Aims Cardiovascular-kidney-metabolic (CKM) syndrome has developed into a global public health crisis. Although integrated care is increasingly used to treat patients with CKM, current health economic models fail to capture the value of considering the CKM syndrome as a unified condition. We present a conceptual framework to guide development of a new health economic model that captures value holistically across interconnected CKM domains.Materials and Methods Following best-practice guidelines, we undertook a review of published literature to identify and connect the key biological drivers of the CKM syndrome. These insights were synthesised into a biological framework, which was simplified into a streamlined influence diagram of sufficient complexity to guide model development. Both framework and diagram were iteratively reviewed and developed based on feedback from clinicians, health economists and modelling specialists.Results A biological framework and influence diagram were developed to illustrate how the CKM syndrome's biological drivers interconnect and link to key clinical outcomes. We detail the components of these diagrams, explaining the rationale behind connections. We discuss how the proposed framework could inform a model for future health economic evaluation.Conclusion There is a clear unmet need for comprehensive modelling of the CKM syndrome to support evidence-based decision-making and guide management of this highly prevalent, far-reaching disease. As more evidence has become available, the mathematical development, in the near future, of a long-term, holistic and flexible health economic model has become feasible, despite some gaps. This work seeks to shape a shared understanding of the challenges and opportunities in this developing field.

BACKGROUND:To model scenarios exploring potential impacts of disease-modifying therapies (DMTs) for Alzheimer's disease (AD) dementia on future health and social care costs in the United Kingdom. METHODS:A cohort Markov model was developed using population projections and published AD epidemiological data. Stage-specific transition rates (mild cognitive impairment due to AD and mild, moderate, severe AD dementia) and health and social care cost data were applied to estimate cost outcomes over 2020-2040. Potential proportion of eligible population receiving treatment (uptake) and follow-up care models (primary vs. specialist care) were elicited from expert opinion. Scenarios combined ranges of DMT efficacy estimates, uptake, and care model. DMT price was excluded due to no UK precedent. RESULTS:Without DMT access, 1,038,405 people (1.5%) were projected to have AD dementia by 2040. Under the various DMT treatment scenarios, the prevalence of AD dementia by 2040 was projected to be 34,000-98,000 cases lower. Associated cumulative cost offsets were higher, £4.4-12.9billion over 2020-2040, in scenarios where most individuals received primary care follow-up, compared with majority specialist care follow-up (-£2.3billion to +£3.2billion). Assuming DMT efficacy of 25%, 58% uptake and majority primary care follow-up cumulative cost offsets increased from £4.4billion to £10.1billion by 2040 but the UK Health Service would need to diagnose and provide DMT for over a million individuals by 2030 and two million by 2040 to achieve this. CONCLUSIONS:Potential cost offset from DMT are large but highly dependent on the model of healthcare delivery and the ability of healthcare systems to scale up diagnosis and treatment services.

Background Economic models support healthcare decision makers to efficiently assess value and allocate resources; formal validation is critical to ensure confidence in model outputs. The Obesity Lifecycle Model is a patient-level simulation model capturing natural history, clinical complications, quality-of-life and economic outcomes associated with obesity; however, it has yet to undergo formal external and cross-validation. Objective The aim of this study was to validate the Obesity Lifecyle Model as per best practice guidelines from the Professional Society for Health Economics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM) Task Force. Methods Relevant data sources and outcomes were identified for all validations. Selected validation studies informed the model to simulate study outcomes. The model was populated with study characteristics to reproduce studies used in model development (dependent validation), studies not used in model development (independent validation), or other published models (cross-validation). Accuracy between predicted and observed outcomes was assessed using standard statistical methods and mean error calculations. Results The model demonstrated overall concordance with observed outcomes, supported by coefficient of determination (R-2) and ordinary least squares linear regression line (OLS LRL) estimates generally close to 1.0. Independent validation showed an underprediction for cardiovascular disease (CVD) and mortality with an OLS LRL of 0.9309 and an R-2 of 0.8984 across all populations (normoglycaemic/prediabetic populations: OLS LRL = 0.9485, R-2 = 0.8854; T2DM populations: OLS LRL = 0.9208, R-2 = 0.9068). Conclusions The Obesity Lifecycle Model demonstrates favourable concordance with observed clinical and quality-of-life outcomes, supporting its use for evaluating obesity-related complications and informing healthcare decision making.

The latest type 2 diabetes mellitus (T2DM) management guidelines from the UK National Institute for Health and Care Excellence (NICE; NG28) have raised the profile of sodium–glucose cotransporter-2 inhibitors (SGLT2is) so that they are now the preferred first-line therapy in combination with modified-release metformin (or as monotherapy where metformin is contraindicated/not tolerated) for most individuals. Previous NICE recommendations limited use to those with high cardiovascular disease (CVD) risk or existing CVD and/or kidney disease for first-line treatment or people with a need for additional glycaemic optimisation at later stages in the pathway. This change brings the guidelines in line with other national and international recommendations regarding SGLT2i use for the achievement and maintenance of glycaemic targets and lowering of progressive risk for cardiovascular, renal and metabolic (CVRM) complications. Yet, despite a plethora of evidence supporting the role that SGLT2is can play in sustaining long-term health outcomes in people with T2DM, prescribing data from real-world clinical practice show that these therapies are under-prescribed, particularly among those populations most likely to benefit from their use (including individuals with CVD or high CVRM risk). This latest narrative review from the Improving Diabetes Steering Committee examines the place of SGLT2is within the latest NG28 guidelines and likely reasons for suboptimal SGLT2i use, providing pragmatic advice on appropriate approaches to initiation and management in daily practice and setting perceived risks into context against the potential benefits. Practical tools for healthcare professionals and people with T2DM are included, and the Committee’s previously published SGLT2i Prescribing Decision Tool for T2DM Management has been updated and aligned with the most recent guidelines with the aim of providing a helpful and high-quality quick reference resource.

The health economic value of insulin is usually expressed within a cost-effectiveness framework providing an estimated incremental cost per quality-adjusted life year (QALY) gained. Insulin clinical trials adopt a treat-to-target design in which both intervention and control arms aim to achieve similar levels of glycaemic control thereby allowing a comparison of secondary safety outcomes such as hypoglycaemia and weight gain. While of use to inform clinicians about the new insulin's tolerability, it is of limited use for an economic evaluation. An insulin's true potential value requires an assessment of the relationship between the benefits of attaining individualised glycaemic goals versus the factors known to act as barriers to the initiation/intensification of insulin and that also contribute to poor adherence in clinical practice. Addressing the rising demands that diabetes will impose upon the healthcare system will require the simultaneous execution of multiple strategies that acknowledge population dynamics, healthcare delivery constraints, the role of innovation and funding requirements. Accounting for patient-specific characteristics to develop individualised plans and utilising technologies that address relevant barriers to care will require a whole-system perspective on healthcare value and an appreciation of the interconnectivity of stakeholder needs. Importantly, convenience and treatment satisfaction are often not considered valuable features of insulin therapy; not only do they have value, but they are essential to addressing rising demands. PLAIN LANGUAGE SUMMARY: More people around the world are living with diabetes. This is because people are living longer, populations are getting older, and more people are developing the disease. Clinicians will have to prescribe insulin for more people. To make well-informed decisions about how to spend money on diabetes care, we need to understand how much therapies costs and how well they work. In healthcare, people often talk about "value for money." This means getting better results without spending more money, or saving money without making things worse. However, it's not always easy to figure out the value of new types of insulin. The way insulin is studied in clinical trials doesn't always relate well to how it works, and is used, in real-life clinical practice. Many studies don't look at all the things that matter, like how easy it is for people to use the insulin or how it affects their daily lives. When two types of insulin have comparable efficacy in terms of lowering blood sugar, other things - like side effects, how easy it is to use, and how well people stick to their treatment - become important drivers of value. These things are different for each person, may be left out of studies and may not considered to be important by decision makers. In this paper, we first discuss how the health economics of insulin has traditionally been studied, and look at the findings, advantages and disadvantages of these approaches. We also describe how tools like continuous glucose monitors (which track blood sugar all the time) can help people improve outcomes. We introduce what we call the "insulin value system." This looks at how the features of the insulin, the patient's circumstances, and the state of the healthcare system interact to determine the value of a new therapy. In the case of insulin therapies, traditional approaches to value assessment don't always capture the full picture. Our second goal is to talk about the big challenges in diabetes care, for which there are no easy solutions. More people are getting diabetes, and more money will be needed for treatment and disease management. We believe that to really help make a difference, we need to consider the whole healthcare system, how everything is connected, and not just focus on one part. We believe it's important to look at how people live and work, their personal circumstances and how they and the healthcare system interact when assessing the value of insulin. That way, we can better understand how new treatments can help both people and the wider healthcare system.

Type 2 diabetes (T2D) imposes significant personal challenges and societal costs. Continuous glucose monitoring (CGM) is recognised as a state-of-the-art tool, but remains underutilised. Adoption of CGM in primary care should be informed by a broader understanding of the technology’s capabilities and limitations. An expert panel was convened to review current literature and clinical experience to provide practical approaches to CGM for primary care practitioners and discuss the technology’s value in the routine management of T2D. The goals were to review and reach consensus on the current state of CGM in non-specialist practice settings and on strategies for successfully initiating and maintaining people on CGM. Initiation and maintenance of CGM therapy can be successfully conducted in primary care settings. CGM therapy should include proper patient selection, proper setting of expectations, and evidence-based adjustments to therapy. Most patients are likely to see quick, meaningful, and lasting improvements in their diabetes, along with a better understanding of their condition and greater motivation for successful management. Retrospective report interpretation is feasible and intuitive. Barriers to adoption and sustained use include cost, technological limitations, behavioural or psychological factors, and therapeutic inertia. Addressing these barriers is critical to enable better access to CGM. Continuous glucose monitoring can be leveraged by primary care teams to inform treatment decisions and also by patients to inform diabetes self-management. CGM should be considered for all people with T2D. The recommendations provided here should simplify adoption and maintenance use of CGM in primary care and maximise the glycaemic and psychosocial benefits of the technology.

Diabetes mellitus (DM) is a significant public health and economic concern in Saudi Arabia, affecting more than 20% of adults. Insulin remains a cornerstone in DM management, but the country relies significantly on imported products. Hence, this results in high healthcare expenditures and variable availability. In line with Vision 2030, Saudi Arabia has prioritized the localization of insulin manufacturing to ensure sustainable access, reduce import dependency, and enhance national health security. This paper explores the clinical, economic, and policy implications of localizing insulin production in the Kingdom. The current work used a case study methodology to assess the feasibility, challenges, and strategic opportunities for the domestic production of innovative insulins, such as Degludec and IDegAsp. The study supports the development of public-private partnerships, investment in biotechnology infrastructure, and regulatory reform to foster a robust local biopharmaceutical ecosystem. By 2027, Saudi Arabia aims to meet 50% of its insulin demand through local production, making it the first country in the GCC region to produce innovative insulin. This initiative is expected to promote affordability and position the Kingdom as a leader in insulin innovation.

Tirzepatide, an anti-obesity medication, demonstrated significant weight loss efficacy in the SURMOUNT-1 randomized controlled trial. This analysis evaluates the cost-efficiency of tirzepatide in the UK by linking clinical outcomes to drug acquisition costs. Data from SURMOUNT-1 (2539 participants across global sites) were used to assess tirzepatide’s (5, 10, and 15 mg) impact on weight reduction over 72 weeks (72W), with a focus on drug acquisition costs and cost/weight loss outcome. Cost needed to treat and cost-to-target analyses were performed to determine the economic value of achieving specific weight loss goals and improvements in body mass index (BMI). Tirzepatide demonstrated significant weight loss, with greater reductions at higher doses. Cost/kilogram of weight loss at 72W was £102.86, £85.41, and £89.24 for 5, 10, and 15 mg, respectively. Average per-patient costs at 72W for 5

How and why healthcare utilisation and costs vary between patients with Alzheimer’s disease dementia (ADD) is not well understood but is important in ensuring that efforts to improve the diagnosis and treatment of ADD are prioritised effectively. We aimed to investigate variation in healthcare resource utilisation (HCRU) among patients with ADD in England and identify the clinical and demographic factors which characterise subpopulations with the highest HCRU. This was a retrospective cohort study using Discover, a linked electronic health record database of 2.8 million residents in London, England. We identified individuals with ADD using diagnostic codes and estimated HCRU and total healthcare costs over up to 9 years of follow up (2010-2019). Individuals included in the 2019 cross-section were stratified into cost quintiles, and K-medoids clustering was used to identify subpopulations with high costs. We identified 18,116 individuals with ADD between 2010 and 2019 (Table 1). Costs in the highest HCRU cost quintile in 2019 accounted for 56% of all healthcare costs in the ADD population, were approximately 20 times higher than the lowest cost quintile (£13,665 vs. £678 per patient per year [ppy]) and were largely attributed to hospital admissions (Figure 1). Individuals in the higher cost populations tended to be older, male, have a higher comorbidity burden and a lower median survival than those in the lower cost populations. The three groups with the highest costs identified by the cluster analysis had substantial comorbidity burden, with more than 65% of individuals having four or more comorbidities (Figure 2). The most common comorbidities were cardiometabolic diseases, chronic kidney disease, and frailty. The costs in the highest cost cluster were more than double the cluster with lowest costs (£6,355 vs. £3,160 ppy). Healthcare utilisation and costs in individuals with ADD vary widely, with a large proportion of costs being attributable to a minority of patients with multiple comorbidities, particularly cardiometabolic diseases and frailty. Health systems should focus on patients with clinical profiles associated with high costs in efforts to improve the timely diagnosis and treatment of ADD and mitigate the financial costs of ADD on patients, health systems, and society.

Cardiovascular, kidney and metabolic (CKM) conditions are interrelated, significantly contributing to morbidity, mortality and healthcare burden. Despite therapeutic advances, traditional disease-specific approaches often fail to address their complex interplay. Key therapeutic agents-including glucagon-like peptide-1 receptor agonists (GLP-1 RAs), dual GLP-1/glucose-dependent insulinotropic polypeptide RAs, sodium glucose co-transporter inhibitors and the nonsteroidal mineralocorticoid receptor antagonist (MRA) finerenone-offer multi-organ benefits. Emerging therapies, such as triple receptor agonists and second-generation MRAs, target new pathways further expanding treatment options for CKM conditions. A holistic CKM management approach must address and recognise that conditions such as metabolic dysfunction-associated steatotic liver disease, metabolic dysfunction-associated steatohepatitis, obstructive sleep apnoea and obesity are part of the CKM spectrum. Frailty assessment is also important alongside CKM conditions, warranting comprehensive geriatric assessment and deprescribing when appropriate. Multidisciplinary care-including lifestyle interventions, pathway redesign, pharmacological advances and novel technologies-is essential for improving outcomes. As the CKM landscape evolves, future strategies should prioritise early intervention, personalised treatment and addressing unmet needs in high-risk populations. This review advocates for an integrated CKM framework, exploring treatment strategies, emerging therapies and technological innovations. It also examines the role of artificial intelligence and digital health tools in risk stratification, early diagnosis and long-term condition management, alongside ethical and regulatory considerations.

INTRODUCTION:Mild cognitive impairment (MCI) is common in older adults, but the burden on patients and health systems is not well understood. We aimed to estimate the impact of MCI on healthcare utilization and costs. METHODS:This was a matched cohort study in UK Biobank comparing healthcare costs and Alzheimer's disease (AD) dementia incidence rates in participants with MCI to propensity score-matched participants without MCI. RESULTS:Of 164,508 eligible participants, 6605(4%) had cognitive testing scores consistent with MCI. Ten-year inpatient costs were 7.6% higher in MCI versus matched no-MCI participants, while 6-year primary care costs were 9.1% higher. Among MCI participants, AD dementia incidence rates were substantially higher than in non-MCI participants (7.2 5-year incidence rate ratio 95% CI: 3.3 to 15.7), and eventual AD dementia accrued higher additional inpatient costs (mean £20,199) over 10 years. DISCUSSION:MCI is characterized by modestly higher healthcare utilization and costs. Subsequent AD dementia diagnosis was strongly associated with costs. Highlights:Baseline cognitive tests identified individuals with all-cause MCI in the UK Biobank.We compared individuals with MCI to propensity score-matched participants without MCI.Inpatient costs were 7.6% higher over 10 years, and primary care costs were 9.1% higher over 6 years for participants with MCI.AD dementia incidence rate ratio was 7.2 higher in participants with MCI.Among MCI participants, eventual AD dementia was a key driver of costs resulting in higher inpatient costs (mean £20,199) over 10 years.

AIMS:There is current apprehension among some clinicians and conflicting evidence regarding ocular complications in relation to Glucagon-like peptide-1 receptor agonists (GLP-1RAs). We aimed to generate multi-disciplinary, expert-led consensus recommendations relating to ocular complications to facilitate optimum prescribing of GLP-1RAs. MATERIALS AND METHODS:A modified Delphi was conducted following the ACcurate COnsensus Reporting Document (ACCORD) for Delphi research. A structured literature review informed an anonymous online Delphi questionnaire, followed by a virtual consensus meeting. Eligible participants included ophthalmologists, diabetologists, and obesity specialists practising in Europe. RESULTS:Responses from 58 participants across 17 countries were analysed. Respondents agreed that diabetic retinopathy (DR) worsening events are primarily linked to rapid blood glucose-lowering, rather than a direct drug effect. The benefits of GLP-1RAs were deemed to outweigh potential ocular risks and should not limit access to these medicines. Prescribers should ensure that people with diabetes are screened for diabetic retinopathy before commencing GLP-1RAs, particularly in high-risk populations (>10 years duration and/or poor glucose control, (haemoglobin A1c [HbA1c] >10% or 86 mmol/mol)). When prescribing GLP-1RA to those with sight loss in one eye and/or prior history of non-arteritic anterior ischaemic optic neuropathy (NAION), the risk of ocular complications should be discussed. The Delphi study highlighted current uncertainty in the evidence, with some topics on the relationship between GLP-1RAs and ocular complications reaching limited consensus. CONCLUSIONS:Further research is needed into the direct effects of GLP-1RAs on the retina and ocular complications. New evidence should be disseminated rapidly to optimise outcomes and safety.

Background: Multimorbidity (having two or more comorbidities), is common among people with dementia and associated with lower survival and increased healthcare use. We aimed to identify comorbidity clusters in people living with Alzheimer’s disease (AD) dementia in the UK, describe comorbidity-cluster prevalence and patterns, and estimate associations of clusters with healthcare resource utilisation (HCRU) and costs. Methods: This was a cohort study using Discover dataset (electronic health records from approximately 2.8 million North-West London residents). We identified individuals with AD dementia using diagnostic codes, and estimated HCRU and total healthcare costs (including primary and hospital-based care). Individuals were grouped based on comorbidity profile using k-medoids clustering. Multivariable modelling was used to estimate associations between comorbidity clusters and healthcare costs. Results: Among 18,116 individuals with AD dementia, eight comorbidity clusters were identified. The three highest-cost clusters incurred mean costs per patient year(ppy) of £6355, £5560, and £5284 respectively. The highest-cost cluster had a high burden of comorbidities with the most prevalent: frailty (83.2 %), hypertension (81.8 %), type 2 diabetes mellitus (81.4 %), and chronic kidney disease (69.7 %). Costs in the three highest-cost clusters were 1.7 to 2.0 times higher than the lowest-cost cluster (mean cost £3160ppy), which featured the lowest overall comorbidity burden. The lowest median survival times were in the two highest-cost clusters. Cluster membership was strongly associated with costs even after adjusting for a wide range of demographic and clinical factors. Compared with the lowest-cost cluster the average marginal increases in costs for the clusters ranged between £1072 (95 %CI:£478-£1666) and £3531ppy (95 %CI: £2850-£4212). Conclusions: HCRU and costs in individuals with AD dementia show notable differences, with a large proportion of costs attributable to a minority of individuals with multiple comorbidities (particularly cardiometabolic diseases and frailty). Health systems should ensure initiatives to improve timely diagnosis and treatment of people with AD taking account of the high multimorbidity prevalence in this population.