Epidemiology Of Osteoporosis Research Articles

POSB196 Epidemiology of Osteoporosis: Risk Factor Distribution, Osteoporosis Prevalence and Treatment Gap in the General Population ≥50 Years of Age in Germany

In Germany, over 7 million adults ≥50 years of age have osteoporosis. New risk factors for fractures were recently added to the Dachverband Osteologie guidelines.1 Recent data regarding the distribution of these risk factors in the German population is lacking. This study estimated the prevalence of these risk factors and the osteoporosis epidemiology and treatment gap in the general population ≥50 years old in Germany.

Osteoporosis in 10 years time: a glimpse into the future of osteoporosis.

Patients living with osteoporosis are projected to increase dramatically in the next decade. Alongside the forecasted increased societal and economic burden, we will live a crisis of fractures. However, we will have novel pharmacological treatment to face this crisis and, more importantly, new optimized treatment strategies. Fracture liaison services will be probably implemented on a large scale worldwide, helping to prevent additional fractures in high-risk patients. In the next decade, novel advances in the diagnostic tools will be largely available. Moreover, new and more precise fracture risk assessment tools will change our ability to detect patients at high risk of fractures. Finally, big data and artificial intelligence will help us to move forward into the world of precision medicine. In the present review, we will discuss the future epidemiology and costs of osteoporosis, the advances in early and accurate diagnosis of osteoporosis, with a special focus on biomarkers and imaging tools. Then we will examine new and refined fracture risk assessment tools, the role of fracture liaison services, and a future perspective on osteoporosis treatment.

The cross-talk between matrix metalloproteinase-9, RANKL/OPG system and cardiovascular risk factors in ovariectomized rat model of postmenopausal osteoporosis.

Epidemiology and pathogenesis of cardiovascular diseases (CVD) and osteoporosis are strikingly overlapping. This study presents matrix metalloproteinase-9 (MMP-9), as a simple molecular link more consistently associated with the pathophysiology of both osteoporosis and CVD risk factors. 40 adult female rats were randomly distributed into 4 groups [control sham-operated, untreated osteoporosis, carvedilol-treated osteoporosis and alendronate-treated osteoporosis]. After 8 weeks, blood samples were collected to estimate Lipid profile (Total cholesterol, HDL, Triglycerides), inflammatory markers (IL-6, TNF alpha, CRP and NO), and Bone turnover markers (BTM) (Alkaline phosphatase, osteocalcin and pyridinoline). The tibias were dissected to estimate MMP-9 and NF-kB gene expression, OPG, RANKL levels and for histological examination. Induction of osteoporosis resulted in a significant elevation in BTM, inflammatory markers and dyslipidemia. MMP-9 was significantly elevated and positively correlated with BTM, inflammation and dyslipidemia markers. Carvedilol and alendronate exerted a bone preservative role and attenuated dyslipidaemia and inflammation in accordance with their respective effect on MMP-9.

Сучасні погляди на проблеми остеопорозу: українсько-португальський обмін досвідом

Стаття є оглядом ключових питань, які обговорювались на українсько-португальській конференції з питань остеопорозу 21-22 червня 2016 року в м. Лісабон (Португалія). Представлені дані щодо епідеміології остеопорозу та впливу різних чинників на стан кісткової тканини.

Epidemiology of glucocorticoid-induced osteoporosis and management of associated fracture risk in Japan.

Glucocorticoid-induced osteoporosis (GIOP) is associated with a high fracture risk. Practice guidelines by the Japanese Society for Bone and Mineral Research in 2014 recommend bone densitometry and appropriate treatment to reduce this risk. The study objectives were to describe characteristics of GIOP patients in Japan and to evaluate their management in a subgroup of patients without comorbid cancer. This retrospective cohort study was performed using the Medical Data Vision (MDV) database from Japan. Adult patients initiating oral glucocorticoid treatment with a total GIOP risk score ≥ 3, based on the 2014 practice guideline, identified between 2009 and 2019 were eligible. A subgroup of patients without any cancer diagnosis was also identified. Data were extracted on demographics, concurrent medical conditions, use of bone densitometry, and osteoporosis treatment. 25,569 patients were eligible, of whom 12,227 had a confirmed cancer diagnosis. Mean age was 68.5 years and 12,356 patients (48.3%) were women. Concurrent medical conditions of interest were documented in 14,887 patients, most frequently rheumatoid arthritis (n = 4185) and asthma (n = 3085). Yearly bone densitometry was performed in 6.5% (n = 865) of the cancer-free subgroup; 51.8% (n = 6905) were prescribed an osteoporosis treatment, most frequently bisphosphonates (n = 5132; 74.3%). Between 2011 and 2018, rates of densitometry were stable, whereas prescription rates increased from 40.0 to 51.8%. In spite of publication of guidelines for GIOP management, there is an important treatment gap in their application in everyday practice. For this reason, public health measures to increase physician awareness of GIOP are needed.

Diabetes mellitus and osteoporosis: pathogenetic relationship and current principles of treatment

Diabetes mellitus (DM) is a well known risk factor for osteoporosis and an increased risk of fractures. A lot of data has been published about the relationship between diabetes and bone health. DM type 1 and DM type 2 have different effects on bone mineral density (BMD). The central link in pathogenesis of bone fragility in patients with DM type 1 is a violation of the activity and gifferentiation of osteoblasts. On the contrary, hyperinsulinemia in DM type 2 activates the division and gifferentiation of osteoblasts and contributes to an increase in BMD. However, Higher BMD values in patients with DM type 2 are combined with slowdown in bone metabolism. As the result, high-quality bone remodeling does not occur. And bone strength decreases despite the high BMD. Despite the differences, DM type 1 and DM type 2 have common pathogenic pathways, that lead to increased bone fragility. For example, non-enzymatic glycation of bone matrix collagen and increase in concentration of sclerostin, which blocks the Wnt signaling pathway. In this review, we will analyze current data about epidemiology and pathogenesis of osteoporosis in DM and discuss the practical issues of the clinic, diagnosis, stratification of fracture risk and treatment. Special attention will be paid to the effects of glucose-lowering and anti-osteoporotic drugs on bone tissue.

Development and validation of the risk engine for an Australian Health Economics Model of Osteoporosis.

This study aimed to document and validate the risk engine of the Australian Health Economics Model of Osteoporosis (AusHEMO). AusHEMO is a state-transition microsimulation model. The fracture risks were simulated using fracture incidence rates from the Dubbo Osteoporosis Epidemiology Study. The AusHEMO was validated regarding its face, internal and cross validities. Goodness-of-fit analysis was conducted and Lin's coefficient of agreement and mean absolute difference with 95% limits of agreement were reported. The development of AusHEMO followed general and osteoporosis-specific health economics guidelines. AusHEMO showed good face validity regarding the model's structure, evidence, problem formulation and results. In addition, the model has been proven good internal and cross validities in goodness-of-fit test. Lin's coefficient was 0.99, 1 and 0.94 for validation against the fracture incidence rates, Australian life expectancies and residual lifetime fracture risks, respectively. In summary, the development of the risk engine of AusHEMO followed the best practice for osteoporosis disease modelling and the model has been shown to have good face, internal and cross validities. The AusHEMO can be confidently used to predict long-term fracture-related outcomes and health economic evaluations when costs data are included. Health policy-makers in Australia can use the AusHEMO to select which osteoporosis interventions such as medications and public health interventions represent good value for money.

Liver cirrhosis and secondary osteoporosis

Osteoporosis is a bone loss disease caused by the imbalance of osteoblast and osteoclast. It is a common complication of patients with liver cirrhosis, cholestatic liver disease, and liver transplantation. Over the past few decades, many researchs have raised the awareness of immune cell activation, chronic inflammation, intestinal microflora, etc. in liver cirrhosis and secondary osteoporosis. This article reviews the progress of the epidemiology, pathogenesis, diagnosis and treatment of liver cirrhosis and secondary osteoporosis.

Natural language processing of radiology reports for the identification of patients with fracture.

Fracture liaison services address the post-fracture treatment gap in osteoporosis (OP). Natural language processing (NLP) is able to identify previously unrecognized patients by screening large volumes of radiology reports. The aim of this study was to compare an NLP software tool, XRAIT (X-Ray Artificial Intelligence Tool), with a traditional fracture liaison service at its development site (Prince of Wales Hospital [POWH], Sydney) and externally validate it in an adjudicated cohort from the Dubbo Osteoporosis Epidemiology Study (DOES). XRAIT searches radiology reports for fracture-related terms. At the development site (POWH), XRAIT and a blinded fracture liaison clinician (FLC) reviewed 5,089 reports and 224 presentations, respectively, of people 50 years or over during a simultaneous 3-month period. In the external cohort of DOES, XRAIT was used without modification to analyse digitally readable radiology reports (n = 327) to calculate its sensitivity and specificity. XRAIT flagged 433 fractures after searching 5,089 reports (421 true fractures, positive predictive value of 97%). It identified more than a threefold higher number of fractures (421 fractures/339 individuals) compared with manual case finding (98 individuals). Unadjusted for the local reporting style in an external cohort (DOES), XRAIT had a sensitivity of 70% and specificity of 92%. XRAIT identifies significantly more clinically significant fractures than manual case finding. High specificity in an untrained cohort suggests that it could be used at other sites. Automated methods of fracture identification may assist fracture liaison services so that limited resources can be spent on treatment rather than case finding.

The treatment gap: The missed opportunities for osteoporosis therapy.

Despite substantial advances in delineation of the epidemiology, pathophysiology, risk assessment and treatment of osteoporosis over the last three decades, a substantial proportion of men and women at high risk of fracture remain untreated - the so-called "treatment gap". This review summarises the important patient-, physician- and policyrelated causes of this treatment gap, before discussing in greater detail: (a) the evidence base for the efficacy of bisphosphonates in osteoporosis; (b) recent evidence relating to the adverse effects of this widely used therapeutic class, most notably atypical femoral fracture and osteonecrosis of the jaw; (c) available strategies to improve both secondary and primary prevention pathways for the management of this disorder.

PMS4 Epidemiology, Treatment Patterns, and Economic Burden of Postmenopausal Osteoporosis and Associated Fractures in China in 2017

PMS4 Epidemiology, Treatment Patterns, and Economic Burden of Postmenopausal Osteoporosis and Associated Fractures in China in 2017

Review of certain articles of the American society of bone and mineral research (ASMBR) annual congress 2019

The annual congress of the American Society of Bone and Mineral Research (ASBMR) presents the most significant results among the basic and clinical research in the field of osteoporosis and other metabolic bone diseases. Professor of Medicine John Bilezikian, M.D., Columbia University College of Physicians and Surgeons New York, New York and Lynda F. Bonewald Ph.D. Director, Indiana Center for Musculoskeletal Health, Indianapolis, Indiana, every year present the most outstanding abstracts before the ASBMR. However, not all of these researches are relevant for Russia, as some of them relates to the epidemiology and pharmacoeconomics of osteoporosis specifically in the US. This review presents only a very limited selection of congress abstracts, combined on topics that seem relevant today.

New Approaches for Variable Selection in Longitudinal Studies: An Application to Genetic Association Studies and Bone Loss

We study the problem of variable selection in the context of longitudinal studies by linear mixed effect models when the dimensionality of predictors subject to selection is high. We consider a fully Bayesian formulation of the problem with spike-and-slab a prior distributions which is an appealing solution, however, we find it computationally demanding. As an alternative, we propose a general penalized log-likelihood framework based on marginalized observation equation and a heterogeneous error term. The parameters of the model are estimated by a block wise coordinate gradient descent algorithm. Given the formulation of the considered linear mixed effect models as random slope and intercept models, we consider yet another variable selection procedure which is more ad hoc but has an advantage of computational speed. The procedure consists of two steps and is based on assessing the significance of co-variates from biased predictors of subject-specific random effects. We study the impact of this mis-specification on the accuracy of variable selection. We demonstrate the applicability of the proposed frameworks by studying the association between single nucleotide polymorphisms and bone loss that contributes to the development of osteopenia and osteoporosis in post-menopausal women and aged men and is a strong risk factor for bones fractures and its related mortality. The data is obtained from the longitudinal Dubbo Osteoporosis Epidemiology Study.

Osteoporosis researches in Endocrinology & Metabolism Research Institute (EMRI) of Tehran University of Medical Sciences; a Scientometrics study

We investigated the research conducted on osteoporosis at EMRI to provide practical implications and suggestions for the development of future research. We searched osteoporosis and related concepts, as well as various forms of affiliations to EMRI to find published documents indexed in Web of Science, PubMed, and Scopus databases until January 27, 2020. The main purpose and scopes of the studies were classified into seven main study areas. Co-authorship relations were examined using the VOSviewer and keyword analysis was carried out by the ScientoPy. A total 201 papers on the subject of osteoporosis with organizational affiliation to EMRI were found after initial screening and removing duplicates. A time trend analysis of publications showed a growing trend of EMRI’s publication in the field of osteoporosis since 2014. A total of 558 independent authors participated in osteoporosis-related research at EMRI, and the average contribution of authors was 6.72 per papers. The Co-authorship network for authors contributing in at least five publications, showed 4 main clusters of independent authors. The co-occurrence network of keywords included three large and intertwined clusters including the epidemiology of osteoporosis and its resulting fractures and risk factors, bone markers and monitoring the effectiveness of treatment with them, and nutrition and supplements in the field of osteoporosis and fractures. EMRI has significantly contributed in osteoporosis science and related subjects during recent years, especially in public health aspects of osteoporosis and its risk factors and consequences. More attention should be paid to other areas such clinical and basic science studies.

Decline in Muscle Strength and Performance Predicts Fracture Risk in Elderly Women and Men.

Muscle strength and performance are associated with fractures. However, the contribution of their rate of decline is unclear. To assess the independent contribution of the rate of decline in muscle strength and performance to fracture risk. Community-dwelling women (n = 811) and men (n = 440) aged 60 years or older from the prospective Dubbo Osteoporosis Epidemiology Study followed from 2000 to 2018 for incident fracture. Clinical data, appendicular lean mass/height2 (ht)2, bone mineral density, quadricep strength/ht (QS), timed get-up-and-go (TGUG), 5 times repeated sit-to-stand (5xSTS), and gait speed (GS) measured biennially. Rates of decline in muscle parameters were calculated using ordinary least squares regression and fracture risk was assessed using Cox's models. Incident low-trauma fracture ascertained by x-ray report. Apart from lean mass in women, all muscle parameters declined over time. Greater rates of decline in physical performance were associated with increased fracture risk in women (Hazard ratios [HRs] ranging from 2.1 (95% CI: 1.5-2.9) for GS to 2.7 (95% CI: 1.9-3.6) for 5xSTS, while in men only the decline in GS was associated with fracture risk (HR: 3.4 [95% CI: 1.8-6.3]). Baseline performance and strength were also associated with increased fracture risk in men (HRs ranging from 1.8 (95% CI: 1.1-3.0) for QS to 2.5 (95% CI: 1.5-4.1) for TGUG, but not in women. Rate of decline in physical performance in both genders, and baseline strength and performance in men, contributed independently to fracture risk. Sit-to-stand and GS were the tests most consistently associated with fractures. Further studies are required to determine whether muscle strength and/or performance improve the predictive accuracy of fracture prediction models.

A Risk Assessment Tool for Predicting Fragility Fractures and Mortality in the Elderly

Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current undermanagement of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and its consequences. The study involved 8965 people aged ≥60 years from the Dubbo Osteoporosis Epidemiology Study and the Canadian Multicentre Osteoporosis Study. Incident fracture was identified from X-ray reports and questionnaires, and death was ascertained though contact with a family member or obituary review. We used a multistate model to quantify the effects of the predictors on the transition risks to an initial and subsequent incident fracture and mortality, accounting for their complex interrelationships, confounding effects, and death as a competing risk. There were 2364 initial fractures, 755 subsequent fractures, and 3300 deaths during a median follow-up of 13 years (interquartile range [IQR] 7-15). The prediction model included sex, age, bone mineral density, history of falls within 12 previous months, prior fracture after the age of 50 years, cardiovascular diseases, diabetes mellitus, chronic pulmonary diseases, hypertension, and cancer. The model accurately predicted fragility fractures up to 11 years of follow-up and post-fracture mortality up to 9 years, ranging from 7 years after hip fractures to 15 years after non-hip fractures. For example, a 70-year-old woman with a T-score of -1.5 and without other risk factors would have 10% chance of sustaining a fracture and an 8% risk of dying in 5 years. However, after an initial fracture, her risk of sustaining another fracture or dying doubles to 33%, ranging from 26% after a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction model for individualization of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. © 2020 American Society for Bone and Mineral Research.

OR29-02 Natural Language Processing of Radiology Reports Improves Identification of Patients with Fracture

Fracture liaison services (FLS) address the treatment gap for those with osteoporosis (OP) who fracture and are not treated. Given the limited human resources in FLS, screening high volumes of radiology reports for fractures with Natural Language Processing (NLP) could identify patients that have not been recognized or treated. This study is an analytical and clinical validation of X-Ray Artificial Intelligence Tool software (XRAIT) at its development site (a tertiary hospital) and external validation in an adjudicated cohort from the Dubbo Osteoporosis Epidemiology Study (DOES).Methods: XRAIT uses NLP to perform a Boolean search of radiology reports for fracture and related terms. It can be trained for site-specific reporting styles and use rules to refine identification (e.g. age>50y; bone involved; etc). At the development site, XRAIT was used to search the emergency patient presentations of people over 50 years of age and compared to referrals to FLS (usual care) during the same 3-month period. XRAIT analyzed all plain radiographs and CT scans (n = 5089) while n = 224 were referred to FLS for usual care. External validation: XRAIT was used to analyze digitally readable radiology reports in an untrained cohort from DOES (n = 327) to calculate sensitivity and specificity.Results: XRAIT identified a 5-fold higher number of potential significant fractures (349/5089) compared to manual case finding (70/224). 339/349 were confirmed fractures (97.1%). Only 29% of those eligible were started or recommended anti-resorptive therapy, including those seen by the fracture liaison service. XRAIT unadjusted for the local radiology reporting styles in DOES had a sensitivity of 69.6% and specificity of 95%. Conclusion: XRAIT identifies clinically significant fractures efficiently with minimal additional human resources. Its high specificity in an untrained cohort suggests it could be used at other sites. Automated methods of patient identification may assist fracture liaison services to identify fractures that still remain largely untreated.

Epidemiology of Osteoporosis: A Case-Control Study among the Pre and Post Menopausal women of Allahabad District

Epidemiology of Osteoporosis: A Case-Control Study among the Pre and Post Menopausal women of Allahabad District

Estimation and projection about the standardized prevalence of osteoporosis in mainland China.

Osteoporosis is the most common bone disease. We aimed to investigate the standardized prevalence of osteoporosis in mainland China at the national and regional levels, with projections until 2050. A comprehensive literature search was performed in PubMed, EMBASE, Cochrane Library, CNKI, Wanfang, and CBM-SinoMed. We constructed resample sets to calculate the standardized prevalence in each study. Multilevel mixed-effects logistic regression was used to estimate the age-specific and sex-specific prevalence. The United Nations Population Division (UNPD) data and regional population data from the fifth and sixth censuses in mainland China were used to estimate and project the national and regional prevalence of osteoporosis. The standardized prevalence of osteoporosis ranged from 5.04% (2.12~11.34%) to 7.46% (3.13~16.32%) in males aged ≥ 50 years and from 26.28% (15.38~40.40%) to 39.19% (25.74~53.95%) in females aged ≥ 50 years from 1990 to 2050. Moreover, we did not find a significant difference in the standardized prevalence among three geographic regions (Central China, West China, and East China). We found that osteoporosis is a serious public health challenge in mainland China. The findings in our study add insight into the epidemiology of osteoporosis and would be beneficial for the prevention and treatment of osteoporosis in mainland China.

Comparison of calcaneal quantitative ultrasound and bone densitometry parameters as fracture risk predictors in type 2 diabetes mellitus

To investigate the utility of calcaneal quantitative ultrasound compared with bone densitometry (DXA) in predicting incident low-trauma fracture in type 2 diabetes. This retrospective cohort study included a subset of participants in the Dubbo Osteoporosis Epidemiology Study who had concurrent calcaneal quantitative ultrasound and DXA measurement, comprising 809 people without type 2 diabetes and 96 with type 2 diabetes. Fracture data had been collected prospectively. Cox proportional hazard models and receiver operating curves (ROC) were used to compare calcaneal quantitative ultrasound and DXA parameters as predictors for any low-trauma fracture. The median age of participants was 71years (IQR 68-76, 50% men) for those without type 2 diabetes and 70 years (IQR 68-76, 55% men) for those with type 2 diabetes. There was no difference in low-trauma fracture incidence between groups when stratified by sex. In those without type 2 diabetes, the hazard ratio for fracture per 1 sd decrease in broadband ultrasound attenuation and femoral neck bone mineral density (BMD) was 1.47 [95% confidence interval (CI) 1.26-1.71] and 1.39 (95% CI 1.17-1.64), respectively. The corresponding figures in type 2 diabetes were 1.81 (95% CI 1.03-3.19) for broadband ultrasound attenuation and 2.55 (95% CI 1.28-5.08) for femoral neck BMD. Broadband ultrasound attenuation is comparable with femoral neck BMD as a predictor for low trauma incident fracture in type 2 diabetes. Calcaneal quantitative ultrasound offers several advantages over DXA and should be considered in further studies of bone health screening or in clinical practice where DXA is unavailable.