Cost-effectiveness of Virtual Bone Strength Testing in Osteoporosis Screening Programs for Postmenopausal Women in the United States

Bone health and awareness of osteoporosis in women aged 40 to 60 years in Jiaxing City, China

The objective of this study is to evaluate the pattern of bone mineral density (BMD) in native Jiaxing women, and to investigate their awareness of osteoporosis. A total of 538 native Jiaxing women aged 40 to 60 years were recruited from January 2022 to December 2023 when they had routine examinations in the physical examination center of Jiaxing Maternal and Child Health Hospital. The Chinese version of Osteoporosis Prevention and Cognition Tool was used to evaluate participants' cognitive level of osteoporosis. BMD of participants' lumbar spine (L1-L4) and left hip (Neck/Troch/Ward) was measured by dual-energy X-ray absorptiometry. The mean total score of the awareness about osteoporosis (general knowledge, complications, and prevention) was 22.08 ± 2.74, which was suboptimal. The higher the education level, the higher the score of awareness (P < .01). Medical staff had the highest awareness rate of osteoporosis and the farmer had the lowest. Lumber spine and hip BMD of all sites was significantly decreased with increasing age (P < .001). Premenopausal women had higher BMD than postmenopausal women at all lumbar spine and hip sites (P < .01). The overall frequency of osteoporosis was 10.8% in the lumbar spine, 8.6% in the total hip, and 17.7% in either site. Osteoporosis and osteopenia are highly prevalent among native Jiaxing women but their awareness of osteoporosis is inadequate. To reduce the prevalence of osteoporosis, especially among the unemployed, we should carry out effective health education through multimedia to raise their awareness of osteoporosis. In addition, menopausal hormone therapy should also be considered in menopausal women.

3D Finite Element Models Reconstructed From 2D Dual-Energy X-Ray Absorptiometry (DXA) Images Improve Hip Fracture Prediction Compared to Areal BMD in Osteoporotic Fractures in Men (MrOS) Sweden Cohort

Bone strength is an important contributor to fracture risk. Areal bone mineral density (aBMD) derived from dual-energy X-ray absorptiometry (DXA) is used as a surrogate for bone strength in fracture risk prediction tools. 3D finite element (FE) models predict bone strength better than aBMD, but their clinical use is limited by the need for 3D computed tomography and lack of automation. We have earlier developed a method to reconstruct the 3D hip anatomy from a 2D DXA image, followed by subject-specific FE-based prediction of proximal femoral strength. In the current study, we aim to evaluate the method's ability to predict incident hip fractures in a population-based cohort (Osteoporotic Fractures in Men [MrOS] Sweden). We defined two subcohorts: (i) hip fracture cases and controls cohort: 120 men with a hip fracture (<10 years from baseline) and two controls to each hip fracture case, matched by age, height, and body mass index; and (ii) fallers cohort: 86 men who had fallen the year before their hip DXA scan was acquired, 15 of which sustained a hip fracture during the following 10 years. For each participant, we reconstructed the 3D hip anatomy and predicted proximal femoral strength in 10 sideways fall configurations using FE analysis. The FE-predicted proximal femoral strength was a better predictor of incident hip fractures than aBMD for both hip fracture cases and controls (difference in area under the receiver operating characteristics curve, ΔAUROC = 0.06) and fallers (ΔAUROC = 0.22) cohorts. This is the first time that FE models outperformed aBMD in predicting incident hip fractures in a population-based prospectively followed cohort based on 3D FE models obtained from a 2D DXA scan. Our approach has potential to notably improve the accuracy of fracture risk predictions in a clinically feasible manner (only one single DXA image is needed) and without additional costs compared to the current clinical approach. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Cost-effectiveness of opportunistic QCT-based osteoporosis screening for the prediction of incident vertebral fractures

Objectives

Opportunistic quantitative computed tomography (oQCT) derived from non-dedicated routine CT has demonstrated high accuracy in diagnosing osteoporosis and predicting incident vertebral fractures (VFs). We aimed to investigate the cost-effectiveness of oQCT screening compared to dual-energy X-ray absorptiometry (DXA) as the standard of care for osteoporosis screening.

Methods

Three screening strategies ("no osteoporosis screening", "oQCT screening", and "DXA screening") after routine CT were simulated in a state-transition model for hypothetical cohorts of 1,000 patients (women and men aged 65 years) over a follow-up period of 5 years (base case). The primary outcomes were the cumulative costs and the quality-adjusted life years (QALYs) estimated from a U.S. health care perspective for the year 2022. Cost-effectiveness was assessed based on a willingness-to-pay (WTP) threshold of $70,249 per QALY. The secondary outcome was the number of prevented VFs. Deterministic and probabilistic sensitivity analyses were conducted to test the models' robustness.

Results

Compared to DXA screening, oQCT screening increased QALYs in both sexes (additional 2.40 per 1,000 women and 1.44 per 1,000 men) and resulted in total costs of $3,199,016 and $950,359 vs. $3,262,934 and $933,077 for women and men, respectively. As a secondary outcome, oQCT screening prevented 2.6 and 2.0 additional VFs per 1,000 women and men, respectively. In the probabilistic sensitivity analysis, oQCT screening remained cost-effective in 88.3% (women) and 90.0% (men) of iterations.

Conclusion

oQCT screening is a cost-effective ancillary approach for osteoporosis screening and has the potential to prevent a substantial number of VFs if considered in daily clinical practice.

Cost-effectiveness analysis of ovarian function preservation with GnRH agonist during chemotherapy in premenopausal women with early breast cancer

STUDY QUESTION

Is it economically worthwhile to use GnRH agonist (GnRHa) to prevent menopausal symptoms (MS) and protect fertility in premenopausal women with breast cancer (BC) during chemotherapy from the US perspective?

SUMMARY ANSWER

It is cost-effective to administer GnRHa during chemotherapy in order to forefend MS in premenopausal patients with BC when the willingness-to-pay (WTP) threshold is $50 000.00 per quality-adjusted life-year (QALY), and to preserve fertility in young patients with BC who undergo oocyte cryopreservation (OC), or no OC, when the WTP thresholds per live birth are $71 333.33 and $61 920.00, respectively.

WHAT IS KNOWN ALREADY

Chemotherapy often results in premature ovarian insufficiency (POI) in premenopausal survivors of BC, causing MS and infertility. Administering GnRHa during chemotherapy has been recommended for ovarian function preservation by international guidelines.

STUDY DESIGN, SIZE, DURATION

Two decision-analytic models were developed, respectively, for preventing MS and protecting fertility over a 5-year period, which compared the cost-effectiveness of two strategies: adding GnRHa during chemotherapy (GnRHa plus Chemo) or chemotherapy alone (Chemo).

PARTICIPANTS/MATERIALS, SETTING, METHODS

The participants were early premenopausal women with BC aged 18-49 years who were undergoing chemotherapy. Two decision tree models were constructed: one for MS prevention and one for fertility protection from the US perspective. All data were obtained from published literature and official websites. The models' primary outcomes included QALYs and incremental cost-effectiveness ratios (ICERs). The robustness of the models was tested by sensitivity analyses.

MAIN RESULTS AND THE ROLE OF CHANCE

In the MS model, GnRHa plus Chemo resulted in an ICER of $17 900.85 per QALY compared with Chemo, which was greater than the WTP threshold of $50 000.00 per QALY; therefore, GnRHa plus Chemo was a cost-effective strategy for premenopausal women with BC in the USA. Probabilistic sensitivity analysis (PSA) results showed an 81.76% probability of cost-effectiveness in the strategy. In the fertility model, adding GnRHa for patients undergoing OC and those who were unable to undergo OC resulted in ICERs of $67 933.50 and $60 209.00 per live birth in the USA, respectively. PSA indicated that GnRHa plus Chemo was more likely to be cost-effective over Chemo when the WTP for an additional live birth exceed $71 333.33 in Context I (adding GnRHa to preserve fertility in young patients with BC after OC) and $61 920.00 in Context II (adding GnRHa to preserve fertility in young patients with BC who cannot accept OC).

LIMITATIONS, REASONS FOR CAUTION

The indirect costs, such as disease-related mental impairment and non-medical costs (e.g. transportation cost) were not included. All data were derived from previously published literature and databases, which might yield some differences from the real world. In addition, the POI-induced MS with a lower prevalence and the specific strategy of chemotherapy were not considered in the MS model, and the 5-year time horizon for having a child might not be suitable for all patients in the fertility model.

WIDER IMPLICATIONS OF THE FINDINGS

When considering the economic burden of cancer survivors, the results of this study provide an evidence-based reference for clinical decision-making, showing that it is worthwhile to employ GnRHa during chemotherapy to prevent MS and preserve fertility.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the Natural Science Foundation of Fujian Province [2021J02038]; and the Startup Fund for Scientific Research, Fujian Medical University [2021QH1059]. All authors declare no conflict of interest.

TRIAL REGISTRATION NUMBER

N/A.

AI-based opportunistic CT screening of incidental cardiovascular disease, osteoporosis, and sarcopenia: cost-effectiveness analysis

PURPOSE

To assess the cost-effectiveness and clinical efficacy of AI-assisted abdominal CT-based opportunistic screening for atherosclerotic cardiovascular (CV) disease, osteoporosis, and sarcopenia using artificial intelligence (AI) body composition algorithms.

METHODS

Markov models were constructed and 10-year simulations were performed on hypothetical age- and sex-specific cohorts of 10,000 U.S. adults (base case: 55 year olds) undergoing abdominal CT. Using expected disease prevalence, transition probabilities between health states, associated healthcare costs, and treatment effectiveness related to relevant conditions (CV disease/osteoporosis/sarcopenia) were modified by three mutually exclusive screening models: (1) usual care ("treat none"; no intervention regardless of opportunistic CT findings), (2) universal statin therapy ("treat all" for CV prevention; again, no consideration of CT findings), and (3) AI-assisted abdominal CT-based opportunistic screening for CV disease, osteoporosis, and sarcopenia using automated quantitative algorithms for abdominal aortic calcification, bone mineral density, and skeletal muscle, respectively. Model validity was assessed against published clinical cohorts.

RESULTS

For the base-case scenarios of 55-year-old men and women modeled over 10 years, AI-assisted CT-based opportunistic screening was a cost-saving and more effective clinical strategy, unlike the "treat none" and "treat all" strategies that ignored incidental CT body composition data. Over a wide range of input assumptions beyond the base case, the CT-based opportunistic strategy was dominant over the other two scenarios, as it was both more clinically efficacious and more cost-effective. Cost savings and clinical improvement for opportunistic CT remained for AI tool costs up to $227/patient in men ($65 in women) from the $10/patient base-case scenario.

CONCLUSION

AI-assisted CT-based opportunistic screening appears to be a highly cost-effective and clinically efficacious strategy across a broad array of input assumptions, and was cost saving in most scenarios.

Postmenopausal osteoporosis: current status of bone densitometry

Osteoporosis is the most common of all metabolic bone disorders characterized by loss of bone strength, due to modifications in bone turnover. It leads to bone fragility and increased fracture risk. Because of the increasing aging of the world population, the number of people affected by osteoporosis is continuously increasing. The WHO operational definition of osteoporosis, based on a measurement of bone mineral density (BMD) by dual-energy X-ray absorptiometry (DXA), identifies patients at greatest risk of fracture. However, in the population overall a greater total number of fractures occurs in individuals with BMD values above threshold for osteoporosis diagnosis; for this reason, algorithms have been developed to improve the identification of individuals at high fracture risk, including clinical risk factors for fracture. The correct diagnosis of osteoporosis with an appropriate and accurate use of diagnostic imaging results in better management in terms of adequate treatment and follow-up. Moreover, screening strategies will improve identification of patients who are most likely to benefit from drug treatment to prevent fracture. All women after the age of 65 years previously untested and women after the age of 50 years with previous low trauma fractures should be screened by DXA. In fact, osteoporosis-related fractures cause a significant increase in morbidity and mortality, decreasing the quality of life, with an increasing social and economic burdens. For this reason, fracture risk assessment should be a high priority amongst health measures.

Opportunistic diagnosis of osteoporosis, fragile bone strength and vertebral fractures from routine CT scans; a review of approved technology systems and pathways to implementation

Osteoporosis causes bones to become weak, porous and fracture more easily. While a vertebral fracture is the archetypal fracture of osteoporosis, it is also the most difficult to diagnose clinically. Patients often suffer further spine or other fractures, deformity, height loss and pain before diagnosis. There were an estimated 520,000 fragility fractures in the United Kingdom (UK) in 2017 (costing £4.5 billion), a figure set to increase 30% by 2030. One way to improve both vertebral fracture identification and the diagnosis of osteoporosis is to assess a patient's spine or hips during routine computed tomography (CT) scans. Patients attend routine CT for diagnosis and monitoring of various medical conditions, but the skeleton can be overlooked as radiologists concentrate on the primary reason for scanning. More than half a million CT scans done each year in the National Health Service (NHS) could potentially be screened for osteoporosis (increasing 5% annually). If CT-based screening became embedded in practice, then the technique could have a positive clinical impact in the identification of fragility fracture and/or low bone density. Several companies have developed software methods to diagnose osteoporosis/fragile bone strength and/or identify vertebral fractures in CT datasets, using various methods that include image processing, computational modelling, artificial intelligence and biomechanical engineering concepts. Technology to evaluate Hounsfield units is used to calculate bone density, but not necessarily bone strength. In this rapid evidence review, we summarise the current literature underpinning approved technologies for opportunistic screening of routine CT images to identify fractures, bone density or strength information. We highlight how other new software technologies have become embedded in NHS clinical practice (having overcome barriers to implementation) and highlight how the novel osteoporosis technologies could follow suit. We define the key unanswered questions where further research is needed to enable the adoption of these technologies for maximal patient benefit.

Prediction of femoral osteoporosis using machine-learning analysis with radiomics features and abdomen-pelvic CT: A retrospective single center preliminary study

Background

Osteoporosis has increased and developed into a serious public health concern worldwide. Despite the high prevalence, osteoporosis is silent before major fragility fracture and the osteoporosis screening rate is low. Abdomen-pelvic CT (APCT) is one of the most widely conducted medical tests. Artificial intelligence and radiomics analysis have recently been spotlighted. This is the first study to evaluate the prediction performance of femoral osteoporosis using machine-learning analysis with radiomics features and APCT.

Materials and methods

500 patients (M: F = 70:430; mean age, 66.5 ± 11.8yrs; range, 50–96 years) underwent both dual-energy X-ray absorptiometry and APCT within 1 month. The volume of interest of the left proximal femur was extracted and 41 radiomics features were calculated using 3D volume of interest analysis. Top 10 importance radiomic features were selected by the intraclass correlation coefficient and random forest feature selection. Study cohort was randomly divided into 70% of the samples as the training cohort and the remaining 30% of the sample as the validation cohort. Prediction performance of machine-learning analysis was calculated using diagnostic test and comparison of area under the curve (AUC) of receiver operating characteristic curve analysis was performed between training and validation cohorts.

Results

The osteoporosis prevalence of this study cohort was 20.8%. The prediction performance of the machine-learning analysis to diagnose osteoporosis in the training and validation cohorts were as follows; accuracy, 92.9% vs. 92.7%; sensitivity, 86.6% vs. 80.0%; specificity, 94.5% vs. 95.8%; positive predictive value, 78.4% vs. 82.8%; and negative predictive value, 96.7% vs. 95.0%. The AUC to predict osteoporosis in the training and validation cohorts were 95.9% [95% confidence interval (CI), 93.7%-98.1%] and 96.0% [95% CI, 93.2%-98.8%], respectively, without significant differences (P = 0.962).

Conclusion

Prediction performance of femoral osteoporosis using machine-learning analysis with radiomics features and APCT showed high validity with more than 93% accuracy, specificity, and negative predictive value.

Bone density and strength from thoracic and lumbar CT scans both predict incident vertebral fractures independently of fracture location

In a population-based study, we found that computed tomography (CT)-based bone density and strength measures from the thoracic spine predicted new vertebral fracture as well as measures from the lumbar spine, suggesting that CT scans at either the thorax or abdominal regions are useful to assess vertebral fracture risk.

INTRODUCTION

Prior studies have shown that computed tomography (CT)-based lumbar bone density and strength measurements predict incident vertebral fracture. This study investigated whether CT-based bone density and strength measurements from the thoracic spine predict incident vertebral fracture and compared the performance of thoracic and lumbar bone measurements to predict incident vertebral fracture.

METHODS

This case-control study of community-based men and women (age 74.6 ± 6.6) included 135 cases with incident vertebral fracture at any level and 266 age- and sex-matched controls. We used baseline CT scans to measure integral and trabecular volumetric bone mineral density (vBMD) and vertebral strength (via finite element analysis, FEA) at the T8 and L2 levels. Association between these measurements and vertebral fracture was determined by using conditional logistic regression. Sensitivity and specificity for predicting incident vertebral fracture were determined for lumbar spine and thoracic bone measurements.

RESULTS

Bone measurements from T8 and L2 predicted incident vertebral fracture equally well, regardless of fracture location. Specifically, for predicting vertebral fracture at any level, the odds ratio (per 1-SD decrease) for the vBMD and strength measurements at L2 and T8 ranged from 2.0 to 2.7 (p < 0.0001) and 1.8 to 2.8 (p < 0.0001), respectively. Results were similar when predicting fracture only in the thoracic versus the thoracolumbar spine. Lumbar and thoracic spine bone measurements had similar sensitivity and specificity for predicting incident vertebral fracture.

CONCLUSION

These findings indicated that like those from the lumbar spine, CT-based bone density and strength measurements from the thoracic spine may be useful for identifying individuals at high risk for vertebral fracture.

Triple-Phase Computed Tomography May Replace Dual-Energy X-ray Absorptiometry Scan for Evaluation of Osteoporosis in Liver Transplant Candidates

Assessment of bone density is an important part of liver transplantation (LT) evaluation for early identification and treatment of osteoporosis. Dual-energy X-ray absorptiometry (DXA) is currently the standard clinical test for osteoporosis; however, it may contribute to the appointment burden on LT candidates during the cumbersome evaluation process, and there are limitations affecting its accuracy. In this study, we evaluate the utility of biomechanical analysis of vertebral images obtained during dual-energy abdominal triple-phase computed tomography (TPCT) in diagnosing osteoporosis among LT candidates. We retrospectively reviewed cases evaluated for LT between January 2017 and March 2018. All patients who underwent TPCT within 3 months of DXA were included. The biomechanical computed tomography (BCT) analysis was performed at a centralized laboratory (O.N. Diagnostics, Berkeley, CA) by 2 trained analysts blinded to the DXA data. DXA-based osteoporosis was defined as a T score ≤-2.5 at the hip or spine. BCT-based osteoporosis was defined as vertebral strength ≤4500 N for women or ≤6500 N for men or trabecular volumetric bone mineral density ≤80 mg/cm³ . Comparative data were available for 91 patients who had complete data for both DXA and BCT: 31 women and 60 men, age 54 ± 11 years (mean ± standard deviation), mean body mass index 28 ± 6 kg/m² . Using DXA as the clinical reference, sensitivity of BCT to detect DXA-defined osteoporosis was 83.3% (20/24 patients) and negative predictive value was 91.7%; specificity and positive predictive value were 65.7% and 46.5%, respectively. BCT analysis of vertebral images on triple-phase computed tomography, routinely obtained during transplant evaluation, can reliably rule out osteoporosis in LT candidates. Patients with suspicion of osteoporosis on TPCT may need further evaluation by DXA.

Vertebral fracture assessment (VFA) for osteoporosis screening in US postmenopausal women: is it cost-effective?

Vertebral fracture assessment (VFA) is cost-effective when it was incorporated in the routine screening for osteoporosis in community-dwelling women aged ≥ 65 years, which support guidelines, such as the National Osteoporosis Foundation (NOF) for the diagnostic use of VFA as an important addition to fracture risk assessment.

INTRODUCTION

To evaluate the cost-effectiveness of VFA as a screening tool to reduce future fracture risk in US community-dwelling women aged ≥ 65 years.

METHODS

An individual-level state-transition cost-effectiveness model from a healthcare perspective was constructed using derived data from published literature. The time horizon was lifetime. Five screening strategies were compared, including no screening at all, central dual-energy X-ray absorptiometry (DXA) only, VFA only, central DXA followed by VFA if the femoral neck T-score (FN-T) ≤ - 1.5, or if the FN-T ≤ - 1.0. Various initiation ages and rescreening intervals were evaluated. Oral bisphosphonate treatment for 5-year periods was assumed. Incremental cost-effectiveness ratios (2017 US dollars per quality-adjusted life-year (QALY) gained) were used as the outcome measure.

RESULTS

The incorporation of VFA slightly increased life expectancy by 0.1 years and reduced the number of subsequent osteoporotic fractures by 3.7% and 7.7% compared with using DXA alone and no screening, respectively, leading to approximately 30 billion dollars saved. Regardless of initiation ages and rescreening intervals, central DXA followed by VFA if the FN-T ≤ - 1.0 was most cost-effective ($40,792 per QALY when the screening is initiated at age 65 years and with rescreening every 5 years). Results were robust to change in VF incidence and medication costs.

CONCLUSION

In women aged ≥ 65 years, VFA is cost-effective when it was incorporated in routine screening for osteoporosis. Our findings support the National Osteoporosis Foundation (NOF) guidelines for the diagnostic use of VFA as an important addition to fracture risk assessment.

Traumatic fractures in China from 2012 to 2014: a National Survey of 512,187 individuals

The China National Fracture Study has been conducted to provide a national dataset of traumatic fractures across China. A national representative sample of 512,187 individuals was selected. The population-weighted incidence rates, distribution, injury mechanisms, and risk factors for traumatic fractures were identified for various groups of individuals.

INTRODUCTION

The China National Fracture Study (CNFS) has been conducted to provide a comprehensive and up-to-date national dataset of traumatic fractures across China. This study aims to report the national incidences and distributions of traumatic fractures that occurred in 2012, 2013, and 2014 and to analyze the risk factors.

METHODS

A national representative sample of individuals was selected from 24 rural counties and 24 urban cities of 8 provinces using stratified random sampling and the probability proportional to size (PPS) methodology. Participants were interviewed to identify whether they sustained traumatic fractures of the trunk and/or four extremities that had occurred in 2012, 2013, and 2014. The main risk factors associated with traumatic fractures were analyzed by multiple logistic regression models.

RESULTS

A total of 512,187 individuals, including 259,649 males and 252,538 females, participated in the CNFS. The population-weighted incidence rates of traumatic fractures in China were calculated to be 2.5 (95% CI, 2.2-2.8) per 1000 population in 2012, 2.8 (95% CI, 2.5-3.3) in 2013, and 3.2% (95% CI, 2.8-3.6) in 2014. The population-weighted incidence rates of fragility fractures among participants aged 65 years and older were calculated to be 27.4 (95% CI, 21.4-33.4) per 1000 population in 2012, 36.0 (95% CI, 28.6-43.5) in 2013, and 42.4 (95% CI, 34.9-49.9) in 2014. The most common cause of fracture was low-energy injuries, followed by traffic accidents. For all age groups, sleeping less than 7 h was a risk factor for traumatic fractures. Alcohol consumption and previous fracture history were identified as risk factors for adults aged 15 years and over. Cigarette smoking was found to be a risk factor for males aged 15-64 years old. For individuals aged 15-64 years old, underweight incurred a risk effect for males and overweight for females. Alcohol consumption, sleeping less than 7 h per day, living in the central and eastern regions, a body mass index less of than 18.5, and having a previous fracture history were identified as strong risk factors for fragility fractures.

CONCLUSION

The national incidence, distribution, and injury mechanisms for traumatic fractures were revealed in the CNFS. Risk factors were identified for various groups of individuals.

Biomechanical Computed Tomography analysis (BCT) for clinical assessment of osteoporosis

The surgeon general of the USA defines osteoporosis as "a skeletal disorder characterized by compromised bone strength, predisposing to an increased risk of fracture." Measuring bone strength, Biomechanical Computed Tomography analysis (BCT), namely, finite element analysis of a patient's clinical-resolution computed tomography (CT) scan, is now available in the USA as a Medicare screening benefit for osteoporosis diagnostic testing. Helping to address under-diagnosis of osteoporosis, BCT can be applied "opportunistically" to most existing CT scans that include the spine or hip regions and were previously obtained for an unrelated medical indication. For the BCT test, no modifications are required to standard clinical CT imaging protocols. The analysis provides measurements of bone strength as well as a dual-energy X-ray absorptiometry (DXA)-equivalent bone mineral density (BMD) T-score at the hip and a volumetric BMD of trabecular bone at the spine. Based on both the bone strength and BMD measurements, a physician can identify osteoporosis and assess fracture risk (high, increased, not increased), without needing confirmation by DXA. To help introduce BCT to clinicians and health care professionals, we describe in this review the currently available clinical implementation of the test (VirtuOst), its application for managing patients, and the underlying supporting evidence; we also discuss its main limitations and how its results can be interpreted clinically. Together, this body of evidence supports BCT as an accurate and convenient diagnostic test for osteoporosis in both sexes, particularly when used opportunistically for patients already with CT. Biomechanical Computed Tomography analysis (BCT) uses a patient's CT scan to measure both bone strength and bone mineral density at the hip or spine. Performing at least as well as DXA for both diagnosing osteoporosis and assessing fracture risk, BCT is particularly well-suited to "opportunistic" use for the patient without a recent DXA who is undergoing or has previously undergone CT testing (including hip or spine regions) for an unrelated medical condition.

New Developments in Fracture Risk Assessment for Current Osteoporosis Reports

PURPOSE OF REVIEW

Identifying individuals at high fracture risk can be used to target those likely to derive the greatest benefit from treatment. This narrative review examines recent developments in using specific risk factors used to assess fracture risk, with a focus on publications in the last 3 years.

RECENT FINDINGS

There is expanding evidence for the recognition of individual clinical risk factors and clinical use of composite scores in the general population. Unfortunately, enthusiasm is dampened by three pragmatic randomized trials that raise questions about the effectiveness of widespread population screening using clinical fracture prediction tools given suboptimal participation and adherence. There have been refinements in risk assessment in special populations: men, patients with diabetes, and secondary causes of osteoporosis. New evidence supports the value of vertebral fracture assessment (VFA), high resolution peripheral quantitative CT (HR-pQCT), opportunistic screening using CT, skeletal strength assessment with finite element analysis (FEA), and trabecular bone score (TBS). The last 3 years have seen important developments in the area of fracture risk assessment, both in the research setting and translation to clinical practice. The next challenge will be incorporating these advances into routine work flows that can improve the identification of high risk individuals at the population level and meaningfully impact the ongoing crisis in osteoporosis management.

Medical costs of osteoporosis in the Iranian elderly patients

Background: In the coming years and near future, Iran will experience a main demographic transition resulting in an aging phenomenon and increased number of people over 65 years. Aging leads to increased medical expenditures associated with chronic diseases such as osteoporosis. This study aimed to investigate the patient-specific hospitalization costs of osteoporosis treatment in elderly patients.

Methods: A retrospective cost analysis of hospitalization arising from osteoporosis conducted on all the elderly patients (adults aged 65 years and above) in a teaching hospital in Tehran through examining hospital admissions during 2017. The elderly patients consisted of 295 with a length of stay ≥ 24 hours. Cost analysis was performed using a bottom-up micro-costing approach and payer perspective (patient and insurer); and the result was statistically significant (p≤0.05). Nonparametric tests, including Mann–Whitney and Kruskal–Wallis tests, were used to investigate the relationship between affecting variables. Hospital training was considered as a control variable. The data were analyzed using SPSS 11 software

Results: The mean age of the patients was 71.3 years; of the patients, 79% were female and 21% male. The overall crude prevalence of osteoporosis was 80% among people ≥ 65 years and 85% among patients who experienced relevant surgeries. The average cost of hospitalization was $3794.13. Also, 3 main areas of hospital costs were identified: consumables (57.70%), hoteling (17.24%), and surgical services (15.76%). The prevalence of osteoporosis was 4 times higher in women compared with men. Moreover, there were significant differences between the variables affecting hospital costs, such as gender, length of stay, diagnosis, intensive care unit services, and surgery (p<0.05).

Conclusion: Age-associated diseases such as osteoporosis increase the health care costs. The dominant cost drivers in this study were the consumables, hoteling, and surgical services, respectively. Policymakers and health care planners should consider such variables as gender, previous surgeries in the patients’ records, length of stay, and intensive care unit services as driving factors and determinants of hospital costs for older seniors with osteoporosis.

Predicting bone strength from CT data: Clinical applications

In this review we summarise over 15 years of research and development around the prediction of whole bones strength from Computed Tomography data, with particular reference to the prediction of the risk of hip fracture in osteoporotic patients. We briefly discuss the theoretical background, and then provide a summary of the laboratory and clinical validation of these modelling technologies. We then discuss the three current clinical applications: in clinical research, in clinical trials, and in clinical practice. On average the strength predicted with finite element models (QCT-FE) based on computed tomography is 7% more accurate that that predicted with areal bone mineral density from Dual X-ray Absorptiometry (DXA-aBMD), the current standard of care, both in term of laboratory validation on cadaver bones and in terms of stratification accuracy on clinical cohorts of fractured and non-fractured women. This improved accuracy makes QCT-FE superior to DXA-aBMD in clinical research and in clinical trials, where the its use can cut in half the number of patients to be enrolled to get the same statistical power. For routine clinical use to decide who to treat with antiresorptive drugs, QCT-FE is more accurate but less cost-effective than DXA-aBMD, at least when the decision is on first line treatment like bisphosphonates. But the ability to predict skeletal strength from medical imaging is now opening a number of other applications, for example in paediatrics and oncology.

Cost-Effectiveness of Osteoporosis Screening Using Biomechanical Computed Tomography for Patients With a Previous Abdominal CT

Osteoporosis screening rates by DXA are low (9.5% women, 1.7% men) in the US Medicare population aged 65 years and older. Addressing this care gap, we estimated the benefits of a validated osteoporosis diagnostic test suitable for patients age 65 years and older with an abdominal computed tomography (CT) scan taken for any indication but without a recent DXA. Our analysis assessed a hypothetical cohort of 1000 such patients in a given year, and followed them for 5 years. Separately for each sex, we used Markov modeling to compare two mutually exclusive scenarios: (i) utilizing the CT scans, perform one-time "biomechanical computed tomography" (BCT) analysis to identify high-risk patients on the basis of both femoral strength and hip BMD T-scores; (ii) ignore the CT scan, and rely instead on usual care, consisting of future annual DXA screening at typical Medicare rates. For patients with findings indicative of osteoporosis, 50% underwent 2 years of treatment with alendronate. We found that BCT provided greater clinical benefit at lower cost for both sexes than usual care. In our base case, compared to usual care, BCT prevented hip fractures over a 5-year window (3.1 per 1000 women; 1.9 per 1000 men) and increased quality-adjusted life years (2.95 per 1000 women; 1.48 per 1000 men). Efficacy and savings increased further for higher-risk patient pools, greater treatment adherence, and longer treatment duration. When the sensitivity and specificity of BCT were set to those for DXA, the prevented hip fractures versus usual care remained high (2.7 per 1000 women; 1.5 per 1000 men), indicating the importance of high screening rates on clinical efficacy. Therefore, for patients with a previously taken abdominal CT and without a recent DXA, osteoporosis screening using biomechanical computed tomography may be a cost-effective alternative to current usual care. © 2019 American Society for Bone and Mineral Research.

Findings of CT-Derived Bone Strength Assessment in Inflammatory Bowel Disease Patients Undergoing CT Enterography in Clinical Practice

BACKGROUND

Inflammatory bowel disease (IBD) patients are at risk of developing complications from metabolic bone disease, but the exact prevalence is unknown. We evaluated fracture risk in IBD patients using (1) biomechanical CT analysis (BCT) using bone strength and bone mineral density (BMD), (2) Cornerstone guidelines, and (3) other clinical features predicting fracture risk.

METHODS

A retrospective review of consecutive IBD patients who underwent CT enterography (CTE) with BCT from March 2014 to March 2017 was performed. Measured outcomes were overall fracture risk classification (not increased, increased, or high) and femoral neck BMD World Health Organization classification (normal, osteopenia, or osteoporosis).

RESULTS

Two hundred fifty-seven patients with IBD underwent CTE and BCT. Fracture risk was classified as not increased in 45.5% (116/255) of patients, increased in 44.7% (114/255), and high in 9.8% (25/255). Femoral neck BMD was classified as normal in 56.8% (142/250), osteopenia in 37.6% (94/250), and osteoporosis in 5.6% (14/250). In multivariate analysis, only increasing age was associated with increased fracture risk (odds ratio, 1.06; 95% confidence interval, 1.04-1.08; P < 0.001). Cornerstone guidelines were met by 35.3% (41/116), 56.1% (64/114), and 76.0% (19/25) of patients in the not increased, increased, and high-risk groups, respectively (P = 0.0001). No Cornerstone criteria were met by 40% (56/139) of patients in the increased and high-risk groups.

CONCLUSIONS

Using BCT, increased or high fracture risk was detected in more than half of this cohort, the prevalence being associated with increased age. A significant proportion of patients with increased or high fracture risk did not meet Cornerstone guidelines. Therefore, IBD patients who do not meet Cornerstone guidelines may benefit from BCT screening.

Prediction of incident vertebral fracture using CT-based finite element analysis

Prior studies show vertebral strength from computed tomography-based finite element analysis may be associated with vertebral fracture risk. We found vertebral strength had a strong association with new vertebral fractures, suggesting that vertebral strength measures identify those at risk for vertebral fracture and may be a useful clinical tool.

INTRODUCTION

We aimed to determine the association between vertebral strength by quantitative computed tomography (CT)-based finite element analysis (FEA) and incident vertebral fracture (VF). In addition, we examined sensitivity and specificity of previously proposed diagnostic thresholds for fragile bone strength and low BMD in predicting VF.

METHODS

In a case-control study, 26 incident VF cases (13 men, 13 women) and 62 age- and sex-matched controls aged 50 to 85 years were selected from the Framingham multi-detector computed tomography cohort. Vertebral compressive strength, integral vBMD, trabecular vBMD, CT-based BMC, and CT-based aBMD were measured from CT scans of the lumbar spine.

RESULTS

Lower vertebral strength at baseline was associated with an increased risk of new or worsening VF after adjusting for age, BMI, and prevalent VF status (odds ratio (OR) = 5.2 per 1 SD decrease, 95% CI 1.3-19.8). Area under receiver operating characteristic (ROC) curve comparisons revealed that vertebral strength better predicted incident VF than CT-based aBMD (AUC = 0.804 vs. 0.715, p = 0.05) but was not better than integral vBMD (AUC = 0.815) or CT-based BMC (AUC = 0.794). Additionally, proposed fragile bone strength thresholds trended toward better sensitivity for identifying VF than that of aBMD-classified osteoporosis (0.46 vs. 0.23, p = 0.09).

CONCLUSION

This study shows an association between vertebral strength measures and incident vertebral fracture in men and women. Though limited by a small sample size, our findings also suggest that bone strength estimates by CT-based FEA provide equivalent or better ability to predict incident vertebral fracture compared to CT-based aBMD. Our study confirms that CT-based estimates of vertebral strength from FEA are useful for identifying patients who are at high risk for vertebral fracture.

Artificial Intelligence Applied to Osteoporosis: A Performance Comparison of Machine Learning Algorithms in Predicting Fragility Fractures From MRI Data

BACKGROUND

A current challenge in osteoporosis is identifying patients at risk of bone fracture.

PURPOSE

To identify the machine learning classifiers that predict best osteoporotic bone fractures and, from the data, to highlight the imaging features and the anatomical regions that contribute most to prediction performance.

STUDY TYPE

Prospective (cross-sectional) case-control study.

POPULATION

Thirty-two women with prior fragility bone fractures, of mean age = 61.6 and body mass index (BMI) = 22.7 kg/m² , and 60 women without fractures, of mean age = 62.3 and BMI = 21.4 kg/m² . Field Strength/ Sequence: 3D FLASH at 3T.

ASSESSMENT

Quantitative MRI outcomes by software algorithms. Mechanical and topological microstructural parameters of the trabecular bone were calculated for five femoral regions, and added to the vector of features together with bone mineral density measurement, fracture risk assessment tool (FRAX) score, and personal characteristics such as age, weight, and height. We fitted 15 classifiers using 200 randomized cross-validation datasets. Statistical Tests: Data: Kolmogorov-Smirnov test for normality. Model Performance: sensitivity, specificity, precision, accuracy, F1-test, receiver operating characteristic curve (ROC). Two-sided t-test, with P < 0.05 for statistical significance.

RESULTS

The top three performing classifiers are RUS-boosted trees (in particular, performing best with head data, F1 = 0.64 ± 0.03), the logistic regression and the linear discriminant (both best with trochanteric datasets, F1 = 0.65 ± 0.03 and F1 = 0.67 ± 0.03, respectively). A permutation of these classifiers comprised the best three performers for four out of five anatomical datasets. After averaging across all the anatomical datasets, the score for the best performer, the boosted trees, was F1 = 0.63 ± 0.03 for All-features dataset, F1 = 0.52 ± 0.05 for the no-MRI dataset, and F1 = 0.48 ± 0.06 for the no-FRAX dataset. Data Conclusion: Of many classifiers, the RUS-boosted trees, the logistic regression, and the linear discriminant are best for predicting osteoporotic fracture. Both MRI and FRAX independently add value in identifying osteoporotic fractures. The femoral head, greater trochanter, and inter-trochanter anatomical regions within the proximal femur yielded better F1-scores for the best three classifiers.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1029-1038.

Osteoporosis and Hip Fracture Risk From Routine Computed Tomography Scans: The Fracture, Osteoporosis, and CT Utilization Study (FOCUS)

Methods now exist for analyzing previously taken clinical computed tomography (CT) scans to measure a dual-energy X-ray absorptiometry (DXA)-equivalent bone mineral density (BMD) at the hip and a finite element analysis-derived femoral strength. We assessed the efficacy of this "biomechanical CT" (BCT) approach for identifying patients at high risk of incident hip fracture in a large clinical setting. Using a case-cohort design sampled from 111,694 women and men aged 65 or older who had a prior hip CT scan, a DXA within 3 years of the CT, and no prior hip fracture, we compared those with subsequent hip fracture (n = 1959) with randomly selected sex-stratified controls (n = 1979) and analyzed their CT scans blinded to all other data. We found that the age-, race-, and body mass index (BMI)-adjusted hazard ratio (HR; per standard deviation) for femoral strength was significant before (women: HR = 2.8, 95% confidence interval [CI] 2.2-3.5; men: 2.8, 2.1-3.7) and after adjusting also for the (lowest) hip BMD T-score by BCT (women: 2.1, 1.4-3.2; men: 2.7, 1.6-4.6). The hazard ratio for the hip BMD T-score was similar between BCT and DXA for both sexes (women: 2.1, 1.8-2.5 BCT versus 2.1, 1.7-2.5 DXA; men: 2.8, 2.1-3.8 BCT versus 2.5, 2.0-3.2 DXA) and was higher than for the (lowest) spine/hip BMD T-score by DXA (women: 1.6, 1.4-1.9; men: 2.1, 1.6-2.7). Compared with the latter as a clinical-practice reference and using both femoral strength and the hip BMD T-score from BCT, sensitivity for predicting hip fracture was higher for BCT (women: 0.66 versus 0.59; men: 0.56 versus 0.48), with comparable respective specificity (women: 0.66 versus 0.67; men: 0.76 versus 0.78). We conclude that BCT analysis of previously acquired routine abdominal or pelvic CT scans is at least as effective as DXA testing for identifying patients at high risk of hip fracture. © 2018 American Society for Bone and Mineral Research.

Are CT-Based Finite Element Model Predictions of Femoral Bone Strength Clinically Useful?

PURPOSE OF REVIEW

This study reviews the available literature to compare the accuracy of areal bone mineral density derived from dual X-ray absorptiometry (DXA-aBMD) and of subject-specific finite element models derived from quantitative computed tomography (QCT-SSFE) in predicting bone strength measured experimentally on cadaver bones, as well as their clinical accuracy both in terms of discrimination and prediction. Based on this information, some basic cost-effectiveness calculations are performed to explore the use of QCT-SSFE instead of DXA-aBMD in (a) clinical studies with femoral strength as endpoint, (b) predictor of the risk of hip fracture in low bone mass patients.

RECENT FINDINGS

Recent improvements involving the use of smooth-boundary meshes, better anatomical referencing for proximal-only scans, multiple side-fall directions, and refined boundary conditions increase the predictive accuracy of QCT-SSFE. If these improvements are adopted, QCT-SSFE is always preferable over DXA-aBMD in clinical studies with femoral strength as the endpoint, while it is not yet cost-effective as a hip fracture risk predictor, although pathways that combine both QCT-SSFE and DXA-aBMD are promising.