This study identified the costs and health-related quality of life impacts of several post-fracture multidisciplinary care pathways specific to individual skeletal site (hip, distal forearm, vertebrae, humerus). These care pathways may assist healthcare providers in allocating resources for osteoporotic fractures in more effective and cost-efficient ways. This micro-costing study was undertaken to provide the estimated healthcare costs of several fracture site-specific health service use pathways associated with different trajectories of health-related quality of life (HRQoL) 12-months post-fracture. The study included 4126 adults aged ≥ 50 years with a fragility fracture (1657 hip, 681 vertebrae, 1354 distal forearm, 434 humerus) from the International Costs & Utilities Related to Osteoporotic fractures Study (ICUROS). ICUROS participants were asked to recall the frequency and duration (where applicable) of their health and community care service use at 4- and 12-month follow-up visits. Patient-level costs were identified and aggregated to determine the average cost of healthcare use related to the fracture in each care pathway (presented in Australian 2021 dollars). Mean cost differences were calculated and analysed using a one-way analysis of variance (ANOVA) and post hoc Bonferroni correction to determine any statistically significant differences. The total direct cost of fractures was estimated at $89564, $38926, $18333, and $38461AUD per patient for hip, vertebral, wrist, and humeral participants, respectively. A Kruskal–Wallis test yielded a statistically significant difference in cost values between most care pathways (p < 0.001). Of the 20 care pathways, those associated with recovery of HRQoL had lower mean costs per patient across each fracture site. This study identified the costs and HRQoL impacts of several multidisciplinary care pathways for individual fracture sites based on the health service utilization of an international cohort of older adults. These care pathways may assist healthcare providers in allocating resources for fragility fractures in more effective and cost-efficient ways.

Summary The IOF Epidemiology and Quality of Life Working Group has reviewed the potential role of population screening for high hip fracture risk against well-established criteria. The report concludes that such an approach should strongly be considered in many health care systems to reduce the burden of hip fractures. Introduction The burden of long-term osteoporosis management falls on primary care in most healthcare systems. However, a wide and stable treatment gap exists in many such settings; most of which appears to be secondary to a lack of awareness of fracture risk. Screening is a public health measure for the purpose of identifying individuals who are likely to benefit from further investigations and/or treatment to reduce the risk of a disease or its complications. The purpose of this report was to review the evidence for a potential screening programme to identify postmenopausal women at increased risk of hip fracture. Methods The approach took well-established criteria for the development of a screening program, adapted by the UK National Screening Committee, and sought the opinion of 20 members of the International Osteoporosis Foundation’s Working Group on Epidemiology and Quality of Life as to whether each criterion was met (yes, partial or no). For each criterion, the evidence base was then reviewed and summarized. Results and Conclusion The report concludes that evidence supports the proposal that screening for high fracture risk in primary care should strongly be considered for incorporation into many health care systems to reduce the burden of fractures, particularly hip fractures. The key remaining hurdles to overcome are engagement with primary care healthcare professionals, and the implementation of systems that facilitate and maintain the screening program.

Heavy menstrual bleeding is the main symptom of uterine fibroids (UF), significantly affecting quality of life of women with symptomatic UF, and is measured in most clinical trials involving UF patients. The objective was to develop a predictive utility function based on incremental changes in menstrual blood loss (MBL) to estimate QoL in patients with symptomatic UF for use in health economic models. A parsimonious regression model was developed to promote replicability and transparency while utilizing the most important clinical factors in UF patients such as MBL. An ordinary least squares (OLS) regression was parameterized on patient-level data from clinical trials. The OLS model included MBL volume and age as parameters and EQ-5D index values as outcome. EQ-5D values were generated from Uterine Fibroid Symptom and Quality of Life (UFS-QoL) measures. Within-patient correlation was not modelled, and all patient observations were pooled together to ensure all data was used. The OLS model was fitted using 1,706 observations. The estimated intercept was 0.69568, the coefficient for MBL volume in mL was -0.0003877 and the coefficient for age was 0.00296. Thus, the model predicts that, all else equal, a 100 mL decrease in MBL volume increases EQ-5D index value by 0.04 and a one-year increase in age corresponds to a 0.003 increase in EQ-5D. Improvement in MBL is predicted to be associated with proportional improvements in the overall quality of life of UF patients. The prediction model offers a simple and transparent way to estimate quality of life based on changes in MBL for direct use in health economic modelling.

Romosozumab is a novel bone-building drug that reduces fracture risk. This health economic analysis indicates that sequential romosozumab-to-alendronate can be a cost-effective treatment option for postmenopausal women with severe osteoporosis at high risk of fracture. To estimate the cost-effectiveness of sequential treatment with romosozumab followed by alendronate (“romosozumab-to-alendronate”) compared with alendronate alone in patients with severe osteoporosis at high risk of fracture in Sweden. A microsimulation model with a Markov structure was used to simulate fractures, costs, and quality-adjusted life years (QALYs), for women treated with romosozumab-to-alendronate or alendronate alone. Patients aged 74 years with a recent major osteoporotic fracture (MOF) were followed from the start of treatment until the age of 100 years or death. Treatment with romosozumab for 12 months was followed by alendronate for up to 48 months or alendronate alone with a maximum treatment duration of 60 months. The analysis had a societal perspective. Efficacy of romosozumab and alendronate were derived from phase III randomized controlled trials. Resource use and unit costs were collected from the literature. Cost-effectiveness was estimated using incremental cost-effectiveness ratio (ICER) with QALYs as effectiveness measures. The base case analysis showed that sequential romosozumab-to-alendronate treatment was associated with 0.089 additional QALYs at an additional cost of €3002 compared to alendronate alone, resulting in an ICER of €33,732. At a Swedish reference willingness-to-pay per QALY of €60,000, romosozumab-to-alendronate had a 97.9% probability of being cost-effective against alendronate alone. The results were most sensitive to time horizon, persistence assumptions, patient age, and treatment efficacy. The results of this study indicate that sequential romosozumab-to-alendronate can be a cost-effective treatment option for postmenopausal women with severe osteoporosis at high risk of fracture.

A novel cost-effectiveness model framework was developed to incorporate the elevated fracture risk associated with a recent fracture and to allow sequential osteoporosis therapies to be evaluated. Treating patients with severe osteoporosis after a recent fracture with a bone-forming agent followed by antiresorptive therapy can be cost-effective compared with antiresorptive therapy alone. Incorporating these novel technical attributes in economic evaluations can support appropriate policy and reimbursement decision-making. To develop a cost-effectiveness model accommodating increased fracture risk after a recent fracture and treatment sequencing. A micro-simulation cost-utility model was developed to accommodate both treatment sequencing and increased risk with recent fracture. The risk of fracture was estimated and simulated using the FRAX® algorithms combined with Swedish registry data on imminent fracture relative risk. In the base-case cost-effectiveness analysis, a sequential treatment starting with a bone-forming agent for 12 months followed by an antiresorptive agent for 48 months initiated immediately after a major osteoporotic fracture (MOF) in a 70-year-old woman with a T-score of 2.5 or less was compared to an antiresorptive treatment alone for 60 months. The model was populated with data relevant for a UK population reflecting a personal social service perspective. The cost per additional quality-adjusted life year (QALY) gained in the base-case setting was estimated at £34,584. Sensitivity analyses revealed the sequential treatment to be cost-saving compared with administering a bone-forming treatment alone. Without simulating an elevated fracture risk immediately after a recent fracture, the cost per QALY changed from £34,584 to £62,184. Incorporating imminent fracture risk in economic evaluations has a significant impact on the cost-effectiveness when evaluating fracture prevention treatments in patients with osteoporosis who sustained a recent fracture. Bone-forming treatment followed by antiresorptive therapy can be cost-effective compared to antiresorptive therapy alone depending on treatment acquisition costs.

Own health state utility values (HSUV, “experience-based utility”) is important for economic valuation and other purposes. There is only one preference-based EQ-5D value set derived from direct patient experience. Furthermore, the impact of interactions between EQ-5D dimensions on HSUV is poorly understood. Therefore we constructed a value set using direct patient experience and explored the impact of interactions between health states. The ICUROS was a multinational prospective observational study on the consequences of fragility fracture. In the study, patients who sustained a fragility fracture completed EQ-5D-3L and Time-trade-off (TTO) questionnaires for five time points: before fracture (recall), within two weeks after fracture, and at 4, 12 and 18 months after fracture. We derived a value set by fitting a random intercept linear model with TTO as the dependent variable and ‘moderate’ (Level 2, “L2”) or ‘severe’ impairment (Level 3, “L3”) in each EQ-5D dimension as dummy variables. We also explored the potential impact of interactions between impairment in dimensions using rigorous Lasso regression with cluster robust standard errors. In total 4,873 patients reported 17,779 EQ-5D and TTO pairs. Mean (SD) age at study enrolment was 71 (11) years and 81% were women. In the random intercept model, all coefficients had the expected sign and were statistically significant (p<0.001). The resulting value set was: 0.92 - 0.03xMobillityL2 - 0.08xMobillityL3 - 0.12xSelf-careL2 - 0.14xSelf-careL3 - 0.02xUsual ActivitiesL2 - 0.03xActivitiesL3 - 0.02xPain/DiscomfortL2 - 0.10xPain/DiscomfortL3 - 0.05xAnxiety/DepressionL2 ´- 0.11xAnxiety/DepressionL3. The Lasso regression indicated that interactions between mobility and self-care, anxiety/depression and self-care, and anxiety/depression and usual activities may be important. This experience-based EQ-5D-3L value set had consistently ordered and statistically significant coefficients, demonstrating face validity. Furthermore, the results show that explicit modelling of interactions may improve the predictive power of EQ-5D value sets. Compared to value sets based on hypothetical health, the decrements associated with impaired health were generally smaller.

We investigated changes in health-related quality of life (HRQoL) due to hip fracture in Mexican adults aged ≥ 50 years during the first year post-fracture. Mean accumulated loss was 0.27 quality-adjusted life years (QALYs). HRQoL before fracture was the main contributor to explain the loss of QALYs.

Rising greenhouse gas emissions (GHGEs) are responsible for climate change and have both direct and indirect implications for health. Over 160 parties have communicated their CO2 reduction targets to the UNFCCC for 2030 and 2050, i.e. for the EU a target of at least 40% below 1990 levels, for Asia and the APAC region a range from 25% to over 40%. The main drivers for GHGE are the energy industry, agriculture, transport, and household consumption, but the healthcare sector globally contributes an estimated 5-8% of the total GHGE. The majority of healthcare sector CO2 emissions come from procurement of goods and services, hospitals and pharmaceutical industry. Some countries have developed different strategies to curb the healthcare GHGE such as taxation and green public procurement (GPP); GPP may also include procurement of pharmaceuticals and devices (e.g. Sweden, UK). Besides, manufacturers have developed sustainability strategies and reduction plans for GHGE and waste. At product level companies have started to review and improve the carbon footprint (PCF) by mapping the CO2 profile throughout the life cycle ("cradle to grave"). Priorities are in high volume indications with routine use of disposable devices, e.g. inhalers, diabetes injectors. Inhalers for respiratory patients contribute to GHGE as most contain propellants. The UK NHS has reported that propellants from inhalers account for 8% of the NHS's entire carbon footprint. More than 640 million inhalers are used globally every year. However, product HTA and appraisals typically favour low cost inhalers and do not consider benefits to the system such as less waste and less CO2e. Budget Impact Analyses may include the monetary value of a more favourable PCF using a social cost of carbon (SCC), estimated at 36 to 220 US$/tCO2e. Such analysis may inform decisions which contribute to the national efforts to reduce CO2 emissions.

Osteoporotic fractures increase the risk of subsequent fracture. This risk is distinctly elevated immediately after the fragility fracture (‘imminent risk’) and can remain elevated for 10 years, highlighting the importance of early identification and treatment. Treatment sequences for new bone-forming agents are being assessed for use in patients at imminent risk of fracture. Here, we describe a new cost-effectiveness model framework relevant to the use of bone-forming agents. We developed a Markov-microsimulation model to simulate the projected treatment pathway, quality adjusted life years (QALYs) and lifetime costs of a patient with a fragility fracture, with treatment sequencing and time since fracture as factors. The patient could switch treatment when a lack of response was confirmed, or at any time point, dependent on clinical practice. In each 6-month cycle, we assessed risk of subsequent hip, vertebral and non-hip/non-vertebral fracture, remaining without subsequent fracture, or death. Fracture risk was derived from FRAX® and imminent fracture risk algorithms, and was updated for each patient in the event of subsequent fracture. Hypothetical examples were used for illustrative purposes. Treatment with a bone-forming agent immediately after fragility fracture was compared with treatment given 2 years after fracture. In an illustrative 75-year old woman with an initial vertebral fracture, the 10-year cumulative risk of a subsequent fracture was 11% lower for immediate treatment versus treatment after 2 years, fracture-related costs were 6% lower, QALY gain was 0.0172 and total costs were £1,758 higher. Similar values were derived with a lifetime perspective. This new economic modelling framework allows an estimation of the consequences of recurring fragility fractures over time and of the utility of flexible treatment sequencing. Our model will enable future evaluation of the cost effectiveness of individual treatment strategies.

The present study, drawn from a sample of the Icelandic population, quantified high immediate risk and utility loss of subsequent fracture after a sentinel fracture (at the hip, spine, distal forearm and humerus) that attenuated with time.

Bacterial and viral infections are often clinically indistinguishable, particularly in patients with respiratory tract infections. It is important to set a framework for evaluating diagnostic tests aiming to differentiate between these infections, since misdiagnosis can lead to antibiotic misuse and complications. The objective is to demonstrate the development of a cost-effectiveness model framework that integrates diagnostic pathways with antibiotic treatment decisions and its consequences, and accounts for the cost of antimicrobial resistance (AMR). A health-economic model was developed, which compares a new diagnostic test to standard-of-care (SoC), by simulating patients' diagnostic and treatment pathways, quality-adjusted life years and associated costs. The model consists of three parts: 1.) A decision tree describing patients' diagnostic pathways upon arrival at the emergency department; 2.) A Markov model simulating the therapeutic decision and its consequences, such as antibiotic adverse events; and 3.) An optional functionality that accounts for the cost of AMR. In a hypothetical scenario in which bacteria was the causative agent in 15% of pediatric patients and the new diagnostic had 15% higher sensitivity and specificity compared to SoC, holding all other model inputs equal, the antibiotic prescription rate was reduced by more than 30%, and costs due to antibiotic treatment plus related side effects, not including AMR, were reduced by approximately 30%. Additional results will be presented. This modelling framework is useful for comparing diagnostic tests to SoC, taking diagnostic accuracy, treatment decisions and treatment-related consequences into account, and for assessing the impact on antibiotic consumption. Furthermore, this framework accounts for the cost of AMR. Since this cost is a negative externality resulting from the consumption of antibiotics, it is usually not included in health economic evaluations. In the future the model will be used to assess the cost-effectiveness, and antibiotic-related aspects, of a new diagnostic in comparison to SoC.