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

Fracture risk prediction in postmenopausal women from GO Study: the comparison between FRAX, Garvan, and POL-RISK algorithms

In the longitudinal, retrospective study, the ability of the FRAX, Garvan, and POL-RISK algorithms to predict osteoporotic fractures was compared in a group of 457 women. Using the rigid threshold of 10% showed a significant discrepancy in sensitivity and specificity of all tools. New thresholds for high risk of fractures were established for each calculator separately: 6.3% for FRAX major fracture, 20.0% for Garvan any fracture, and 18.0% for POL-RISK any fracture. Such thresholds allow for improving the diagnostic accuracy of all three calculators.

INTRODUCTION

The aim of the longitudinal, retrospective study was to compare three tools designed to assess fracture risk: FRAX, Garvan, and POL-RISK in their prediction of fracture incidence.

MATERIAL

The study group consisted of 457 postmenopausal women with a mean age of 64.21 ± 5.94 years from the Gliwice Osteoporosis (GO) Study. Comprehensive data on clinical factors related to fractures were collected for all participants. Bone densitometry was performed at the proximal femur using the Prodigy device (GE, USA). Fracture risk was established using the FRAX, Garvan, and POL-RISK algorithms. Data on the incidence of osteoporotic fractures were collected over the last 10 years.

RESULTS

During the period of observation 72, osteoporotic fractures occurred in 63 subjects. For a preliminary comparison of the predictive value of analyzed diagnostic tools, the fracture risk threshold of 10% was used. For FRAX, the fracture probability exceeding 10% was observed only in 11 subjects who experienced fractures; thus, the fracture was properly predicted only in 22.9% of women. For Garvan, the respective value was 90.5%, and for POL-RISK, it was 98.4%. That gave a very low true positive value for FRAX and a very high false positive value for Garvan and POL-RISK. Based on ROC curves, new thresholds for high risk of fractures were established for each calculator separately: 6.3% for FRAX major fracture, 20.0% for Garvan any fracture, and 18.0% for POL-RISK any fracture. Such thresholds improve the diagnostic accuracy of all compared fracture prediction tools.

CONCLUSION

The current study showed that different fracture risk assessment tools, although having similar clinical purposes, require different cut-off thresholds for making therapeutic decisions. Better identification of patients requiring therapy based on such an approach may help reduce the number of new fractures.

Decomposing and simplifying the Fracture Risk Assessment Tool-a module from the Taiwan-specific calculator

The Fracture Risk Assessment Tool (FRAX®) is a widely utilized country-specific calculator for identifying individuals with high fracture risk; its score is calculated from 12 variables, but its formulation is not publicly disclosed. We aimed to decompose and simplify the FRAX® by utilizing a nationwide community survey database as a reference module for creating a local assessment tool for osteoporotic fracture community screening in any country. Participants (n = 16384; predominantly women (75%); mean age = 64.8 years) were enrolled from the Taiwan OsteoPorosis Survey, a nationwide cross-sectional community survey collected from 2008 to 2011. We identified 11 clinical risk factors from the health questionnaires. BMD was assessed via dual-energy X-ray absorptiometry in a mobile DXA vehicle, and 10-year fracture risk scores, including major osteoporotic fracture (MOF) and hip fracture (HF) risk scores, were calculated using the FRAX®. The mean femoral neck BMD was 0.7 ± 0.1 g/cm2, the T-score was -1.9 ± 1.2, the MOF was 8.9 ± 7.1%, and the HF was 3.2 ± 4.7%. Following FRAX® decomposition with multiple linear regression, the adjusted R2 values were 0.9206 for MOF and 0.9376 for HF when BMD was included and 0.9538 for MOF and 0.9554 for HF when BMD was excluded. The FRAX® demonstrated better prediction for women and younger individuals than for men and elderly individuals after sex and age stratification analysis. Excluding femoral neck BMD, age, sex, and previous fractures emerged as 3 primary clinical risk factors for simplified FRAX® according to the decision tree analysis in this study population. The adjusted R2 values for the simplified country-specific FRAX® incorporating 3 premier clinical risk factors were 0.8210 for MOF and 0.8528 for HF. After decomposition, the newly simplified module provides a straightforward formulation for estimating 10-year fracture risk, even without femoral neck BMD, making it suitable for community or clinical osteoporotic fracture risk screening.

Age-dependent FRAX-based assessment and intervention thresholds for therapeutic decision making in osteoporosis in the Malaysian population

Fracture risk stratification is crucial in countries with limited access to bone density measurement. 24.8% women were in the high-risk category while 30.4% were in the low-risk category. In the intermediate risk group, after recalculation of fracture risk with bone density, 38.3% required treatment. In more than half, treatment decisions can be made without bone density.

PURPOSE

We aimed to examine the role of age-dependent intervention thresholds (ITs) applied to the Fracture Risk Assessment (FRAX) tool in therapeutic decision making for osteoporosis in the Malaysian population.

METHODS

Data were collated from 1380 treatment-naïve postmenopausal women aged 40-85 years who underwent bone mineral density (BMD) measurements for clinical reasons. Age-dependent ITs, for both major osteoporotic fracture (MOF) and hip fracture (HF), were calculated considering a woman with a BMI of 25 kg/m2, aged between 40 and 85years, with a prior fragility fracture, sans other clinical risk factors. Those with fracture probabilities equal to or above upper assessment thresholds (UATs) were considered to have high fracture risk. Those below the lower assessment thresholds (LATs) were considered to have low fracture risk.

RESULTS

The ITs of MOF and HF ranged from 0.7 to 18% and 0.2 to 8%, between 40 and 85years. The LATs of MOF ranged from 0.3 to 11%, while those of HF ranged from 0.1 to 5.2%. The UATs of MOF and HF were 0.8 to 21.6% and 0.2 to 9.6%, respectively. In this study, 24.8% women were in the high-risk category while 30.4% were in the low-risk category. Of the 44.8% (n=618) in the intermediate risk group, after recalculation of fracture risk with BMD input, 38.3% (237/618) were above the ITs while the rest (n=381, 61.7%) were below the ITs. Judged by the Youden Index, 11.5% MOF probability which was associated with a sensitivity of 0.62 and specificity of 0.83 and 4.0% HF probability associated with a sensitivity of 0.63 and a specificity 0.82 were found to be the most appropriate fixed ITs in this analysis.

CONCLUSION

Less than half of the study population (44.8%) required BMD for osteoporosis management when age-specific assessment thresholds were applied. Therefore, in more than half, therapeutic decisions can be made without BMD based on these assessment thresholds.

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.

Development of a diverse osteoporosis screening tool for older US adults from the health and retirement study

Existing osteoporosis screening tools have limitations, including using race as a predictor, and development on homogeneous samples. This biases risk assessment of osteoporosis in diverse populations and increases health inequities. We develop a tool that relies on variables easily learned during point-of-care, known by individuals, and with negligible racial bias. Data from the 2012-2016 waves of the population-based cohort Health and Retirement Study (HRS) were used to build a predictive model of osteoporosis diagnosis on a 75 % training sample of adults ages 50-90. The model was validated on a 25 % holdout sample and a cross-sectional sample of American individuals ages 50-80 from the National Health and Nutrition Examination Survey (NHANES). Sensitivity and specificity were compared across sex and race/ethnicity. The model has high sensitivity in the HRS holdout sample (89.9 %), which holds for those identifying as female and across racial/ethnic groups. Specificity is 57.9 %, and area under the curve (AUC) is approximately 0.81. Validation in the NHANES sample using empirically measured osteoporosis produced relatively good values of sensitivity, specificity, and consistency across groups. The model was used to create a publicly-available, open-source tool called the Osteoporosis Health Equality (& Equity) Evaluation (OsteoHEE). The model provided high sensitivity for osteoporosis diagnosis, with consistently high results for those identifying as female, and across racial/ethnic groups. Use of this tool is expected to improve equity in screening and increase access to bone density scans for those at risk of osteoporosis. Validation on alternative samples is encouraged.

Optimal fracture prediction thresholds for therapy onset, established from FRAX and Garvan algorithms: a longitudinal observation of the population representative female cohort from the RAC-OST-POL Study

The study shows that the use of unified cutoff thresholds to identify high fracture risks by two popular calculators-FRAX and Garvan-leads to a significant discrepancy between the prediction of fractures and their actual prevalence over the period of 10 years. On the basis of the ROC analyses, a proposal of differentiated thresholds is presented. They were established at 6% for FRAX major fracture risk, 1.4% for FRAX hip fracture risk, 14.4% for Garvan any fracture risk, and 8.8% for Garvan hip fracture risk.

PURPOSE/INTRODUCTION

The aim of the study was to verify how much were the tools, designed to predict fracture risks, precise vs. the actual fracture incidence values over a prospective observation.

METHODS

The study group consisted of a population-based postmenopausal sample from the RAC-OST-POL Study. At baseline, there were 978 subjects at the mean age of 66.4 ± 7.8 years and, after a 10-year follow-up, 640 women remained at the mean age of 75.0 ± 6.95 years. At baseline, the fracture risk was established by the FRAX and Garvan tools.

RESULTS

During the observation period, 190 osteoporotic fractures were identified in 129 subjects. When high-risk fracture cutoff thresholds (of 10% for major/any and 3% for hip fractures) were employed, only 19.59% of major fractures and 50% of hip fractures were identified in the high-risk group. For the Garvan tool, the percentage of correctly predicted fractures for any and hip fractures was 86.05% and 71.43%, respectively. Nevertheless, the fracture prediction by the Garvan tool was associated with the qualification of numerous subjects to the high-risk group, who subsequently did not experience a fracture in the 10-year follow-up period (false-positive prediction). Based on the ROC analyses, new high-risk thresholds were proposed individually for each calculator, improving the sensitivity, specificity, and diagnostic accuracy of these tools. They were established at 6% for FRAX major fracture risk, 1.4% for FRAX hip fracture risk, 14.4% for Garvan any fracture risk, and 8.8% for Garvan hip fracture risk.

CONCLUSIONS

The current prospective study enabled to establish new, optimal thresholds for therapy initiation. Such a modified approach may enable a more accurate identification of treatment requiring patients and, in consequence, reduce the number of new fractures.

Screening for Osteoporosis Risk Among Community-Dwelling Older Adults: A Scoping Review

BACKGROUND AND PURPOSE

Due to potential health-related consequences of osteoporosis (OP), health care providers who do not order imaging, such as physical therapists, should be aware of OP screening tools that identify individuals who need medical and rehabilitation care. However, current knowledge and guidance on screening tools is limited. Therefore, we explored OP screening tools that are appropriate and feasible for physical therapy practice, and evaluated tools' effectiveness by examining their clinimetric properties.

METHODS

A systematic search of the following databases was performed: PubMed, PEDro, PsycINFO, CINAHL, and Web of Science. Articles were included if the study population was 50 years and older, had a diagnosis of OP, if the screening tool was within the scope of physical therapy practice, and was compared to either a known diagnosis of OP or bone densitometry scan results. Included articles underwent multiple reviews for inclusion and exclusion, with each review round having a different randomly selected pair of reviewers. Data were extracted from included articles for participant demographics, outcome measures, cut-off values, and clinimetric properties. Results were categorized with positive and negative likelihood ratios (+LR/-LR) based on the magnitude of change in the probability of having or not having OP.

RESULTS

+LRs ranged from 0.15 to 20.21, with the Fracture Risk Assessment Tool (FRAX) and Study of Osteoporotic Fractures (SOF) having a large shift in posttest probability. -LRs ranged from 0.03 to 1.00, with the FRAX, Male Osteoporosis Risk Estimation Scores, Osteoporosis Self-Assessment Tool (OST), and Simple Calculated Osteoporosis Risk Estimation having a large shift in posttest probability.

CONCLUSION

Tools with moderate-large shift for both +LR and -LR recommended for use are: (1) OST; (2) FRAX; and (3) SOF. The variability in cut-off scores and clinimetric properties based on gender, age, and race/ethnicities made it impossible to provide one specific recommendation for an OP screening tool. Future research should focus on OP risk prediction among males and racial and ethnic groups.

Height Loss Is an Independent Predictor of Fracture Incidence in Postmenopausal Women: The Results from the Gliwice Osteoporosis Study (GO Study)

BACKGROUND

The aim of a longitudinal, retrospective study was to establish variables predicting fracture incidence over a decade.

METHODS

The study sample comprises a group of 457 postmenopausal women aged over 55 years, recruited from the database of an outpatient osteoporotic clinic. Several variables with potential influence on bone status, including the measurement of body height and hip bone densitometry, were collected. BMD at the femoral neck (FN BMD) was established using a Prodigy device (Lunar, GE, USA). Current body height was compared with the maximal historical body height in early adulthood, as reported by the patient.

RESULTS

Three hundred and ninety-four women did not have fractures during the follow up, and 63 subjects presented fractures. Subjects with fracture had lower FN BMD with a T-score of -1.86 ± 1.04 compared to -1.44 ± 0.89 in those without fractures (p < 0.001). Mean height loss (HL) was 3.47 ± 2.11 cm in fractured subjects and 2.50 ± 2.47 cm in unfractured ones, and differed significantly, p < 0.01. Fracture incidence was significantly related to age, rheumatoid arthritis, falls, and previous fractures. In the multivariable analysis using logistic regression, FN BMD, baseline fracture, and HL were identified as the significant predictors of fractures of follow up.

CONCLUSIONS

Osteoporotic fractures in postmenopausal women were predicted by FN BMD, prior fracture(s), and HL easily established during physical examination.

Use of the Osteoporosis Self-Assessment Tool as a Screening Tool for Osteoporosis in Saudi Postmenopausal Women

BACKGROUND

Osteoporosis is commonly referred to as the "silent disease," as bone loss is gradual and asymptomatic. In older women and men, osteoporosis can lead to increased bone fragility, thus increasing the risk of fractures. These fractures are associated with healthcare costs, physical disabilities, impaired quality of life, and mortality. Therefore, the study's main objective was to assess the applicability of the osteoporosis self-assessment tool (OST) in predicting osteoporosis in Saudi postmenopausal women who are 60 years of age and older and to give a thorough understanding of how such a method can aid in the early diagnosis of osteoporosis in Saudi Arabia and give physicians enough time to treat it.  Methods: This study was done at King Abdulaziz Medical City, Riyadh, Saudi Arabia, where we included postmenopausal Saudi women 60 years of age and older who took the bone mineral density (BMD) test in the family medicine department. The approximate target population in this group, between the years 2016 and 2022, was 2969 patients. All data was taken from the BestCare database at King Abdulaziz Medical City in Riyadh. Data were typed in an Excel sheet (Redmond, USA), then transferred to the R Studio software. The data collection method was chart review, so no informed consent was needed from patients. Names and medical record numbers were not stored.  Results: The study included 2969 participants. According to the bone mineral density (BMD) T score results, 490 participants (16.5%) were normal, 1746 participants (58.8%) had osteopenia, and 733 participants (24.7%) suffered from osteoporosis. BMD T scores for normal, osteopenia, and osteoporosis participants were -0.6 (-0.9, -.3), -1.8 (-2.1), and -3 (-3.5, -2.7), consecutively. Estimated OSTI scores for those patients were 2 (0, 4), 1 (-2, 3), and -1 (-4, 1), consecutively. According to the OSTI score for normal participants, 4.29% were classified as being at high risk of osteoporosis. A high risk of osteoporosis was identified in 0.74% of those with osteopenia. 27.83% of osteoporosis patients were classified as being at high risk of osteoporosis. To differentiate normal individuals from those with osteopenia, the cutoff value with optimal sensitivity was 3.5. At such a cutoff value, the test sensitivity was 81.04%. To differentiate normal participants from those with osteoporosis, the cutoff value with optimal sensitivity was 2.5. At such a cutoff value, the test sensitivity was 86.49%. To differentiate osteopenia from osteoporosis patients, the cutoff threshold with optimal sensitivity was 1.5. At such a threshold, sensitivity was 78.44%.  Conclusion: OSTA is a simple and validated tool that can identify subjects at increased risk of osteoporosis. Its use could facilitate a more cost-effective use of BMD; by avoiding measurements in low-risk groups.

[Osteoporosis Screening Values of Osteoporosis Self-Assessment Tool for Asians Index and Body Mass Index in Middle-Aged and Elderly Tibetan Population in Tibet]

Objective

To analyze the screening value of osteoporosis self-screening tool for Asia (OSTA) and body mass index (BMI) for osteoporosis (OP) in middle-aged and elderly Tibetan population in the Tibetan region.

Methods

Data on demographic information, bone mineral density (BMD), and other information of 627 middle-aged and elderly people were collected. Analysis of the correlation between OSTA index, BMI and BMD, and receiver operating characteristic (ROC) curve was performed to evaluate the OP screening effects.

Results

OSTA index and BMI were correlated with BMD in both female and male populations ( P<0.05). In both male and female populations, OSTA index screening results for OP yielded higher area under the curve ( AUC) than BMI did, with the AUC for female OSTA index being 0.886 and that for female BMI being 0.785, while that for male OSTA index being 0.957 and that for male BMI being 0.834. When comparing the different age groups, the AUC of OSTA index and BMI of the middle-age group was higher than those of the quasi-elderly group and the elderly group, with the AUC of OSTA index and BMI of the middle-age being 0.939 and 0.858, those of the quasi-elderly group being 0.860 and 0.813, and those of the elderly group being 0.750 and 0.650, respectively. When the optimal cut-off value of diagnosis with OSTA index was －2.20, the sensitivity and specificity were both 100%. When the optimal cut-off value for diagnosis with BMI was 17.512 kg/m2, the sensitivity and specificity were both 100%.

Conclusion

OSTA index and BMI have different OP screening effects in different middle-aged and elderly Tibetan populations, and OSTA index shows better effects for OP screening than BMI does.

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

Purpose

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.

Methods

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.

Results

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%.

Conclusion

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.

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.

Comparison of fracture risk calculators in elderly fallers: a hospital-based cross-sectional study

OBJECTIVE

Elderly patients presenting with falls are known to carry an extremely high risk of future fragility fractures. Current osteoporosis guidelines recommend using fracture risk calculators such as FRAX, QFracture or Garvan to guide management. However, they differ considerably in their inputs and may therefore provide contrasting risk estimations in certain individuals. In this study, we compare these risk calculators in a high-risk cohort of elderly patients admitted to hospital with falls.

DESIGN

Hospital-based cross-sectional study.

SETTING

Secondary care, London, UK.

PARTICIPANTS

Data from 120 consecutive elderly patients who had falls presenting to a single hospital over 4 months were collected. 10-year major and hip fracture risks were calculated using FRAX, QFracture and Garvan. 1-year major and hip fracture risks from QFracture were assessed against prospective incidence of fracture.

RESULTS

Median 10-year major fracture risk was: FRAX 19.5%, QFracture 26.0%, Garvan 32.5%. Median 10-year hip fracture risk was: FRAX 9.6%, QFracture 21.1%, Garvan 6.5%. Correlation between FRAX and QFracture was r=0.672 for major, r=0.676 for hip fracture (both p<0.0001); FRAX and Garvan r=0.778 (p<0.0001) for major, r=0.128 (p=0.206) for hip fracture; QFracture and Garvan r=0.658 (p<0.0001) for major, r=0.318 (p<0.001) for hip fracture. QFracture 1-year predicted major and hip fracture rates were 1.8% and 1.2%, respectively, compared with actual rates of 2.1% and 0%, respectively.

CONCLUSIONS

Although strong correlations between calculators were observed in the study cohort, there were differences of up to 13% between estimated risks. QFracture captured several elderly-specific inputs not considered by other calculators and so projected higher fracture risk than the other calculators. QFracture provided 1-year fracture risks that were comparable with the prospective observed fracture incidence in the cohort. This study has important clinical implications for the use of fracture risk calculators to guide treatment decisions, particularly in the high-risk cohort of elderly patients admitted to hospital following falls.

Evaluation of community-based screening tools for the early screening of osteoporosis in postmenopausal Vietnamese women

Background

Osteoporosis affects people worldwide. However, there are few validated tools for the early screening of osteoporosis in Vietnam. We set out to evaluate the performance of the osteoporosis self-assessment tool for Asians (OSTA) and the osteoporosis screening tool for Chinese (OSTC) for the early screening of osteoporosis in postmenopausal Vietnamese women.

Methods

We analyzed retrospective data from 797 postmenopausal Vietnamese women. The bone mineral density (BMD) in the lumbar vertebrae (L1–L4) and the left and right femoral necks of all participants were measured using dual-energy X-ray absorptiometry (DXA). Osteoporosis was defined as the BMD (T-score) < -2.5. The OSTA and OSTC scores were calculated from the age and weight of participants. Receiver operating characteristic analysis was conducted to compare the performance of the two tools with the BMD measurements by DXA at different anatomical sites.

Results

The rates of osteoporosis determined by BMD varied between anatomical sites, and ranged from 43.4% to 54.7% in the lumbar vertebrae and 29.2% and 8.9% in the left and right femoral necks, respectively. For the vertebrae, the area under the curve (AUC) for OSTA ranged from 70.9% to 73.9% and for OSTC ranged from 68.7% to 71.6%. The predictive value of both tools was higher for femoral necks, with the AUC of OSTA for the left and right femoral necks being 80.0% and 85.8%, respectively. The corresponding figures for OSTC were 80.5% and 86.4%, respectively. The highest sensitivity and specificity of OSTA were 74.6% and 81.4%, while these figures for OSTC were 73.9% and 82.6%, respectively.

Conclusion

OSTA and OSTC were shown to be useful self-assessment tools for osteoporosis detection in Vietnam postmenopausal women. Further research is encouraged to determine the applicability of tools for other populations and settings.

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

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

The Assessment of the Osteoporosis Self-Assessment Tool for Asians and Calcaneal Quantitative Ultrasound in Identifying Osteoporotic Fractures and Falls Among Chinese People

The lack of DXA has made the diagnosis and treatment of osteoporosis extremely difficult in the vast rural areas of China, which has the largest population with high risks of osteoporosis. The aims of this cross-sectional study were to evaluate the association between the osteoporosis self-assessment tool for Asians (OSTA) and calcaneus quantitative ultrasound (QUS) in populations residing in Shanghai, China, and their assessment in predicting osteoporotic fractures and falls. A population of 12,033 participants, including 1272 males (average age 68.3 ± 9.8 years, range 28-100 years) and 10,761 females (average 56.8 ± 11.4 years, range 23-99 years), was gathered. OSTA and calcaneus QUS (Sonost 2000, OsteoSys) values were measured. Spearman's correlation and Cohen's kappa were used to determine the association and agreement between the OSTA and QUS. Receiver operating characteristic (ROC) curves were adapted to assess the performance and optimal cutoff values for the OSTA and QUS in osteoporotic fracture and fall screening. In total, the prevalence of osteoporotic fractures (low-trauma fractures including fractures of the spine, hip, forearm, humerus and ribs) was 15.2% in women, and 17.7% reported a history of falls (falling from standing height more than once in the past year). The percentages of men with the same history were 8.4% and 11.7%, respectively. The association between the OSTA and QUS was found to be r_s = 0.393, κ = 0.137, p < 0.001. The OSTA (cutoff < -1) revealed an area under ROC curve (AUC) of 0.590 in identifying female individuals with moderate or high risk of osteoporosis defined by QUS (T-score < -1). The QUS T-score lower than -1.55 or -1.40 in postmenopausal women may lead to an increased risk of falls or osteoporotic fractures, respectively. The agreement between QUS and the OSTA seemed to be limited in determining individuals at risk of osteoporosis. Measuring bone mineral density (BMD) by dual energy X-ray absorptiometry (DXA) may still be necessary in the clinical diagnosis of osteoporosis. OSTA and QUS T-scores less than the respective cutoff values may indicate an increased risk of osteoporotic fractures and falls that individual should be further treated and screened by DXA.

Comparison of screening tools for optimizing fracture prevention in Canada

The best screening strategy to identify treatment qualification based upon indicators of high fracture risk (low-trauma fractures of the hip, spine, or multiple fracture episodes at other sites; high fracture probability with the Canadian fracture risk assessment [FRAX®] tool major osteoporotic fracture [MOF] computed with bone mineral density [BMD] > 20%; or vertebral fracture on vertebral fracture assessment [VFA]) was FRAX-MOF without BMD using a cutoff of ≥ 10%.

PURPOSE

To inform clinical practice guidelines in Canada, we compared multiple screening tools using the population-based Manitoba BMD Program registry.

METHODS

The study populations consisted of (a) 28,906 individuals > 50 years or older, and (b) 15,429 women age > 65 years undergoing baseline BMD assessment (2010-2018). We considered two treatment qualifications: Treatment Approach 1: prior high-risk fracture, high fracture probability (FRAX-MOF with BMD > 20%), or vertebral fracture on VFA; Treatment Approach 2: Approach 1 or an osteoporotic BMD T score. Candidate screening tools were FRAX-MOF without BMD, age alone, weight alone, SCORE, ORAI, SOFSURF, OSIRIS, ABONE, and OST. Healthcare records were assessed for the presence of incident fracture diagnoses.

RESULTS

Among all individuals, FRAX-MOF without BMD demonstrated the best ability to identify those satisfying Treatment Approach 1 (area under the curve [AUC 0.863]) and was significantly better than all other screening tools (P < 0.001). For identification of individuals satisfying Treatment Approach 2, FRAX-MOF without BMD showed moderate stratification (AUC 0.735), slightly lower than OSIRIS (AUC 0.752, P < 0.05), similar to SCORE (AUC 0.739, P > 0.05) and significantly better than all other screening tools (P < 0.05). For prediction of incident MOF, FRAX-MOF without BMD achieved the highest performance (AUC 0.652), and was significantly better than all other screening tools except OSIRIS. AUCs among women age > 65 years tended to be greater with a similar ranking, and no tool outperformed FRAX-MOF without BMD. Based upon a summary score, the highest ranked strategy was FRAX-MOF without BMD using a cutoff of 10%.

CONCLUSIONS

All screening tools show some ability to identify individuals qualifying for treatment and stratify risk for incident fracture. For treatment based upon indicators of high fracture risk, the best performing strategy was FRAX-MOF without BMD using a cutoff of ≥ 10%.

FRAX score and recent fall history predict the incidence for sarcopenia in community-dwelling older adults: a prospective cohort study

We hypothesized that the baseline FRAX score and previous falls would predict the incidence of sarcopenia in community-dwelling older adults who received medical check-ups. The FRAX score (hazard ratio [HR] = 1.087, 95% CI 1.014-1.167) and previous falls (HR = 5.181, 95% CI 1.002-26.777) were determined to be independent risk factors for the incidence of sarcopenia.

PURPOSE

This prospective study was performed to elucidate the prevalence and incidence of sarcopenia in community-dwelling older adults who received medical check-ups, and to determine whether FRAX score and fall history predict the incidence of sarcopenia.

METHODS

Participants were recruited from a group of individuals who had registered for an annual town-sponsored medical check-up. Study inclusion criteria were aged older than 60 years, living independently, and ability to walk without assistance. Individuals who received nursing care were excluded from the study. A total of 426 residential participants were analyzed. Demographic information, fall history of the previous year, and FRAX score without bone mineral density were assessed. The assessment for sarcopenia was based on the recommendations of the Asian Working Group for Sarcopenia.

RESULTS

The final sample for the assessment of sarcopenia incidence comprised 258 participants. The mean follow-up time was 2.92 years. The rate of sarcopenia was 1.06 cases per 100 person-years at risk. The Cox multivariate logistic regression model in our analysis was adjusted for age, gender, muscle mass, and covariates and showed that the FRAX score (HR = 1.087, 95% CI 1.014-1.167) and recent history of falls (HR = 5.181, 95% CI 1.002-26.777) were independent risk factors for the incidence of sarcopenia.

CONCLUSION

FRAX and history of falling can be a simple screening tool to raise awareness of the prevention of osteoporosis and sarcopenia in clinical settings.

Comparison of OSTA, FRAX and BMI for Predicting Postmenopausal Osteoporosis in a Han Population in Beijing: A Cross Sectional Study

Purpose

To validate the efficacies of three screening tools including the Osteoporosis Self-Assessment Tool for Asians (OSTA), Fracture Risk Assessment Tool (FRAX) without bone mineral density (BMD), and body mass index (BMI) for predicting postmenopausal osteoporosis (OP) and to define the ideal thresholds for avoidance of dual-energy X-ray absorptiometry (DXA) scanning in a Han Chinese population in Beijing.

Patients and Methods

A total of 2055 community-dwelling Han Beijing postmenopausal females aged ≥45 years were enrolled in this study. All participants completed a questionnaire, and BMD was measured by DXA. OP was defined by a T-score at least -2.5 SD less than that of average young adults in different diagnostic criteria [lumbar spine, femoral neck, total hip, worst hip, WHO]. The abilities of the OSTA, FRAX, and BMI to predict OP were analyzed by receiver operating characteristic (ROC) curves. Sensitivity, specificity, and area under the ROC curves (AUC) were calculated. Ideal thresholds for identifying OP were proposed.

Results

The prevalence of OP ranged from 8.1% to 28.4% according to different diagnostic criteria. The AUC range for the OSTA (0.758-0.849) was similar to the FRAX (0.728-0.855), which revealed that both tools predicted OP reliably. The AUC range for BMI was 0.643-0.682, suggesting limited predictive value. According to WHO criteria, the AUC values for the FRAX for hip fracture risk (FRAX-HF) and for the OSTA were 0.796 and 0.798, with corresponding sensitivities of 74.79% and 69.64% and specificities of 70.45% and 75.07%, respectively. At defined thresholds, the FRAX-HF and OSTA allowed avoidance of DXA in 42.4-37.6% of participants, at a cost of missing only 7.2-8.6% of individuals with OP.

Conclusion

The OSTA and FRAX-HF may be reliable and effective tools for identifying postmenopausal OP in the Han Beijing population without BMD.

The performance of osteoporosis self-assessment tool for Asians (OSTA) in identifying the risk of osteoporosis among Malaysian population aged 40 years and above

The concordance between osteoporosis self-assessment tool for Asians (OSTA) and dual-energy X-ray absorptiometry (DXA) was fair in the study. Modification of OSTA cutoff values improved its sensitivity to identify subjects at risk for suboptimal bone health (osteopenia/osteoporosis) and osteoporosis.

PURPOSE

Osteoporosis self-assessment tool for Asians (OSTA) is a convenient screening algorithm used widely to identify patients at risk of osteoporosis. Currently, the number of studies validating OSTA in Malaysian population is limited. This study aimed to validate the performance of OSTA in identifying subjects with osteoporosis determined with DXA.

METHODS

This cross-sectional study recruited 786 Malaysians in Klang Valley, Malaysia. Their bone health status was assessed by DXA and OSTA. The association and agreement between OSTA and bone mineral density assessment by DXA were determined by Pearson's correlation and Cohen's kappa, respectively. Receiver operating characteristics (ROC) curves were used to determine the sensitivity, specificity, and area under the curve (AUC) for OSTA.

RESULTS

OSTA and DXA showed a fair association in the study (r = 0.382, κ = 0.159, p < 0.001). OSTA (cutoff < - 1) revealed a sensitivity of 32.3%, specificity of 92.3%, and AUC of 0.618 in identifying subjects with suboptimal bone health. The sensitivity of OSTA (cutoff < - 4) in determining subjects at risk of osteoporosis was better among women (sensitivity = 20%) than men (sensitivity = 0%). Modified OSTA cutoff values improved the sensitivity of OSTA in identifying subjects with suboptimal bone health (men = 81.0% at cutoff 3.4, women = 82.8% at cutoff 2.0) and osteoporosis (men = 81.8% at cutoff 1.8, women = 81.3% at cutoff 0.8).

CONCLUSION

OSTA with its original cutoff values is ineffective in identifying individuals at risk for osteoporosis. Adjusting the cutoff values significantly increases the sensitivity of OSTA, thus highlighting the need to validate this instrument among the local population before using it for osteoporosis screening clinically.

Functional risk for fracture by safe functional motion testing: a short version of the safe functional motion test

Background:

‘Unsafe’ movement strategies used to perform everyday activities were quantified using scores for tasks included in the Short Form Safe Functional Motion test series (SSFM). Baseline scores were independently associated with incident fractures after adjusting for factors known to effect fracture risk. The purpose of the present study is to determine whether the SSFM, a series of tests of habitual motion, is associated with incident fragility fracture at any skeletal sites.

Methods:

An osteoporosis clinic database was queried for adults with baseline SSFM scores and corresponding data for prevalent fractures, femoral neck bone mineral density (fnBMD), osteoporosis medication use, and incident fractures at 1-year and 3-year follow ups [n = 1700 (118 incident fractures) and n = 1058 (202 incident fractures), respectively]. Multiple logistic regressions, adjusted for sex, age, fnBMD, osteoporosis medication use, and any prevalent fractures at baseline, were used to determine whether baseline SSFM scores were associated with incident fragility fractures.

Results:

An Sfm-3 score was a significant independent predictor of any fracture at 1 year [adjusted odds ratio (95% CI) = 1.118 (1.025, 1.219) for each 10-point decrease in Sfm-3; p = 0.012], and 3-year follow up [adjusted odds ratio (95% CI) = 1.183 (1.098, 1.274) for each 10-point decrease in Sfm-3; p < 0.0001].

Conclusions:

Scores on the SSFM predict fracture risk such that for each 10-point drop in score the odds of fracture are increased by up to 18% independent of risk associated with age, bone mineral density, use of bone-sparing medications, and history of a fracture.

Bone mineral density as a dose-response predictor for osteoporosis: a propensity score analysis of longitudinal incident study (KCIS no. 39)

BACKGROUND

Osteoporosis is a global disease burden for aging society. The role of quantitative ultrasound (QUS) in the prediction for osteoporosis in a dose-response manner is hardly addressed.

AIM

We aimed to show the dose-response of QUS measurement in the prediction for osteoporosis by a community-based study.

DESIGN

A prospective cohort study.

METHODS

Participants were recruited between 2000 and 2004. Demographic data and heel QUS measurement were collected at baseline. Diagnosis of osteoporosis was ascertained by the follow-up of this cohort over time. In order to reduce the imbalance of baseline characteristics in the observational study, we applied propensity score by using proportional odds regression analysis to match the quintiles of QUS T-score.

RESULTS

A total of 44 957 subjects composed of 17 678 men (39.3%) and 27 279 women (69.7%) were recruited. After adjustments for propensity score, an increase in one unit of QUB T-score led to 7% reduction in the risk for osteoporosis [adjusted odds ratio (OR) = 0.93, 95% confidence interval (CI): 0.89-0.96, P < 0.0001]. Higher quintile of QUS T-score yielded a lower risk of osteoporosis with a gradient relationship [OR: 0.82 (95%CI: 0.72-0.92); OR: 0.81 (95%CI: 0.71-0.91); OR: 0.77 (95%CI: 0.68-0.87) and OR: 0.76 (95%CI: 0.67-0.86)] from the second to highest quintile opposed to first quintile (P < 0.0001). The cumulative incidence of osteoporosis was higher in the lower quintile during follow-up (log-rank test, P < 0.001).

CONCLUSION

QUS is an independent predictor for osteoporosis in a dose-response manner using a large population-based cohort. Due to the lower cost and portability of QUS measurement, the pre-screening for osteoporosis by QUS can be considered in the area with limited resources can be a feasible and alternative method.

Performance of Osteoporosis Self-Assessment Tool (OST) in Predicting Osteoporosis-A Review

Bone health screening plays a vital role in the early diagnosis and treatment of osteoporosis to prevent fragility fractures among the elderly and high-risk individuals. Dual-energy X-ray absorptiometry (DXA), which detects bone mineral density, is the gold standard in diagnosing osteoporosis but is not suitable for screening. Therefore, many screening tools have been developed to identify individuals at risk for osteoporosis and prioritize them for DXA scanning. The Osteoporosis Self-assessment Tool (OST) is among the first tools established to predict osteoporosis in postmenopausal women. It can identify the population at risk for osteoporosis, but its performance varies according to ethnicity, gender, and age. Thus, these factors should be considered to ensure the optimal use of OST worldwide. Overall, OST is a simple and economical screening tool to predict osteoporosis and it can help to optimize the use of DXA.

Screening for Osteoporosis to Prevent Fractures: US Preventive Services Task Force Recommendation Statement

IMPORTANCE

By 2020, approximately 12.3 million individuals in the United States older than 50 years are expected to have osteoporosis. Osteoporotic fractures, particularly hip fractures, are associated with limitations in ambulation, chronic pain and disability, loss of independence, and decreased quality of life, and 21% to 30% of patients who experience a hip fracture die within 1 year. The prevalence of primary osteoporosis (ie, osteoporosis without underlying disease) increases with age and differs by race/ethnicity. With the aging of the US population, the potential preventable burden is likely to increase in future years.

OBJECTIVE

To update the 2011 US Preventive Services Task Force (USPSTF) recommendation on screening for osteoporosis.

EVIDENCE REVIEW

The USPSTF reviewed the evidence on screening for and treatment of osteoporotic fractures in men and women, as well as risk assessment tools, screening intervals, and efficacy of screening and treatment in subgroups. The screening population was postmenopausal women and older men with no known previous osteoporotic fractures and no known comorbid conditions or medication use associated with secondary osteoporosis.

FINDINGS

The USPSTF found convincing evidence that bone measurement tests are accurate for detecting osteoporosis and predicting osteoporotic fractures in women and men. The USPSTF found adequate evidence that clinical risk assessment tools are moderately accurate in identifying risk of osteoporosis and osteoporotic fractures. The USPSTF found convincing evidence that drug therapies reduce subsequent fracture rates in postmenopausal women. The USPSTF found that the evidence is inadequate to assess the effectiveness of drug therapies in reducing subsequent fracture rates in men without previous fractures.

CONCLUSIONS AND RECOMMENDATION

The USPSTF recommends screening for osteoporosis with bone measurement testing to prevent osteoporotic fractures in women 65 years and older. (B recommendation) The USPSTF recommends screening for osteoporosis with bone measurement testing to prevent osteoporotic fractures in postmenopausal women younger than 65 years at increased risk of osteoporosis, as determined by a formal clinical risk assessment tool. (B recommendation) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of screening for osteoporosis to prevent osteoporotic fractures in men. (I statement).

Individualized fracture risk assessment: State-of-the-art and room for improvement

Fragility fracture is a serious clinical event, because it is associated with increased risk of mortality and reduced quality of life. The risk of fracture is determined by multiple risk factors, and their effects may be interactional. Over the past 10 years, a number of predictive models (e.g., FRAX, Garvan Fracture Risk Calculator, and Qfracture) have been developed for individualized assessment of fracture risk. These models use different risk profiles to estimate the probability of fracture over 5- and 10-year period. The ability of these models to discriminate between those individuals who will and will not have a fracture (i.e., area under the receiver operating characteristic curve [AUC]) is generally acceptable-to-good (AUC, 0.6 to 0.8), and is highly variable between populations. The calibration of existing models is poor, particularly in Asian populations. There is a strong need for the development and validation of new prediction models based on Asian data for Asian populations. We propose approaches to improve the accuracy of existing predictive models by incorporating new markers such as genetic factors, bone turnover markers, trabecular bone score, and time-variant factors. New and more refined models for individualized fracture risk assessment will help identify those most likely to sustain a fracture, those most likely to benefit from treatment, and encouraging them to modify their risk profile to decrease risk.

Comparison of three tools for predicting primary osteoporosis in an elderly male population in Beijing: a cross-sectional study

Purpose

In this cross-sectional study, three clinical tools, the Osteoporosis Self-Assessment Tool for Asians (OSTA), Fracture Risk Assessment Tool (FRAX) without bone mineral density (BMD), and body mass index (BMI), for predicting primary osteoporosis (OP) were compared and ideal thresholds for omission of screening BMD were proposed in a community-dwelling elderly Han Beijing male population.

Patients and methods

A total of 1,349 community-dwelling elderly Han Beijing males aged ≥50 years were enrolled in this study. All subjects completed a questionnaire and measured BMD by dual-energy X-ray absorptiometry (DXA). Osteoporosis was defined as a T-score of -2.5 SD or lower than that of the average young adult in different diagnostic criteria (lumbar spine [L1-L4], femoral neck, total hip, worst hip, and World Health Organization [WHO]). FRAX without BMD, OSTA, and BMI were assessed for predicting OP by receiver operating characteristic (ROC) curves. Sensitivity, specificity, and areas under the ROC curves (AUCs) were determined. Ideal thresholds for omission of screening BMD were proposed.

Results

The prevalence of OP ranged from 1.8% to 12.8% according to different diagnostic criteria. This study showed that the BMI has highest discriminating ability. The AUC of FRAX without BMD ranged from 0.536 to 0.630, which suggested limiting predictive value for identifying OP in elderly Beijing male. The AUCs of BMI (0.801-0.880) were slightly better than OSTA (0.722-0.874) in predicting OP at all sites. The AUC of BMI to identify OP in worst hip was 0.824, yielding a sensitivity of 84.8% and a specificity of 64.4%. 40% of participants on BMD measurements saved only 0.1%-2.7% missed OP. Compared to OSTA and FRAX without BMD, the BMI got the best predictive value for OP.

Conclusion

BMI may be a simple and effective tool for identifying OP in the elderly male population in Beijing to omit BMD screening reasonably.

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.

Evaluation of Singh Index and Osteoporosis Self-Assessment Tool for Asians as risk assessment tools of hip fracture in patients with type 2 diabetes mellitus

Background

Type 2 diabetes mellitus (T2DM), an epidemic disease around world, has recently been identified as a risk factor for osteoporosis-associated fracture. However, there is no consensus on the best method of assessing fracture risk in patients with T2DM. The aim of this study was to evaluate the usefulness of the Osteoporosis Self-Assessment Tool for Asians (OSTA) and the Singh Index (SI) in hip fracture risk assessment in patients with T2DM.

Methods

We enrolled 261 postmenopausal women with T2DM: 87 had hip fracture resulting from low-energy trauma and 174 age-matched controls had no fracture (two controls per fracture case). Bone mineral density (BMD) was measured with dual-energy X-ray absorptiometry in the lumbar spine and hip region. The SI was obtained from standard antero-posterior radiographs of the pelvis. The OSTA was calculated with a formula based on weight and age. Data were analyzed with descriptive statistics and tests of difference. Receiver operating characteristic analysis was used to determine optimum cutoff values, sensitivity, and specificity of screening methods. Discriminative abilities of different screening tools were compared with the area under the curve (AUC).

Results

There were significant differences in BMD at all sites (lumbar spine, femoral neck, trochanter, and total hip) and in SI between the fracture and non-fracture groups (P < 0.05). There was no significant difference in OSTA between the groups (P > 0.05). The area under the curve was 0.747 (95% CI: 0.680–0.813) for lumbar spine BMD, 0.699 (95% CI: 0.633–0.764) for total hip BMD, 0.659 (95% CI: 0.589–0.729) for femoral neck BMD, 0.631 (95% CI: 0.557–0.704) for trochanter BMD, 0.534 (95% CI: 0.459–0.610) for OSTA, 0.636 (95% CI: 0.564–0.709) for SI, and 0.795 (95% CI: 0.734–0.857) for OSTA plus SI. The AUC for combined OSTA plus SI was significantly superior to other parameters besides BMD of the lumbar spine.

Conclusions

The combination of OSTA plus SI could be a clinical alternative tool for screening of hip fracture risk in large diabetic populations. These tests are inexpensive and simple to perform and could be especially useful in areas where BMD measurement is not accessible.

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

[This corrects the article DOI: 10.1097/MD.0000000000003415.].