Fracture risk prediction using phalangeal bone mineral density or FRAX(®)?-A Danish cohort study on men and women

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.

Associations between Long-Term Air Pollution Exposure and Risk of Osteoporosis-Related Fracture in a Nationwide Cohort Study in South Korea

Bone health is a major concern for aging populations globally. Osteoporosis and bone mineral density are associated with air pollution, but less is known about the impacts of air pollution on osteoporotic fracture. We aimed to assess the associations between long-term air pollution exposure and risk of osteoporotic fracture in seven large Korean cities. We used Cox proportional hazard models to estimate hazard rations (HRs) of time-varying moving window of past exposures of particulate matter (PM10), sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3) for osteoporotic fracture in Korean adults (age ≥ 50 years) in the National Health Insurance Service-National Sample Cohort data, followed 2002 to 2015. HRs were calculated for an interquartile range (IQR) increase. Comorbidity and prescription associated with osteoporosis, age, sex, body mass index, health behaviors, and income were adjusted in the models. Effect modification by age, sex, exercise, and income was examined. We assessed 56,467 participants over 535,481 person-years of follow up. Linear and positive exposure-response associations were found for SO2, while PM10 and NO2 showed nonlinear associations. SO2 was associated with osteoporosis-related fracture with marginal significance (HR for an IQR [2 ppb] increase = 1.04, 95% CI: 1.00, 1.09). The SO2 HR estimates were robust in analyses applying various moving windows of exposure (from one to three years of past exposure) and two-pollutant models. The central HR estimate of O3 implied positive associations but was not significant (HR for 0.007 ppm increase = 1.01, 95% CI: 0.97, 1.06). PM10, CO, and NO2 did not show associations. Vulnerable groups by sex, age, exercise, and income varied across air pollutants and there was no evidence of effect modifications. Long-term exposure to SO2, but not PM10, CO, NO2 and O3, was associated with increased osteoporotic fracture risks in Korean adults.

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.

Screening to Prevent Osteoporotic Fractures: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

IMPORTANCE

Osteoporotic fractures cause significant morbidity and mortality.

OBJECTIVE

To update the evidence on screening and treatment to prevent osteoporotic fractures for the US Preventive Services Task Force.

DATA SOURCES

PubMed, the Cochrane Library, EMBASE, and trial registries (November 1, 2009, through October 1, 2016) and surveillance of the literature (through March 23, 2018); bibliographies from articles.

STUDY SELECTION

Adults 40 years and older; screening cohorts without prevalent low-trauma fractures or treatment cohorts with increased fracture risk; studies assessing screening, bone measurement tests or clinical risk assessments, pharmacologic treatment.

DATA EXTRACTION AND SYNTHESIS

Dual, independent review of titles/abstracts and full-text articles; study quality rating; random-effects meta-analysis.

MAIN OUTCOMES AND MEASURES

Incident fractures and related morbidity and mortality, diagnostic and predictive accuracy, harms of screening or treatment.

RESULTS

One hundred sixty-eight fair- or good-quality articles were included. One randomized clinical trial (RCT) (n = 12 483) comparing screening with no screening reported fewer hip fractures (2.6% vs 3.5%; hazard ratio [HR], 0.72 [95% CI, 0.59-0.89]) but no other statistically significant benefits or harms. The accuracy of bone measurement tests to identify osteoporosis varied (area under the curve [AUC], 0.32-0.89). The pooled accuracy of clinical risk assessments for identifying osteoporosis ranged from AUC of 0.65 to 0.76 in women and from 0.76 to 0.80 in men; the accuracy for predicting fractures was similar. For women, bisphosphonates, parathyroid hormone, raloxifene, and denosumab were associated with a lower risk of vertebral fractures (9 trials [n = 23 690]; relative risks [RRs] from 0.32-0.64). Bisphosphonates (8 RCTs [n = 16 438]; pooled RR, 0.84 [95% CI, 0.76-0.92]) and denosumab (1 RCT [n = 7868]; RR, 0.80 [95% CI, 0.67-0.95]) were associated with a lower risk of nonvertebral fractures. Denosumab reduced the risk of hip fracture (1 RCT [n = 7868]; RR, 0.60 [95% CI, 0.37-0.97]), but bisphosphonates did not have a statistically significant association (3 RCTs [n = 8988]; pooled RR, 0.70 [95% CI, 0.44-1.11]). Evidence was limited for men: zoledronic acid reduced the risk of radiographic vertebral fractures (1 RCT [n = 1199]; RR, 0.33 [95% CI, 0.16-0.70]); no studies demonstrated reductions in clinical or hip fractures. Bisphosphonates were not consistently associated with reported harms other than deep vein thrombosis (raloxifene vs placebo; 3 RCTs [n = 5839]; RR, 2.14 [95% CI, 0.99-4.66]).

CONCLUSIONS AND RELEVANCE

In women, screening to prevent osteoporotic fractures may reduce hip fractures, and treatment reduced the risk of vertebral and nonvertebral fractures; there was not consistent evidence of treatment harms. The accuracy of bone measurement tests or clinical risk assessments for identifying osteoporosis or predicting fractures varied from very poor to good.

Anti-CCP-positive patients with RA have a higher 10-year probability of fracture evaluated by FRAX®: a registry study of RA with osteoporosis/fracture

Background

Positive anticyclic citrullinated peptide (anti-CCP+) is associated with bone loss in patients with rheumatoid arthritis (RA). However, whether overall positivity or specific levels of anti-CCP are associated with prevalent fracture or a 10-year probability of fracture remains unclear.

Methods

This interim analysis of an RA registry was conducted at Chang Gung Memorial Hospital in Kaohsiung (CGMHK) for RA-related osteoporosis/fracture. Consecutive patients with RA who had visited the rheumatology clinic at CGMHK since September 1, 2014, and fulfilled the classification criteria of RA were enrolled. The demographics, disease duration, Disease activity in 28 joints based on erythrocyte sedimentation rate (DAS28-ESR), lifestyle, evidence of previous fracture, risk factors of fracture in the Fracture Risk Assessment Tool (FRAX®), and FRAX® score of each participant were collected. Anti-CCP, rheumatoid factor (RF), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and bone mineral density (BMD) were measured at enrollment. The patients were grouped by positivity or quartiles of anti-CCP level (I–IV).

Results

Five hundred twenty-one patients with RA were enrolled through May 31, 2016. In total, 359 (68.9%) patients were anti-CCP+. Compared with anti-CCP− patients, anti-CCP+ patients had a significantly higher DAS28-ESR (p = 0.0001) and 10-year probability of major (15.0 [18.9] vs. 12.0 [15.3], p = 0.0461) or hip (5.0 [9.2] vs. 3.6 [8.2], p = 0.0118) fracture, but a significantly lower BMD of the FN (p = 0.0196). The rates of osteoporosis and previous fracture were comparable. There were 130, 127, 132, and 132 patients in groups I–IV, respectively. The DAS28-ESR was significantly different (p = 0.0001) among the groups and correlated to anti-CCP levels. The BMD and 10-year probability of major (p = 0.0067) and hip (p = 0.0013) fracture among the groups were also different.

Conclusions

Anti-CCP+ RA patients had a higher 10-year probability of major or hip fracture, independent of anti-CCP levels, and a lower BMD of the FN than anti-CCP− patients.

Do we need bone mineral density to estimate osteoporotic fracture risk? A 10-year prospective multicentre validation study

Objective

Evaluate the performance of FRAX®, with and without bone mineral densitometry (BMD), in predicting the occurrence of fragility fractures over 10 years.

Methods

Participants aged ≥40 years at baseline, with a complete set of data and a minimum of 8.5 years of follow-up were identified from three cohorts (n=2626). Ten-year fracture risk at baseline were estimated with FRAX® and assessed by comparison with observed fractures and receiver operating characteristic analysis.

Results

During a mean (SD) follow-up of 9.12 (1.5) years, 178 participants suffered a major osteoporotic (MOP) fracture and 28 sustained a hip fracture. The predictive performance of FRAX® was superior to that of BMD alone for both MOP and hip fractures. The area under the curve (AUC) of FRAX® without BMD was 0.76 (95% CI 0.72 to 0.79) for MOP fractures and 0.78 (95% CI 0.69 to 0.86) for hip fractures. No significant improvements were found when BMD was added to clinical variables to predict either MOP (0.78, 95% CI 0.74 to 0.82, p=0.25) or hip fractures (0.79, 95% CI 0.69 to 0.89, p=0.72).

AUCs for FRAX® (with and without BMD) were greater for men than for women. FRAX®, with and without BMD, tended to underestimate the number of MOP fractures and to overestimate the number of hip fractures in females. In men, the number of observed fractures were within the 95% CI of the number predicted, both with and without BMD.

Conclusion

FRAX® without BMD provided good fracture prediction. Adding BMD to FRAX® did not improve the performance of the tool in the general population.

Machine Learning Principles Can Improve Hip Fracture Prediction

Apply machine learning principles to predict hip fractures and estimate predictor importance in Dual-energy X-ray absorptiometry (DXA)-scanned men and women. Dual-energy X-ray absorptiometry data from two Danish regions between 1996 and 2006 were combined with national Danish patient data to comprise 4722 women and 717 men with 5 years of follow-up time (original cohort n = 6606 men and women). Twenty-four statistical models were built on 75% of data points through k-5, 5-repeat cross-validation, and then validated on the remaining 25% of data points to calculate area under the curve (AUC) and calibrate probability estimates. The best models were retrained with restricted predictor subsets to estimate the best subsets. For women, bootstrap aggregated flexible discriminant analysis ("bagFDA") performed best with a test AUC of 0.92 [0.89; 0.94] and well-calibrated probabilities following Naïve Bayes adjustments. A "bagFDA" model limited to 11 predictors (among them bone mineral densities (BMD), biochemical glucose measurements, general practitioner and dentist use) achieved a test AUC of 0.91 [0.88; 0.93]. For men, eXtreme Gradient Boosting ("xgbTree") performed best with a test AUC of 0.89 [0.82; 0.95], but with poor calibration in higher probabilities. A ten predictor subset (BMD, biochemical cholesterol and liver function tests, penicillin use and osteoarthritis diagnoses) achieved a test AUC of 0.86 [0.78; 0.94] using an "xgbTree" model. Machine learning can improve hip fracture prediction beyond logistic regression using ensemble models. Compiling data from international cohorts of longer follow-up and performing similar machine learning procedures has the potential to further improve discrimination and calibration.

Diagnostic devices for osteoporosis in the general population: A systematic review

INTRODUCTION

A diagnostic gap exists in the current dual photon X-ray absorptiometry (DXA) based diagnostic approach to osteoporosis. Other diagnostic devices have been developed, but no comprehensive review concerning the applicability of these diagnostic devices for population-based screening have been performed.

MATERIAL AND METHODS

A systematic review of Embase, Medline and the Cochrane Central Register for Controlled Trials was performed for population-based studies that focused on technical methods that could either indicate bone mineral density (BMD) by DXA, substitute for DXA in prediction of fracture risk, or that could have an incremental value in fracture prediction in addition to DXA. Quality of included studies was rated by QUADAS 2.

RESULTS

Many other technical devices have been tested in a population-based setting. Five studies aiming to indicate BMD and 17 studies aiming to predict fractures were found. Overall, the latter studies had higher methodological quality. The highest number of studies was found for quantitative ultrasound (QUS). The ability to indicate BMD or predict fractures was moderate to minor for all examined devices, using reported area under the curve (AUC) of Receiver Operating Characteristic curves values as standard.

CONCLUSIONS

Of the methods assessed, only QUS appears capable of perhaps replacing DXA as standalone examination in the future whilst radiographic absorptiometry could provide important information in areas with scarcity of DXA. QUS may be of added value even after DXA has been performed. Evaluation of proposed cutoff-values from population-based studies in separate population-based cohorts is still lacking for most examination devices.

The accuracy of osteoporotic fracture risk prediction tools: a systematic review and meta-analysis

OBJECTIVES

To identify and synthesise the best available evidence on the accuracy of the currently available tools for predicting fracture risk.

METHODS

We systematically searched PubMed MEDLINE, Embase and Cochrane databases to 2014. Two reviewers independently selected articles, collected data from studies, and carried out a hand search of the references of the included studies. The Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) checklist was used, and the primary outcome was the area under the curve (AUC) and 95% CIs, obtained from receiver operating characteristic (ROC) analyses. We excluded tools if they had not been externally validated or were designed for specific disease populations. Random effects meta-analyses were performed with the selected tools.

RESULTS

Forty-five studies met inclusion criteria, corresponding to 13 different tools. Only three tools had been tested more than once in a population-based setting: FRAX (26 studies in 9 countries), GARVAN (6 studies in 3 countries) and QFracture (3 studies in the UK, 1 also including Irish participants). Twenty studies with these three tools were included in a total of 17 meta-analyses (for hip or major osteoporotic fractures; men or women; with or without bone mineral density).

CONCLUSIONS

Most of the 13 tools are feasible in clinical practice. FRAX has the largest number of externally validated and independent studies. The overall accuracy of the different tools is satisfactory (>0.70), with QFracture reaching 0.89 (95% CI 0.88 to 0.89). Significant methodological limitations were observed in many studies, suggesting caution when comparing tools based solely on the AUC.

Dual-Energy X-Ray Absorptiometry for Measurement of Phalangeal Bone Mineral Density on a Slot-Scanning Digital Radiography System

OBJECTIVE

In this paper, we assess the feasibility of using two detectors in a slot-scanning digital radiography system to acquire images for measuring bone mineral density (BMD) of the middle phalanx of the middle finger using dual-energy X-ray absorptiometry (DXA).

METHODS

Simulations were used to evaluate the spectral separation of the low- and high-energy spectra and detective quantum efficiency was used for assessing image quality. Scan parameters were chosen to optimize spectral separation, image quality, and radiation dose. We introduce the measurement of volumetric BMD (vBMD) using basis material decomposition. We assess the accuracy of our methods by comparing measurements taken using bone images against reference data derived from subsequent incineration of the bones. In vivo scans were conducted to evaluate the system precision (repeatability) and agreement with a clinical densitometer.

RESULTS

Average errors for bone mineral content (BMC), areal BMD (aBMD), and vBMD were 4.85%, 5.49%, and 12.77%, respectively. Our system had good agreement with a clinical densitometer based on concordance correlation coefficient values of 0.92 and 0.98 for aBMD and BMC, respectively. Precision studies yielded coefficient of variation (CV) values of 1.35% for aBMD, 1.48% for BMC, and 1.80% for vBMD. The CV values of all measurements were within 2%, indicating that the methods have clinically acceptable precision.

CONCLUSION

We conclude that our techniques yield bone measurements with high accuracy, clinically acceptable precision, and good agreement with a clinical densitometer.

SIGNIFICANCE

We have shown the clinical potential of phalangeal DXA measurements of aBMD and vBMD on a slot-scanning digital radiography system.