Validation of a 5-year risk score of hip fracture in postmenopausal women. The Danish Nurse Cohort Study

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.

Computer-aided diagnosis systems for osteoporosis detection: a comprehensive survey

Computer-aided diagnosis (CAD) has revolutionized the field of medical diagnosis. They assist in improving the treatment potentials and intensify the survival frequency by early diagnosing the diseases in an efficient, timely, and cost-effective way. The automatic segmentation has led the radiologist to successfully segment the region of interest to improve the diagnosis of diseases from medical images which is not so efficiently possible by manual segmentation. The aim of this paper is to survey the vision-based CAD systems especially focusing on the segmentation techniques for the pathological bone disease known as osteoporosis. Osteoporosis is the state of the bones where the mineral density of bones decreases and they become porous, making the bones easily susceptible to fractures by small injury or a fall. The article covers the image acquisition techniques for acquiring the medical images for osteoporosis diagnosis. The article also discusses the advanced machine learning paradigms employed in segmentation for osteoporosis disease. Other image processing steps in osteoporosis like feature extraction and classification are also briefly described. Finally, the paper gives the future directions to improve the osteoporosis diagnosis and presents the proposed architecture. Graphical abstract.

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.

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.

Performance of risk assessment instruments for predicting osteoporotic fracture risk: a systematic review

We systematically reviewed the literature on the performance of osteoporosis absolute fracture risk assessment instruments. Relatively few studies have evaluated the calibration of instruments in populations separate from their development cohorts, and findings are mixed. Many studies had methodological limitations making susceptibility to bias a concern.

INTRODUCTION

The aim of this study was to systematically review the literature on the performance of osteoporosis clinical fracture risk assessment instruments for predicting absolute fracture risk, or calibration, in populations other than their derivation cohorts.

METHODS

We performed a systematic review, and MEDLINE, Embase, Cochrane Library, and multiple other literature sources were searched. Inclusion and exclusion criteria were applied and data extracted, including information about study participants, study design, potential sources of bias, and predicted and observed fracture probabilities.

RESULTS

A total of 19,949 unique records were identified for review. Fourteen studies met inclusion criteria. There was substantial heterogeneity among included studies. Six studies assessed the WHO's Fracture Risk Assessment (FRAX) instrument in five separate cohorts, and a variety of risk assessment instruments were evaluated in the remainder of the studies. Approximately half found good instrument calibration, with observed fracture probabilities being close to predicted probabilities for different risk categories. Studies that assessed the calibration of FRAX found mixed performance in different populations. A similar proportion of studies that evaluated simple risk assessment instruments (≤5 variables) found good calibration when compared with studies that assessed complex instruments (>5 variables). Many studies had methodological features making them susceptible to bias.

CONCLUSIONS

Few studies have evaluated the performance or calibration of osteoporosis fracture risk assessment instruments in populations separate from their development cohorts. Findings are mixed, and many studies had methodological limitations making susceptibility to bias a possibility, raising concerns about use of these tools outside of the original derivation cohorts. Further studies are needed to assess the calibration of instruments in different populations prior to widespread use.

Risk assessment tools to identify women with increased risk of osteoporotic fracture: complexity or simplicity? A systematic review

A huge number of risk assessment tools have been developed. Far from all have been validated in external studies, more of them have absence of methodological and transparent evidence, and few are integrated in national guidelines. Therefore, we performed a systematic review to provide an overview of existing valid and reliable risk assessment tools for prediction of osteoporotic fractures. Additionally, we aimed to determine if the performance of each tool was sufficient for practical use, and last, to examine whether the complexity of the tools influenced their discriminative power. We searched PubMed, Embase, and Cochrane databases for papers and evaluated these with respect to methodological quality using the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) checklist. A total of 48 tools were identified; 20 had been externally validated, however, only six tools had been tested more than once in a population-based setting with acceptable methodological quality. None of the tools performed consistently better than the others and simple tools (i.e., the Osteoporosis Self-assessment Tool [OST], Osteoporosis Risk Assessment Instrument [ORAI], and Garvan Fracture Risk Calculator [Garvan]) often did as well or better than more complex tools (i.e., Simple Calculated Risk Estimation Score [SCORE], WHO Fracture Risk Assessment Tool [FRAX], and Qfracture). No studies determined the effectiveness of tools in selecting patients for therapy and thus improving fracture outcomes. High-quality studies in randomized design with population-based cohorts with different case mixes are needed.

FRAX and the assessment of the risk of developing a fragility fracture

Osteoporosis is common and the health and financial cost of fragility fractures is considerable. The burden of cardiovascular disease has been reduced dramatically by identifying and targeting those most at risk. A similar approach is potentially possible in the context of fragility fractures. The World Health Organization created and endorsed the use of FRAX, a fracture risk assessment tool, which uses selected risk factors to calculate a quantitative, patient-specific, ten-year risk of sustaining a fragility fracture. Treatment can thus be based on this as well as on measured bone mineral density. It may also be used to determine at-risk individuals, who should undergo bone densitometry. FRAX has been incorporated into the national osteoporosis guidelines of countries in the Americas, Europe, the Far East and Australasia. The United Kingdom National Institute for Health and Clinical Excellence also advocates its use in their guidance on the assessment of the risk of fragility fracture, and it may become an important tool to combat the health challenges posed by fragility fractures.