Osteoporosis Risk Assessment Instrument Research Articles

Evaluation of the performance of osteoporosis/fracture screening models to identify high-risk women for osteoporosis: Bushehr elderly health (BEH) program.

This study aimed to evaluate the performance of valid risk assessment models developed for osteoporosis/ fracture screening to identify women in need of bone density measurement in a population of Iranian elderly women. This study was performed using the data of Bushehr Elderly Health (BEH) program, a population-based cohort study of elderly population aged ≥ 60 years. Seven osteoporosis risk assessment tools, including Osteoporosis Risk Assessment Instrument (ORAI), Malaysian Osteoporosis Screening Tool (MOST), Osteoporosis Prescreening Risk Assessment (OPERA), Osteoporosis Prescreening Model for Iranian Postmenopausal women (OPMIP), Osteoporosis Index of Risk (OSIRIS), and Osteoporosis Self-Assessment Tool for Asians (OSTA), as well as Fracture Risk Assessment Tool (FRAX) were included in the study. By using osteoporosis definition based on BMD results, the performance measurement criteria of diagnostic tests such as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Youden index for each model were calculated and the models were compared. A total of 1237 female participants with the mean age of 69.1 ± 6.3 years were included. Overall, 733 (59%) participants had osteoporosis, and about 80% had no history of fracture. The sensitivity of the seven models ranged from 16.7% (OSIRIS) to 100% (ORAI and MOST) at their recommended cut-off points. Moreover,their specificity ranged from 0.0% (ORAI and MOST) to 78.9% (OSTA). The FRAX and OPERA had the optimal performance with the Youden index of 0.237 and 0.226, respectively. Moreover, after combining these models, the sensitivity of them increased to 85.4%. We found that the FRAX (model with 11 simple variables) and OPERA (model with 5 simple variables) had the best performance. By combining the models, the performance of each was improved. Further studies are needed to adopt the model and to find the best cut-off point in the Iranian postmenopausal women.

Diagnostic Accuracy of Different Screening Tools for Identifying Osteoporosis Risk Among Post-Menopausal Filipino Women Aged 45–65 Years

Abstract Early screening of osteoporosis decreases fracture risk. Several identified clinical risk factors led to the development of screening tools to estimate osteoporosis risk. Bone Mineral Densitometry (BMD) as a diagnostic tool for screening is not practical because of high cost and poor availability. The extensively studied osteoporosis screening tools are: Simple Calculated Osteoporosis Risk Estimation (SCORE), the Osteoporosis Risk Assessment Instrument (ORAI), the Age Bulk One or Never Estrogen (ABONE), body weight (WEIGHT), and the Osteoporosis Risk Index (OSIRIS). These tools were developed and validated in Caucasians. Validation of these tools for specific populations is necessary because of the observed variations in BMD across geographic and ethnic groups. To date, the utility of these screening tools in the Philippines is unknown. We conducted a cross-sectional analysis of all patients who underwent BMD screening for osteoporosis in a tertiary hospital from January 2015 to September 2020. The study participants were postmenopausal Filipino women aged 45 to 65 years. The subjects had no history of osteopenia, osteoporosis, hip or spine fractures, use of osteoporosis medications, renal insufficiency, bilateral oophorectomy, hysterectomy, or early menopause. We identified demographic and clinical risk factors. These risk factors were used to calculate the risk score of five osteoporosis risk assessment tools: ORAI, ABONE, WEIGHT, OSTA, and ORISIS. Using the DEXA T-score as an external criterion, the sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and diagnostic accuracy for each tool were calculated. Included were 1869 subjects with a mean age of 57.9 + 4.3 years old. Osteoporosis, with a T-score of <-2.5 at the lumbar or femoral neck area, was seen in 665 (35.58%). Risk factors such as weight, height, BMI, menopausal years, history of previous fractures, and intake of oral calcium supplements correlated significantly with a higher risk (OR=1.025, 95%CI: 0.974–1.079; OR=1.059, 95%CI: 0.84–1.338; OR=1.063, 95%CI: 0.817–1.383; OR=1.74, 95%CI: 1.198–2.528; and OR=1.088, 95%CI: 0.869–1.319), of having osteoporosis in the said population. ORAI and WEIGHT have the highest probability of identifying patients with a sensitivity of 88.42% and 91.28%, and accuracy of 85.71% and 87.98%. Both performed equally in screening for osteoporosis in this setting. However, ABONE, OSTA, and ORISIS underestimated the number of high-risk osteoporosis patients, because of their low sensitivity and diagnostic accuracy. Both ORAI and WEIGHT are simple and easy to calculate and can serve as an initial screening tool to identify Filipino postmenopausal women who are at high risk for osteoporosis. A prospective study with a correlation of fracture occurrences may provide evidence for the value of these tools as a screening test.

MON-391 Implementation of an Osteoporosis Risk Assessment Instrument (ORAI) to Increase Referral Rates for DEXA Scanning in the Primary Care Setting

Background/Purpose: Osteoporosis (OP)was first identified and named by healthcare professionals in the 18th century. Today, OP is still the source of fractures which impair mobility, leading to sub-acute stays at rehabilitation centers. A major obstacle is that primary care providers (PCPs) fail to identify warning signs of OP, and inform patients that Dual Energy X-Ray Absorptiometry (DEXA) scans that are one of the best procedures to assess bone health. This project addressed the issue of low rate of referrals for DEXA scans. Theoretical Framework: The Knowledge-to-Action (KTA) model was used to guide this study. Intervention: Implementation of osteoporosis risk assessment instrument. Methods (Design, Sample, Setting, Measures, Analysis): This includes pre-implementation phase, patients’ charts were reviewed; post-implementation phase, the number of people referred to have DEXA scans were analyzed; the evaluation phase, results compared to the previous data. The project focus exclusively on women and men ages 50 to 89 years in two primary care offices in New Jersey. Descriptive analyses concentrated on whether or not ORAI was the tool to increase DEXA scans. Results: The data analysis reflected that the baseline referral rates increased from 1.3 % to 42 % and patients who scored high on the risk assessment instrument have been referred more often than not. Moreover, patients who are at risk and younger than 65 years of age, risk assessment tools led to a positive referral for a DEXA scan. Those who are older than 65 years, risk assessment tools like ORAI should be given with fracture risk assessment tools. This is especially the case when dealing with men, a demographic group often overlooked in the fight against OP. Conclusions Implications: If this project is to be applied at other clinics, more and more patients would be referred, raising awareness of the medical benefits of early detection. Reasonably, covering a broader section of patients, earlier in their lives, will increase clinical income, bringing more patients to primary care offices.

Evaluation of Lifestyle and Some Biochemical Parameters Involved in Bone Health in Pre and Postmenopausal Cameroonian Women

Aims: A healthy skeletal system with strong bones is essential to overall health. This study aimed to assess lifestyle and bone’s biomarkers of women.
 Study Design: This was a cross-sectional study.
 Place and Duration of Study: The enrollment took place at the Yaounde Military Hospital from November 2016 to July 2017.
 Methodology: A set of 105 postmenopausal and 127 premenopausal participants were enrolled from November 2016 to July 2017 in Yaounde. Their physical activities level was evaluated using a questionnaire. Sunlight exposure between 10:00AM and 4:00PM was assessed. Colorimetric methods were used to evaluate calcium, albumin, and alkaline phosphatase activity in plasma. These parameters were then compared within year since menopause (YSM) and osteoporosis risk assessment instrument (ORAI) sub-groups.
 Results: 13.4% participants were moderately active. Only 22.8% participants had at least 30 minutes sun exposure daily. A multivariable analysis of demographic, lifestyle, biochemical characteristic revealed age, BMI, albumin and calcium were the main factors that influenced bone health among our participants. A significant difference of calcium concentration was found between the two groups whereas albumin was significantly higher in premenopausal than postmenopausal. Albumin was the only variable with a significant difference in the YSM sub-groups while only calcium was non-significantly higher among the ORAI sub-groups.
 Conclusion: Elevated plasma level of calcium, albumin and alkaline phosphatase could be indicators of high bone turnover.

A comparison of 6 osteoporosis risk assessment tools among postmenopausal women in Kuala Lumpur, Malaysia

ObjectivesTo compare and assess the performance of 6 osteoporosis risk assessment tools for screening osteoporosis in Malaysian postmenopausal women. MethodsSix osteoporosis risk assessments tools (the Simple Calculated Osteoporosis Risk Estimation [SCORE], the Osteoporosis Risk Assessment Instrument, the Age Bulk One or Never Estrogen, the body weight, the Malaysian Osteoporosis Screening Tool, and the Osteoporosis Self-Assessment Tool for Asians) were used to screen postmenopausal women who had not been previously diagnosed with osteoporosis/osteopenia. These women also underwent a dual-energy X-ray absorptiometry (DXA) scan to confirm the absence or presence of osteoporosis. ResultsA total of 164/224 participants were recruited (response rate, 73.2%), of which only 150/164 (91.5%) completed their DXA scan. Sixteen participants (10.7%) were found to have osteoporosis, whilst 65/150 (43.3%) were found to have osteopenia. Using precision-recall curves, the recall of the tools ranged from 0.50 to 1.00, whilst precision ranged from 0.04 to 0.14. The area under the curve (AUC) ranged from 0.027 to 0.161. The SCORE had the best balance between recall (1.00), precision (0.04–0.12), and AUC (0.072–0.161). ConclusionsWe found that the SCORE had the best balance between recall, precision, and AUC among the 6 screening tools that were compared among Malaysian postmenopausal women.

Are other feasible options available for screening of risk assessment of osteoporosis in postmenopausal women at community level in Southern Coastal India

Background: Osteoporosis is a chronic debilitating condition which exhibits iceberg phenomenon. Identification at an early stage of disease will enable preventive measures to reduce the incidence of disease and complications. Owing to the cost of diagnostic test, this study, various screening tools such as WHO fracture risk assessment tool, osteoporosis self-assessment tool for Asians, simple calculated osteoporosis risk estimation and osteoporosis risk assessment instrument have been used for assessment, in order to screen postmenopausal women in the preliminary stages.Methods: A facility-based cross-sectional study was conducted among 107 postmenopausal women carried over a period of five months.Results: Prevalence of osteoporosis and osteopenia was 24.3% and 69.2%. The area under the curve for osteoporosis self-assessment tool for Asians (OSTA), simple calculated osteoporotic risk estimation (SCORE) and osteoporotic risk assessment instrument (ORAI) was 0.731, 0.407 and 0.172 respectively. OSTA proved to be effective in differentiating normal BMD from low BMD score (i.e., osteopenia and osteoporosis) with a cut off of 1.1, SCORE to be more effective in screening osteoporosis than the other tools because it had a higher positive probability with a cut off 22. FRAX tool predicted probability of five and three percent probability of major fracture and hip fracture risk in ten yearsConclusions: Various tools assessed in the studies can be utilized at community level for identifying high risk women in post-menopausal stage but with different cut offs. This will reduce the cost of screening and also facilitate non pharmacological measures to reduce the progression of disease.

Evaluation of Different Screening Tools for Predicting Femoral Neck Osteoporosis in Rural South Indian Postmenopausal Women

The measurement of bone mineral density by dual-energy X-ray absorptiometry scan is the “gold standard” for the diagnosis of osteoporosis, which has limited availability in many parts of India. This study was done to assess the diagnostic performance of 6 internationally validated tools (Simple Calculated Osteoporosis Risk Estimation [SCORE], age, bulk, one or never estrogen [ABONE], Osteoporosis Risk Assessment Instrument [ORAI] and Osteoporosis Self-Assessment Tool for Asians [OSTA], Fracture Risk Assessment Tool [FRAX®], and calcaneal quantitative ultrasound [QUS]) for the diagnosis of osteoporosis at the femoral neck (FN). This was a cross-sectional study conducted in 2108 ambulatory South Indian rural postmenopausal women who were assessed with SCORE, ABONE, ORAI, OSTA, and FRAX® tools. QUS was performed in 850 subjects. Bone mineral density was estimated by dual-energy X-ray absorptiometry scan at the FN, and sensitivity and specificity were calculated for all tools for predicting FN osteoporosis. The receiver operating characteristic curve was constructed for each tool and the area under the curve (AUC) was calculated. FN osteoporosis was seen in 27%. The sensitivities of SCORE, ABONE, OSTA, ORAI, FRAX®, and QUS were 91.3%, 91.0%, 88.5%, 81.0%, 72.7%, and 81.9%, and the specificities were 36.0%, 33.5%, 41.7%, 52.0%, 60.5%, and 50.3%, respectively, for the FN osteoporosis. When the receiver operating characteristics were constructed, the AUC was good only for SCORE (0.806), and the performance of the rest was under fair category (0.713–0.766). In our large cohort of rural postmenopausal women, the SCORE screening tool was found to be useful with good sensitivity and good AUC for predicting FN osteoporosis. Thus, this tool may be used in resource-limited countries to screen the population at risk and to enable treating physicians to make appropriate management decisions.

Worldwide Fracture Prediction

The substantial increase in the burden of non-communicable diseases in general and osteoporosis in particular, necessitates the establishment of efficient and targeted diagnosis and treatment strategies. This chapter reviews and compares different tools for osteoporosis screening and diagnosis; it also provides an overview of different treatment guidelines adopted by countries worldwide. While access to dual-energy X-ray absorptiometry to measure bone mineral density (BMD) is limited in most areas in the world, the introduction of risk calculators that combine risk factors, with or without BMD, have resulted in a paradigm shift in osteoporosis screening and management. To-date, forty eight risk assessment tools that allow risk stratification of patients are available, however only few are externally validated and tested in a population-based setting. These include Osteoporosis Self-Assessment Tool; Osteoporosis Risk Assessment Instrument; Simple Calculated Osteoporosis Risk Estimation; Canadian Association of Radiologists and Osteoporosis Canada calculator; Fracture Risk Assessment Calculator (FRAX); Garvan; and QFracture. These tools vary in the number of risk factors incorporated. We present a detailed analysis of the development, characteristics, validation, performance, advantages and limitations of these tools. The World Health Organization proposes a dual-energy X-ray absorptiometry-BMD T-score ≤ -2.5 as an operational diagnostic threshold for osteoporosis, and many countries have also adopted this cut-off as an intervention threshold in their treatment guidelines. With the introduction of the new fracture assessment calculators, many countries chose to include fracture risk as one of the major criteria to initiate osteoporosis treatment. Of the 52 national guidelines identified in 36 countries, 30 included FRAX derived risk in their intervention threshold and 22 were non-FRAX based. No universal tool or guideline approach will address the needs of all countries worldwide. Osteoporosis screening and management guidelines are best tailored according to the needs and resources of individual counties. While few countries have succeeded in generating valuable epidemiological data on osteoporotic fractures, to validate their risk calculators and base their guidelines, many have yet to find the resources to assess variations and secular trends in fractures, the performance of various calculators, and ultimately adopt the most convenient care pathway algorithms.

The utility of dual-energy X-ray absorptiometry, calcaneal quantitative ultrasound, and fracture risk indices (FRAX® and Osteoporosis Risk Assessment Instrument) for the identification of women with distal forearm or hip fractures: A pilot study

ABSTRACTPurpose: Dual-energy X-ray absorptiometry (DXA) is considered the “gold standard” in predicting osteoporotic fractures. Calcaneal quantitative ultrasound (QUS) variables are also known to predict fractures. Fracture risk assessment tools may also guide us for the detection of individuals at high risk for fractures. The aim of this case–control study was to evaluate the utility of DXA bone mineral density (BMD), calcaneal QUS parameters, FRAX® (Fracture Risk Assessment Tool), and Osteoporosis Risk Assessment Instrument (ORAI) for the discrimination of women with distal forearm or hip fractures. Materials and methods: This case–control study included 20 women with a distal forearm fracture and 18 women with a hip fracture as cases and 76 age-matched women served as controls. BMD at the spine, proximal femur, and radius was measured using DXA and acoustic parameters of bone were obtained using a calcaneal QUS device. FRAX® 10-year probability of fracture and ORAI scores were also calculated in all participants. Receiver operating characteristic (ROC) analysis was used to assess fracture discriminatory power of all the tools. Results: While all DXA BMD, and QUS variables and FRAX® fracture probabilities demonstrated significant areas under the ROC curves for the discrimination of hip-fractured women and those without, only 33% radius BMD, broadband ultrasound attenuation (BUA), and FRAX® major osteoporotic fracture probability calculated without BMD showed significant discriminatory power for distal forearm fractures. Conclusions: It can be concluded that QUS variables, particularly BUA, and FRAX® major osteoporotic fracture probability without BMD are good candidates for the identification of both hip and distal forearm fractures.

Osteoporosis screening in postmenopausal women aged 50–64 years: BMI alone compared with current screening tools

ObjectivesConsensus on when to initiate DXA screening for early postmenopausal women (<65 years of age) is lacking. Low body mass index (BMI) has been proposed as one of the major risk factors for osteoporosis. This study sought to compare the predictive performance of BMI alone with 5 screening modalities (the U.S. Preventive services task force [USPSTF] FRAX threshold of 9.3%, a risk factor based approach [≥1 risk factors], the osteoporosis self-assessment tool [OST <2], the osteoporosis risk assessment instrument [ORAI ≥9], and the simple calculated osteoporosis risk estimation [SCORE ≥6]) in identifying early postmenopausal women with osteoporosis. MethodsPostmenopausal women aged 50–64 years presenting for a DXA test were recruited between January 1, 2007, and March 1, 2009. Demographic data and osteoporosis risk factors were obtained through a telephone survey. The performance of each screening tool in predicting osteoporosis was compared. ResultsOf 445 study participants, 95% were White, 38 had osteoporosis (T-score ≤−2.5). BMI (<28) was associated with the highest Sensitivity (95%), the lowest Negative Likelihood Ratio (LR-) of 0.14, an AUC of 0.73, and the number needed to scan (NNS) of 8. The USPSTF approach had the lowest sensitivity (24%), highest LR- (0.91), lowest AUC (0.62), and highest NNS (9). Among 5 established modalities, SCORE (≥6) appears to be the best (sensitivity: 92%, LR-: 0.24, AUC: 0.75, NNS: 9). ConclusionBMI (<28) had a comparable numerical screening performance overall to the current screening modalities. BMI (<28) could be considered a potential indicator when screening early postmenopausal White women for osteoporosis. However, a better osteoporosis screening tool remains to be developed.

Risk Assessment Tools for Osteoporosis Screening in Postmenopausal Women: A Systematic Review

Osteoporotic fractures are common in postmenopausal women. Tools are available to estimate the risk of low bone mineral density (BMD) or fracture. This systematic review retrieved articles that evaluated osteoporosis risk assessment tools among postmenopausal women in North America. For identifying BMD T-score ≤-2.5, most studies of the Simple Calculated Osteoporosis Risk Estimation tool (SCORE) and Osteoporosis Risk Assessment Instrument (ORAI) reported sensitivity ≥90 %. Area under the receiver operating characteristic curve (AUC) was usually <0.75 for SCORE and ≥0.75 for ORAI. Among women 50-64 years old, a Fracture Risk Assessment Tool (FRAX) threshold ≥9.3 % had a sensitivity of 33 % for identifying BMD T-score ≤-2.5 and 26 % for predicting major osteoporotic fracture (MOF). For predicting MOF, sensitivity was higher for SCORE and Osteoporosis Self-assessment Tool equation (OST), and higher in women ≥65 years old. For predicting BMD T-score ≤-2.5 in women ≥65 years old, the sensitivities of SCORE; ORAI; and Age, Body Size, No Estrogen (ABONE) were very high. No optimal osteoporosis risk assessment tool is available for identifying low BMD and MOF risk.

Systematic review and meta-analysis of the performance of clinical risk assessment instruments for screening for osteoporosis or low bone density.

We performed a systematic review and meta-analysis of the performance of clinical risk assessment instruments for screening for DXA-determined osteoporosis or low bone density. Commonly evaluated risk instruments showed high sensitivity approaching or exceeding 90% at particular thresholds within various populations but low specificity at thresholds required for high sensitivity. Simpler instruments, such as OST, generally performed as well as or better than more complex instruments. The purpose of the study is to systematically review the performance of clinical risk assessment instruments for screening for dual-energy X-ray absorptiometry (DXA)-determined osteoporosis or low bone density. Systematic review and meta-analysis were performed. Multiple literature sources were searched, and data extracted and analyzed from included references. One hundred eight references met inclusion criteria. Studies assessed many instruments in 34 countries, most commonly the Osteoporosis Self-Assessment Tool (OST), the Simple Calculated Osteoporosis Risk Estimation (SCORE) instrument, the Osteoporosis Self-Assessment Tool for Asians (OSTA), the Osteoporosis Risk Assessment Instrument (ORAI), and body weight criteria. Meta-analyses of studies evaluating OST using a cutoff threshold of <1 to identify US postmenopausal women with osteoporosis at the femoral neck provided summary sensitivity and specificity estimates of 89% (95%CI 82-96%) and 41% (95%CI 23-59%), respectively. Meta-analyses of studies evaluating OST using a cutoff threshold of 3 to identify US men with osteoporosis at the femoral neck, total hip, or lumbar spine provided summary sensitivity and specificity estimates of 88% (95%CI 79-97%) and 55% (95%CI 42-68%), respectively. Frequently evaluated instruments each had thresholds and populations for which sensitivity for osteoporosis or low bone mass detection approached or exceeded 90% but always with a trade-off of relatively low specificity. Commonly evaluated clinical risk assessment instruments each showed high sensitivity approaching or exceeding 90% for identifying individuals with DXA-determined osteoporosis or low BMD at certain thresholds in different populations but low specificity at thresholds required for high sensitivity. Simpler instruments, such as OST, generally performed as well as or better than more complex instruments.

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.

Osteoporosis Risk Prediction for Bone Mineral Density Assessment of Postmenopausal Women Using Machine Learning

PurposeA number of clinical decision tools for osteoporosis risk assessment have been developed to select postmenopausal women for the measurement of bone mineral density. We developed and validated machine learning models with the aim of more accurately identifying the risk of osteoporosis in postmenopausal women compared to the ability of conventional clinical decision tools.Materials and MethodsWe collected medical records from Korean postmenopausal women based on the Korea National Health and Nutrition Examination Surveys. The training data set was used to construct models based on popular machine learning algorithms such as support vector machines (SVM), random forests, artificial neural networks (ANN), and logistic regression (LR) based on simple surveys. The machine learning models were compared to four conventional clinical decision tools: osteoporosis self-assessment tool (OST), osteoporosis risk assessment instrument (ORAI), simple calculated osteoporosis risk estimation (SCORE), and osteoporosis index of risk (OSIRIS).ResultsSVM had significantly better area under the curve (AUC) of the receiver operating characteristic than ANN, LR, OST, ORAI, SCORE, and OSIRIS for the training set. SVM predicted osteoporosis risk with an AUC of 0.827, accuracy of 76.7%, sensitivity of 77.8%, and specificity of 76.0% at total hip, femoral neck, or lumbar spine for the testing set. The significant factors selected by SVM were age, height, weight, body mass index, duration of menopause, duration of breast feeding, estrogen therapy, hyperlipidemia, hypertension, osteoarthritis, and diabetes mellitus.ConclusionConsidering various predictors associated with low bone density, the machine learning methods may be effective tools for identifying postmenopausal women at high risk for osteoporosis.

Performance of Risk Indices for Identifying Low Bone Mineral Density and Osteoporosis in Mexican Mestizo Women with Rheumatoid Arthritis

We evaluated the utility of 6 generic and 2 specific risk indices for identifying low bone mineral density (BMD) or osteoporosis in women with rheumatoid arthritis (RA); and their correlation with 10-year probability of fractures as assessed with the World Health Organization fracture risk assessment (FRAX) tool. Mexican Mestizo women with RA were evaluated in this cross-sectional study using 6 generic indices [Simple Calculated Osteoporosis Risk Estimation (SCORE); Osteoporosis Risk Assessment Instrument (ORAI); Osteoporosis Self-Assessment Tool; Age, Body Size, No Estrogen; Osteoporosis Index of Risk (OSIRIS); and Guidelines of the US National Osteoporosis Foundation], 2 specific indices (Amsterdam and modified Amsterdam), and FRAX. BMD results on dual-energy x-ray absorptiometry (DEXA) at the lumbar spine and femoral neck were considered the "gold standard." Sensitivity, specificity, and predictive values (PV) of the indices and their correlations with FRAX results were estimated. Among 191 patients, 46 had osteoporosis (24.1%) and 119 had low BMD (62.3%). For predicting osteoporosis, SCORE showed the highest sensitivity (96%), whereas OSIRIS (87%) and ORAI (82%) showed the highest specificities. OSIRIS also had the greatest positive PV (92%). The specific indices had low sensitivity and low specificity (Amsterdam, 50% and 79%, respectively; modified Amsterdam, 56% and 70%). All the indices had a low but significant correlation with FRAX. These findings support the use of some generic indices to identify patients with RA who should undergo DEXA testing. Currently available specific indices did not perform satisfactorily. New specific risk indices for osteoporosis in RA should be developed to increase sensitivity and specificity for predicting osteoporosis.

Identifying Women with Low Bone Mass: A Systematic Review of Screening Tools

Several osteoporosis risk-factor screening tools have been developed to identify women at increased risk of low bone mineral density, who would most benefit from dual x-ray absorptiometry (DXA) screening. The purpose of this systematic review was to assess the effectiveness of these screening tools in determining postmenopausal Caucasian women at risk of developing osteoporosis. Appropriate databases and sources of primary studies were identified. A systematic review of the literature using a comprehensive search strategy was employed, and all citations were stored. Exclusion criteria were established, and critical quality was assessed. Study characteristics were tabulated and comparisons made. Upon reviewing the evidence, 6 screening tools (Simple Calculated Osteoporosis Risk Estimation, the Osteoporosis Risk Assessment Instrument, the Osteoporosis Self-Assessment Tool [OST], the body weight criterion, the Osteoporosis Index of Risk, and Age, Body Size, No Estrogen) were identified. Studies show that these screening tools are useful in identifying postmenopausal Caucasian women in need of DXA screening and possible intervention for osteoporosis. For clinical and community practice, the OST is the simplest approach to determine individuals at risk of osteoporosis and in need of DXA screening. There is still a need for further development and validation of screening tools in both men and ethnicities other than Caucasian.

The Osteoporosis Self-Assessment Tool versus alternative tests for selecting postmenopausal women for bone mineral density assessment: a comparative systematic review of accuracy

We performed a systematic review of studies comparing the Osteoporosis Self-Assessment Tool (OST) and other tests used to select women for bone mineral density (BMD) assessment. In comparative meta-analyses, we found that the accuracy of OST was similar to other tests that are based on information from the medical history. By contrast, assessment by quantitative ultrasonography at the heel was more accurate than OST in discriminating between women with high and low BMD. The methodological quality of the included studies was generally low. Numerous tests are suggested for triaging postmenopausal women for bone mineral density (BMD) assessment by dual-energy X-ray absorptiometry. Previous studies suggest that OST, based on age and weight only, may be as accurate as more complex triage tests. We systematically compare the accuracy of OST and alternative triage tests in postmenopausal women. We searched PubMed, Embase, Web of Science, citation lists, and conference proceedings. Our main measure of accuracy was the diagnostic odds ratio (DOR). We compared summary estimates of DOR (sDOR) for OST and alternative tests in pairwise meta-analyses by using the Moses-Littenberg approach. Summary estimates of DOR for OST and the clinical decision rules Simple Calculated Osteoporosis Risk Estimation (SCORE) and Osteoporosis Risk Assessment Instrument (ORAI) did not differ significantly in white women (relative sDOR: 0.57-1.17, all p >or= 0.11). By contrast, sDOR was higher for Stiffness Index assessed by calcaneal quantitative ultrasonography than for OST (relative sDOR: 1.9, p = 0.005). Studies were few in Asian and black women. Methodological quality, assessed with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) checklist, was generally low. In white women, the accuracy of OST and alternative clinical decision rules was similar, whereas Stiffness Index was more accurate than OST. Low study quality renders transferability to clinical settings uncertain.

Clinical performance of osteoporosis risk assessment tools in women aged 67 years and older.

Clinical performance of osteoporosis risk assessment tools was studied in women aged 67 years and older. Weight was as accurate as two of the tools to detect low bone density. Discriminatory ability was slightly better for the OST risk tool, which is based only on age and weight. Screening performance of osteoporosis risk assessment tools has not been tested in a large, population-based US cohort. We conducted a diagnostic accuracy analysis of the Osteoporosis Self-assessment Tool (OST), Osteoporosis Risk Assessment Instrument (ORAI), Simple Calculated Osteoporosis Risk Estimation (SCORE), and individual risk factors (age, weight or prior fracture) to identify low central (hip and lumbar spine) bone mineral density (BMD) in 7779 US women aged 67 years and older participating in the Study of Osteoporotic Fractures. The OST had the greatest area under the receiver operating characteristic curve (AUC 0.76, 95% CI 0.74, 0.77). Weight had an AUC of 0.73 (95% CI 0.72, 0.75), which was >or=AUC values for the ORAI, SCORE, age or prior fracture. Using cut points from the development papers, the risk tools had sensitivities >or=85% and specificities <or=48%. When new cut points were set to achieve a likelihood ratio of negative 0.1-0.2, the tools ruled out fewer than 1/4 of women without low central BMD. Weight identified low central BMD as accurately as the ORAI and SCORE. The risk tools would be unlikely to show an advantage over simple weight cut points in an osteoporosis screening protocol for elderly women.

Individualization of osteoporosis risk

Anti-fracture therapy is often pursued in individuals with osteoporosis or low bone mineral density with or without a prior fracture [1–3], because they are at high risk of subsequent fracture [4, 5]. In recent years, there has been a proliferation of clinical prediction rules, including clinical risk indices and scores, for identifying individuals with osteoporosis. The main problem with these clinical prediction rules is that they categorize individuals into low-risk versus high-risk groups based on some arbitrary threshold. As a result, when this risk stratification-based approach is applied to an individual, its prognostic performance is often poor. Among the clinical indices for predicting osteoporosis, the Osteoporosis Self-Assessment Tool (OST) [6] is perhaps the simplest score and has perhaps been the most widely studied. However, the clinical usefulness of this score in different populations has not been systematically studied. In this issue, Rud and colleagues [7] systematically summarize some key prognostic properties of the OST score across different Asian and Caucasian populations. They especially focus on the prognostic value of OST in ruling out osteoporosis (i.e., LR−). Their meta-analysis showed that the overall LR− was 0.19 (95% confidence interval: 0.17 and 0.21) with considerable heterogeneity between populations. Although Rud and colleagues do not report other prognostic measures of the OST score in their paper, it is possible to estimate the LR+, sensitivity, specificity, and summary receiver operating characteristic curve (sROC) from the data (Table 1). These results suggest that in both Asian and Caucasian populations, the OST score has good sensitivity, but poor specificity, and moderate discriminatory value (i.e., with sROC being between 0.74 and 0.79). The odds for OST positivity among women with osteoporosis is 11 times (in Asians) and 7.8 times (in Caucasians) higher than the odds for positivity among women without osteoporosis. This diagnostic odds ratio is much lower than the criterion required for an “adequate test”. However, these results are broadly consistent with prognostic values of the simple calculated osteoporosis risk estimation (SCORE), osteoporosis risk assessment instrument (ORAI) and National Osteoporosis Foundation guidelines, which were also found to have poor specificity and high sensitivity [8]. When the prevalence of osteoporosis is 17% (which is observed in Caucasian populations [7]) and given the observed LR− and LR+ in Table 1, it can be estimated that if an individual is classified as “low risk” by OST, the probability that the individual has no osteoporosis is 0.96; and if the individual is classified as “high risk”, the probability that the individual has osteoporosis is only ~0.25. In other words, the OST score is useful in ruling out the possibility of osteoporosis, but it performs badly in ruling in the possibility of osteoporosis. The best positive and negative predictive values are achieved when the sensitivity is around 70% and specificity is approximately 80% (Fig. 1). However, in all studies reviewed, the OST score has a sensitivity of >90% and specificity of <57%. Several factors contribute to the relatively poor performance of OST. First, the prevalence of osteoporosis in the populations under review, and the relationships between age, weight and BMD is not constant across the population. For example, the prevalence of osteoporosis varied between 7 to 21%, with and the LR− being between 0.02 and 0.49 among the Asian populations under review. Indeed, a Osteoporos Int (2007) 18:1153–1156 DOI 10.1007/s00198-007-0415-z

Validation of various osteoporosis risk indices in elderly Chinese females in Singapore

This study aimed to compare the sensitivity and specificity of various published indices for identifying elderly Chinese females at risk of osteoporosis in Singapore. The indices considered were the Simple Calculated Osteoporosis Risk Estimation (SCORE), the Osteoporosis Risk Assessment Instrument (ORAI), the Age Bulk One or Never Estrogens (ABONE), body weight (WEIGHT), and the Osteoporosis Self-Assessment Tool for Asians (OSTA). Altogether, 135 postmenopausal Chinese female subjects aged 55 years and older participated in the study, and their bone mineral density (BMD) was measured with dual-energy x-ray absorptiometry. Subjects were classified as osteoporotic if their femoral neck BMD T-score was -2.5 or lower. Receiver operating characteristic (ROC) curves were generated to determine the indices' cut-off points, sensitivity, and specificity. OSTA had the highest discriminatory power, with an estimated area under the ROC curve of 0.82. This was followed by SCORE (0.80), WEIGHT (0.78), ORAI (0.76), and ABONE (0.70). At the cut-off point of -2, OSTA achieved sensitivity and specificity of 91% and 59%, respectively. The study showed that OSTA is an effective index for identifying postmenopausal women at risk for osteoporosis.