Does the Prediction Accuracy of Osteoporotic Fractures by BMD and Clinical Risk Factors Vary With Fracture Site?

The METS-IR is independently related to bone mineral density, FRAX score, and bone fracture among U.S. non-diabetic adults: a cross-sectional study based on NHANES

AIM

The purpose of this study was to investigate the association between the metabolic score for insulin resistance (METS-IR) and bone mineral density (BMD) in American non-diabetic adults.

METHODS

We conducted a cross-sectional study with 1114 non-diabetic adults from the National Health and Nutrition Examination Survey cycle (2013-2014). The associations between METS-IR and BMD of total femur and spine were assessed by the multiple linear regression and verified the non-linear relationship with a smooth curve fit and threshold effect model. Furthermore, we evaluated the relationship between METS-IR, FRAX score, and history of bone fractures.

RESULTS

We found that BMD of the total femur and spine increased by 0.005 g/cm3 and 0.005 g/cm3, respectively, for a one-unit increase of METS-IR in all participants. This positive association was more pronounced among higher METS-IR participants, and there was a non-linear relationship, which was more significant when the MTTS-IRfemur was < 41.62 or the METS-IRspine was < 41.39 (βfemur = 0.008, βspine = 0.011, all P < 0.05). We also found that METS-IR was positively correlated with both FRAX scores in all female participants. However, METS-IR was positively correlated only with the 10-year hip fracture risk score in male participants with fractures. No significant association between METS-IR and a history of bone fractures.

CONCLUSIONS

In American non-diabetic adults, there is a correlation between elevated levels of METS-IR within the lower range and increased BMD as well as decreased risk of fractures, suggesting that METS-IR holds promise as a novel biomarker for guiding osteoporosis (OP) prevention. However, it is important to carefully balance the potential benefits and risks of METS-IR in OP.

The metabolic score of insulin resistance is positively correlated with bone mineral density in postmenopausal patients with type 2 diabetes mellitus

The prevalence of type 2 diabetes mellitus (T2DM) complicated with osteoporosis (OP) is increasing yearly. Early prevention, detection and treatment of OP are important in postmenopausal patients with T2DM. This study aimed to explore the correlation between insulin resistance and bone mineral density (BMD), and OP in postmenopausal patients with T2DM. In this study, postmenopausal patients with T2DM who visited our hospital from January 2021 to March 2022 were divided into the OP group (n = 91) and non-OP group (n = 119) according to whether they were complicated with OP or not. The general data of patients, BMD, blood routine, glucose metabolism, lipid metabolism, liver and kidney function indexes were collected, and the homeostatic model assessment for IR (HOMA-IR), the triglyceride-glucose (TyG) index and the metabolic score for IR (METS-IR) were calculated. A weighted multivariate linear regression model assessed the correlation between insulin resistance (IR) related indexes and lumbar spine, femoral neck, and hip BMD. A weighted logistic regression model assessed the odds ratios (ORs) and 95% confidence intervals (95% CIs) for the association between the IR-related indexes and OP risk. The nonlinear relationship was also evaluated by smooth curve fitting (SCF) and a weighted generalized additive model (GAM). Moreover, the Receiver-operating characteristics (ROC) curve was used to analyze the predictive efficiency of METS-IR in postmenopausal patients with T2DM with OP. HOMA-IR, TyG, and METS-IR in the OP group were lower than those in the non-OP group (all P < 0.05). Weighted multiple linear regression after adjusting covariates showed that METS-IR was positively correlated with the lumbar spine, femoral neck, and hip BMD (β_METS-IR = 0.006,0.005,0.005, all P < 0.001). The results of weighted Logistic regression and GAM showed that when METS-IR < 44.5, each unit of increased METS-IR value was associated with a decreased OP risk of 12% (P = 0.002). When METS-IR ≥ 44.5, there was no significant correlation between METS-IR and the risk of OP (OR = 1.00, P = 0.934). Similar trends were not observed in HOMA-IR and TyG. The ROC suggested helpful discriminative power of the METS-IR index for T2DM. We confirmed that METS-IR, as a novel alternative marker of IR, had a positive association with BMD in postmenopausal patients with T2DM, and METS-IR was a protective factor for OP in a specific range.

The effect of fracture recency on observed 5-year fracture probability: A study based on the FRISBEE cohort

Introduction

Prediction models, especially the FRAX®, 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® 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® uncorrected, adjusted for recency and further adjusted for the MOF/hip ratios calibration factors previously derived for the Belgian FRAX®. We compared the fracture risk estimated by FRAX® 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® 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® score for fracture recency improves fracture prediction. However, correction for calibration and recency tends to overestimate fracture risk in this population of elderly women.

Detrimental Association Between Blood Cadmium Concentration and Trabecular Bone Score

Osteoporosis has been recognized as a significant cause of disability in the elderly leading to heavy socioeconomic burden. Current measurements such as dual-energy X-ray absorptiometry (DEXA) and bone mineral density (BMD) have limitations. In contrast, trabecular bone score (TBS) is an emerging tool for bone quality assessment. The objective of our study was to investigate the relationship between TBS and trace elements (cadmium and lead). We analyzed all subjects from the 2005-2006 and 2007-2008 National Health and Nutrition Examination Survey (NHANES) dataset and included a total of 8,244 participants in our study; 49.4% of the enrolled subjects were male. We used blood cadmium (Cd) and lead (Pb) concentrations to define environmental exposure. The main variables were TBS and BMD. Other significant demographic features were included as covariates and later adjusted using linear regression models to determine the association between TBS and four quartiles based on the blood trace element concentrations with or without sex differences. The fully adjusted regression model revealed a negative relationship between TBS and blood cadmium (B-Cd) significant for both males and females (both p < 0.05). The β-coefficient for males was -0.009 (95% confidence intervals (CI): (-0.015 to -0.004)) and -0.019 for female (95% CI: (-0.024 to -0.013)). We also found a dose-dependent relationship between TBS and B-Cd for both sexes (both trend's p < 0.05). Our study concluded that TBS could measure Cd-related bone quality deterioration for both males and females.

Fracture distribution in postmenopausal women: a FRISBEE sub-study

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).

INTRODUCTION

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Risk factors of primary and recurrent fractures in postmenopausal osteoporotic Chinese patients: A retrospective analysis study

BACKGROUND

As postmenopausal osteoporotic fractures can cause higher rates of disability and mortality in women; it is essential to analyze the factors associated with primary and recurrent fractures in postmenopausal osteoporosis (PMOP) patients.

METHODS

Retrospective analysis of 2478 PMOP patients aged ≥ 50 years who attended the Shanghai General Hospital from January 2007 to December 2016, including 1239 patients with no fractures and 1239 patients with histories of fractures (1008 in the primary fracture group and 231 in the re-fracture group). All patients' basic clinical data, serum biochemical and bone metabolic markers, bone mineral density (BMD), and other indicators were recorded uniformly. Comparing the differences between the clinical characteristics of patients with primary and recurrent fractures, as well as the differences in the clinical characteristics of patients with primary and recurrent fractures in combination with different diseases, further analyses the risk factors for primary and recurrent fractures in PMOP patients. SPSS.26 was used for statistical analysis.

RESULTS

Compared to the unfractured group, the fractured group was older and had lower height and bone mineral density (all P < 0.01), with the re-fractured group having lower BMD at each key site than the primary fracture group (all P < 0.01). Analysis of the combined disease subgroups showed that serum BGP levels were lower in the primary and re-fracture patients with diabetes than in the non-diabetic subgroup (P < 0.05), and serum CTX levels were lower in the re-fracture group with diabetes than in the primary fracture group with diabetes (P < 0.05). Patients with recurrent fractures with cardio-vascular diseases had lower BMD than the subgroup without cardio-vascular diseases (P < 0.05) and also had lower BMD than the group with primary fractures with cardio-vascular diseases (P < 0.05). Multiple logistic regression analysis showed that advanced age, overweight, low lumbar spine and total hip BMD were risk factors for primary and recurrent fractures; and comorbid chronic liver and kidney diseases were risk factors for primary fractures.

CONCLUSION

PMOP patients with advanced age, overweight, low bone mineral density, and comorbid chronic liver and kidney diseases are at greater risk of fractures and require early intervention to reduce fractures occurrence. Moreover, those who are elderly, overweight, and have low bone density should also be aware of the risk of re-fractures.

Cluster analysis demonstrates co-existing sites of fragility fracture and associated comorbidities

We undertook cluster analysis in 11,003 patients who had sustained ≥ 1 fragility fracture, to find associations between fracture sites and comorbidities. We identified three distinct groups of fracture sites and four clusters of fractures and comorbidities. Knowledge of factors associated with fracture sites will aid prophylaxis in at-risk patients.

INTRODUCTION

Fragility fracture (FF) prevalence is increasing. Subsequent fractures lead to greater morbidity and mortality. Few data are available on the association between FF sites and comorbidities.

OBJECTIVES

1. Establish the most common sites of FF and clusters within patients. 2. Identify patterns of co-existing FF and associated comorbidities.

METHODS

We retrospectively reviewed clinical records of patients undergoing bone mineral density estimation at a district hospital in North-West England, 2004-2016, identifying those who had sustained ≥ 1 FF. Demographics, FF site(s), comorbidities, and medications were recorded. Cluster analysis was performed on fracture sites alone, and sites and comorbidities, using Jaccard similarity coefficient. Results were plotted on a dendrogram and divided into clusters.

RESULTS

Of 28,868 patients, 11,003 had sustained ≥ 1 FF, 84.6% female, with overall mean age 67.5 years and median T-score - 1.12 SD. FF of the forearm was more frequent (n = 5045), most commonly co-existing with tibia/fibula fractures. Three FF site clusters were identified: ankle and elbow; forearm, tibia/fibula, ribs and spine; and pelvis, femur and humerus. When including comorbidities, four clusters were identified: forearm, tibia/fibula, spine, associated with family history of FF, smoking, corticosteroids and bisphosphonates; pelvis associated with hyperparathyroidism, PMR, coeliac disease and HRT; femur and humerus associated with IBD and RA; and ribs associated with alcohol and hyperthyroidism.

CONCLUSION

Cluster analysis demonstrated three fracture site clusters, and four subgroups of FF sites and comorbidities. Cluster analysis is a novel method to evaluate comorbidities associated with FF sites. Knowledge of factors associated with FF sites will aid prophylaxis in at-risk patients.

Serum calcium–phosphorus product for predicting the risk of osteoporotic vertebral compression fractures in elderly patients: a retrospective observational study

Background

This study retrospectively analyzed and evaluated the potential correlations of serum calcium, serum phosphorus, and calcium-phosphorus product (Ca–P product) with the incidence of osteoporotic vertebral compression fractures (OVCFs), with the aim of exploring whether the Ca–P product can be used as a serological indicator to predict the risk of OVCFs.

Methods

This study randomly enrolled 400 elderly patients in our hospital with OVCFs and 400 patients with hip and knee arthroplasty due to femoral head necrosis or osteoarthritis from August 2013 to April 2021. Age, sex, past medical history, and admission biochemical indicators, including albumin, blood urea nitrogen, serum creatinine, serum calcium and serum phosphorus, were collected for statistical analysis.

Results

Albumin, serum calcium, serum phosphorus, Ca–P product, corrected serum calcium and corrected Ca–P product were lower in the OVCF group than in the non-OVCF group (P < 0.05). Multivariate logistic regression analysis showed that low values of serum calcium, serum phosphorus, Ca–P product, corrected blood calcium, and corrected Ca–P product can all be risk factors for OVCF. The ROC curve showed that the Ca–P product and corrected Ca–P product were effective in predicting the risk of OVCFs. The predictive value of the Ca–P product was the best; the cutoff point was 29.88, the sensitivity was 0.72 and the specificity was 0.62. The cutoff point of the corrected Ca–P product was 30.50, the sensitivity was 0.74, and the specificity was 0.62.

Conclusion

The Ca–P product and corrected Ca–P product can be used as serological indicators to predict the risk of OVCFs in elderly individuals. Early clinical interventions targeting this risk factor can further reduce the risk of OVCFs. Also, timely and regular testing of the serum calcium and phosphorus level is recommended and encouraged for this group of people.

Prediction of an Imminent Fracture After an Index Fracture - Models Derived From the Frisbee Cohort

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 American Society for Bone and Mineral Research (ASBMR).

MOF/Hip Fracture Ratio in a Belgian Cohort of Post-menopausal Women (FRISBEE): Potential Impact on the FRAX® Score

The ratio between major osteoporotic fractures (MOFs) and hip fractures in the Belgian FRAX® tool to predict fractures is currently based on Swedish data. We determined these ratios in a prospective cohort of Belgian postmenopausal women. 3560 women, aged 60-85 years (70.1 ± 6.4 years), were included in a prospective study from 2007 to 2013 and surveyed yearly (FRISBEE). We analyzed the number of validated incident fractures until October 2020 by age and sites and compared the MOFs/hip ratios in this cohort with those from the Swedish databases. We registered 1336 fractures (mean follow-up of 9.1 years). The MOFs/hip ratios extracted from the FRISBEE cohort were 10.7 [95% CI: (5.6-20.5)], 6.4 [4.7-8.7], and 5.0 [3.9-6.5] for women of 60-69, 70-79, and 80-89 years old, respectively. These ratios were 1.7-1.8 times higher for all age groups than those from the Swedish data, which decreased from 6.5 (60-64 years group) down to 1.8 (85-89 age group). The overall MOFs/hip ratio in Frisbee was 6.0 [5.9-6.1], which was higher than any Swedish ratio between 65 and 85 years. Nevertheless, the decrease of the ratios with age paralleled that observed in Sweden. In this Brussels prospective cohort, MOFs/hip ratios were 1.7-1.8 times those observed in Sweden currently used for MOFs prediction in the Belgian FRAX® version. This discrepancy can greatly modify the estimation of the risk of MOFs, which is among the main criteria used to recommend a pharmacological treatment for osteoporosis in several countries.

Impact of non-hip fractures in elderly women: a narrative review

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.

Effect of body mass index on vertebral and hip fractures in older people and differences according to sex: a retrospective Japanese cohort study

OBJECTIVES

The purpose of this study was to investigate the incidence of vertebral and hip fractures in the older people and to clarify the relationship between these fractures and body mass index (BMI) along with the impact of sex differences.DesignThis was a retrospective cohort study.SettingWe used administrative claims data between April 2010 and March 2018.

PARTICIPANTS

Older people aged ≥75 years who underwent health examinations in 2010 and were living in the Fukuoka Prefecture, Japan were included in the study. A total of 24 691 participants were included; the mean age was 79.4±4.3 years, 10 853 males and 13 838 females, and an the mean duration of observation was 6.9±1.6 years.

PRIMARY AND SECONDARY OUTCOME MEASURES

We estimated the incidence of vertebral and hip fractures by BMI category (underweight: <18.5 kg/m², normal weight: 18.5-24.9 kg/m², overweight and obese: ≥25.0 kg/m²) using a Kaplan-Meier curve in males and females and determined fracture risk by sex using Cox proportional hazards regression analyses.

RESULTS

The incidence of vertebral and hip fractures was 16.8% and 6.5%, respectively. The cumulative incidence of vertebral and hip fracture at the last observation (8 years) in each BMI groups (underweight/normal weight/overweight and obese) estimated using the Kaplan-Meier curve was 14.7%/10.4%/9.0% in males and 24.9%/23.0%/21.9% in females, and 6.3%/2.9%/2.4% in males and 14.1%/9.0%/8.1% in females, respectively, and both fractures were significantly higher in underweight groups regardless of sex. Multivariable Cox proportional hazards models showed that underweight was a significant risk factor only in males for vertebral fractures and in both males and females for hip fractures.

CONCLUSION

Underweight was associated with fractures in the ageing population, but there was a sex difference in the effect for vertebral fractures.

Independent External Validation of FRAX and Garvan Fracture Risk Calculators: A Sub-Study of the FRISBEE Cohort

Probabilistic models including clinical risk factors with or without bone mineral density (BMD) have been developed to estimate the 5‐ or 10‐year absolute fracture risk. We investigated the performance of the FRAX and Garvan tools in a well‐characterized population‐based cohort of 3560 postmenopausal, volunteer women, aged 60 to 85 years at baseline, included in the Fracture Risk Brussels Epidemiological Enquiry (FRISBEE) cohort, during 5 years of follow‐up. Baseline data were used to calculate the estimated 10‐year risk of hip and major osteoporotic fractures (MOFs) for each participant using FRAX (Belgium). We computed the 5‐year risk according to the Garvan model with BMD. For calibration, the predicted risk of fracture was compared with fracture incidence across a large range of estimated fracture risks. The accuracy of the calculators to predict fractures was assessed using the area under the receiver operating characteristic curves (AUC). The FRAX tool was well calibrated for hip fractures (slope 1.09, p < 0.001; intercept −0.001, p = 0.46), but it consistently underestimated the incidence of major osteoporotic fractures (MOFs) (slope 2.12, p < 0.001; intercept −0.02, p = 0.06). The Garvan tool was well calibrated for “any Garvan” fractures (slope 1.05, p < 0.001; intercept 0.01, p = 0.37) but largely overestimated the observed hip fracture rate (slope 0.32, p < 0.001; intercept 0.006, p = 0.05). The predictive value for hip fractures was better for FRAX (AUC: 0.841, 95% confidence interval [CI] 0.795–0.887) than for Garvan (AUC: 0.769, 95% CI 0.702–0.836, p = 0.01). The Garvan AUC for “any Garvan” fractures was 0.721 (95% CI 0.693–0.749) and FRAX AUC for MOFs was 0.708 (95% CI 0.675–0.741). In conclusion, in our Belgian cohort, FRAX estimated quite well hip fractures but underestimated MOFs, while Garvan overestimated hip fracture risk but showed a good estimation of “any Garvan” fractures. Both models had a good discriminatory value for hip fractures but only a moderate discriminatory ability for MOFs or “any Garvan” fractures. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Associations of overweight, obesity and osteoporosis with ankle fractures

BACKGROUND

Studies exploring risk factors for ankle fractures in adults are scarce, and with diverging conclusions. This study aims to investigate whether overweight, obesity and osteoporosis may be identified as risk factors for ankle fractures and ankle fracture subgroups according to the Danis-Weber (D-W) classification.

METHODS

108 patients ≥40 years with fracture of the lateral malleolus were included. Controls were 199 persons without a previous fracture history. Bone mineral density of the hips and spine was measured by dual-energy x-ray absorptiometry, and history of previous fracture, comorbidities, medication, physical activity, smoking habits, body mass index and nutritional factors were registered.

RESULTS

Higher body mass index with increments of 5 gave an adjusted odds ratio (OR) of 1.30 (95% confidence interval (CI) 1.03-1.64) for ankle fracture, and an adjusted OR of 1.96 (CI 0.99-4.41) for sustaining a D-W type B or C fracture compared to type A. Compared to patients with normal bone mineral density, the odds of ankle fracture in patients with osteoporosis was 1.53, but the 95% CI was wide (0.79-2.98). Patients with osteoporosis had reduced odds of sustaining a D-W fracture type B or C compared to type A (OR 0.18, CI 0.03-0.83).

CONCLUSIONS

Overweight increased the odds of ankle fractures and the odds of sustaining an ankle fracture with possible syndesmosis disruption and instability (D-W fracture type B or C) compared to the stable and more distal fibula fracture (D-W type A). Osteoporosis did not significantly increase the odds of ankle fractures, thus suffering an ankle fracture does not automatically warrant further osteoporosis assessment.

Prior loss of body mass index, low body mass index, and central obesity independently contribute to higher rates of fractures in elderly women and men

We aimed to comprehensively evaluate the association of body composition with fracture risk using longitudinal data from a Swedish cohort of 44,366 women and men (mean age of 70 years) and a subcohort of 5022 women. We estimated hazard ratios (HRs) of fracture for baseline body mass index (BMI), BMI change during the prior 12 and 18 years, baseline waist-to-height ratio, total and regional distribution of fat and lean mass, with and without areal bone mineral density (BMD) adjustment. During follow-up (median 8.7 years), 7290 individuals sustained a fracture, including 4279 fragility fractures, of which 1813 were hip fractures. Higher baseline BMI and prior gain in BMI were inversely associated with all types of fracture. Lower fracture rate with higher baseline BMI was seen within every category of prior BMI change, whereas higher prior BMI gain conferred a lower rate of fracture within those with normal baseline BMI. Each standard deviation (SD) higher baseline waist-to-height ratio, after adjustment for BMI, was associated with higher rates of hip fracture in both women and men (HR 1.12; 95% CI, 1.05-1.19). In the subcohort (median follow-up 10 years), higher baseline fat mass index (FMI) and appendicular lean mass index (LMI) showed fracture-protective effects. After BMD adjustment, higher baseline BMI, total LMI, FMI, and higher prior BMI gain were associated with higher fracture rate. Baseline fat distribution also was associated with fracture rate; a 1-SD higher android to gynoid fat mass ratio in prior BMI gainers was associated with BMD-adjusted HRs of 1.16 (95% CI, 1.05-1.28) for any fracture and 1.48 (95% CI, 1.16-1.89) for hip fracture. This pattern was not observed among prior BMI losers. These findings indicate that for optimal fracture prevention, low baseline BMI, prior BMI loss and high baseline central obesity should be avoided in both women and men. © 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).

Risk factors for imminent fractures: a substudy of the FRISBEE cohort

Multiple factors increase the risk of an imminent fracture, including a recent fracture, older age, osteoporosis, comorbidities, and the fracture site. These findings could be a first step in the development of a model to predict an imminent fracture and select patients most at need of immediate treatment.

INTRODUCTION

The risk of a recurrent fragility fracture is maximal during the first 2 years following an incident fracture. In this prospective cohort study, we looked at the incidence of recurrent fractures within 2 years after a first incident fracture and we assessed independent clinical risk factors (CRFs) increasing this imminent fracture risk.

METHODS

A total of 3560 postmenopausal women recruited from 2007 to 2013 were surveyed yearly for the occurrence of fragility fractures. We identified patients who sustained a fracture during the first 2 years following a first incident fragility fracture. We quantified the risk of a new fracture and assessed independent CRFs, associated with an imminent fracture at various sites.

RESULTS

A recent fracture was a significant CRF for an imminent fracture (OR (95% CI): 3.7 (2.4-5.7) [p < 0.0001]). The incidence of an imminent fracture was higher in subjects above 80 years (p < 0.001). Other CRFs highly predictive in a multivariate analysis were osteoporosis diagnosis (p < 0.01), a central fracture as the index fracture (p < 0.01), and the presence of comorbidities (p < 0.05), with likelihood ratios of 1.9, 1.9, and 2.2, respectively. An imminent fracture was better predicted by a central fracture (p < 0.01) than by a major osteoporotic fracture. The hazard ratio was the highest for a central fracture.

CONCLUSION

In patients with a recent fracture, older age, osteoporosis, comorbidities, and fracture site were associated with an imminent fracture risk. These findings could be a first step in the development of a model to predict an imminent fracture and select patients most at need of immediate and most appropriate treatment.

Development of prediction model for osteoporotic vertebral compression fracture screening without using clinical risk factors, compared with FRAX and other previous models

This study developed a prediction model to assess the need for asymptomatic osteoporotic vertebral compression fracture (OVCF) screening in women without using clinical risk factors. Our results demonstrated that the combination of age, height loss, and femoral neck T-score can predict OVCF comparable to previous models, including FRAX.

PURPOSE

Osteoporotic vertebral compression fracture (OVCF) is a major fracture in osteoporosis patients. Early detection of OVCF can reduce the risk of subsequent fractures and death. Many existing diagnostic tools can screen for the risk of osteoporotic fracture but none aim to identify OVCF. The objective of this research is to study a predictive model for capturing OVCF and compare it with previous models.

METHODS

A retrospective review was conducted that included women aged ≥ 50 years who underwent dual-energy X-ray absorptiometry and vertebral fracture screening between 2012 and 2019. The data included age, height, weight, history of height loss (HHL), and bone mass density (BMD). Receiver operating characteristic analysis and univariate and multivariate logistic regression were performed. The predictive OVCF model was formulated, and the result was compared to other models.

RESULTS

A total of 617 women, a 179 of which had OVCFs, were eligible for analysis. Multivariate regression analysis showed age > 65, height loss > 1.5 cm, and femoral neck T-score < -1.7 as independent risk factors for OVCF. This model revealed comparable performance with FRAX. The model without BMD revealed superior performance to FRAX and other standard osteoporosis assessment models.

CONCLUSIONS

BMD and vertebral fracture screening should be eligible for individual women age > 65 years with an HHL more than 1.5 cm, regardless of BMD. Vertebral fracture assessment should be additionally conducted on these women with a femoral neck T-score less than -1.7.

Osteoporosis treatment gap in a prospective cohort of volunteer women

Despite the availability of efficient drugs to prevent osteoporotic fractures, only a minority of women receives osteoporosis therapy after a fracture. The high treatment gap in our cohort consisted of unselected volunteer patients highlights the urgent need of additional education, especially for the medical profession, regarding the risk-benefit balance of treatment.

INTRODUCTION

Despite the availability of efficient drugs to prevent osteoporotic fractures, only a minority of women receives osteoporosis therapy after a fracture, with a treatment gap around 80%. This can have dramatic consequences for patients and the healthcare systems.

METHODS

In this study based on longitudinal data from the FRISBEE (Fracture RIsk Brussels Epidemiological Enquiry) cohort of 3560 volunteer women aged 60 to 85 years, we evaluated the 1-year treatment gap after a first major incident fragility fracture.

RESULTS

There were 386 first validated fragility fractures, 285 major osteoporotic fractures (MOF) and 101 "other major" fractures. The rate of untreated patients was 85.0% (82.8% for MOF versus 91.0 % for "other major" fracture sites) (p = 0.04), with a lower rate for spine (70.5%) and hip (72.5%) versus shoulder (91.6%) and wrist (94.1%) (p < 0.0001). More specifically, the treatment gap for patients with osteoporosis, defined by a T-score < - 2.5 SD was 74.6% versus 76.5% for patients with osteoporosis defined by the presence of hip, shoulder, or spine fractures, independently of DXA results. When considering age groups, the rate of untreated women was 87.9% for women 60-70 years old, 88.2% between 70 and 80 years and 77.8% above 80 years (p = 0.03), with a greater difference between women who were younger or older than 80 years at inclusion: 88.1% versus 77.8% (p = 0.009). A diagnosis of osteoporosis (p = 0.01) and age (p = 0.03) were the only clinical risk factors (CRFs) significantly associated with treatment initiation.

CONCLUSIONS

This study highlights the urgent need of additional education, especially for the medical profession, regarding the risk-benefit balance of treatment.

What is the validity of self-reported fractures?

We assessed the validity of self-reported fractures, over a median follow-up period of 6.2 years, in a well characterized population-based cohort of 3560 postmenopausal women, aged 60-85 years, from the Fracture Risk Brussels Epidemiological Enquiry (FRISBEE) study. Incident low-traumatic (falls from a standing height or less) or non-traumatic fractures, including peripheral fractures, were registered during each annual follow-up telephone interview. A self-reported fracture was considered as a true positive if it was validated by written reliable medical reports (radiographs, CT scans or surgical report). False positives fractures were considered to be those for which the radiology report indicated that there was no fracture at the reported site. Among self-reported fractures, false positive rates were 14.4% for all fractures. The rate of false positives of 11.2% (n = 48/429) was not negligible for the four classical major osteoporotic fractures (MOFs: hip, clinical spine, forearm or shoulder fractures). In terms of fracture site, we found the lowest false positive rate (4.4%) at the hip, and the highest (16.8%) at the spine, with the proximal humerus and the wrist in between, at about 10% each. The global rates of false positives were 12.5% (n = 22/176) for other major fractures and 22.3% (n = 49/220) for minor fractures. Younger subjects, individuals with fractures at sites other than the hip, with a lower education level, or with a higher BMI were more likely to report false positive fractures. Our data indicate that the inaccuracy of self-reported fractures is clinically relevant for several major fractures, which could influence any fracture risk prediction model.

Underevaluation of fractures by self-report: an analysis from the FRISBEE cohort

We assessed the rate of non-reported fractures in the FRISBEE cohort. Over a median follow-up period of 9.2 years, we registered 992 fractures. The global percentage of non-reported fractures was 21.3%. Underreporting of fracture event might influence any model of fracture risk prediction.

INTRODUCTION

Most fracture cohort studies rely on participant self-report of fracture event. This approach may lead to fracture underreporting. The purpose of the study was to assess the rate of non-reported fractures in a well-characterized population-based cohort of 3560 postmenopausal women, aged 60-85 years, included in the Fracture Risk Brussels Epidemiological Enquiry (FRISBEE) study.

METHODS

Incident low-traumatic or non-traumatic fractures were registered annually during phone calls. In 2018, we reviewed the medical files of 67.9% of our study participants and identified non-reported fractures ("false negatives fractures (FN)"). We also evaluated whether the rate of FN was influenced by baseline patients' characteristics and fracture risk factors. Generalized estimating equation (GEE) was used to calculate odds ratio (OR) and 95% CI.

RESULTS

Over a median follow-up period of 9.2 years, we registered 992 fractures (781 by self-report, confirmed by a radiological report and 211 unreported). The global false negative rate for all fractures was 21.3%, including 22% for MOFs (major osteoporotic fractures), 13.1% for other major fractures, and 25.8% for minor fractures. The rate of non-reported fractures varied by fracture site: for MOFs, it was 2.7% (n = 2/73) at the hip, 5.3% at the proximal humerus (n = 5/94), 7.1% at the wrist (n = 11/154), and 46.5% at the spine (n = 100/215). For "other major" fractures, the highest rate of false negatives fractures was found at the pelvic bone (21%, n = 13/62), followed by the elbow (17.9%, n = 5/28), long bones (10.5%, n = 2/19), ankle (6.2%, n = 4/65), and knee (5.9%, n = 1/17). Older subjects (OR 1.7; 95% CI, 1.2-2.4; P = 0.003), subjects with early non-substituted menopause (OR 1.8; 95% CI, 1.0-3.3; P = 0.04), with a lower education level (OR 1.5; 95%CI, 1.1-2.2; P = 0.01), and those under drug therapy for osteoporosis (OR 1.5; 95% CI, 1.0-2.2; P = 0.05) were associated with a higher rate of FN.

CONCLUSIONS

In conclusion, underreporting of a substantial proportion of fracture events will influence any model of fracture risk prediction and induce bias when estimating the associations between candidate risk factors and incident fractures.