Identification of at-risk women for osteoporosis screening

Assessing the utility of osteoporosis self-assessment tool for Asians in patients undergoing hip surgery

Objectives

Diagnosis and treatment of osteoporosis are instrumental in obtaining good outcomes of hip surgery. Measuring bone mineral density (BMD) using dual-energy X-ray absorptiometry (DXA) is the gold standard for diagnosing osteoporosis. However, due to limited access to DXA, there is a need for a screening tool to identify patients at a higher risk of osteoporosis. We analyzed the potential utility of the Osteoporosis Self-assessment Tool for Asians (OSTA) as a screening tool for osteoporosis.

Methods

A total of 1378 female patients who underwent hip surgery at 8 institutions were analyzed. For each patient, the BMD of the proximal femoral region was measured by DXA (DXA-BMD), and the correlation with OSTA score (as a continuous variable) was assessed. Receiver operating characteristic (ROC) curve analysis was performed to assess the ability of OSTA score to predict osteoporosis. Lastly, the OSTA score was truncated to yield an integer (OSTA index) to clarify the percentage of patients with osteoporosis for each index.

Results

DXA-BMD showed a strong correlation with OSTA (r = 0.683; P < 0.001). On ROC curve analysis, the optimal OSTA score cut-off value of -5.4 was associated with 73.8% sensitivity and 80.9% specificity for diagnosis of osteoporosis (area under the curve: 0.842). A decrease in the OSTA index by 1 unit was associated with a 7.3% increase in the probability of osteoporosis.

Conclusions

OSTA is a potentially useful tool for screening osteoporosis in patients undergoing hip surgery. Our findings may help identify high-risk patients who require further investigation using DXA.

A Machine Learning-Based Preclinical Osteoporosis Screening Tool (POST): Model Development and Validation Study

Background

Identifying persons with a high risk of developing osteoporosis and preventing the occurrence of the first fracture is a health care priority. Most existing osteoporosis screening tools have high sensitivity but relatively low specificity.

Objective

We aimed to develop an easily accessible and high-performance preclinical risk screening tool for osteoporosis using a machine learning-based method among the Hong Kong Chinese population.

Methods

Participants aged 45 years or older were enrolled from 6 clinics in the 3 major districts of Hong Kong. The potential risk factors for osteoporosis were collected through a validated, self-administered questionnaire and then filtered using a machine learning-based method. Bone mineral density was measured with dual-energy x-ray absorptiometry at the clinics; osteoporosis was defined as a t score of -2.5 or lower. We constructed machine learning models, including gradient boosting machines, support vector machines, and naive Bayes, as well as the commonly used logistic regression models, for the prediction of osteoporosis. The best-performing model was chosen as the final tool, named the Preclinical Osteoporosis Screening Tool (POST). Model performance was evaluated by the area under the receiver operating characteristic curve (AUC) and other metrics.

Results

Among the 800 participants enrolled in this study, the prevalence of osteoporosis was 10.6% (n=85). The machine learning-based Boruta algorithm identified 15 significantly important predictors from the 113 potential risk factors. Seven variables were further selected based on their accessibility and convenience for daily self-assessment and health care practice, including age, gender, education level, decreased body height, BMI, number of teeth lost, and the intake of vitamin D supplements, to construct the POST. The AUC of the POST was 0.86 and the sensitivity, specificity, and accuracy were all 0.83. The positive predictive value, negative predictive value, and F1-score were 0.41, 0.98, and 0.56, respectively.

Conclusions

The machine learning-based POST was conveniently accessible and exhibited accurate discriminative capabilities for the prediction of osteoporosis; it might be useful to guide population-based preclinical screening of osteoporosis and clinical decision-making.

Ten existing osteoporosis prediction tools for the successful application of National Health Insurance-reimbursed anti-osteoporosis medications in long-term care residents in Taiwan

BACKGROUND/PURPOSE

Osteoporotic fracture introduce enormous societal and economic burden, especially for long-term care residents (LTCRs). Although osteoporosis prevention for LTCRs is urgently needed, obstacles such as frail status and inconvenient hospital visits hurdled them from necessary examinations and diagnoses. We aimed to test 10 existing osteoporosis screening tools (OSTs), which can be easily used in institutions and serve as a prediction, for accurately determining the outcome of a Taiwan's National Health Insurance (NHI)-reimbursed anti-osteoporosis medications (AOMs) application for LTCRs.

METHODS

This prospective analysis recruited 444 patients from LTC institutions between October 2018 and November 2019. Predictions of whether the NHI-reimbursed AOMs criteria was met were tested for 10 OSTs. The results of OSTs categorized into self-reported or validated based on previous fracture history were self-reported by LTCRs or validated by imaging data and medical records, respectively. The receiver operating characteristic curve and the optimal cut-off points for LTCRs based on Youden's index were explored.

RESULTS

Overall, the validated OSTs had a higher positive predictive value (PPV) and negative predictive value (NPV) summation than the corresponding reported OSTs. The validated FRAX-Major was the best OST (PPV = 63.6%, NPV = 82.4% for the male group and, PPV = 78.8%, NPV = 90.0% for the female group). After applying the optimum cut-off derived from Youden's index, the validated FRAX-Major (PPV = 75.4%, NPV = 92.0%)) remained performed best for men. In female population, validated FRAX-Major (PPV = 87.2%, NPV = 84.1%) and validated osteoporosis prescreening risk assessment (OPERA; PPV = 96.1%, NPV = 79.7%)) both provided good prediction results.

CONCLUSION

FRAX-Major and OPERA have better prediction ability for LTCRs to acquire NHI-reimbursed AOMs. The validated fracture history and adjusted cut-off points could prominently increase the PPV during prediction.

Predicting the risk of osteoporosis in older Vietnamese women using machine learning approaches

Osteoporosis contributes significantly to health and economic burdens worldwide. However, the development of osteoporosis-related prediction tools has been limited for lower-middle-income countries, especially Vietnam. This study aims to develop prediction models for the Vietnamese population as well as evaluate the existing tools to forecast the risk of osteoporosis and evaluate the contribution of covariates that previous studies have determined to be risk factors for osteoporosis. The prediction models were developed to predict the risk of osteoporosis using machine learning algorithms. The performance of the included prediction models was evaluated based on two scenarios; in the first one, the original test parameters were directly modeled, and in the second the original test parameters were transformed into binary covariates. The area under the receiver operating characteristic curve, the Brier score, precision, recall and F1-score were calculated to evaluate the models' performance in both scenarios. The contribution of the covariates was estimated using the Permutation Feature Importance estimation. Four models, namely, Logistic Regression, Support Vector Machine, Random Forest and Neural Network, were developed through two scenarios. During the validation phase, these four models performed competitively against the reference models, with the areas under the curve above 0.81. Age, height and weight contributed the most to the risk of osteoporosis, while the correlation of the other covariates with the outcome was minor. Machine learning algorithms have a proven advantage in predicting the risk of osteoporosis among Vietnamese women over 50 years old. Additional research is required to more deeply evaluate the performance of the models on other high-risk populations.

Decision Tree Modeling for Osteoporosis Screening in Postmenopausal Thai Women

Osteoporosis is still a serious public health issue in Thailand, particularly in postmenopausal women; meanwhile, new effective screening tools are required for rapid diagnosis. This study constructs and confirms an osteoporosis screening tool-based decision tree (DT) model. Four DT algorithms, namely, classification and regression tree; chi-squared automatic interaction detection (CHAID); quick, unbiased, efficient statistical tree; and C4.5, were implemented on 356 patients, of whom 266 were abnormal and 90 normal. The investigation revealed that the DT algorithms have insignificantly different performances regarding the accuracy, sensitivity, specificity, and area under the curve. Each algorithm possesses its characteristic performance. The optimal model is selected according to the performance of blind data testing and compared with traditional screening tools: Osteoporosis Self-Assessment for Asians and the Khon Kaen Osteoporosis Study. The Decision Tree for Postmenopausal Osteoporosis Screening (DTPOS) tool was developed from the best performance of CHAID’s algorithms. The age of 58 years and weight at a cutoff of 57.8 kg were the essential predictors of our tool. DTPOS provides a sensitivity of 92.3% and a positive predictive value of 82.8%, which might be used to rule in subjects at risk of osteopenia and osteoporosis in a community-based screening as it is simple to conduct.

Osteoporosis Screening and Fracture Risk Assessment Tool: Its Scope and Role in General Clinical Practice

Osteoporosis is a widely prevalent condition among postmenopausal women characterized by low bone mass and skeletal fragility that increases the risk of fractures specifically in the hip, spine, wrist, humerus, and pelvis. It has become a major public health problem around the world. An osteoporotic fracture affects one in every three women and one in every five men aged 50 and above. Hip and spine fractures are linked to a higher death rate and can cause ambulation problems, depression, chronic pain, independence loss, and persistent discomfort. It not only puts a lot of strain on the individual but also causes a significant cost to society. Osteoporosis is a silent disease that goes unrecognized until a patient develops a pathological fracture. Diagnosis of osteoporosis is based on bone mineral density (BMD) estimation by dual-energy x-ray absorptiometry (DXA) as defined by WHO. However, in many resource-constrained and underdeveloped or low-middle income countries, it is not widely available. There are a number of questionnaire-based techniques available to identify such postmenopausal women and older men who may be at risk of having low BMD and osteoporosis. Our aim of the study is to search and compile such simple yet useful and validated screening and assessment tools for osteoporosis that can help to identify people at risk of having low BMD and the potential candidate who can benefit from BMD estimation in a resource-restricted geographical area or low/middle-income countries and benefit from treatment. Though these tools are not diagnostic can have broader applicability in general clinical practice and usefulness in identifying high-risk individuals and may prove cost-effective. Although it has limitations, FRAX is a widely used osteoporotic fracture risk assessment tool around the globe and when used with femoral neck BMD it has greater accuracy.

Conceptual design of the dual X-ray absorptiometry health informatics prediction system for osteoporosis care

Osteoporotic fractures are a major and growing public health problem, which is strongly associated with other illnesses and multi-morbidity. Big data analytics has the potential to improve care for osteoporotic fractures and other non-communicable diseases (NCDs), reduces healthcare costs and improves healthcare decision-making for patients with multi-disorders. However, robust and comprehensive utilization of healthcare big data in osteoporosis care practice remains unsatisfactory. In this paper, we present a conceptual design of an intelligent analytics system, namely, the dual X-ray absorptiometry (DXA) health informatics prediction (HIP) system, for healthcare big data research and development. Comprising data source, extraction, transformation, loading, modelling and application, the DXA HIP system was applied in an osteoporosis healthcare context for fracture risk prediction and the investigation of multi-morbidity risk. Data was sourced from four DXA machines located in three healthcare centres in Ireland. The DXA HIP system is novel within the Irish context as it enables the study of fracture-related issues in a larger and more representative Irish population than previous studies. We propose this system is applicable to investigate other NCDs which have the potential to improve the overall quality of patient care and substantially reduce the burden and cost of all NCDs.

Development of a model for identification of individuals with high risk of osteoporosis

Many developing countries, including Vietnam, lack DXA resources for the diagnosis of osteoporosis, which poses difficulties in the treatment and prevention of osteoporosis at the individual level. We have developed and validated a prediction model for individualized assessment of osteoporosis based on age and body weight for men and women.

PURPOSE

To estimate the prevalence of osteoporosis and to develop and validate a prediction model for estimating the absolute risk of osteoporosis in the Vietnamese population.

METHODS

The study involved 1477 women and 669 men aged 50 years and older, who were recruited from the general population in Ho Chi Minh City (Vietnam). Bone mineral density (BMD) at the femoral neck, total hip, and lumbar spine was measured by DXA (Hologic Horizon). The diagnosis of osteoporosis was based on BMD T-score (T-score ≤ - 2.5) at the femoral neck or lumbar spine which was derived from a published reference range for the Vietnamese population. The logistic regression model was used to develop the prediction model for men and women separately. The bootstrap method was used to evaluate the model performance using 3 indices: the area under the receiver's operating characteristic curve (AUC), Brier score, and R-squared values.

RESULTS

The prevalence of osteoporosis at any site was 28.3% in women and 15.5% in men. The best predictors of osteoporosis risk were age and body weight. Using these indices, a cut-off of 0.195 for women yielded an AUC of 0.825, Brier score = 0.112, and it explained 33.8% of total variance in risk of osteoporosis between individuals. Similarly, in men, the internal validation with a cut-off of 0.09 yielded good accuracy, with AUC = 0.858, Brier score = 0.040, and R-squared = 30.3%.

CONCLUSION

We have developed and validated a prediction model for individualized assessment of osteoporosis. In settings without DXA, this model can serve as a useful screening tool to identify high-risk individuals for DXA scan.

Modified SCORE tool for prediction of bone mineral density in Egyptian elderly women. Comparison of seven osteoporosis screening tools

We aimed to compare the performance of seven risk screening tools for detecting elderly Egyptian women with osteoporosis and to modify the tool with the best performance to increase the efficiency of referral for bone mineral density (BMD) testing. There are few studies about the epidemiology of osteoporosis in Egypt, in addition, there was no study done before to evaluate the performance of these seven screening tools in a large sample size. This aims to help clinicians restrict the use of DXA scan for those patients defined as "high risk" for osteoporosis which can substantially reduce the cost for the community and the patients, especially in developing countries. We conducted a cross-sectional study on 681 elderly women for measurement of BMD using DXA scans. The performance of the Simple Calculated Osteoporosis Risk Estimation (SCORE) was superior to other indices with the highest sensitivity and specificity. The newly modified SCORE tool at cutoff point ≥1 is a simple easy tool and shows good sensitivity (up to 94%) and acceptable specificity (up to 46.7%) in detecting osteoporosis in elderly women with fewer items and easier calculation.

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

Objectives

To compare and assess the performance of 6 osteoporosis risk assessment tools for screening osteoporosis in Malaysian postmenopausal women.

Methods

Six 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.

Results

A 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).

Conclusions

We 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.

Improvement of region of interest extraction and scanning method of computer-aided diagnosis system for osteoporosis using panoramic radiographs

OBJECTIVES

Patients undergoing osteoporosis treatment benefit greatly from early detection. We previously developed a computer-aided diagnosis (CAD) system to identify osteoporosis using panoramic radiographs. However, the region of interest (ROI) was relatively small, and the method to select suitable ROIs was labor-intensive. This study aimed to expand the ROI and perform semi-automatized extraction of ROIs. The diagnostic performance and operating time were also assessed.

METHODS

We used panoramic radiographs and skeletal bone mineral density data of 200 postmenopausal women. Using the reference point that we defined by averaging 100 panoramic images as the lower mandibular border under the mental foramen, a 400 × 100-pixel ROI was automatically extracted and divided into four 100 × 100-pixel blocks. Valid blocks were analyzed using program 1, which examined each block separately, and program 2, which divided the blocks into smaller segments and performed scans/analyses across blocks. Diagnostic performance was evaluated using another set of 100 panoramic images.

RESULTS

Most ROIs (97.0%) were correctly extracted. The operation time decreased to 51.4% for program 1 and to 69.3% for program 2. The sensitivity, specificity, and accuracy for identifying osteoporosis were 84.0, 68.0, and 72.0% for program 1 and 92.0, 62.7, and 70.0% for program 2, respectively. Compared with the previous conventional system, program 2 recorded a slightly higher sensitivity, although it occasionally also elicited false positives.

CONCLUSIONS

Patients at risk for osteoporosis can be identified more rapidly using this new CAD system, which may contribute to earlier detection and intervention and improved medical care.

Osteoporosis and its perspective in Pakistan: A review of evidence and issues for addressing fragility fractures

Despite major advances in osteoporosis diagnosis and treatment, low rates of investigating and treating osteoporosis in patients with fragility fracture are reported in Pakistan. Cost of therapies, time and cost of resources for diagnosis, concerns about medications and lack of clarity regarding the onus of responsibility to undertake this care, are some of the barriers to osteoporosis identification and treatment. Data from our part of the world on osteoporosis as well as on fragility fractures is sparse. This review addresses the current screening and diagnostic strategies for osteoporosis and reviews the existing literature to highlight the issues prevalent in our society on this major public health problem.

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.

Osteoporosis Risk Calculators

Osteoporosis is a silent disease until fractures occur, patient recognition is the greatest clinical challenge. Although more than 20 million women in the US are estimated to have established osteoporosis the majority are not appropriately identified. Bone densitometry is the current gold standard for diagnosis of osteoporosis; but may not be feasible or cost-effective to recommend for all postmenopausal women. Therefore, questionnaires incorporating risk factors have been developed to aid the clinician in identifying women with osteoporosis. We will review Qfracture, CAnadian Risk for Osteoporosis Calculator (CAROC), the Simple Calculated Osteoporosis Risk Index (SCORE), the Osteoporosis Risk Assessment Index (ORAI), the Osteoporotic Self-assessment Tool (OST), ABONE, and the United States Preventive Services Task Force recommendations.

Validation of osteoporosis risk assessment tools in middle-aged Thai women

OBJECTIVES

To validate osteoporosis risk assessment tools in middle-aged Thai women.

METHODS

A total of 1038 women who had bone mineral density (BMD) measurements using dual-energy X-ray absorptiometry were reviewed. Clinical data were used to validate the diagnostic test performance of various osteoporosis risk assessment tools, including ABONE, FRAX^®, ORAI, OSIRIS, SCORE, SOFSURF, and OSTA. The following parameters were evaluated: sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and accuracy; those with 95% confidence interval (CI) of the receiver operator characteristics area under the curve (ROC-AUC) > 0.5 were considered statistically significant.

RESULTS

The subjects had a mean age of 53.01 ± 6.20 years and body mass index (BMI) of 23.98 ± 3.38 kg/m². Among the osteoporosis risk assessment tools being evaluated, the tools that had ROC-AUC >0.8 and 95% CI >0.5, and could predict osteoporosis at the femoral neck with high specificity of >75% and NPV of >90%, were FRAX^® without BMD (ROC-AUC 0.83; 95% CI 0.73-0.93; specificity 99.90; NPV 98.89), SCORE (ROC-AUC 0.86; 95% CI 0.78-0.94; specificity 98.79; NPV 98.99), and OSTA (ROC-AUC 0.86; 95% CI 0.79-0.94; specificity 75.03; NPV 99.73).

CONCLUSION

The prevalence of osteoporosis in the middle-aged Thai women attending Siriraj Menopause Clinic is 7.3% at the lumbar spine and/or femoral neck. FRAX^® without BMD, SCORE, and OSTA have appropriate validity as tools for ruling out osteoporosis in these women.

Risk assessment instruments for screening bone mineral density in a Mediterranean population

AIM

To evaluate the power of six osteoporosis-screening instruments in women in a Mediterranean country.

METHODS

Data concerning several osteoporosis risk factors were prospectively collected from 1000 postmenopausal women aged 42-87 years who underwent dual-energy X-ray absorptiometry (DEXA) screening. Six osteoporosis risk factor screening tools were applied to this sample to evaluate their performance and choose the most appropriate tool for the study population.

RESULTS

The most important screening tool for osteoporosis status was the Simple Calculated Osteoporosis Risk Estimation, which had an area under the curve (AUC) of 0.678, a sensitivity of 72%, and a specificity of 72%, with a cut-off point of 20.75. The most important screening tool for osteoporosis risk was the Osteoporosis Self-assessment Tool, which had an AUC of 0.643, a sensitivity of 77%, and a specificity of 46%, with a cut-off point of -2.9.

CONCLUSION

Some commonly used clinical risk instruments demonstrate high sensitivity for distinguishing individuals with DEXA-ascertained osteoporosis or reduced bone mineral density.

Comparisons of Different Screening Tools for Identifying Fracture/Osteoporosis Risk Among Community-Dwelling Older People

A prospective study was conducted to compare criterion, predictive, and construct validities of 9 fracture/osteoporosis assessment tools, including calcaneal quantitative ultrasonography (QUS), Age Bulk One or Never Estrogens (ABONE), body weight criterion (BWC), Fracture Risk Assessment Tool (FRAX), Garvan fracture risk calculator (GARVAN), Osteoporosis Risk Assessment Instrument (ORAI), Osteoporosis Index of Risk (OSIRIS), Osteoporosis Self-Assessment Tool for Asians (OSTA), and Simple Calculated Osteoporosis Risk Estimation (SCORE), among older men and women in Taiwan.Using the femoral neck dual-energy x-ray absorptiometry (DXA) T-score as an external criterion, the sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and the area under the receiver operating characteristic curve (AUC) for each tool were calculated. The ability of these tools to predict injurious falls was examined. A principal component analysis was applied to understand whether these tools were measuring the same underlying construct.The FRAX, BWC, ORAI, OSIRIS, OSTA, and SCORE had AUCs of ≥0.8 in men, while the GARVAN, OSIRIS, OSTA, and SCORE had AUCs of ≥0.8 in women. The sensitivity, negative predictive value, and likelihood ratio of the ABONE, BWC, ORAI, OSIRIS, OSTA, and SCORE tools in both men and women were 100%, ≥90%, and 0.0, respectively; the specificity and positive predictive value and likelihood ratio were far from satisfactory. The GARVAN displayed the best predictive ability of a fall in both men (AUCs, 0.653-0.686) and women (AUCs, 0.560-0.567), despite being smaller in women. The 9 screening tools and 2 central DXA measurements assessed 5 different factors, while the ABONE, BWC, ORAI, OSIRIS, OSTA, and SCORE measured the same one.Simple self-assessment tools can serve as initial screening instruments to rule out persons who have osteoporosis; however, these tools may measure a different construct other than fracture/osteoporosis risk.

Development and Validation of an Osteoporosis Self-Assessment Tool for Taiwan (OSTAi) Postmenopausal Women-A Sub-Study of the Taiwan OsteoPorosis Survey (TOPS)

Background

To develop an OSTAi tool and compare this with the National Osteoporosis Foundation recommendations in 2013 (NOF 2013) for bone mineral density (BMD) testing among Taiwan postmenopausal women.

Methods

Taiwan Osteoporosis Association (TOA) conducted a nationwide BMD survey by a bus installed with a dual energy X-ray absorptiometry (DXA) between 2008 and 2011. All of the participants completed questionnaire, which included demographics and risk factors of osteoporotic fracture in FRAX tool. We used the database to analyze potential risk factors for osteoporosis and followed the model by Koh et al. to develop a risk index via multiple variable regression analysis and item reduction. We used the index values to set up a simple algorithm (namely OSTAi) to identify those who need BMD measurement. Receiver operating characteristic (ROC) curve and the area under the curve (AUC) was used to compare the sensitivity/specificity analysis of this model with that of recommendations by NOF 2013.

Results

A total of 12,175 Taiwan postmenopausal women enrolled in this survey. The index value was derived by age and body weight of the participants according to weighted odds of each risk factor and the selected cutoff value was set at “-1”. There are 6393 (52.5%) participants whose index value is below “-1” and whose risk of osteoporosis was 57.5% (3674/6393). The AUC for OSTAi and NOF 2013 were 0.739 (95% confidence interval (CI), 0.728–0.749, P<0.001) and 0.618 (95% CI, 0.606–0.630, P<0.001), respectively. The sensitivity and specificity of OSTAi, at the selected cutoff value of -1, and NOF 2013 to identify osteoporosis were 73.1%, 62.0% and 78.3%, 45.7%, respectively.

Conclusions

As OSTA for Asian populations, OSTAi is an useful tool to identify Taiwan postmenopausal women with osteoporosis, In comparison with NOF 2013, OSTAi may be an easier and better tool for referral to BMD measurement by DXA in this area.

Clinical performance of seven prescreening tools for osteoporosis in Iranian postmenopausal women

This study was designed to evaluate seven prescreening osteoporosis models in postmenopausal Iranian women. This study was performed on 8644 postmenopausal women who have been referred for bone mineral densitometry (BMD) in BMD center of Shariati hospital in Tehran between 2001 and 2011. Diagnostic properties of seven prescreening instruments were evaluated. With regard to area under curve (AUC), these models have low accuracy (AUC ≤ 0.65). Considering only femoral neck or total femur area, these models had low accuracy but were more sensitive. Except for three models with sensitivities of ≤65 % in both osteoporosis and fracture threshold, other models were around 70 % sensitive. However, these models were not considered clinically useful regarding their positive predictive values (PPV) especially in BMDs ≤02.5. With regard to different measures of diagnostic property, none of these models were good screening tools for osteoporosis or fracture threshold. Although some of them are sensitive, considering other measures such as PPV indicates that they are not completely useful for clinical use. Attempts should be made for developing newer prescreening methods and calibration of the existing models with regard to the studied population.

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.

Development and validation of osteoporosis risk-assessment model for Korean postmenopausal women

Currently, dual-energy X-ray absorptiometry (DXA) is the gold standard for detecting osteoporosis, but is not recommended for general population screening. Therefore, this study aims to develop an osteoporosis risk-assessment model to identify high-risk individuals among Korean postmenopausal women. Data from 1,209 and 1,046 postmenopausal women who participated in the 2009 and 2010 Korean National Health and Nutrition Examination Survey, respectively, were used for development and validation of an osteoporosis risk-assessment model. Osteoporosis was defined as T score less than or equal to -2.5 at either the femoral neck or lumbar spine. Performance of the candidate models and the Osteoporosis Self assessment Tool for Asians (OSTA) were compared with respect to sensitivity, specificity, and area under the receiver operating characteristics curve (AUC). To compare the developed Korean Osteoporosis Risk-Assessment Model (KORAM) with OSTA, a net reclassification improvement was further calculated. In the development dataset, the prevalence of osteoporosis was 33.9 %. KORAM, consisting of age, weight, and hormone therapy, had a sensitivity of 91.2 %, a specificity of 50.6 %, and an AUC of 0.709 with a specific cut-off score of -9. Comparable results were shown in the validation dataset: sensitivity 84.8 %, specificity 51.6 %, and AUC 0.682. Additionally, risk categorization with KORAM showed improved reclassification over that of OSTA from 7.4 to 41.7 %. KORAM can be easily used as a pre-screening tool to identify candidates for DXA tests. Further studies investigating cost-effectiveness and replicability in other datasets are required to establish the clinical utility of KORAM.

Osteoporosis self-assessment tool performance in a large sample of postmenopausal women of mendoza, Argentina

The Osteoporosis Self-assessment Tool (OST) is a clinical instrument designed to select patients at risk of osteoporosis, who would benefit from a bone mineral density measurement. The OST only takes into account the age and weight of the subject. It was developed for Asian women and later validated for European and North American white women. The performance of the OST in a sample of 4343 women from Greater Mendoza, a large metropolitan area of Argentina, was assessed. Dual X-ray absorptiometry (DXA) scans of lumbar spine and hip were obtained. Patients were classified as either osteoporotic (N = 1830) or nonosteoporotic (n = 2513) according to their lowest T-score at any site. Osteoporotic patients had lower OST scores (P < 0.0001). A receiver operating characteristic (ROC) curve showed an area under the curve of 71% (P < 0.0001), with a sensitivity of 83.7% and a specificity of 44% for a cut-off value of 2. Positive predictive value was 52% and negative predictive value was 79%. The odds ratio for the diagnosis of osteoporosis was 4.06 (CI95 3.51 to 4.71; P < 0.0001). It is concluded that the OST is useful for selecting postmenopausal women for DXA testing in the studied population.

Evaluation of Clinical Decision Rules for Bone Mineral Density Testing among White Women

Background. Osteoporosis is a devastating, insidious disease that causes skeletal fragility. Half of women will suffer osteoporotic fractures during their lifetimes. Many fractures occur needlessly, because of inattentiveness to assessment, diagnosis, prevention, and treatment of osteoporosis. Study Purpose. Study Purpose. To evaluate the discriminatory performance of clinical decision rules to determine the need to undergo bone mineral density testing. Methods. A nationally representative sample from the Third National Health and Nutrition Examination Survey consisted of 14,060 subjects who completed surveys, physical examinations, laboratory tests, and bone mineral density exams. Multivariable linear regression tested the correlation of covariates that composed the clinical decision rules with bone mineral density. Results. Increased age and decreased weight were variables in the final regression models for each gender and race/ethnicity. Among the indices, the Osteoporosis Self-Assessment Tool, which is composed of age and weight, performed best for White women. Study Implications. These results have implications for the prevention, assessment, diagnosis, and treatment of osteoporosis. The Osteoporosis Self-Assessment Tool performed best and is inexpensive and the least time consuming to implement.

Development and validation of a tool for identifying women with low bone mineral density and low-impact fractures: the São Paulo Osteoporosis Risk Index (SAPORI)

The performance of the São Paulo Osteoporosis Risk Index (SAPORI) was tested in 1,915 women from the original cohort, São Paulo Osteoporosis Study (SAPOS) (N = 4332). This new tool was able to identify women with low bone density (spine and hip) and low-impact fracture, with an area under the receiving operator curve (ROC) of 0.831, 0.724, and 0.689, respectively.

INTRODUCTION

A number of studies have demonstrated the clinical relevance of risk factors for identifying individuals at risk of fracture (Fx) and osteoporosis (OP). The SAPOS is an epidemiological study for the assessment of risk factors for Fx and low bone density in women from the community of the metropolitan area of São Paulo, Brazil. The aim of the present study was to develop and validate a tool for identifying women at higher risk for OP and low-impact Fx.

METHODS

A total of 4,332 pre-, peri-, and postmenopausal women were analyzed through a questionnaire addressing risk factors for OP and Fx. All of them performed bone densitometry at the lumbar spine and proximal femur (DPX NT, GE-Lunar). Following the identification of the main risk factors for OP and Fx through multivariate and logistic regression, respectively, the SAPORI was designed and subsequently validated on a second cohort of 1,915 women from the metropolitan community of São Paulo. The performance of this tool was assessed through ROC analysis.

RESULTS

The main and significant risk factors associated with low bone density and low-impact Fx were low body weight, advanced age, Caucasian ethnicity, family history of hip Fx, current smoking, and chronic use of glucocorticosteroids. Hormonal replacement therapy and regular physical activity in the previous year played a protective role (p < 0.05). After the statistical adjustments, the SAPORI was able to identify women with low bone density (T-score ≤ -2 standard deviations) in the femur, with 91.4% sensitivity, 52% specificity, and an area under the ROC of 0.831 (p < 0.001). At the lumbar spine, the performance was similar (81.5% sensitivity, 50% specificity, and area under ROC of 0.724; p < 0.001). Regarding the identification of low-impact Fx, the sensitivity was 71%, the specificity was 52%, and the area under the ROC was 0.689 (p < 0.001).

CONCLUSION

The SAPORI is a simple, useful, fast, practice, and valid tool for identifying women at higher risk for low bone density and osteoporotic fractures.

Performance of risk indices for identifying low bone mineral density and osteoporosis in Mexican Mestizo women with rheumatoid arthritis

OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Selecting men for bone densitometry: performance of osteoporosis risk assessment tools in Portuguese men

SUMMARY

Clinicians need tools to identify patients most likely to benefit from bone mineral density (BMD) testing, for which cost-effectiveness does not allow generalized screening. This study supports the utility of osteoporosis risk assessment tools in selecting men for BMD testing. Different cutoff values may be appropriate for different countries and/or ethnic origins.

INTRODUCTION

Our aim was to evaluate the utility of three osteoporosis (OP) risk assessment tools in a large group of Portuguese men aged 50 or more and to determine the best cutoff value to be used for selecting men for bone densitometry.

METHODS

We assessed the performance of three simple tools in 202 randomly selected men: body weight criterion (BWC), osteoporosis self-assessment tool for Asians (OSTA), and a modified version of the OSTA equation (OST). Previously published cutoff values (validated in postmenopausal women) and three additional cutoff values were tested. Sensitivity (SE), specificity (SP), predictive values, and area under the receiver operating characteristic (AUROC) curve for correctly selecting men with OP (defined by BMD testing) were determined.

RESULTS

Mean age of the cohort was 63.8 years. According to the World Health Organization diagnostic categories, 16.8% had osteoporosis. The best performing cutoffs for correctly selecting men with OP for BMD testing were OST < 3 (SE = 75.5%, SP = 50.0%, AUROC = 0.632), OSTA < 3 (SE = 73.5%, SP = 58.3%, AUROC = 0.659), and BWC < 75 kg (SE = 73.5%, SP = 61.3%, AUROC = 0.674).

CONCLUSIONS

OP risk assessment tools seem to be useful in men aged 50 or more. Best cutoff values are different from those recommended for postmenopausal women. Different cutoff values may be appropriate for different countries and/or ethnic origins.

Review of osteoporosis pharmacotherapy for geriatric patients

BACKGROUND

Fractures are a significant problem in geriatric patients, and understanding the evidence for benefit and possible harm of osteoporosis treatments is critical to appropriate management of this patient population.

OBJECTIVE

The purpose of this article was to review the evidence and treatment considerations related to use of the approved osteoporosis treatments in the United States across the continuum of ages in the geriatric population.

METHODS

MEDLINE and the Web of Science were searched to find English-language articles published from 2000 through July 2009. Search terms included: practice guideline, osteoporosis, calcium, vitamin D, pharmacoeconomics, ethnicity, and treatment. The generic names of each of the osteoporosis treatments approved in the United States were searched to find relevant clinical trials and randomized controlled trials (RCTs). Pivotal trials that included fracture data or focused specifically on elderly patients (> or = 60 years of age) were selected. Bibliographies in the identified articles were searched for additional articles, and the prescribing information for each of the approved treatments was reviewed.

RESULTS

Many osteoporosis studies have a mean patient age >60 years, but data for older patients are limited. Subanalyses of older patient groups have found risedronate to be beneficial for vertebral fractures in patients aged 70 to 79 years (absolute risk reduction [ARR], 8.4%; P < 0.001) and teriparatide to be beneficial for both vertebral (ARR, 6.4%; P < 0.05) and new nonvertebral fragility fractures (ARR, 9.9%; P < 0.05) in women aged > or = 75 years. However, no RCTs of geriatric patients who were either nonambulatory or had multiple comorbidities were identified in the literature.

CONCLUSIONS

Evidence indicates that the osteoporosis treatments currently available in the United States are beneficial for treating osteoporosis in geriatric patients. However, data are limited for the oldest patients (> or = 80 years) and those with significant comorbidities. Because of the limited availability of data for geriatric patients with significant comorbidities, the properties of the various agents, including efficacy, tolerability, and potential contraindications, should be considered carefully for each geriatric patient.

Using risk factors and quantitative ultrasound to identify postmenopausal caucasian women at risk of osteoporosis

There is a need to prescreen large numbers of individuals for osteoporosis due to current demands on clinical resources. Some previous attempts to predict individuals at risk have used simple indices based on patient information, or Quantitative Ultrasound (QUS) and have shown good sensitivity but also demonstrated low specificity, which means that many individuals with good bone mineral density were also selected. The aim of this study was to determine if a tool based on a combination of risk factors and QUS measurements could also be made to provide improved specificity. A risk factors measurement questionnaire was created and completed for a sample of Caucasian postmenopausal women (n=235) who had undergone Dual-energy X-ray absorptiometry scanning. QUS measurements were also taken at various skeletal sites. Assessment tools were generated using stepwise regression to predict osteoporosis, evaluated by receiver operating characteristic curves, and assessed using area under the curve values. Specificity values were determined at a sensitivity of 0.90 to establish the comparative utility of each assessment tool. Using only a risk factors model the specificities were 0.28 at the lumbar spine, 0.45 for the femoral neck and 0.68 for the total hip. In a risk factors+QUS data model the specificities measured were 0.44 for the lumbar spine, 0.78 for the femoral neck, and 0.84 for the total hip. These novel assessment tools can identify those with low bone mineral density at a number of skeletal sites and help towards avoiding many unnecessary investigations in the future.

The utility of clinical decision tools for diagnosing osteoporosis in postmenopausal women with rheumatoid arthritis

Background

Patients with rheumatoid arthritis have a higher risk of low bone mineral density than normal age matched populations. There is limited evidence to support cost effectiveness of population screening in rheumatoid arthritis and case finding strategies have been proposed as a means to increase cost effectiveness of diagnostic screening for osteoporosis. This study aimed to assess the performance attributes of generic and rheumatoid arthritis specific clinical decision tools for diagnosing osteoporosis in a postmenopausal population with rheumatoid arthritis who attend ambulatory specialist rheumatology clinics.

Methods

A cross-sectional study of 127 ambulatory post-menopausal women with rheumatoid arthritis was performed. Patients currently receiving or who had previously received bone active therapy were excluded. Eligible women underwent clinical assessment and dual-energy-xray absorptiometry (DXA) bone mineral density assessment.

Clinical decision tools, including those specific for rheumatoid arthritis, were compared to seven generic post-menopausal tools to predict osteoporosis (defined as T score < -2.5). Sensitivity, specificity, positive predictive and negative predictive values and area under the curve were assessed. The diagnostic attributes of the clinical decision tools were compared by examination of the area under the receiver-operator-curve.

Results

One hundred and twenty seven women participated. The median age was 62 (IQR 56–71) years. Median disease duration was 108 (60–168) months. Seventy two (57%) women had no record of a previous DXA examination. Eighty (63%) women had T scores at femoral neck or lumbar spine less than -1. The area under the ROC curve for clinical decision tool prediction of T score <-2.5 varied between 0.63 and 0.76. The rheumatoid arthritis specific decision tools did not perform better than generic tools, however, the National Osteoporosis Foundation score could potentially reduce the number of unnecessary DXA tests by approximately 45% in this population.

Conclusion

There was limited utility of clinical decision tools for predicting osteoporosis in this patient population. Fracture prediction tools that include risk factors independent of BMD are needed.

Use of decision rules for osteoporosis prevention and treatment: Implications for nurse practitioners

PURPOSE

To describe the current literature regarding the benefits of bone mineral density (BMD) screening and to discuss clinical decision rules for BMD screening.

DATA SOURCES

Extensive review of the scientific literature regarding osteoporosis, BMD screening, and current clinical decision rules.

CONCLUSIONS

Osteoporosis is a disease characterized by deterioration of bone and increased susceptibility to fractures, crippling, and disfigurement. BMD testing is the best predictor for osteoporosis and associated fractures; however, routine global BMD testing is cost-prohibitive. A need exists for a selective and practical clinical decision rule for referral for testing.

IMPLICATIONS FOR PRACTICE

Several effective clinical decision rules are presented, and their uses and applications are described. The osteoporosis self-assessment tool is recommended by the authors because of its predictive power and ease of use.

Framework for evaluating disease severity measures in older adults with comorbidity

BACKGROUND

Accounting for the influence of concurrent conditions on health and functional status for both research and clinical decision-making purposes is especially important in older adults. Although approaches to classifying severity of individual diseases and conditions have been developed, the utility of these classification systems has not been evaluated in the presence of multiple conditions.

METHODS

We present a framework for evaluating severity classification systems for common chronic diseases. The framework evaluates the: (a) goal or purpose of the classification system; (b) physiological and/or functional criteria for severity graduation; and (c) potential reliability and validity of the system balanced against burden and costs associated with classification.

RESULTS

Approaches to severity classification of individual diseases were not originally conceived for the study of comorbidity. Therefore, they vary greatly in terms of objectives, physiological systems covered, level of severity characterization, reliability and validity, and costs and burdens. Using different severity classification systems to account for differing levels of disease severity in a patient with multiple diseases, or, assessing global disease burden may be challenging.

CONCLUSIONS

Most approaches to severity classification are not adequate to address comorbidity. Nevertheless, thoughtful use of some existing approaches and refinement of others may advance the study of comorbidity and diagnostic and therapeutic approaches to patients with multimorbidity.

Prediction of absolute risk of non-spinal fractures using clinical risk factors and heel quantitative ultrasound

The relationship between osteoporosis risk factors, bone quantitative ultrasound (QUS) and non-spinal fracture risk was estimated in a cohort of 5,201 postmenopausal women from Spain who were prospectively evaluated during three years. Several clinical risk factors and low heel QUS values were independently associated with non-spinal fracture risk.

INTRODUCTION

Low-trauma, non-spinal fractures are a growing source of morbidity and mortality in the elderly. The aim of the present study was to examine the association of heel quantitative ultrasound (QUS) and a series of osteoporosis and fracture risk factors, with incident low energy non-spinal fractures in a population of elderly women, and to incorporate them into fracture prediction models.

METHODS

5,201 women aged 65 or older were enrolled in a three-year cohort study. Participants completed an osteoporosis and fracture risk factors questionnaire. QUS was measured at the heel with a gel-coupled device. Cox-proportional hazard analyses were performed to evaluate the association with the first incident low-trauma non-spinal fracture.

RESULTS

Three hundred and eleven women (6.0%) sustained a total of 363 low-trauma fractures, including 133 forearm/wrist, 54 hip, 50 humerus, 37 leg and 17 pelvic fractures. For every standard deviation decrease in the quantitative ultrasound index, the adjusted hazard ratios (95% CI) for any non-vertebral, hip, forearm/wrist, and humerus fractures were 1.31 (1.15-1.49), 1.40 (1.01-1.95), 1.50 (1.19-1.89) and 1.35 (0.97-1.87), respectively. Similar results were observed with other QUS variables. The best predictive models indicated that age, a history of falls, a previous low-trauma fracture, a family history of fracture, a calcium intake from dairy products of less than 250 mg/day, and lower values of QUS parameters were independently associated with the risk of non-spinal fractures.

CONCLUSIONS

Both clinical risk factors and QUS are independent predictors of risk of fragility non-spinal fractures. A prediction algorithm using these variables was developed to estimate the absolute risk of non-spinal fractures in elderly women in Spain.

[Proportion of individuals with indication criteria for bone densitometry and frequency of factors of risk of low osseous mass in primary care consultations]

OBJECTIVE

To find the number of individuals with indication for Bone Densitometry in Primary Care, according to the criteria of the WHO, the Agency for Evaluating Medical Technology of Catalonia (AETM) and the International Committee on Clinical Guides to Osteoporosis (CIGCO), and the frequency of factors of risk of low osseous mass.

DESIGN

Multi-centre, prospective, transversal study.

SETTING

Primary care consultations.

PARTICIPANTS

Patients over 18 (307 women and 139 men) with mean age of 54.3+/-16.8, who attended for consultation with an appointment.

MAIN MEASUREMENTS

Presence or absence of factors relating to each of the indication criteria for bone densitometry.

RESULTS

A 36.3% of individuals had indication of densitometry under the AETM criteria, 76.7% with the WHO criteria, and 50.5% with the CIGCO criteria (applicable only to women). Percentages increased with age and were higher for women. Concordance between the various criteria was under 37%.

CONCLUSIONS

The percentage of individuals with indication for bone densitometry was highly variable under different criteria. It was greater in women and increased with age. Concordance between different criteria was low.

Prescreening tools to determine who needs DXA

Clinical decision rules (CDRs) are designed to help physicians practice better. A number of CDRs to assist in identifying women with low bone mass have been developed since the mid 1990s, including SCORE, OST (OSTA), OSIRIS, SOFSURF, NOF, ABONE, pBW, ORAI, and weight-only-EPIDOS (which we have termed WO-E). This review discusses these CDRs in terms of development and validation cohorts and their sensitivity and specificity. The sensitivities of the available CDRs exceed 80% and specificities are about 50%. After much analysis, it appears that most experts prefer OST for its simplicity and SCORE for its flexibility, but there is no consensus on what risk factors to use in the CDRs and what regions of interest (spine, total hip, femoral neck, or a combination) to test with dual-energy x-ray absorptiometry (DXA). Because of the lack of consensus, there are barriers to the clinical application of these CDRs. Agreement on a single CDR for worldwide use is required to optimally fulfill the objective of identifying low bone mass.

Osteoporosis diagnosis and screening

Osteoporosis and osteoporotic fracture are major causes of morbidity and mortality in the United States and worldwide. Nearly half of all women and one quarter of men >50 years of age will experience an osteoporosis-related fracture during their lifetime. The diagnosis of osteoporosis in postmenopausal women and older men can be made definitively by comparing bone mineral density (BMD) measurements from dual-energy x-ray absorptiometry (DXA) to mean peak bone mass in young adults. Efforts to increase access to DXA and improve the sensitivity and specificity of osteoporosis risk assessment instruments may help ensure that individuals with osteoporosis are diagnosed early. The early identification of individuals with low BMD and/or clinical risk factors, accurate diagnosis of osteoporosis and osteopenia, and initiation of appropriate treatment are crucial to reducing the incidence of vertebral and nonvertebral fractures. The World Health Organization is moving toward absolute risk assessment and this may help to better identify patients for screening and treatment in the future.

Racial disparity in treatment of osteoporosis after diagnosis

INTRODUCTION

Racial disparities have been identified in a number of areas in clinical medicine. Patients diagnosed with osteoporosis should be treated similarly regardless of race. However, limited data are available on the relative frequency of treatment by race after diagnosis of osteoporosis.

METHODS

We analyzed all 739 dual-energy X-ray absorptiometry (DXA) results obtained of women 50 years old and older between 1998 and 2002 at our medical center. Our study sample was 82% Caucasian and 15% African American. Of 353 women who had low bone mineral density on first DXA, we abstracted the electronic and paper medical records to compare treatment rates by race.

RESULTS

Of the women diagnosed with osteoporosis or osteopenia, 80.0% and 68.3%, respectively, were started on antiresorptive medications. Of the African American women, 61.9% diagnosed with osteoporosis were started on antiresorptive treatment compared with 83.3% of Caucasian women (p<0.05). African American women with low bone mass were less likely than Caucasian women to be smokers (p<0.05) and use alcohol (p<0.01) but were more likely to be on corticosteroids (p<0.05). No other significant differences were found among treated and nontreated groups that might explain the disparity in treatment.

CONCLUSION

A smaller proportion of African American than Caucasian women with osteoporosis received antiresorptive medications after a DXA diagnosis. This significant disparity requires further study in a larger population.

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

INTRODUCTION

This study aimed to compare the sensitivity and specificity of various published indices for identifying elderly Chinese females at risk of osteoporosis in Singapore.

METHODS

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.

RESULTS

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.

CONCLUSION

The study showed that OSTA is an effective index for identifying postmenopausal women at risk for osteoporosis.

Utility of screening tools for the prediction of low bone mass in African American men

INTRODUCTION

Osteoporosis remains under-diagnosed, particularly in African American men, despite the availability of reliable diagnostic tests. In women, several screening tools, including heel ultrasound and clinical assessment tools, reliably predict low bone mass, however the usefulness of these screening tools in African American men is unknown. The aim of this study was to determine the utility of screening tools, namely heel ultrasound, the osteoporosis self-assessment tool (OST), weight-based criterion (WBC) and body mass index (BMI), in screening for low bone mass in African American men.

MATERIALS AND METHODS

African American men 35 years of age and older were invited to participate. The OST risk index is a score based on age and weight [(weight in kilograms--age in years)x0.2]. Bone mineral density (BMD) of the heel was measured by heel ultrasound, and BMD of both the lumbar spine and hip were determined by dual energy X-ray absorptometry (DXA). One hundred and twenty-eight men fulfilled the inclusion criteria for our study.

RESULTS

The population prevalence of osteopenia and osteoporosis were 39% and 7%, respectively. Using a heel ultrasound T-score cut-off value of -1 or less, we predicted low bone mass (T-score of -2 or less at the hip) with a sensitivity of 83%, a specificity of 71% and an area under the curve (AUC) of 0.80. Using an OST cut-off value of 4, we predicted low bone mass with a sensitivity of 83%, a specificity of 57% and an AUC of 0.83. The OST risk index ranged from 18.1 to -6.1, based on which we categorized risk as: low, 5 or greater; moderate, 0-4; high, -1 or less. Of the men with a high-risk OST score, 87% had either osteopenia or osteoporosis based on World Health Organization (WHO) criteria. Using the WBC alone with a cut-off value of 85 kg, we predicted low bone mass with a sensitivity of 74%, a specificity of 50% and an AUC of 0.70. A BMI cut-off value of 30 or greater yielded a sensitivity of 83%, a specificity of 43% and an AUC of 0.70 for the diagnosis of low bone mass.

DISCUSSION

The prevalence of osteopenia and osteoporosis were unexpectedly high in outpatient African American male veterans, who are considered to be at low risk for low bone mass. Heel ultrasound was able to predict low bone mass with sufficiently high sensitivity and specificity for use as a screening tool. Surprisingly, WBC and BMI proved ineffective in predicting low bone mass with adequate sensitivity and specificity. The OST, a clinical formula based on weight and age, appeared to be an easy and reliable screening tool for identifying men at high risk for low bone mass.

Identification of women at increased risk of osteoporosis: no need to use different screening tools at different ages

OBJECTIVES

To assess and compare various approaches for selecting women for a bone mineral density (BMD) examination in three different age groups: (1) the most commonly recommended strategy, i.e., selection based on the presence of at least one major risk factor for osteoporosis (personal history of fracture, maternal history of hip fracture, low weight, early menopause), (2) by weight, and (3) calculation of an individual risk score based on the predictive equation (logistic regression model) including the factors most predictive of osteoporosis in each age group.

METHODS

Data from three population-based samples of postmenopausal women of different ages 60-70 years (n=399), 70-80 years (n=392), and 80 years or older (n=3628). Within each age group, the value of these different approaches was primarily assessed in terms of their discriminant value (sensitivity and positive predictive value (PPV)) for osteoporosis. Other women besides osteoporotic women might also be considered at high risk of fracture (and hence treated), in particular osteopenic women (T-score<-1.5) with multiple risk factors for fracture. Hence, we also estimated and compared the overall number of selected women who might be considered at high risk of fracture after BMD testing, according to selection criteria.

RESULTS

In each age group and classifying a similar percentage of women at high risk, use of weight as a tool for identifying osteoporotic women has a higher sensitivity and PPV than the currently recommended approach. Increasing the cutoff for weight increases sensitivity. However, identifying the majority (around 80%) of all osteoporotic women requires testing more than half the population. Combining weight with other factors into more complex risk scores usually does not significantly improve the discriminant value of the assessment. When similar percentages of women are selected, more women with osteopenia and multiple risk factors are identified when selection is based on usual referral criteria. However, since more osteoporotic women are identified after selection by weight (higher PPV for osteoporosis), the overall number of women who might be considered at high risk of fracture after BMD testing is higher after selection by weight.

CONCLUSIONS

In each age group considered, selecting women for BMD testing based on weight is the simplest and most effective screening method for identifying osteoporotic women as well as other subgroups of women who might also be considered to be at high risk of fracture.

Performance of osteoporosis risk assessment tools in postmenopausal women aged 45-64 years

Osteoporosis risk factor assessment is of uncertain utility in women under 65 years of age. Previous comparative studies of osteoporosis risk assessment tools were not stratified by age. We compared the discriminatory ability of three previously validated osteoporosis risk assessment tools in a referral population of postmenopausal women aged 45-64 years (n=2539) and aged 65-96 years (n=1496) seen at a university-based outpatient osteoporosis center in Belgium. Risk scores for the Osteoporosis Self-assessment Tool, Osteoporosis Risk Assessment Instrument, and Simple Calculated Osteoporosis Risk Estimation were calculated for each patient. The reference standard was osteoporosis at the femoral neck, defined as a T-score < or =-2.5 based on bone mineral density measured by dual energy X-ray absorptiometry. Osteoporosis was present in 139 of 2539 (5.5%) women aged 45-64 years and 241 of 1496 (16.1%) women aged 65 years or older. The tools had similar overall discriminatory ability to identify women with osteoporosis [area under the ROC curve 0.750-0.768, P=0.23 for women aged 45-64 years; area under the ROC curve 0.745-0.762, P=0.06 for women aged 65 years or older (P>0.05 indicates no difference among tools)]. The likelihood ratios for the high-risk score categories ranged from 3.60 to 6.73 for the younger women and 3.45 to 6.99 for the older women when different score thresholds were set to maximize the performance of each tool in each age group. We conclude that the diagnostic accuracy of three osteoporosis risk assessment tools was similar in postmenopausal women aged 45-64 years and women aged 65 years or older. Use of structured risk assessment tools to identify women at high risk of osteoporosis in the early postmenopausal period warrants further study. Of the three tools evaluated, the OST is the simplest and has the best potential for use in clinical practice.

Artificial neural networks in prediction of bone density among post-menopausal women

Artificial neural networks (ANN) are promising tools in learning complex interplay of factors on a particular outcome. We performed this study to compare the predictive power of ANN and conventional methods in prediction of bone mineral density (BMD) in Iranian post-menopausal women. A database of 10 input variables from 2158 participants was randomly divided into training (1400), validation (150) and test (608) groups. Multivariate linear regression and ANN models were developed and validated on the training, and validation sets and outcomes (femoral neck and lumbar T-scores) were predicted and compared on the test group using different numbers of input variables. Results were evaluated by comparing the mean square of differences between predicted and reference values (non-central chi-square test) and by measuring area under the receiver operating characteristic curve (AUROC) around cut-off value of -2.5 for T-scores. For models with less than 3 input variables in femoral neck and 4 variables in spinal column, performance of regression and ANN models was almost the same. As more variables imported into models, ANN outperformed linear regression models. AUROC varied in 2 to 10 variable models as follows: for ANN in spine, from 0.709 to 0.774; linear models in spine, from 0.709 to 0.744; ANN in femoral neck, from 0.801 to 0.867; linear models in femoral neck, from 0.799 to 0.834. The ANN model performed better than five established patient selection tools in the test group. Superior performance of neural networks than linear models demonstrate their advantage especially in mass screening applications, when even a slight enhancement in performance results in significant decrease in number of misclassifications.

Validation of dental panoramic radiography measures for identifying postmenopausal women with spinal osteoporosis

OBJECTIVE

Measurements of mandibular inferior cortical shape and width detected on dental panoramic radiographs may be a useful screening tool for spinal osteoporosis in postmenopausal women. The purposes of this study were to clarify whether these measures are validated compared with simple screening tools based on questionnaires, such as the osteoporosis self-assessment tool (OST) and whether these measures can be used in postmenopausal women with histories of hysterectomy, oophorectomy, or estrogen use.

SUBJECTS AND METHODS

We calculated the diagnostic performances of panoramic measurements and the OST for identifying women with spinal osteoporosis in both 159 healthy postmenopausal and 157 postmenopausal women with histories of hysterectomy, oophorectomy, or estrogen use. Spinal osteoporosis was defined as a bone mineral density T score of -2.5 or less at the lumbar spine. Cortical shape and width were evaluated on dental panoramic radiographs. Receiver operating characteristic curve analyses were used to determine the optimal cutoff thresholds for cortical width and the OST in healthy postmenopausal women.

RESULTS

The sensitivity and specificity, respectively, for identifying women with spinal osteoporosis were 89.5% and 33.9% for cortical width, 86.8% and 57.8% for the OST, and 86.8% and 63.6% for cortical shape in healthy postmenopausal women. Sensitivity and specificity, respectively, were 92.5% and 35.0% for cortical width, 72.5% and 58.1% for the OST, and 80.0% and 64.1% for cortical shape in postmenopausal women with histories of hysterectomy, oophorectomy, or estrogen use.

CONCLUSION

Dentists may be able to refer postmenopausal women with suspected spinal osteoporosis for bone densitometry on the basis of dental panoramic radiographs with diagnostic performance similar to that of osteoporosis screening tools based on questionnaires.

Postmenopausal osteoporosis and alendronate

Osteoporosis is a systemic metabolic disorder associated with a decreased bone mass and resistance. Bisphosphonates suppress bone resorption and bone turnover by a mechanism that depends on their structure. They are characterized by low gastrointestinal absorption. In postmenopausal women, alendronate (ALN) reduces bone resorption markers and increases bone mineral density (BMD) in the lumbar spine, femoral neck, and total body. Individuals receiving ALN have been studied for up to 10 years with an apparent linear increase in BMD over that time period estimated at 13.7% at the lumbar spine. Treatment with ALN reduced the risk of both vertebral and non-vertebral fractures, including hip fractures, in postmenopausal women with osteoporosis. Direct comparisons of the results obtained with different antiresortive agents is difficult, because the designs of the respective studies, populations and other factors. However, the meta-analysis of available publications seems to indicate that ALN reduces the relative risk of vertebral fractures in a greater proportion than any other agent. Furthermore, ALN prevents the reduction in BMD after hormone replacement therapy discontinuation.

Clinical risk factor evaluation to defer postmenopausal women from bone mineral density measurement: an Italian study

To identify clinical risk factors (CRFs) best related to low bone mineral density (BMD) and to assess their abilityin deferring women from dual-energy X-ray absorptiometry (DXA), 1187 Italian postmenopausal women, dividedinto development (709) and validation (478) groups, were studied. CRFs were investigated by questionnaire. DXAwas performed at the spine and femoral neck. A T-score < -2.5 at both measurement sites classified those with lowBMD. In the development group, using the logistic regression, the CRFs best predicting low BMD were years sincemenopause, age at menarche, weight, previous fracture, and muscle weakness. The predicted probability of low BMD(PPL-BMD), calculated by the logistic equation, was used to build receiver-operating characteristic (ROC) curves(area = 0.786, standard error [SE] = 0.017) on diagnosed BMD status. The PPL-BMD cutoff below which to deferwomen from DXA was set corresponding to the ROC curve sensitivity of 99%, 98%, and 97%. The coefficients ofthe logistic regression were then used to calculate the PPL-BMD of the validation group. In the validation group, theoverall ability of CRFs to predict low BMD (ROC area = 0.744, SE = 0.023) was not different from that of the developmentgroup. At the PPL-BMD cutoff of 0.132, the percentage of DXA-deferred cases (14.5% vs 19.0%) and low-BMD-missed cases (0.7% vs 1.7%) was similar in both groups. The rates of DXA-deferred women by CRFs arereproducible and this tool should be useful in clinical practice.

Lebanese guidelines for osteoporosis assessment and treatment: who to test? What measures to use? When to treat?

With the demographic explosion of the population worldwide, the human, social, and economic costs of osteoporosis will continue to rise. It is estimated that the magnitude of the problem might be even larger in developing countries, including those in the Middle East. Although several organizations and countries have developed or adapted guidelines to their local needs, as of today there are no guidelines for osteoporosis assessment in the Middle East. In April 2002, a panel of osteoporosis experts met and discussed practice guidelines for osteoporosis assessment and treatment in Lebanon. The process, which involved an overview of international guidelines as well as local data on osteoporosis, resulted in a draft for Lebanese guidelines that addressed three main questions: "Who to test?" "What measures to use?" and "When to treat?". Representatives from five major Lebanese societies (Endocrinology, Rheumatology, Orthopedics, Obstetrics and Gynecology, and Radiology) subsequently reviewed, discussed, and officially endorsed the guidelines after revisions. The Lebanese guidelines were also endorsed by the Eastern Mediterranean branch of the World Health Organization.