Economic Consequences and Potentially Preventable Costs Related to Osteoporosis in the Netherlands

Cost-effectiveness analysis of fracture liaison services: a Markov model using Dutch real-world data

This study assessed the lifetime cost-effectiveness of a fracture liaison service (FLS) compared to no-FLS in the Netherlands from a societal perspective and suggested that FLS was cost-effective in patients with a recent fracture aged 50 years and older. The implementation of FLS could lead to lifetime health-economic benefits.

INTRODUCTION

The objective of this study was to investigate the lifetime cost-effectiveness of a fracture liaison service (FLS) compared to no-FLS in the Netherlands from a societal perspective and using real-world data.

METHODS

Annual fracture incidence, treatment scenarios as well as treatment initiation in the years 2017-2019 were collected from a large secondary care hospital in the Netherlands. An individual-level, state transition model was designed to simulate lifetime costs and quality-adjusted life years (QALYs). Treatment pathways were differentiated by gender, presence of osteoporosis and/or prevalent vertebral fracture, and treatment status. Results were presented as incremental cost-effectiveness ratios (ICER). Both one-way and probabilistic sensitivity analyses were conducted.

RESULTS

For patients with a recent fracture aged 50 years and older, the presence of an FLS was associated with a lifetime €45 higher cost and 0.11 additional QALY gained leading to an ICER of €409 per QALY gained, indicating FLS was cost-effective compared to no-FLS at the Dutch threshold of €20,000/QALY. The FLS remained cost-effectiveness across different age categories. Our findings were robust in all one-way sensitivity analyses, the higher the treatment initiation rate in FLS, the greater the cost-effective of FLS. Probabilistic sensitivity analyses revealed that FLS was cost-effective in 90% of the simulations at the threshold of €20,000/QALY, with women 92% versus men 84% by gender.

CONCLUSION

This study provides the first health-economic analysis of FLS in the Netherlands, suggesting the implementation of FLS could lead to lifetime health-economic benefits.

OSTEO18, a novel urinary proteomic signature, associated with osteoporosis in heart transplant recipients

Background

Immunosuppressive treatment in heart transplant (HTx) recipient causes osteoporosis. The urinary proteomic profile (UPP) includes peptide fragments derived from the bone extracellular matrix. Study aims were to develop and validate a multidimensional UPP biomarker for osteoporosis in HTx patients from single sequenced urinary peptides identifying the parent proteins.

Methods

A single-center HTx cohort was analyzed. Urine samples were measured by capillary electrophoresis coupled with mass spectrometry. Cases with osteoporosis and matching controls were randomly selected from all available 389 patients. In derivation case-control dataset, 1576 sequenced peptides detectable in ≥30 % of patients. Applying statistical analysis on these, an 18-peptide multidimensional osteoporosis UPP biomarker (OSTEO18) was generated by support vector modeling. The 2 replication datasets included 118 and 94 patients. For further validation, the whole cohort was analyzed. Statistical methods included logistic regression and receiver operating characteristic curve (ROC) analysis.

Results

In derivation dataset, the AUC, sensitivity and specificity of OSTEO18 were 0.83 (95 % CI: 0.76-0.90), 74.3 % and 87.1 %, respectively. In replication datasets, results were confirmatory. In the whole cohort (154 osteoporotic patients [39.6 %]), the ORs for osteoporosis increased (p < 0.0001) across OSTEO18 quartiles from 0.39 (95 % CI: 0.25-0.61) to 3.14 (2.08-4.75). With full adjustment for known osteoporosis risk factors, OSTEO18 improved AUC from 0.708 to 0.786 (p = 0.0003) for OSTEO18 categorized (optimized threshold: 0.095) and to 0.784 (p = 0.0004) for OSTEO18 as continuously distributed classifier.

Conclusion

OSTEO18 is a clinically meaningful novel biomarker indicative of osteoporosis in HTx recipients and is being certified as in-vitro diagnostic.

Development and usability of a decision aid to initiate anti-osteoporosis medication treatment in patients visiting the fracture liaison service with a recent fracture

This study describes the development of a decision aid (DA), aimed at supporting patients in their decision whether to start anti-osteoporosis medication. People with recent fractures or osteoporosis and health professionals were supportive of the DA initiative. An experimental study been started to assess (cost-)effectiveness of the DA.

PURPOSE

At fracture liaison services (FLS), patients with a recent fracture ánd osteoporosis or a prevalent vertebral fracture are advised to start anti-osteoporosis medication (AOM). This study describes the development of a decision aid (DA) to support patients and healthcare providers (HCPs) in their decision about whether to start AOM.

METHODS

The DA was developed according to International Patient Decision Aid Standards (IPDAS). A systematic procedure was chosen including scope, design, prototype development, and alpha testing. A previously developed DA for women with osteoporosis was used as a basis. Furthermore, input from literature searches, the Dutch guideline on management of osteoporosis, and from people with a fracture or osteoporosis was used. The updated DA was evaluated during alpha testing.

RESULTS

The DA facilitates the decision of patients whether to initiate AOM treatment and provides information on fractures and osteoporosis, general risk factors that increase the likelihood of a subsequent fracture, the role of lifestyle, personalized risk considerations of a subsequent fracture with and without AOM treatment, and AOM options and their characteristics in an option grid. Alpha testing with 15 patients revealed that patient preferences and needs were adequately presented, and several suggestions for improvement (e.g. adding more specific information, simplifying terminology, improving icon use) were accounted for. Participants from the alpha testing recommended use of the DA during outpatient visits.

CONCLUSION

Professionals and persons with osteoporosis were supportive of the proposed DA and its usability. The DA could help in a shared decision-making process between patients and HCPs.

Artificial Intelligence Applications for Osteoporosis Classification Using Computed Tomography

Osteoporosis, marked by low bone mineral density (BMD) and a high fracture risk, is a major health issue. Recent progress in medical imaging, especially CT scans, offers new ways of diagnosing and assessing osteoporosis. This review examines the use of AI analysis of CT scans to stratify BMD and diagnose osteoporosis. By summarizing the relevant studies, we aimed to assess the effectiveness, constraints, and potential impact of AI-based osteoporosis classification (severity) via CT. A systematic search of electronic databases (PubMed, MEDLINE, Web of Science, ClinicalTrials.gov) was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 39 articles were retrieved from the databases, and the key findings were compiled and summarized, including the regions analyzed, the type of CT imaging, and their efficacy in predicting BMD compared with conventional DXA studies. Important considerations and limitations are also discussed. The overall reported accuracy, sensitivity, and specificity of AI in classifying osteoporosis using CT images ranged from 61.8% to 99.4%, 41.0% to 100.0%, and 31.0% to 100.0% respectively, with areas under the curve (AUCs) ranging from 0.582 to 0.994. While additional research is necessary to validate the clinical efficacy and reproducibility of these AI tools before incorporating them into routine clinical practice, these studies demonstrate the promising potential of using CT to opportunistically predict and classify osteoporosis without the need for DEXA.

Hospital-wide surveillance of fracture risk assessment by both FRAX and medication patterns in acute care hospital

To identify patients at a high risk for primary and secondary osteoporotic fractures using fracture risk assessments performed using the current method and the proposed method, in an acute care hospital and to identify departments where high-risk patients are admitted. This retrospective study included patients aged 40-90 years who were hospitalized at Fujita Health University Hospital. We collated the clinical data and prescriptions of all study participants. We also gathered data pertaining to risk factors according to Fracture Risk Assessment Tool (FRAX). Of the 1,595 patients, the mean number of major osteoporotic fracture risk predicted using FRAX was 11.73%. The department of rheumatology showed the highest fracture risk (18.55 ± 16.81) and had the highest number of patients on medications that resulted in reduced bone mineral density (1.07 ± 0.98 medication). Based on the FRAX, the proportion of patients in the high-risk group in this department was significantly higher compared with those in the remaining departments with respect to glucocorticoid administration, rheumatoid arthritis, and secondary osteoporosis. However, the departments included in the high-risk group were not necessarily the same as the departments included in the top group, based on the administered medications. FRAX score is calculated based on various risk factors; however, only glucocorticoid corresponds to medications. We should focus on medication prescription patterns in addition to FRAX to improve fracture risk assessment in hospital-wide surveillance. Therefore, we recommend the use of FRAX along with the prescribed medications to identify departments that admit high-risk patients.

Pharmacotherapy costs and medicines reimbursement policies of osteoporosis in the Republic of Bulgaria and Republic of North Macedonia

The aim of the present study was to analyze and compare the number of health insured persons suffering from osteoporosis and antiosteoporotic drugs reimbursed by the National Health Insurance Funds (NHIF) in the Republic of Bulgaria (RBG) and Republic of North Macedonia (RNM) for the period 2015–2018. The reimbursement cost paid by the NHIF for the same period in both countries was surveyed.

The results show an increase in both the number of patients with osteoporosis and the cost of the treatment. The most prescribed drug in R. Bulgaria is denosumab and it has the highest costs respectively, while in R.N. Macedonia the most prescribed and respectively the most expensive treatment is the bisphosphonate ibandronic acid, tablets of 150 mg. The trend of rising costs in both countries is likely to continue due to the increasing number of patients with osteoporosis.

The number of patients and cost of pharmacotherapy in RNM and RBG are increasing but the reimbursement policy in RNM is more restrictive in terms of reimbursed medicines. On the other side, the RNM is with a higher level of reimbursement that might positively affect the cost of pharmacotherapy.

Osteoking improves OP rat by enhancing HSP90‑β expression

Osteoporosis (OP) is a chronic bone disease that affects individuals worldwide. Osteoporosis is primarily asymptomatic, and patients with OP suffer from pain, inconvenience, economic pressure and osteoporotic fracture (OPF). Osteoking, a Traditional Chinese Medicine compound that originates from the Yi ethnic group, has been used for a number of years to treat fractures. In our previous study, osteoking exhibited therapeutic effects on rats with OPF by promoting calcium deposition. Based on bioinformatics and network pharmacology analyses of a component‑target‑disease database, heat shock protein HSP 90‑β (HSP90‑β), also known as HSP90‑β, was identified to be a key target of osteoking in OP. High HSP90‑β expression levels were observed in osteoporotic rats and rat bone mesenchymal stem cells (rBMSCs) following osteoking treatment. After 12 weeks of administration in vivo, there was increased bone mineral density (BMD) (P<0.05), increased bone alkaline phosphatase (P<0.05), and improved bone microstructure in the osteoking group compared with those of the negative control group. In vitro, increased calcium deposition in rBMSCs was observed after 4 weeks of osteoking treatment. These results suggest that the mechanisms of osteoking are closely associated with HSP90‑β and activate the bone morphogenetic protein (BMP) signalling pathway, primarily through BMP‑2. Osteoking treatment improves OP in rats by enhancing HSP90‑β expression.

Fracture prevention by screening for high fracture risk: a systematic review and meta-analysis

This systematic review and meta-analysis showed a significant reduction of (major) osteoporotic fractures and hip fractures after screening using fracture risk assessment and bone densitometry compared with usual care. The results indicate that screening is effective for fracture risk reduction, especially hip fractures. To perform a systematic review and meta-analysis of population screening for high fracture risk on fracture prevention compared with usual care. MEDLINE and Embase were searched for studies published until June 20th 2019. Randomized studies were selected that screened for high fracture risk using at least bone densitometry, screened in a general population, provided subsequent treatment with anti-osteoporosis medication, had a usual care group as comparator, and had at least one fracture-related outcome (all fractures, (major) osteoporotic fractures, or hip fractures). The primary assessment was the hazard ratio (HR) for fracture-related outcomes. All-cause mortality was a secondary outcome. Random-effects models were used to estimate pooled HRs. We identified 1186 potentially eligible articles and included three randomized studies: the ROSE study, the SCOOP study, and the SOS with a total number of N = 42,009 participants. Respectively, 11%, 15%, and 18% of the participants in the intervention group started medication. Meta-analysis showed a statistically significant and clinically relevant reduction of osteoporotic fractures (HR = 0.95, 95% confidence interval (CI) = 0.89-1.00), major osteoporotic fractures (HR = 0.91; 95%CI = 0.84-0.98), and hip fractures (HR = 0.80; 95%CI = 0.71-0.91), but no reduction of all fractures (HR = 0.95; 95%CI = 0.89-1.02). The pooled HR for the secondary outcome all-cause mortality was 1.04 (95% CI = 0.95-1.14). Numbers needed to screen to prevent one fracture were 247 and 272 for osteoporotic fractures and hip fractures, respectively (corresponding to 113 and 124 performed bone densitometry examinations, and 25 and 28 persons being treated). This meta-analysis showed that population screening is effective to reduce osteoporotic fractures and hip fractures. Implementation of screening in older women should be considered as serious option to prevent osteoporotic fractures, especially hip fractures.

Osteoporosis: Current Concepts

Osteoporosis is a worldwide disease characterized by reduction of bone mass and alteration of bone architecture resulting in increased bone fragility and increased fracture risk. Causes of osteoporosis include increasing age, female sex, postmenopausal status, hypogonadism or premature ovarian failure, low body mass index, ethnic background, rheumatoid arthritis, low bone mineral density (BMD), vitamin D deficiency, low calcium intake, hyperkyphosis, current smoking, alcohol abuse, immobilization, and long-term use of certain medications. The diagnosis of osteoporosis is established by measurement of BMD of the hip and spine using dual energy X-ray absorptiometry. According to the World Health Organization criteria, osteoporosis is defined as a BMD that lies 2.5 standard deviation or more below the average value for young healthy women. Bone turnover biomarker detection may be useful in monitoring osteoporosis treatment and assessing fracture risk but not for diagnosis of osteoporosis. Management of osteoporosis consists of nonpharmacological interventions, which are recommended for all subjects, and pharmacological therapy in all postmenopausal women who have had an osteoporotic fracture or have BMD values consistent with osteoporosis.