their estimated 10-year risk of fracture using FRAX® before and after adjustment for recency and the 2-year probability of fracture using the FRISBEE model. After 6.8 years of follow-up, we validated 480 incident and 54 imminent MOFs. Of the subjects who had an imminent fracture, 94.0% had a fracture risk estimated above 20% by the FRAX® before correction for recency and 98.1% after adjustment, with a specificity of 20.2% and 5.9%, respectively. The sensitivity and specificity of the FRISBEE model at 2 years were 72.2% and 55.4%, respectively, for a threshold of 10%. For these thresholds, 47.3% of the patients were identified at high risk in both models before the correction, and 17.2% of them had an imminent MOF. The adjustment for recency did not change this selection. Before the correction, 34.2% of patients were selected for treatment by FRAX® only, and 18.8% would have had an imminent MOF. This percentage increased to 47% after the adjustment for recency, but only 6% of those would suffer a MOF within 2 years. In our Belgian FRISBEE cohort, the imminent model was less sensitive but more selective in the selection of subjects in whom an imminent fracture should be prevented, resulting in a lower NNT. The correction for recency in this elderly population further decreased the selectivity of FRAX®. These data should be validated in additional cohorts before using them in everyday practice.

Searchable abstracts of presentations at key conferences in endocrinology ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

Only previous glucocorticoid use and rheumatoid arthritis were predictors of an early fracture (< 2 years after inclusion). A shorter 'time to first fracture' was not an independent clinical risk factor for imminent fractures. PURPOSE:Risk factors for fragility fractures independent of BMD were assessed in several prediction models. However, predictors of a shorter 'time to first fracture' and its impact on imminent fractures are unknown. METHODS:We studied the concept of 'time to first fracture' in the FRISBEE ("Fracture RIsk Brussels Epidemiological Enquiry") cohort (3560 postmenopausal women). Validated fractures were divided into 3 groups: first fracture < 2 years, 2-5 years, and > 5 years after inclusion. Factors associated with first fracture risk were evaluated with uni- and multivariate analyses using Cox modeling. We examined 'time to first fracture' as a risk factor for imminent fractures in untreated subjects and in those receiving pharmacological treatment. RESULTS:Classical risk factors (age, prior fracture, fall history and low BMD) were associated with first fracture in all groups. Previous glucocorticoids and rheumatoid arthritis (RA) were predictors for fracture < 2 years. Imminent fractures were similar in subjects with or without osteoporosis treatment, despite a higher estimated 10-year risk of fragility fracture in those treated, suggesting that treatment is efficient. 'Time to first fracture' was not an independent risk factor for imminent fractures. CONCLUSION:Among the risk factors considered, previous glucocorticoid use and RA were predictors for early fracture, consistent with the concept of very high risk. The 'time to first validated fracture' was not an independent risk factor for imminent fractures. Patients with a first osteoporotic fracture should thus be considered at very high risk for re-fracture, independent of the 'time to first fracture'.

Introduction: Prediction models, especially the FRAX (R), are largely used to estimate the fracture risk at ten years, but the current algorithm does not take into account the time elapsed after a fracture. Kanis et al. recently proposed correction factors allowing to adjust the FRAX (R) score for fracture recency. The objective of this work was to analyze the effect of fracture recency in the FRISBEE cohort. Methods: We identified in the FRISBEE cohort subjects who sustained a validated fracture during the first 5 years following an incident MOF. We calculated their estimated 5-year risk of fracture using FRAX (R) uncorrected, adjusted for recency and further adjusted for the MOF/hip ratios calibration factors previously derived for the Belgian FRAX (R). We compared the fracture risk estimated by FRAX (R) before and after these corrections to the observed incidence of validated fractures in our cohort. Results: In our ongoing cohort, 376 subjects had a first non-traumatic incident validated MOF after inclusion; 81 had a secondary fracture during the 5 years follow-up period after this index fracture. The FRAX (R) score significantly under-evaluated the observed incidence of fractures in our cohort by 54.7 % (fracture rate of 9.7 %; 95 % CI, 6.8-12.9 %) if uncorrected (p < 0.001) and by 32.6 % after correction for recency (14.5 %; 95 % CI, 11.1-18.2 %) (p = 0.01). The calibration for MOF/hip ratios improved the prediction (17.5 %; 95 % CI: 13.7-21.4 %) (p = 0.2). After correcting for recency and for calibration, the predicted value was over-evaluated by 22 % (fracture rate of 26.1 %; 95 % CI, 21.6-30.5 %) but this over-evaluation was not significant (p = 0.1). Conclusion: Our data indicate that the correction of the FRAX (R) score for fracture recency improves fracture prediction. However, correction for calibration and recency tends to overestimate fracture risk in this population of elderly women.

This study showed additional clinical risk factors for the occurrence of multiple fractures with regards to a single fracture, with often higher hazard ratios. It would be important to include the risk of the occurrence of multiple fractures in future prediction models.PURPOSE:To identify clinical risk factors (CRFs) which would specifically increase the risk of multiple fractures.METHODS:Data of the 3560 postmenopausal women of the FRISBEE study were analysed. The CRFs and the fractures are collected annually. The cohort was divided into three groups: those who had no incident fracture, those who had a single incident fracture and those who had 2 two or more incident fractures (i.e. multiple fractures). Statistical analyses were performed using Cox proportional hazards models.RESULTS:Among the 3560 subjects (followed for 9.1 (7.2-10.6) years), 261 subjects had two or more validated fractures during follow-up (146 were major osteoporotic fractures (MOFs)), 628 had one fracture (435 MOFs), 2671 had no fracture (2979 had no MOF); 157 subjects had two or more central fractures, 389 had only one and 3014 had none. The risk factors for those with multiple fractures at any site were age, history of fracture, history of fall, total hip bone mineral density (BMD), spine BMD and rheumatoid arthritis. For those with multiple MOFs, significant CRFs were age, history of fracture, parental hip fracture, total hip BMD and rheumatoid arthritis.CONCLUSION:We found in a prospective cohort study that there were more CRFs and higher hazard ratios for the occurrence of multiple fractures than for a single fracture.

ABSTRACT Patients who sustain a fracture are at greatest risk of recurrent fracture during the next 2 years. We propose three models to identify subjects most at risk of an imminent fracture, according to fracture site (any fracture, major osteoporotic fracture [MOF] or central). They were constructed using data of the prospective Frisbee cohort, which includes 3560 postmenopausal women aged 60 to 85 years who were followed for at least 5 years. A total of 881 subjects had a first incident validated fragility fracture before December 2018. Among these, we validated 130 imminent fractures occurring within the next 2 years; 79 were MOFs, and 88 were central fractures. Clinical risk factors were re-evaluated at the time of the index fracture. Fine and Gray proportional hazard models were derived separately for each group of fractures. The following risk factors were significantly associated with the risk of any imminent fracture: total hip bone mineral density (BMD) (p < 0.001), a fall history (p < 0.001), and comorbidities (p = 0.03). Age (p = 0.05 and p = 0.03, respectively) and a central fracture as the index fracture (p = 0.04 and p = 0.005, respectively) were additional predictors of MOFs and central fractures. The three prediction models are presented as nomograms. The calibration curves and the Brier scores based on bootstrap resampling showed calibration scores of 0.089 for MOF, 0.094 for central fractures, and 0.132 for any fractures. The predictive accuracy of the models expressed as area under the receiver operating characteristic (AUROC) curve (AUC) were 0.74 for central fractures, 0.72 for MOFs, and 0.66 for all fractures, respectively. These AUCs compare well with those of FRAX and Garvan to predict the 5- or 10-year fracture probability. In summary, five predictors (BMD, age, comorbidities, falls, and central fracture as the incident fracture) allow the calculation with a reasonable accuracy of the imminent risk of fracture at different sites (MOF, central fracture, and any fracture) after a recent sentinel fracture. © 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

The association of hip fractures with adverse outcomes is well established, but for non-hip fractures this association still needs to be further investigated. The objective of this narrative review is to describe the state of the art with regards to the health impact of clinically relevant non-hip fracture locations in postmenopausal women. PubMed and Scopus databases were searched from January 2010 until December 2020. Studies were included when the crude rates and/or relative risk of 1-year subsequent fractures and/or mortality were reported as well as the precise fracture site. Twenty-three studies met the inclusion criteria. Regarding mortality rates, there was a high variability between studies, with higher rates for vertebral, proximal humerus and pelvic fractures. There was a small or no impact of wrist, ankle or tibia fractures. The mortality rate increased with age after vertebral, proximal humerus and wrist fractures. Moreover, proximal humerus and vertebral fractures were associated with a higher mortality risk. This narrative review indicates that, besides fractures of the hip, fractures of the vertebrae, proximal humerus or pelvis deserve more attention when trying to prevent adverse outcomes of osteoporosis. More studies on the topic of non-hip fractures are urgently needed.

Glucocorticoids are effective immunomodulatory drugs used for many inflammatory disorders as well as in transplant recipients. However, both iatrogenic and endogenous glucocorticoid excess are also associated with several side effects including an increased risk of osteoporosis and fractures. Glucocorticoid-induced osteoporosis (GIOP) is a common secondary cause of osteoporosis in adults. Despite availability of clear evidence and international guidelines for the prevention of GIOP, a large treatment gap remains. In this narrative review, the Belgian Bone Club (BBC) updates its 2006 consensus recommendations for the prevention and treatment of GIOP in adults. The pathophysiology of GIOP is multifactorial. The BBC strongly advises non-pharmacological measures including physical exercise, smoking cessation and avoidance of alcohol abuse in all adults at risk for osteoporosis. Glucocorticoids are associated with impaired intestinal calcium absorption; the BBC therefore strongly recommend sufficient calcium intake and avoidance of vitamin D deficiency. We recommend assessment of fracture risk, taking age, sex, menopausal status, prior fractures, glucocorticoid dose, other clinical risk factors and bone mineral density into account. Placebo-controlled randomized controlled trials have demonstrated the efficacy of alendronate, risedronate, zoledronate, denosumab and teriparatide in GIOP. We suggest monitoring by dual-energy X-ray absorptiometry (DXA) and vertebral fracture identification one year after glucocorticoid initiation. The trabecular bone score might be considered during DXA monitoring. Extended femur scans might be considered at the time of DXA imaging in glucocorticoid users on long-term (≥ 3 years) antiresorptive therapy. Bone turnover markers may be considered for monitoring treatment with anti-resorptive or osteoanabolic drugs in GIOP. Although the pathophysiology of solid organ and hematopoietic stem cell transplantation-induced osteoporosis extends beyond GIOP alone, the BBC recommends similar evaluation, prevention, treatment and follow-up principles in these patients. Efforts to close the treatment gap in GIOP and implement available effective fracture prevention strategies into clinical practice in primary, secondary and tertiary care are urgently needed.

Five-year fracture risk prediction from the Fracture Risk Brussels Epidemiological Enquiry (FRISBEE) models was externally tested in 9716 Canadian women and demonstrated good discrimination but consistently overestimated risk. Five-year risk prediction models for all fractures, major osteoporotic fractures (MOFs) and central fractures (proximal to forearm and ankle) from the FRISBEE cohort demonstrated good performance in the original derivation cohort. Our aim was to externally validate the FRISBEE-based 5-year prediction models in routine practice. Using the population-based Manitoba Bone Mineral Density (BMD) registry, we identified women aged 60–85 years undergoing baseline BMD assessment from September 1, 2012 to March 31, 2018. Five-year probabilities of all fractures, MOFs and central fractures were calculated using the FRISBEE prediction models. We identified incident non-traumatic fractures up to 5 years from population-based healthcare data sources. Performance characteristics included area under the receiver operating characteristic curve (AUROC), gradient of risk (hazard ratio [HR] per SD increase and across risk tertiles) from Cox regression analysis, and calibration (ratio 5-year observed cumulative incidence to predicted fracture probability). We included 9716 women (mean age 70.7 + / − SD 5.3 years). During a mean observation time of 2.5 years, all fractures, MOFs and central fractures were identified in 377 (3.9%), 264 (2.7%) and 259 (2.7%) of the women. AUROC showed significant fracture risk stratification with the FRISBEE models (all fractures 0.69 [95%CI 0.67–0.72], MOFs 0.71 [95%CI 0.68–0.74], central fractures 0.72 [95%CI 0.69–0.75]). There was a strong gradient of risk for predicting fracture outcomes per SD increase (HRs from 1.98 to 2.26) and across risk tertiles (HRs for middle vs lowest from 2.25 to 2.41, HRs for highest vs lowest from 4.70 to 6.50). However, risk was overestimated for all fractures (calibration-in-the-large 0.63, calibration slope 0.63), MOF (calibration-in-the-large 0.51, calibration slope 0.57) and central fractures (calibration-in-the-large 0.55, calibration slope 0.60). FRISBEE 5-year prediction models were externally validated to stratify fracture risk similar to the derivation cohort, but would need recalibration for Canada as risk was overestimated.

Context: Individualized fracture risk may help to select patients requiring a pharmacological treatment for osteoporosis. FRAX and the Garvan fracture risk calculators are the most used tools, although their external validation has shown significant differences in their risk prediction ability. Objective and Methods: Using data from the Fracture Risk Brussels Epidemiological Enquiry study, a cohort of 3560 postmenopausal women aged 60 to 85 years, we aimed to construct original 5-year fracture risk prediction models using validated clinical risk factors (CRFs). Three models of competing risk analysis were developed to predict major osteoporotic fractures (MOFs), all fractures, and central fractures (femoral neck, shoulder, clinical spine, pelvis, ribs, scapula, clavicle, sternum). Results: Age, a history of fracture, and hip or spine BMD were predictors common to the 3 models. Excessive alcohol intake and the presence of comorbidities were specific additional CRFs for MOFs, a history of fall for all fractures, and rheumatoid arthritis for central fractures. Our models predicted the fracture probability at 5 years with an acceptable accuracy (Brier scores s 0.1) and had a good discrimination power (area under the receiver operating curve of 0.73 for MOFs and 0.72 for central fractures) when internally validated by bootstrap. Three simple nomograms, integrating significant CRFs and the mortality risk, were constructed for different fracture sites. In conclusion, we derived 3 models predicting fractures with an acceptable accuracy, particularly for MOFs and central fractures.The models are based on a limited number of CRFs, and we constructed nomograms for use in clinical practice.

The association between obesity and fracture sites in postmenopausal women has been little studied. We examined the most common types of fractures in obese and overweight postmenopausal women compared to subjects with a normal BMI in the FRISBEE study, a cohort of postmenopausal women followed since 9.1 (7.2–10.6) years. Chi-squared tests and logistic regressions were used to compare the percentages of fracture sites in overweight/obese subjects to subjects with a normal BMI. Their mean (± SD) age was 76.7 ± 6.9 years and their mean BMI was 26.4 ± 4.4. Seven hundred seventy-seven subjects suffered at least one validated fragility fracture with a total of 964 fractures in the whole cohort. Subjects with a BMI higher than 25 had significantly more ankle fractures and less pelvic fractures than subjects with a normal BMI (OR 1.63, 95% CI 1.02–2.56, P = 0.04 and OR 0.55, 95% CI 0.34–0.89, P = 0.01, respectively). There were no significant differences between overweight and obese subjects. Among those older than 75, there were significantly fewer pelvic fractures in overweight/obese subjects (OR 0.49, 95% CI 0.27–0.87, P = 0.01), but before 75, ankle fractures were significantly more frequent in overweight/obese subjects than in subjects with a normal BMI (OR 1.89, 95% CI 1.01–3.57, P = 0.04). In conclusion, the proportion of ankle and pelvic fractures in obese and overweight subjects differs from that in subjects with a normal BMI, but these differences are age dependent. Fracture prevention strategies should take into account the differential effects of excess weight according to age and the site of fracture.

We registered 1336 incident-validated fractures in a prospective cohort of 3560 postmenopausal (60–85 years) Belgian women (mean follow-up of 9.1 years). The increase of fracture incidence with age varied widely depending on the fracture site and was significantly steeper for central than for peripheral fractures (e.g., not significant for the ankle). The epidemiology of fracture sites other than MOFs has been less studied. We examined the incidence of fractures according to their sites in a prospective cohort of postmenopausal Belgian women. Three thousand five hundred sixty postmenopausal women, aged 60–85 years old, were recruited from 2007 to 2013 and surveyed yearly (FRISBEE). The number of validated incident fractures was recorded and analyzed in relation to age and the fracture site. One thousand three hundred thirty-six fractures were recorded after a mean follow-up of 9.1 years. Seven hundred fifty-six fractures (57%) were MOFs and 580 (43%) non-MOFs, while 813 (61%) were central and 523 (39%) peripheral. The increase of fracture incidence with age differed between fracture sites and was steeper for central than for peripheral fractures. The ratio of MOFs to non-MOFs increased significantly with age, from 1.10 (95% CI: 0.83–1.45) for the 60–69 to 1.69 [1.42–2.01] for the 80–89-year subgroup (P = 0.017). This was also true for central versus peripheral fracture. We differentiated three groups of fracture incidence evolution with age: fractures with a mean increase/decade (compared to the 60–69 age group) of less than 1.5, 1.5–2.0, and 2.0–3.0. The lowest increase was seen for most peripheral fractures, whereas the greatest increase included hip, scapula, pelvis, ribs, and spine fractures. The increase of fracture incidence with age varied widely depending on the fracture site, and the ratio of MOFs to non-MOFs rose significantly with age. Some peripheral fractures, such as the ankle, did not increase significantly with age, suggesting that bone fragility does not play a major role in their occurrence.