Assessing Risk of Osteoporotic Fractures in Primary Care: Development and Validation of the FRA-HS Algorithm

The essential role of combined calcium and vitamin D supplementation in the osteoporosis scenario in italy: Expert opinion paper

An Italian multidisciplinary working group discussed the current Italian scenario of osteoporosis management during a meeting and highlighted the essential role of calcium and vitamin D supplementation in the prevention of fragility fractures.

PURPOSE

This paper aims to review and discuss data on calcium and vitamin D requirements and the role of combined calcium and vitamin D supplementation in the treatment of patients with osteoporosis.

METHODS

The discussion of the experts covered literature data on calcium and vitamin D supplementation, gaps in the diagnosis and treatment of osteoporosis, and the role of the primary care physician in identifying and treating patients with osteoporosis. Articles for consideration were identified through PubMed searches using different combinations of pertinent keywords.

RESULTS

The discussion highlighted that insufficient calcium or vitamin D intake increases the risk of fragility fractures. The experts also drew attention to the essential role of calcium and vitamin D supplementation in achieving an anti-fracture effect and supporting the efficacy of anti-osteoporotic agents without increasing nephrolithiasis and cardiovascular risks. In addition, the discussion underlined the role of the primary care physician in the initial clinical approach to patients with osteoporosis.

CONCLUSIONS

The experts believe that efficient treatment for patients with osteoporosis should include calcium and vitamin D supplementation to achieve adequate levels that are able to inhibit the parathyroid hormone and bone resorption.

A systematic review on the performance of fracture risk assessment tools: FRAX, DeFRA, FRA-HS

PURPOSE

Preventing fragility fractures by treating osteoporosis may reduce disability and mortality worldwide. Algorithms combining clinical risk factors with bone mineral density have been developed to better estimate fracture risk and possible treatment thresholds. This systematic review supported panel members of the Italian Fragility Fracture Guidelines in recommending the use of best-performant tool. The clinical performance of the three most used fracture risk assessment tools (DeFRA, FRAX, and FRA-HS) was assessed in at-risk patients.

METHODS

PubMed, Embase, and Cochrane Library were searched till December 2020 for studies investigating risk assessment tools for predicting major osteoporotic or hip fractures in patients with osteoporosis or fragility fractures. Sensitivity (Sn), specificity (Sp), and areas under the curve (AUCs) were evaluated for all tools at different thresholds. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies-2; certainty of evidence (CoE) was evaluated using the Grading of Recommendations Assessment, Development and Evaluation approach.

RESULTS

Forty-three articles were considered (40, 1, and 2 for FRAX, FRA-HS, and DeFRA, respectively), with the CoE ranging from very low to high quality. A reduction of Sn and increase of Sp for major osteoporotic fractures were observed among women and the entire population with cut-off augmentation. No significant differences were found on comparing FRAX to DeFRA in women (AUC 59-88% vs. 74%) and diabetics (AUC 73% vs. 89%). FRAX demonstrated non-significantly better discriminatory power than FRA-HS among men.

CONCLUSION

The task force formulated appropriate recommendations on the use of any fracture risk assessment tools in patients with or at risk of fragility fractures, since no statistically significant differences emerged across different prediction tools.

Executive summary: Italian guidelines for diagnosis, risk stratification, and care continuity of fragility fractures 2021

Background

Fragility fractures are a major public health concern owing to their worrying and growing burden and their onerous burden upon health systems. There is now a substantial body of evidence that individuals who have already suffered a fragility fracture are at a greater risk for further fractures, thus suggesting the potential for secondary prevention in this field.

Purpose

This guideline aims to provide evidence-based recommendations for recognizing, stratifying the risk, treating, and managing patients with fragility fracture. This is a summary version of the full Italian guideline.

Methods

The Italian Fragility Fracture Team appointed by the Italian National Health Institute was employed from January 2020 to February 2021 to (i) identify previously published systematic reviews and guidelines on the field, (ii) formulate relevant clinical questions, (iii) systematically review literature and summarize evidence, (iv) draft the Evidence to Decision Framework, and (v) formulate recommendations.

Results

Overall, 351 original papers were included in our systematic review to answer six clinical questions. Recommendations were categorized into issues concerning (i) frailty recognition as the cause of bone fracture, (ii) (re)fracture risk assessment, for prioritizing interventions, and (iii) treatment and management of patients experiencing fragility fractures. Six recommendations were overall developed, of which one, four, and one were of high, moderate, and low quality, respectively.

Conclusions

The current guidelines provide guidance to support individualized management of patients experiencing non-traumatic bone fracture to benefit from secondary prevention of (re)fracture. Although our recommendations are based on the best available evidence, questionable quality evidence is still available for some relevant clinical questions, so future research has the potential to reduce uncertainty about the effects of intervention and the reasons for doing so at a reasonable cost.

Prediction Models for Osteoporotic Fractures Risk: A Systematic Review and Critical Appraisal

Osteoporotic fractures (OF) are a global public health problem currently. Many risk prediction models for OF have been developed, but their performance and methodological quality are unclear. We conducted this systematic review to summarize and critically appraise the OF risk prediction models. Three databases were searched until April 2021. Studies developing or validating multivariable models for OF risk prediction were considered eligible. Used the prediction model risk of bias assessment tool to appraise the risk of bias and applicability of included models. All results were narratively summarized and described. A total of 68 studies describing 70 newly developed prediction models and 138 external validations were included. Most models were explicitly developed (n=31, 44%) and validated (n=76, 55%) only for female. Only 22 developed models (31%) were externally validated. The most validated tool was Fracture Risk Assessment Tool. Overall, only a few models showed outstanding (n=3, 1%) or excellent (n=32, 15%) prediction discrimination. Calibration of developed models (n=25, 36%) or external validation models (n=33, 24%) were rarely assessed. No model was rated as low risk of bias, mostly because of an insufficient number of cases and inappropriate assessment of calibration. There are a certain number of OF risk prediction models. However, few models have been thoroughly internally validated or externally validated (with calibration being unassessed for most of the models), and all models showed methodological shortcomings. Instead of developing completely new models, future research is suggested to validate, improve, and analyze the impact of existing models.

A systematic review and meta-analysis of prospective cohort studies on the association between alcohol intake and risk of fracture

Previous studies on the association between alcohol intake and risk of fracture have reached conflicting findings. The aim of this systematic review and meta-analysis of prospective cohort studies was to summarize earlier studies on the association of alcohol intake with risk of fracture. A systematic search of PubMed, Scopus, and ISI Web of Science was conducted up to November 2020. Prospective cohort studies that had considered alcohol consumption as the exposure variable and fracture as the main outcome or as one of the outcome variables were included in this systematic review. Publications in which odds ratios (ORs), rate or risk ratios (RRs), or hazard ratios (HRs) and 95% confidence intervals (CIs) were reported, were included in the meta-analysis. In total, 40 prospective cohort studies including 5,084,303 participants and 170,916 subjects with fracture were included in this systematic review; of them 38 studies with a total sample size of 5,053,117 participants and 169,560 cases of fracture were included in the meta-analysis. Using a random-effects meta-analysis, we found a significant positive association between alcohol consumption and risk of total fractures (RR: 1.35; 95% CI: 1.01, 1.81) and any fractures (RR: 1.24; 95% CI: 1.11, 1.38). However, no significant association was observed between alcohol intake and risk of hip fractures (RR: 1.19; 95% CI: 0.96, 1.48), osteoporotic fractures (RR: 2.01; 95% CI: 0.76, 5.34), vertebral fractures (RR: 0.98; 95% CI: 0.68, 1.40), and wrist fractures (RR: 0.99; 95% CI: 0.85, 1.16). In conclusion, we found that alcohol consumption was positively associated with risk of total fractures and any fractures. However, we did not observe any significant association between alcohol consumption and risk of hip, osteoporotic, vertebral, and wrist fractures.

Performance of predictive tools to identify individuals at risk of non-traumatic fracture: a systematic review, meta-analysis, and meta-regression

There is no consensus on which tool is the most accurate to assess fracture risk. The results of this systematic review suggest that QFracture, Fracture Risk Assessment Tool (FRAX) with BMD, and Garvan with BMD are the tools with the best discriminative ability. More studies assessing the comparative performance of current tools are needed.

INTRODUCTION

Many tools exist to assess fracture risk. This review aims to determine which tools have the best predictive accuracy to identify individuals at high risk of non-traumatic fracture.

METHODS

Studies assessing the accuracy of tools for prediction of fracture were searched in MEDLINE, EMBASE, Evidence-Based Medicine Reviews, and Global Health. Studies were eligible if discrimination was assessed in a population independent of the derivation cohort. Meta-analyses and meta-regressions were performed on areas under the ROC curve (AUCs). Gender, mean age, age range, and study quality were used as adjustment variables.

RESULTS

We identified 53 validation studies assessing the discriminative ability of 14 tools. Given the small number of studies on some tools, only FRAX, Garvan, and QFracture were compared using meta-regression models. In the unadjusted analyses, QFracture had the best discriminative ability to predict hip fracture (AUC = 0.88). In the adjusted analysis, FRAX with BMD (AUC = 0.81) and Garvan with BMD (AUC = 0.79) had the highest AUCs. For prediction of major osteoporotic fracture, QFracture had the best discriminative ability (AUC = 0.77). For prediction of osteoporotic or any fracture, FRAX with BMD and Garvan with BMD had higher discriminative ability than their versions without BMD (FRAX: AUC = 0.72 vs 0.69, Garvan: AUC = 0.72 vs 0.65). A significant amount of heterogeneity was present in the analyses.

CONCLUSIONS

QFracture, FRAX with BMD, and Garvan with BMD have the highest discriminative performance for predicting fracture. Additional studies in which the performance of current tools is assessed in the same individuals may be performed to confirm this conclusion.

Guidelines for the management of osteoporosis and fragility fractures

The purpose of this document, a result of the harmonisation and revision of Guidelines published separately by the SIMFER, SIOMMMS/SIR, and SIOT associations, is to provide practical indications based on specific levels of evidence and various grades of recommendations, drawn from available literature, for the management of osteoporosis and for the diagnosis, prevention, and treatment of fragility fractures. These indications were discussed and formally approved by the delegates of the Italian Scientific Associations involved in the project (SIE, SIGG, SIMFER, SIMG, SIMI, SIOMMMS, SIR, and SIOT).

A New Fracture Risk Assessment Tool (FREM) Based on Public Health Registries

Some conditions are already known to be associated with an increased risk of osteoporotic fractures. Other conditions may also be significant indicators of increased risk. The aim of the current study was to identify conditions for inclusion in a fracture prediction model (fracture risk evaluation model [FREM]) for automated case finding of high-risk individuals of hip or major osteoporotic fractures (MOFs). We included the total population of Denmark aged 45+ years (N = 2,495,339). All hospital diagnoses from 1998 to 2012 were used as possible conditions; the primary outcome was MOFs during 2013. Our cohort was split randomly 50/50 into a development and a validation dataset for deriving and validating the predictive model. We applied backward selection on ICD-10 codes (International Classification of Diseases and Related Health Problems, 10th Revision) by logistic regression to develop an age-adjusted and sex-stratified model. The FREM for MOFs included 38 and 43 risk factors for women and men, respectively. Testing FREM for MOFs in the validation cohort showed good accuracy; it produced receiver-operating characteristic (ROC) curves with an area under the ROC curve (AUC) of 0.750 (95% CI, 0.741 to 0.795) and 0.752 (95% CI, 0.743 to 0.761) for women and men, respectively. The FREM for hip fractures included 32 risk factors for both genders and showed an even higher accuracy in the validation cohort as AUCs of 0.874 (95% CI, 0.869 to 0.879) and 0.851 (95% CI, 0.841 to 0.861) for women and men were found, respectively. We have developed and tested a prediction model (FREM) for identifying men and women at high risk of MOFs or hip fractures by using solely existing administrative data. The FREM could be employed either at the point of care integrated into electronic patient record systems to alert physicians or deployed centrally in a national case-finding strategy where patients at high fracture risk could be invited to a focused DXA program. © 2018 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research (ASBMR).

Advances in treatment of glucocorticoid-induced osteoporosis

PURPOSE OF REVIEW

The aim of this study is to summarize monitoring, prevention and treatment options of glucocorticoid-induced osteoporosis for patients on chronic glucocorticoid therapy.

RECENT FINDINGS

Recent meta-analyses highlight the efficacy of bisphosphonate use in improving bone mineral density and in reducing vertebral fractures in the setting of long-term glucocorticoid use. A new study has now shown that alendronate also reduces the risk of hip fracture in glucocorticoid use. Emerging data indicate that teriparatide and denosumab also reduce the risk of osteoporotic fracture in glucocorticoid-induced osteoporosis.

SUMMARY

Glucocorticoid use is a leading cause of secondary osteoporosis; however, patients at risk of glucocorticoid-induced osteoporosis are often not evaluated or treated in a timely manner. Patients on a dose equivalent of 2.5 mg prednisone or greater for 3 months or longer duration should have their fracture risk assessed. Those at moderate or high risk should start bisphosphonate therapy, or if contraindicated, a second-line agent such as teriparatide or denosumab.

Bone health in menopausal women: a role for General Practitioners

General Practitioners (GPs) are in a prime location to assess patient health needs, knowing clinical history, living habits and risk factors. GPs can identify in healthy people those in which prevention could be useful, in order to avoid or delay some diseases. For this purpose GPs need to change their care model from a waiting model to a proactive model, in order to identify health needs before the development of diseases.