Developing a Malaysian Osteoporosis Screening Tool (MOST) for early osteoporosis detection in Malaysian women

A summary of the Malaysian Clinical Practice Guidelines on the management of postmenopausal osteoporosis, 2022

Objectives

The aim of these Clinical Practice Guidelines is to provide evidence-based recommendations to assist healthcare providers in the screening, diagnosis and management of patients with postmenopausal osteoporosis (OP).

Methods

A list of key clinical questions on the assessment, diagnosis and treatment of OP was formulated. A literature search using the PubMed, Medline, Cochrane Databases of Systematic Reviews, and OVID electronic databases identified all relevant articles on OP based on the key clinical questions, from 2014 onwards, to update from the 2015 edition. The articles were graded using the SIGN50 format. For each statement, studies with the highest level of evidence were used to frame the recommendation.

Results

This article summarizes the diagnostic and treatment pathways for postmenopausal OP. Risk stratification of patients with OP encompasses clinical risk factors, bone mineral density measurements and FRAX risk estimates. Non-pharmacological measures including adequate calcium and vitamin D, regular exercise and falls prevention are recommended. Pharmacological measures depend on patients' fracture risk status. Very high-risk individuals are recommended for treatment with an anabolic agent, if available, followed by an anti-resorptive agent. Alternatively, parenteral anti-resorptive agents can be used. High-risk individuals should be treated with anti-resorptive agents. In low-risk individuals, menopausal hormone replacement or selective estrogen receptor modulators can be used, if indicated. Patients should be assessed regularly to monitor treatment response and treatment adjusted, as appropriate.

Conclusions

The pathways for the management of postmenopausal OP in Malaysia have been updated. Incorporation of fracture risk stratification can guide appropriate treatment.

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.

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.

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.

Development of Osteoporosis Screening Algorithm for Population Aged 50 Years and above in Klang Valley, Malaysia

Background: The current osteoporosis screening instruments are not optimized to be used among the Malaysian population. This study aimed to develop an osteoporosis screening algorithm based on risk factors for Malaysians. Methods: Malaysians aged ≥50 years (n = 607) from Klang Valley, Malaysia were interviewed and their bone health status was assessed using a dual-energy X-ray absorptiometry device. The algorithm was constructed based on osteoporosis risk factors using multivariate logistic regression and its performance was assessed using receiver operating characteristics analysis. Results: Increased age, reduced body weight and being less physically active significantly predicted osteoporosis in men, while in women, increased age, lower body weight and low-income status significantly predicted osteoporosis. These factors were included in the final algorithm and the optimal cut-offs to identify subjects with osteoporosis was 0.00120 for men [sensitivity 73.3% (95% confidence interval (CI) = 54.1%-87.7%), specificity 67.8% (95% CI = 62.7%-85.5%), area under curve (AUC) 0.705 (95% CI = 0.608-0.803), p < 0.001] and 0.161 for women [sensitivity 75.4% (95% CI = 61.9%-73.3%), specificity 74.5% (95% CI = 68.5%-79.8%), AUC 0.749 (95% CI = 0.679-0.820), p < 0.001]. Conclusion: The new algorithm performed satisfactorily in identifying the risk of osteoporosis among the Malaysian population ≥50 years. Further validation studies are required before applying this algorithm for screening of osteoporosis in public.

Knowledge and Attitudes of Maintaining Bone Health among Post-Menopausal Women in Malaysia

Introduction

Public awareness of osteoporosis is low among women in the developing countries. Health education was shown to be effective in improving knowledge and awareness on maintaining bone health. This study aims to identify the level of knowledge and attitudes among post-menopausal women in Malaysia on achieving bone health throughout the menopausal transition period.

Methods

A total of 116 post-menopausal female patients of orthopedic menopause clinic were recruited using a purposive sampling approach. Data on osteoporosis awareness and knowledge were collected using validated structured questionnaires Osteoporosis Prevention and Awareness Tool and Osteoporosis Attitude Knowledge Test. The chi-square test was used to determine the association between post-menopausal women's socio-demographic characteristics and their knowledge and attitude towards maintaining bone health.

Results

Participants' age ranged between 49 and 82 years (61.84, SD=7.87). The knowledge of osteoporosis varied significantly by age (p=0.014) and education (p=0.001) among the studied population. No significant diffrences were found for participants' attitude towards bone health.

Conclusion

This study showed that the age and education levels have significantly different knowledge of bone health.

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.

Prevalence and Predictors of Osteoporosis Among the Chinese Population in Klang Valley, Malaysia

The prevalence of osteoporosis is forecasted to escalate in Malaysia with an increasing elderly population. This study aimed to analyze the prevalence and the risk factors of osteoporosis among middle-aged and elderly Chinese Malaysians. Three hundred sixty seven Malaysian Chinese aged ≥40 years in Klang Valley, Malaysia, were recruited. All subjects completed a structured questionnaire comprised of demographic details, medical history, diet, and lifestyle practices. Body anthropometry and bone mineral density measurements were also performed. The relationship between bone health status and risk factors was determined using multivariate logistic regression. Fifteen-point-three percent of the overall study population and 32.6% of those aged ≥71 years had osteoporosis. The prevalence of osteoporosis among women (18.9%) was higher than men (11.5%). The significant predictors of osteoporosis were age, body weight, and low monthly income. Lean mass, low education level, and being underweight predicted osteoporosis in women. Lean mass was the only significant predictor of osteoporosis in men. Overall, 15.3% of the Malaysian Chinese aged ≥40 years from Klang Valley, Malaysia, had osteoporosis. Osteoporosis was associated positively with increased age and low monthly income and negatively with body weight. Therefore, osteoporosis preventive strategies targeting Chinese elderly from a low socioeconomic background is necessary.

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.

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.

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

We performed a systematic review and meta-analysis of the performance of clinical risk assessment instruments for screening for DXA-determined osteoporosis or low bone density. Commonly evaluated risk instruments showed high sensitivity approaching or exceeding 90% at particular thresholds within various populations but low specificity at thresholds required for high sensitivity. Simpler instruments, such as OST, generally performed as well as or better than more complex instruments.

INTRODUCTION

The purpose of the study is to systematically review the performance of clinical risk assessment instruments for screening for dual-energy X-ray absorptiometry (DXA)-determined osteoporosis or low bone density.

METHODS

Systematic review and meta-analysis were performed. Multiple literature sources were searched, and data extracted and analyzed from included references.

RESULTS

One hundred eight references met inclusion criteria. Studies assessed many instruments in 34 countries, most commonly the Osteoporosis Self-Assessment Tool (OST), the Simple Calculated Osteoporosis Risk Estimation (SCORE) instrument, the Osteoporosis Self-Assessment Tool for Asians (OSTA), the Osteoporosis Risk Assessment Instrument (ORAI), and body weight criteria. Meta-analyses of studies evaluating OST using a cutoff threshold of <1 to identify US postmenopausal women with osteoporosis at the femoral neck provided summary sensitivity and specificity estimates of 89% (95%CI 82-96%) and 41% (95%CI 23-59%), respectively. Meta-analyses of studies evaluating OST using a cutoff threshold of 3 to identify US men with osteoporosis at the femoral neck, total hip, or lumbar spine provided summary sensitivity and specificity estimates of 88% (95%CI 79-97%) and 55% (95%CI 42-68%), respectively. Frequently evaluated instruments each had thresholds and populations for which sensitivity for osteoporosis or low bone mass detection approached or exceeded 90% but always with a trade-off of relatively low specificity.

CONCLUSIONS

Commonly evaluated clinical risk assessment instruments each showed high sensitivity approaching or exceeding 90% for identifying individuals with DXA-determined osteoporosis or low BMD at certain thresholds in different populations but low specificity at thresholds required for high sensitivity. Simpler instruments, such as OST, generally performed as well as or better than more complex instruments.

Investigation of the common paraoxonase 1 variants with paraoxonase activity on bone fragility in Turkish patients

There is increasing evidence of a biochemical link between oxidative stress and bone metabolism. Oxidative stress has been shown to be involved in bone resorption as it causes loss of bone mineral density (BMD). Paraoxonase 1 (PON1), can prevent these effects of the oxidative stress on bone formation. It has been suggested that the PON1 gene as possibly implicated in reduced BMD in bone fragility cases. It has been hypothesized that PON1 gene polymorphisms may influence both the risk of osteoporosis and osteopenia occurrence and prognosis. The aim of our study is to evaluate the relationship between PON1 polymorphisms and bone fragility development. Seventy-four osteoporotic, 121 osteopenic and 79 nonosteoporotic postmenopausal women were recruited. For detection of the polymorphisms, polymerase chain reaction-restriction fragment length polymorphism techniques have been used. BMD was measured at the lumbar spine and hip by dual-energy X-ray absorptiometry. Distributions of PON1 (PON 192 and PON 55) polymorphisms in study groups were not significantly different. But, there was medium strength connection between in the osteopenic with control groups regarding PON1 55-PON1 192 haplotypes and we found a power strength connection between in the osteoporosis with control groups regarding PON1 55-PON1 192 haplotypes. Furthermore, subjects with PON1 192RR and PON1 55LL genotypes had lower PON activity values of osteoporotic subject compared to healthy control and this difference was statistically significant (p < 0.05). This result suggest that PON1 genotypes could be higher risk for osteoporosis, as determined by reduced BMD.

Age, race, weight, and gender impact normative values of bone mineral density

BACKGROUND

Osteoporosis and fractures represent a major public health issue. Accurate normative reference bone mineral density (BMD) values are vital for diagnosing osteoporosis. The generalizability of the T-score method across gender, race, and age in clinic decision-making has been debated. Our aim was to identify the best statistical model to derive normative BMD values in both men and women in the multiethnic United States population.

METHODS

The Third National Health and Nutrition Examination Survey was used as a data source. Gender- and race/ethnicity-stratified data analyses and modeling were conducted on 9779 persons (ages 20 to 65 years) who reported no conditions or medications likely to affect bone metabolism. Sampling and design effects were addressed using STATA 10. Model comparisons were conducted by partial F tests and residual plots.

RESULTS

Polynomial regression provided a statistically significant better fit than linear regression in predicting normative BMD in both men and women. Age-centered polynomial models provided the best model for predicting normative BMD values.

CONCLUSION

The gender- and race-specific lower limit of normal values obtained created a new classification method of low BMD, which might mitigate some of the T-score limitations in men and minority populations.