Agreement between calcaneal quantitative ultrasound and osteoporosis self-assessment tool for Asians in identifying individuals at risk of osteoporosis

Correlations of the Osteoporosis Self-Assessment Tool for Asians (OSTA) and Three Panoramic Indices Using Quantitative Ultrasound (QUS) Bone Densitometry

This study aimed to evaluate the correlation between the Osteoporosis Self-Assessment Tool for Asians (OSTA) and three panoramic indices in relation to z-score and t-score values using quantitative ultrasound (QUS) bone densitometry. The sensitivity, specificity, and area under the curve (AUC) of the OSTA index were also measured using the QUS tool to evaluate the method's performance in identifying people at risk of osteoporosis. The study employed a cross-sectional design with 387 participants (190 men, 197 women). Patients' mandibular cortical indexes (MCI), mandibular cortical widths (MCW), and panoramic mandibular indexes (PMI) were measured from panoramic images. The sensitivity, specificity, and AUC were calculated using an OSTA index cutoff of ≤-1 and a t-score of ≤-1.0 for the QUS bone densitometry. The coefficient correlation of the OSTA index with the z-score (r = -0.563, p < 0.001) and t-score (r = -0.740, p < 0.001) shows a higher value than the MCI, MCW, and PMI, per the QUS. The sensitivity, specificity, and AUC values with a cutoff t-score of ≤-1.0 per the QUS in men was 90%, 50%, and 0.812, and in women, 96.8%, 30%, and 0.862. The OSTA index is a simple method that can be used in general dental practice.

QUS characteristics in Normal Population: a Mini Review and our experience

Objectives

Quantitative ultrasound (QUS) is a bone densitometry method that is less expensive and more portable than DXA. It is also noninvasive. QUS parameters include speed of sound (SOS), broad band ultrasound attenuation (BUA), and stiffness index (SI). This study defined normal values of QUS parameters in Iranian men and women.

Methods

QUS of heels measured in 258 Iranian men and women, aged 20-76 y/o. They were participants of Iranian Multicenter Osteoporosis study (IMOS), selected by randomized sampling. QUS device was an Achilles+ (GE-Lunar) device.

Results

Percentiles of SI (2.5%, 50%, and 97.5%) determined. We found a good agreement between the Iranian reference values and western reference (used by device) value in defining normal and osteoporotic people (κ = 0.875).

Conclusion

Results from this study suggest that QUS of the heel may be a good method for diagnosis of low bone mass in different regions.

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.

The Performance of a Calcaneal Quantitative Ultrasound Device, CM-200, in Stratifying Osteoporosis Risk among Malaysian Population Aged 40 Years and Above

BACKGROUND

Calcaneal quantitative ultrasound (QUS) is widely used in osteoporosis screening, but the cut-off values for risk stratification remain unclear. This study validates the performance of a calcaneal QUS device (CM-200) using dual-energy X-ray absorptiometry (DXA) as the reference and establishes a new set of cut-off values for CM-200 in identifying subjects with osteoporosis.

METHODS

The bone health status of Malaysians aged ≥40 years was assessed using CM-200 and DXA. Sensitivity, specificity, area under the curve (AUC) and the optimal cut-off values for risk stratification of CM-200 were determined using receiver operating characteristic (ROC) curves and Youden's index (J). Results: From the data of 786 subjects, CM-200 (QUS T-score <-1) showed a sensitivity of 82.1% (95% CI: 77.9-85.7%), specificity of 51.5% (95% CI: 46.5-56.6%) and AUC of 0.668 (95% CI: 0.630-0.706) in identifying subjects with suboptimal bone health (DXA T-score <-1) (p < 0.001). At QUS T-score ≤-2.5, CM-200 was ineffective in identifying subjects with osteoporosis (DXA T-score ≤-2.5) (sensitivity 14.4% (95% CI: 8.1-23.0%); specificity 96.1% (95% CI: 94.4-97.4%); AUC 0.553 (95% CI: 0.488-0.617); p > 0.05). Modified cut-off values for the QUS T-score improved the performance of CM-200 in identifying subjects with osteopenia (sensitivity 67.7% (95% CI: 62.8-72.3%); specificity 72.8% (95% CI: 68.1-77.2%); J = 0.405; AUC 0.702 (95% CI: 0.666-0.739); p < 0.001) and osteoporosis (sensitivity 79.4% (95% CI: 70.0-86.9%); specificity 61.8% (95% CI: 58.1-65.5%); J = 0.412; AUC 0.706 (95% CI: 0.654-0.758); p < 0.001). Conclusion: The modified cut-off values significantly improved the performance of CM-200 in identifying individuals with osteoporosis. Since these values are device-specific, optimization is necessary for accurate detection of individuals at risk for osteoporosis using QUS.

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.

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.