Among people on osteoporosis medication, loss of appendicular or total body lean mass is an independent risk factor for hip and major osteoporotic fractures.

People with prior lean mass loss had a ~ 10% higher risk of MOF and ~ 22-26% higher risk of hip fracture, and the results were similar in people on anti-osteoporosis medications. Loss of lean mass is associated with increased fracture risk. Patients should be encouraged to pursue strategies to prevent loss of lean mass. BACKGROUND: Sarcopenia increases fracture risk. If the risk persists after starting osteoporosis medication, patients may need to be encouraged to pursue strategies to prevent loss of lean mass. OBJECTIVE: To estimate the effects of loss in appendicular lean mass (ALM) or total body lean mass (TBLM) on subsequent fracture risk and effect modification with anti-osteoporosis medication use. METHODS: We conducted a registry-based cohort study linked to population-based data. We identified individuals ≥ 40 years of age with two DXA assessments ≥ 1 year apart and minimum 0.5 years of observation. ALM and TBLM were estimated from weight, sex, and percent fat from DXA (R2 = 0.91 and 0.84 vs total body DXA, respectively). We report hazard ratios (HR) from Cox regression models estimating time to first incident major osteoporotic fracture (MOF) and hip fracture, adjusted for fracture risk; osteoporosis medication was included as an interaction term and used to stratify analyses. RESULTS: We included 21,249 individuals (mean 67 [SD 10] years, 95% female, 37% on osteoporosis medication). The mean follow-up was 7 years (SD 4). A total of 1868 and 548 people had incident MOF and hip fracture, respectively. People with prior ALM loss (HR per SD 1.09, 95% CI 1.04-1.15) or TBLM loss (HR per SD 1.09, 95% CI 1.42-1.14) had a higher risk of MOF. Hip fracture risk was greater in people with prior ALM loss (HR per SD 1.22, 95% CI 1.12-1.33) and TBLM loss (HR per SD 1.26, 95% CI 1.16-1.38). There were no interactions with anti-osteoporosis medication use (all p > 0.3). When restricted to people on anti-osteoporosis medication, each SD in ALM or TBLM loss was associated with 8-9% increased MOF risk and 18-23% increased hip fracture risk. CONCLUSIONS: Loss of lean mass is associated with increased fracture risk among individuals on anti-osteoporosis medication. Patients should be encouraged to pursue strategies to prevent sarcopenia.

Treatment reclassification in Canada from the Osteoporosis Canada 2023 clinical practice guidelines: the Manitoba BMD Registry.

Osteoporosis Canada 2023 clinical practice guidelines increase the number of individuals recommended or suggested for anti-osteoporosis pharmacotherapy by refining treatment guidance for those who fell within the 2010 guidelines' moderate-risk category. PURPOSE: In 2023, Osteoporosis Canada updated its 2010 clinical practice guidelines based upon consideration of fracture history, 10-year major osteoporotic fracture (MOF) risk, and BMD T-score in conjunction with age. The 2023 guidelines eliminated risk categories, including the moderate-risk group that did not provide clear treatment guidance. The current study was performed to appreciate the implications of the shift from 2010 risk categories to 2023 treatment guidance. METHODS: The study population consisted of 79,654 individuals age ≥ 50 years undergoing baseline DXA testing from January 1996 to March 2018. Each individual was assigned to mutually exclusive categories based on 2010 and 2023 guideline recommendations. Treatment qualification, 10-year predicted and 10-year observed MOF risk were compared. RESULTS: Treatment reclassification under the 2023 guidelines only affected 33.8% of individuals in the 2010 moderate-risk group, with 13.0% assigned to no treatment, 14.4% to suggest treatment, and 6.4% to recommend treatment. During the mean follow-up of 7.2 years, 6364 (8.0%) individuals experienced one or more incidents of MOF. The observed 10-year cumulative incidence of MOF in the study population was 10.5% versus the predicted 10.7% (observed to predicted mean calibration ratio 0.98, 95% CI 0.96-1.00). Individuals reclassified from 2010 moderate risk to 2023 recommend treatment were at greater MOF risk than those in the 2010 moderate-risk group assigned to 2023 suggest treatment or no treatment, but at lower risk than those in the 2010 high-risk group. CONCLUSIONS: Osteoporosis Canada 2023 clinical practice guidelines affect individuals within the 2010 moderate-risk category, increasing the number for whom anti-osteoporosis pharmacotherapy is recommended or suggested. Increased treatment could reduce the population burden of osteoporotic fractures, though moderate-risk individuals now qualifying for treatment have a lower predicted and observed fracture risk than high-risk individuals recommended for treatment under the 2010 guidelines.

The prognostic value of single photon emission computed tomography (SPECT) myocardial perfusion imaging is independent of left ventricular size.

Many variables have been shown to impact accuracy and prognostic power of myocardial perfusion imaging (MPI); however, effects of left ventricular size have not been extensively studied. In particular, perfusion defects in smaller hearts could be overlooked due to partial volume averaging, potentially reducing the prognostic power of MPI. We determined stress total perfusion deficit (TPD) and rest end diastolic volume (REDV) from single photon emission computed tomography (SPECT) MPI in consecutive patients without pathologically dilated left ventricles. Area under the curve (AUC) and Cox regression analysis were used to assess prediction of subsequent major adverse cardiac events [MACE-death, hospitalized acute myocardial infarction (AMI), hospitalized unstable angina, late revascularization]. Analyses were stratified by sex and REDV tertile. The analytic population included 2,503 patients (965 men and 1,538 women). Outcomes were assessed over an average of 6.4±2.3 years. MACE was observed in 254 (26.3%) of 965 men and 261 (17.0%) of 1,538 women. Stress TPD showed significant AUCs for stratifying MACE risk regardless of sex and REDV tertile (all P<0.05). In Cox regression analysis, increasing stress TPD (but not REDV) was associated with MACE in both men and women. There was no significant TPD*REDV interaction. In conclusion, we found the prognostic power of SPECT MPI to be independent of left ventricular size.

Development and reporting of artificial intelligence in osteoporosis management.

An abundance of medical data and enhanced computational power have led to a surge in Artificial Intelligence (AI) applications. Published studies involving AI in bone and osteoporosis research have increased exponentially, raising the need for transparent model development and reporting strategies. This review offers a comprehensive overview and systematic quality assessment of AI articles in osteoporosis while highlighting recent advancements. A systematic search in the PubMed database, from December 17th, 2020, to February 1st, 2023 was conducted to identify AI articles that relate to osteoporosis. The quality assessment of the studies relied on the systematic evaluation of 12 quality items derived from the MI-CLAIM checklist. The systematic search yielded 97 articles that fell into five areas; bone properties assessment (11 articles), osteoporosis classification (26 articles), fracture detection/classification (25 articles), risk prediction (24 articles) and bone segmentation (11 articles). The average quality score for each study area was 8.9 (range: 7-11) for bone properties assessment, 7.8 (range: 5-11) for osteoporosis classification, 8.4 (range: 7-11) for fracture detection, 7.6 (range: 4-11) for risk prediction, and 9.0 (range: 6-11) for bone segmentation. A 6th area, AI-driven clinical decision support, identified the studies from the five preceding areas which aimed to improve clinician efficiency, diagnostic accuracy and patient outcomes through AI-driven models and opportunistic screening by automating or assisting with specific clinical tasks in complex scenarios. The current work highlights disparities in study quality and a lack of standardized reporting practices. Despite these limitations, a wide range of models and examination strategies have shown promising outcomes to aid in the earlier diagnosis and improve clinical decision making. Through careful consideration of sources of bias in model performance assessment, the field can build confidence in AI-based approaches, ultimately leading to improved clinical workflows and patient outcomes.

This review covers the recent advancements in artificial intelligence (AI) for managing osteoporosis, an increasingly prevalent condition that weakens bone tissues and increases fracture risk. Analyzing 97 studies from December 2020 to February 2023, the present work highlights how AI enhances bone properties assessment, osteoporosis classification, fracture detection and classification, risk prediction, and bone segmentation. A systematic qualitative assessment of the studies revealed improvements in study quality compared with the earlier review period, supported by innovative and more explainable AI approaches. AI shows promise in clinical decision support by offering novel screening tools that can help in the earlier identification of the disease, improve clinical workflows and patient prognosis. New pre-processing strategies and advanced model architectures have played a critical role in these improvements. Researchers have enhanced the accuracy and predictive performance of traditional methods by integrating clinical data with imaging data through advanced multi-factorial AI techniques. These innovations, paired with standardized development and validation processes, promise to personalize medicine and enhance patient care in osteoporosis management.

The Effect of Smoking Cessation versus Current Smoking on Fracture Risk: The Manitoba BMD Registry.

Current tobacco smoking is included in FRAXTM calculator for fracture risk assessment. It is unknown whether previous smoking increases the risk of fracture. The current analysis was performed to compare incident fracture risk associated with current smoking, smoking cessation and non-smoking. The study population comprised 18,115 individuals aged 40 years and older (mean age 68.8 years, 95.1% female) from a large clinical registry of DXA tests for the Province of Manitoba, Canada, with two consecutive visits (mean interval 4.4 years) where current smoking was recorded. Smokers (N=1620) were defined as those reporting current smoking at visit 2 (index date), non-smokers (N=15,942) as answering no to current smoking at both visits, and ex-smokers (N=553) as answering yes to current smoking at visit 1 but no at visit 2. Incident fractures were identified through healthcare data linkage. Compared with non-smokers, risk for any incident fracture (primary outcome) was significantly greater in current smokers (hazard ratio [HR] 1.41, 95% CI 1.19-1.67 adjusted for age/sex; HR 1.22, 95% CI 1.03-1.44 full adjusted) and ex-smokers (HRs 1.56, 95% CI 1.19-2.024 and 1.42, 95% CI 1.09-1.86, respectively). Similar directions and magnitudes of effect were seen for incident major osteoporotic fractures and hip fractures (secondary outcomes), with point estimates for ex-smokers that were close to current smokers. In summary, recent smoking cessation was associated with ongoing increased short-term fracture risk similar to current smoking. Larger studies are needed to better define the time course of fracture risk after smoking cessation.

Bone Mineral Density Monitoring in Contiguous versus Non-Contiguous Lumbar Vertebrae: The Manitoba BMD Registry.

INTRODUCTION: Only change in bone mineral density (BMD) on repeat DXA that exceeds the 95% least significant change (LSC) should be considered clinically meaningful. Frequently lumbar spine DXA must be reported after omitting vertebrae with localized structural artifact, which reduces measurement precision. Previous reports have raised concerns of higher least significant change (LSC) when spine BMD is based on non-contiguous rather than contiguous vertebrae. The current study was performed to compare lumbar spine LSC and BMD response to intervening anti-osteoporosis medication use from non-contiguous versus contiguous vertebrae. METHODOLOGY: LSCs for lumbar spine DXA based on L1-L4 and all combinations of non-contiguous and contiguous vertebrae were calculated using 879 scan-pairs from the Manitoba BMD Program. We compared BMD change from these regions, overall and in relation to intervening anti-osteoporosis medication use, in 11,722 patients who had 2 DXA examinations. RESULTS: LSCs were slightly greater when calculated from combinations of fewer than 4 vertebrae, but there was no meaningful difference between contiguous versus non-contiguous vertebrae. There were consistently high correlations between lumbar spine BMD change from L1-L4 and all combinations of continuous and non-contiguous vertebrae (all Pearson r≥ 0.9, p<0.001). Percentage changes in spine BMD and the fraction with treatment-concordant change exceeding the LSC were similar using contiguous or non-contiguous vertebrae. CONCLUSIONS: Lumbar spine BMD change can be assessed from 2 or 3 non-contiguous vertebrae when clinically necessary, and precision in such cases is similar to using contiguous vertebrae. Non-contiguous vertebrae can detect treatment-concordant changes similar in spine BMD to contiguous vertebrae.

Hip Fracture Risk Assessment Tools for Adults Aged 80 Years and Older.

Importance: While adults aged 80 years and older account for 70% of hip fractures in the US, performance of fracture risk assessment tools in this population is uncertain. Objective: To compare performance of the Fracture Risk Assessment Tool (FRAX), Garvan Fracture Risk Calculator, and femoral neck bone mineral density (FNBMD) alone in 5-year hip fracture prediction. Design, Setting and Participants: Prognostic analysis of 3 prospective cohort studies including participants attending an index examination (1997 to 2016) at age 80 years or older. Data were analyzed from March 2023 to April 2024. Main Outcomes and Measures: Participants contacted every 4 or 6 months after index examination to ascertain incident hip fractures and vital status. Predicted 5-year hip fracture probabilities calculated using FRAX and Garvan models incorporating FNBMD and FNBMD alone. Model discrimination assessed by area under receiver operating characteristic curve (AUC). Model calibration assessed by comparing observed vs predicted hip fracture probabilities within predicted risk quintiles. Results: A total of 8890 participants were included, with a mean (SD) age at index examination of 82.6 (2.7) years; 4906 participants (55.2%) were women, 866 (9.7%) were Black, 7836 (88.1%) were White, and 188 (2.1%) were other races and ethnicities. During 5-year follow-up, 321 women (6.5%) and 123 men (3.1%) experienced a hip fracture; 818 women (16.7%) and 921 men (23.1%) died before hip fracture. Among women, AUC was 0.69 (95% CI, 0.67-0.72) for FRAX, 0.69 (95% CI, 0.66-0.72) for Garvan, and 0.72 (95% CI, 0.69-0.75) for FNBMD alone (FNBMD superior to FRAX, P = .01; and Garvan, P = .01). Among men, AUC was 0.71 (95% CI, 0.66-0.75) for FRAX, 0.76 (95% CI, 0.72-0.81) for Garvan, and 0.77 (95% CI, 0.72-0.81) for FNBMD alone (P < .001 Garvan and FNBMD alone superior to FRAX). Among both sexes, Garvan greatly overestimated hip fracture risk among individuals in upper quintiles of predicted risk, while FRAX modestly underestimated risk among those in intermediate quintiles of predicted risk. Conclusions and Relevance: In this prognostic study of adults aged 80 years and older, FRAX and Garvan tools incorporating FNBMD compared with FNBMD alone did not improve 5-year hip fracture discrimination. FRAX modestly underpredicted observed hip fracture probability in intermediate-risk individuals. Garvan markedly overpredicted observed hip fracture probability in high-risk individuals. Until better prediction tools are available, clinicians should prioritize consideration of hip BMD, life expectancy, and patient preferences in decision-making regarding drug treatment initiation for hip fracture prevention in late-life adults.

Introduction of an order set after hip fracture improves osteoporosis medication initiation and persistence: a population-based before-after analysis.

We found that a standardized order set after hip fracture increased initiation of anti-osteoporosis medication and increased persistence at 1 year, but did not reduce secondary fractures. BACKGROUND: A treatment gap exists after osteoporosis-related fractures. Introducing standardized care can improve treatment. We evaluated the impact of a hip fracture order set (OS) on anti-osteoporosis medication (AOM) initiation, persistence, and secondary fracture prevention. METHODS: In 2015, one hospital in Manitoba, Canada, introduced a hip fracture OS including recommendations for the initiation of AOM (OS group). A control group was identified from the other hospitals in the same region. A retrospective cohort study was conducted using linked administrative health data. All individuals 50 + years with surgical treatment for low-energy hip fracture between 2010 and 2019 were included and followed for AOM initiation, medication persistence at 1 year, and secondary fractures. Between-group differences for each year were assessed using chi-square tests. Logistic regression models tested the impact of socio-demographic and clinical factors on initiation, persistence of AOM. Cox regression tested the risk of secondary fracture. RESULTS: No baseline differences between OS group (813 patients) and control group (2150 patients) were observed in demographics, socioeconomic factors, or comorbidities. An increase in post-fracture AOM initiation was seen with OS introduction (OS group year before 16.7% versus year after 48.6%, p < 0.001). No change was seen in the control group. Persistence on AOM also increased (OS group year before 17.7% versus year after 28.4%, p < 0.001). No difference in secondary fractures was observed (OS group 19.8% versus control group 18.8%, p = 0.38). CONCLUSION: Introduction of a hip fracture OS significantly increased AOM initiation and persistence at 1-year post-fracture. There was no significant difference in secondary fractures.

The potential role for artificial intelligence in fracture risk prediction.

Osteoporotic fractures are a major health challenge in older adults. Despite the availability of safe and effective therapies for osteoporosis, these therapies are underused in individuals at high risk for fracture, calling for better case-finding and fracture risk assessment strategies. Artificial intelligence (AI) and machine learning (ML) hold promise for enhancing identification of individuals at high risk for fracture by distilling useful features from high-dimensional data derived from medical records, imaging, and wearable devices. AI-ML could enable automated opportunistic screening for vertebral fractures and osteoporosis, home-based monitoring and intervention targeting lifestyle factors, and integration of multimodal features to leverage fracture prediction, ultimately aiding improved fracture risk assessment and individualised treatment. Optimism must be balanced with consideration for the explainability of AI-ML models, biases (including information inequity in numerically under-represented populations), model limitations, and net clinical benefit and workload impact. Clinical integration of AI-ML algorithms has the potential to transform osteoporosis management, offering a more personalised approach to reduce the burden of osteoporotic fractures.

Fracture Risk Associated with Different Numbers and Combinations of Lumbar Vertebrae: The Manitoba BMD Registry.

Bone mineral density (BMD) is widely used for assessment of fracture risk. For the lumbar spine, BMD is typically measured from L1-L4 as it provides the largest area for assessment with the best measurement precision. Structural artifact often confounds spine BMD in clinical practice, and the International Society for Clinical Densitometry (ISCD) recommends removing vertebrae with artifact when reporting spine BMD. In its most recent position statements, the ISCD recommended against the use of a single vertebra when reporting spine BMD but stated that further studies should be done. The current analysis was performed to compare the performance of BMD from different numbers and combination of vertebral levels on fracture prediction in a large clinical registry of DXA tests for the Province of Manitoba, Canada. The study population comprised 39,727 individuals aged 40 years and older (mean age 62.7 years, 91.0 % female) with baseline DXA after excluding those with evidence of structural artifact. Mean follow-up for ascertaining fracture outcomes was 8.7 years. Area under the curve (AUC) for incident fracture risk stratification was statistically significant regardless of the BMD measurement site or fracture outcome. AUC differences with the various numbers and combinations of vertebral levels including a single vertebral body were small (less than or equal to 0.01). More substantial AUC differences were seen for femoral neck and total hip BMD versus L1-L4 BMD, approaching 0.1 for hip fracture stratification. In summary, we found that using combinations of fewer than 4 vertebrae including individual lumbar vertebrae predicted incident fractures. Importantly, differences between these different combinations were small when compared with L1-L4. Spine BMD was a better predictor of incident spine fracture compared to the hip, whereas the hip was better for hip fracture and overall fracture prediction.

Simultaneous automated ascertainment of prevalent vertebral fracture and abdominal aortic calcification in clinical practice: role in fracture risk assessment.

Whether simultaneous automated ascertainments of prevalent vertebral fracture (auto-PVFx) and abdominal aortic calcification (auto-AAC) on vertebral fracture assessment (VFA) lateral spine bone density (BMD) images jointly predict incident fractures in routine clinical practice is unclear. We estimated the independent associations of auto-PVFx and auto-AAC primarily with incident major osteoporotic and secondarily with incident hip and any clinical fractures in 11 013 individuals (mean [SD] age 75.8 [6.8] years, 93.3% female) who had a BMD test combined with VFA between March 2010 and December 2017. Auto-PVFx and auto-AAC were ascertained using convolutional neural networks (CNNs). Proportional hazards models were used to estimate the associations of auto-PVFx and auto-AAC with incident fractures over a mean (SD) follow-up of 3.7 (2.2) years, adjusted for each other and other risk factors. At baseline, 17% (n = 1881) had auto-PVFx and 27% (n = 2974) had a high level of auto-AAC (≥ 6 on scale of 0 to 24). Multivariable-adjusted hazard ratios (HR) for incident major osteoporotic fracture (95% CI) were 1.85 (1.59, 2.15) for those with compared with those without auto-PVFx, and 1.36 (1.14, 1.62) for those with high compared with low auto-AAC. The multivariable-adjusted HRs for incident hip fracture were 1.62 (95% CI, 1.26 to 2.07) for those with compared to those without auto-PVFx, and 1.55 (95% CI, 1.15 to 2.09) for those high auto-AAC compared with low auto-AAC. The 5-year cumulative incidence of major osteoporotic fracture was 7.1% in those with no auto-PVFx and low auto-AAC, 10.1% in those with no auto-PVFx and high auto-AAC, 13.4% in those with auto-PVFx and low auto-AAC, and 18.0% in those with auto-PVFx and high auto-AAC. While physician manual review of images in clinical practice will still be needed to confirm image quality and provide clinical context for interpretation, simultaneous automated ascertainment of auto-PVFx and auto-AAC can aid fracture risk assessment.

Individuals with calcification of their abdominal aorta (AAC) and vertebral fractures seen on lateral spine bone density images (easily obtained as part of a bone density test) are much more likely to have subsequent fractures. Prior studies have not shown if both AAC and prior vertebral fracture both contribute to fracture prediction in routine clinical practice. Additionally, a barrier to using these images to aid fracture risk assessment at the time of bone density testing has been the need for expert readers to be able to accurately detect both AAC and vertebral fractures. We have developed automated computer methods (using artificial intelligence) to accurately detect vertebral fracture (auto-PVFx) and auto-AAC on lateral spine bone density images for 11 013 older individuals having a bone density test in routine clinical practice. Over a 5-year follow-up period, 7.1% of those with no auto-PVFx and low auto-AAC, 10.1% of those with no auto-PVFx and high auto-AAC, 13.4% of those with auto-PVFx and low auto-AAC, and 18.0% of those with auto-PVFx and high auto-AAC had a major osteoporotic fracture. Auto-PVFx and auto-AAC, ascertained simultaneously on lateral spine bone density images, both contribute to the risk of subsequent major osteoporotic fractures in routine clinical practice settings.

Effect of abdominal tissue thickness on trabecular bone score and fracture risk in adults with diabetes: the Manitoba BMD registry.

Individuals with type 2 diabetes have lower trabecular bone score (TBS) and increased fracture risk despite higher bone mineral density. However, measures of trabecular microarchitecture from high-resolution peripheral computed tomography are not lower in type 2 diabetes. We hypothesized that confounding effects of abdominal tissue thickness may explain this discrepancy, since central obesity is a risk factor for diabetes and also artifactually lowers TBS. This hypothesis was tested in individuals aged 40 years and older from a large DXA registry, stratified by sex and diabetes status. When DXA-measured abdominal tissue thickness was not included as a covariate, men without diabetes had lower TBS than women without diabetes (mean difference -0.074, P < .001). TBS was lower in women with versus without diabetes (mean difference -0.037, P < .001), and men with versus without diabetes (mean difference -0.007, P = .042). When adjusted for tissue thickness these findings reversed, TBS became greater in men versus women without diabetes (mean difference +0.053, P < .001), in women with versus without diabetes (mean difference +0.008, P < .001), and in men with versus without diabetes (mean difference +0.014, P < .001). During mean 8.7 years observation, incident major osteoporotic fractures were seen in 7048 (9.6%). Adjusted for multiple covariates except tissue thickness, TBS predicted fracture in all subgroups with no significant diabetes interaction. When further adjusted for tissue thickness, HR per SD lower TBS remained significant and even increased slightly. In conclusion, TBS predicts fractures independent of other clinical risk factors in both women and men, with and without diabetes. Excess abdominal tissue thickness in men and individuals with type 2 diabetes may artifactually lower TBS using the current algorithm, which reverses after accounting for tissue thickness. This supports ongoing efforts to update the TBS algorithm to directly account for the effects of abdominal tissue thickness for improved fracture risk prediction.

Individuals with type 2 diabetes are at increased fracture risk despite having higher bone mineral density (BMD). Previous studies suggest that trabecular bone score (TBS), a measure of bone derived from spine DXA images that can be used to assess fracture risk in addition to BMD, may be lower in individuals with type 2 diabetes. However, TBS is artificially lowered by greater abdominal obesity. We showed that abdominal obesity explained the lower TBS measurements that were seen in individuals with type 2 diabetes. However, even when we considered the effect of abdominal obesity, TBS was still able to predict major fractures in both women and men, with and without diabetes.

FRAX predicts cardiovascular risk in women undergoing osteoporosis screening: the Manitoba bone mineral density registry.

Osteoporosis and cardiovascular disease (CVD) are highly prevalent in older women, with increasing evidence for shared risk factors and pathogenesis. Although FRAX was developed for the assessment of fracture risk, we hypothesized that it might also provide information on CVD risk. To test the ability of the FRAX tool and FRAX-defined risk factors to predict incident CVD in women undergoing osteoporosis screening with DXA, we performed a retrospective prognostic cohort study which included women aged 50 yr or older with a baseline DXA scan in the Manitoba Bone Mineral Density Registry between March 31, 1999 and March 31, 2018. FRAX scores for major osteoporotic fracture (MOF) were calculated on all participants. Incident MOF and major adverse CV events (MACE; hospitalized acute myocardial infarction [AMI], hospitalized non-hemorrhagic cerebrovascular disease [CVA], or all-cause death) were ascertained from linkage to population-based healthcare data. The study population comprised 59 696 women (mean age 65.7 ± 9.4 yr). Over mean 8.7 yr of observation, 6021 (10.1%) had MOF, 12 277 women (20.6%) had MACE, 2274 (3.8%) had AMI, 2061 (3.5%) had CVA, and 10 253 (17.2%) died. MACE rates per 1000 person-years by FRAX risk categories low (10-yr predicted MOF <10%), moderate (10%-19.9%) and high (≥20%) were 13.5, 34.0, and 64.6, respectively. Although weaker than the association with incident MOF, increasing FRAX quintile was associated with increasing risk for MACE (all P-trend <.001), even after excluding prior CVD and adjusting for age. HR for MACE per SD increase in FRAX was 1.99 (95%CI, 1.96-2.02). All FRAX-defined risk factors (except parental hip fracture and lower BMI) were independently associated with higher non-death CV events. Although FRAX is intended for fracture risk prediction, it has predictive value for cardiovascular risk.

The American Society for Bone and Mineral Research Task Force on clinical algorithms for fracture risk report.

Using race and ethnicity in clinical algorithms potentially contributes to health inequities. The American Society for Bone and Mineral Research (ASBMR) Professional Practice Committee convened the ASBMR Task Force on Clinical Algorithms for Fracture Risk to determine the impact of race and ethnicity adjustment in the US Fracture Risk Assessment Tool (US-FRAX). The Task Force engaged the University of Minnesota Evidence-based Practice Core to conduct a systematic review investigating the performance of US-FRAX for predicting incident fractures over 10 years in Asian, Black, Hispanic, and White individuals. Six studies from the Women's Health Initiative (WHI) and Study of Osteoporotic Fractures (SOF) were eligible; cohorts only included women and were predominantly White (WHI > 80% and SOF > 99%), data were not consistently stratified by race and ethnicity, and when stratified there were far fewer fractures in Black and Hispanic women vs White women rendering area under the curve (AUC) estimates less stable. In the younger WHI cohort (n = 64 739), US-FRAX without bone mineral density (BMD) had limited discrimination for major osteoporotic fracture (MOF) (AUC 0.53 (Black), 0.57 (Hispanic), and 0.57 (White)); somewhat better discrimination for hip fracture in White women only (AUC 0.54 (Black), 0.53 (Hispanic), and 0.66 (White)). In a subset of the older WHI cohort (n = 23 918), US-FRAX without BMD overestimated MOF. The Task Force concluded that there is little justification for estimating fracture risk while incorporating race and ethnicity adjustments and recommends that fracture prediction models not include race or ethnicity adjustment but instead be population-based and reflective of US demographics, and inclusive of key clinical, behavioral, and social determinants (where applicable). Research cohorts should be representative vis-à-vis race, ethnicity, gender, and age. There should be standardized collection of race and ethnicity; collection of social determinants of health to investigate impact on fracture risk; and measurement of fracture rates and BMD in cohorts inclusive of those historically underrepresented in osteoporosis research.

Using race or ethnicity when calculating disease risk may contribute to health disparities. The ASBMR Task Force on Clinical Algorithms for Fracture Risk was created to understand the impact of the US Fracture Risk Assessment Tool (US-FRAX) race and ethnicity adjustments. The Task Force reviewed the historical development of FRAX, including the assumptions underlying selection of race and ethnicity adjustment factors. Furthermore, a systematic review of literature was conducted, which revealed an overall paucity of data evaluating the performance of US-FRAX in racially and ethnically diverse groups. While acknowledging the existence of racial and ethnic differences in fracture epidemiology, the Task Force determined that currently there is limited evidence to support the use of race and ethnicity­specific adjustments in US-FRAX. The Task Force also concluded that research is needed to create generalizable fracture risk calculators broadly applicable to current US demographics, which do not include race and ethnicity adjustments. Until such population­based fracture calculators are available, clinicians should consider providing fracture risk ranges for Asian, Black, and/or Hispanic patients and should engage in shared decision-making with patients about fracture risk interpretation. Future studies are required to evaluate fracture risk tools in populations inclusive of those historically underrepresented in research.

Assessing Change in Spine Bone Density from Different Numbers and Combinations of Lumbar Vertebrae: The Manitoba BMD Registry.

INTRODUCTION: Change in bone mineral density (BMD) is considered significant when it exceeds the 95 % least significant change (LSC) derived from that facility's precision study. The lumbar spine is often affected by structural artifact such that not all four lumbar vertebrae are evaluable. Guidelines suggest using a site-matched LSC when omitting vertebrae from the BMD measurement. The current study describes significant BMD change related to intervening anti-osteoporosis treatment for different numbers and combinations of lumbar vertebrae using site-matched LSC values. METHODOLOGY: We identified 10,526 untreated adult women mean age 59.6 years with baseline and repeat spine BMD testing (mean interval 4.7 years) where all 4 lumbar vertebrae were evaluable. Change in spine BMD for different combinations of lumbar vertebrae was assessed in relation to intervening anti-resorptive treatment, contrasting women with high treatment exposure (medication possession ratio, MPR ≥ 0.8) versus women who remained untreated. Site-matched LSC values were derived from 879 test-retest precision measurements. RESULTS: There was consistent linear trend between increasing MPR and BMD change exceeding the LSC for all lumbar vertebral combinations, positive with BMD increase and negative with BMD decrease (all p-trend <0.001). In the high treatment exposure group, mean percent increases in spine BMD were similar for all vertebral combinations, from L1-4 to a single vertebra. In untreated women, mean percent decreases in spine BMD were also similar for all vertebral combinations. The net treatment response (proportion of women with treatment-concordant changes minus proportion with treatment-discordant changes exceeding the LSC) was 29.7 % for 4 vertebrae, 27.5-30.0 % for 3 vertebrae, 22.4-28.5 % for 2 vertebrae, and 18.1-21.9 % for a single vertebra. CONCLUSIONS: All numbers and combinations of lumbar vertebrae, when used in conjunction with site-matched LSC values, can provide clinically meaningful follow-up in treated and untreated patients, even when spine BMD is based on a single vertebral body.

Association between amino acids and recent osteoporotic fracture: a matched incident case-control study.

Context: Osteoporotic fracture is a major public health issue globally. Human research on the association between amino acids (AAs) and fracture is still lacking. Objective: To examine the association between AAs and recent osteoporotic fractures. Methods: This age and sex matched incident case-control study identified 44 recent x-ray confirmed fracture cases in the Second Hospital of Jilin University and 88 community-based healthy controls aged 50+ years. Plasma AAs were measured by high performance liquid chromatography coupled with mass spectrometry. After adjusting for covariates (i.e., body mass index, milk intake >1 time/week, falls and physical activity), we conducted conditional logistical regression models to test the association between AAs and fracture. Results: Among cases there were 23 (52.3%) hip fractures and 21 (47.7%) non-hip fractures. Total, essential, and non-essential AAs were significantly lower in cases than in controls. In the multivariable conditional logistic regression models, after adjusting for covariates, each standard deviation increase in the total (odds ratio [OR]: 0.304; 95% confidence interval [CI]: 0.117-0.794), essential (OR: 0.408; 95% CI: 0.181-0.923) and non-essential AAs (OR: 0.290; 95%CI: 0.107-0.782) was negatively associated with recent fracture. These inverse associations were mainly found for hip fracture, rather than non-hip fractures. Among these AAs, lysine, alanine, arginine, glutamine, histidine and piperamide showed the significantly negative associations with fracture. Conclusion: There was a negative relationship between AAs and recent osteoporotic fracture; such relationship appeared to be more obvious for hip fracture.

Secular Trends in Peak Bone Mineral Density: The National Health and Nutrition Examination Survey 1999-2018.

Peak bone mineral density (BMD) is one of the most important factors influencing the development of osteoporosis. It was predicted that a 10% increase in peak BMD will delay the onset of osteoporosis by 13 years. However, changes in peak BMD over time are unknown. This study aimed to investigate secular trends in peak BMD among young adults in the United States. Based on the National Health and Nutrition Examination Survey from 1999-2018, 3,975 males aged 19-28 years and 2370 females aged 31-40 years were our target population for estimating peak lumbar spine BMD. BMD was measured by dual-energy X-ray absorptiometry. Generalized linear models adjusted for multiple covariates were used to examine the secular trends in peak BMD in males and females, respectively. Secular trends for peak lumbar spine BMD from 1999-2000 to 2017-2018 were not statistically significant in males or females (all Plinear and Pquadratic > 0.05). Similar results were observed in race/ethnicity subgroups (all Plinear and Pquadratic > 0.05). However, in stratified analyses by obesity category, peak lumbar spine BMD in obese males and females increased from 1999-2000 to 2009-2010 and then decreased until 2017-2018, while peak lumbar spine BMD in non-obese females decreased from 1999-2000 to 2005-2006 and then increased until 2017-2018 (all Pquadratic < 0.05). Peak lumbar spine BMD was greater in obese males and females than in non-obese males and females up to 2009-2010, but not from 2011-2012 onwards. Overall, there were no significant secular trends in peak lumbar spine BMD. However, secular trends differed between obese and non-obese groups.

Maternal diabetes and fracture risk in offspring: a population-based analysis.

Factors affecting intrauterine environment exerts influence on skeletal health and fracture risk in later life. Diabetes during pregnancy is known to influence birth weight and is associated with fetal overgrowth. However, the effects of maternal diabetes on fracture risk in offspring is unknown. This study was aimed to evaluate the association between maternal diabetes and fracture risk in offspring. Using population-based administrative health data for Manitoba, Canada, we identified deliveries complicated by gestational diabetes and type 2 diabetes between April 1, 1980, and March 31, 2020. The cohort was followed for a median of 15.8 yr. The primary outcome was any incident fracture in offspring. Secondary outcomes were long bone upper extremity fracture, long bone lower extremity fracture, vertebral fracture, and any non-trauma fractures. Cox proportional hazard regression models were used to estimate fracture risk in offspring by maternal diabetes status adjusted for relevant covariates. Of the 585 176 deliveries, 26 397 offspring were born to women with diabetes (3.0% gestational diabetes and 1.5% type 2 diabetes), and 558 779 were born to women without diabetes. The adjusted risk for any fracture was 7% (hazard ratio, 1.07; 95% CI, 2.7-11.5%) higher in the offspring of mothers with diabetes than offspring of mothers without diabetes. Types of fractures were similar between the 2 groups with a predominance of long bone upper extremity fractures. In conclusion, maternal diabetes was associated with a modest increase in fracture risk in offspring. Longitudinal prospective studies are needed to understand intrauterine and postnatal factors that may influence fracture risk in the offspring of mothers with diabetes.

Advanced glycation end products are not associated with bone mineral density, trabecular bone score, and bone turnover markers in adults with and without type 1 diabetes: a cross-sectional study.

It is unclear if AGEs are involved in the bone fragility of type 1 diabetes (T1D). We evaluated whether skin AGEs by skin autofluorescence and serum AGEs (pentosidine, carboxymethyl-lysine [CML]) are independently associated with BMD by DXA (lumbar spine, hip, distal radius), trabecular bone score (TBS), serum bone turnover markers (BTMs: CTX; P1NP; osteocalcin), and sclerostin in participants with and without T1D. Linear regression models were used, with interaction terms to test effect modification by T1D status. In participants with T1D, correlations between skin and serum AGEs as well as between AGEs and 3-year HbA1C were evaluated using Spearman's correlations. Data are mean ± SD or median (interquartile range). We included individuals who participated in a cross-sectional study and had BMD and TBS assessment (106 T1D/65 controls, 53.2% women, age 43 ± 15 yr, BMI 26.6 ± 5.5 kg/m2). Participants with T1D had diabetes for 27.6 ± 12.3 yr, a mean 3-yr HbA1C of 7.5 ± 0.9% and skin AGEs of 2.15 ± 0.54 arbitrary units. A subgroup of 65 T1D/57 controls had BTMs and sclerostin measurements, and those with T1D also had serum pentosidine (16.8[8.2-32.0] ng/mL) and CML [48.0 ± 16.8] ng/mL) measured. Femoral neck BMD, TBS, and BTMs were lower, while sclerostin levels were similar in participants with T1D vs controls. T1D status did not modify the associations between AGEs and bone outcomes. Skin AGEs were significantly associated with total hip and femoral neck BMD, TBS, BTMs, and sclerostin before, but not after, adjustment for confounders. Serum AGEs were not associated with any bone outcome. There were no significant correlations between skin and serum AGEs or between AGEs and 3-yr HbA1C. In conclusion, skin and serum AGEs are not independently associated with BMD, TBS, BTMs, and sclerostin in participants with relatively well-controlled T1D and participants without diabetes.