PharmacoEconomics最新文献

Background and objective: Inflammatory arthritis is a common condition treated in rheumatology clinics, contributing significantly to healthcare costs and societal burden. Understanding the economic impact of inflammatory arthritis requires a comprehensive analysis through cost-of-illness studies. This systematic review aims to gather up-to-date cost-of-illness data on inflammatory arthritis from various countries, identify the primary cost drivers, describe shifts in cost components and appraise the quality of cost-of-illness study reporting in this field.

Methods: An electronic search was performed across four databases, including MEDLINE, Embase, the Cochrane Database of Systematic Reviews and the Health Management Information Consortium, to identify cost-of-illness studies on inflammatory arthritis published over the past two decades. The primary outcome was the annual cost per patient with inflammatory arthritis, categorised by cost components. All costs were standardised to 2024 US dollar values. The quality of the included studies was evaluated using the Larg and Moss checklist and the modified Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist.

Results: From an initial 12,264 publications, 82 studies were included in this review, covering axial spondyloarthritis (n = 49), psoriatic arthritis (n = 30), reactive arthritis (n = 2), rheumatoid arthritis (n = 13; 2019 onwards) and seronegative/seropositive rheumatoid arthritis (n = 8). Annual total societal costs varied considerably across inflammatory arthritis subtypes and countries. Medication expenditures consistently emerged as the primary direct healthcare cost driver, while productivity losses due to morbidity constituted the major component of indirect costs. Carer productivity loss represented a substantial proportion of indirect costs (up to 60.9%), yet was infrequently reported. Over time, we observed an increasing proportion of medication-related costs and a decreasing proportion of productivity losses for axial spondyloarthritis, alongside a reduction in inpatient care costs for psoriatic arthritis. These evolving cost distributions mirror patterns previously reported in rheumatoid arthritis. Methodological gaps were evident, with most studies lacking sensitivity analyses and comprehensive cost perspectives.

Conclusions: A substantial economic impact of inflammatory arthritis across different regions and subtypes was identified. This review emphasises the importance of including comprehensive cost components to fully assess the economic burden of inflammatory arthritis and provides methodological recommendations for future studies.

Objective: To understand the application of productivity-adjusted life years (PALYs) as an outcome measure across various disease contexts.

Methods: We conducted a scoping review of studies published between 2018 and April 2025 that utilised PALYs to illustrate their potential applications and identify methodological approaches that have been applied. Using a citation-based search, we selected studies that applied PALYs to quantify societal health burdens in specific diseases or contexts. Extracted data included health conditions, country, timeframe, model type, outcomes, productivity index components, gross domestic product and sensitivity analysis. Findings were summarised through narrative synthesis.

Results: A total of 41 studies conducted between 2018 and 2025 were reviewed, including chronic diseases such as diabetes and cardiovascular diseases, as well as environmental factors. Conditions such as breast cancer, leukaemia, kidney disease, mental health, knee osteoarthritis, epilepsy and sleep apnoea had the lowest productivity indices. Most of these studies originated from high-income countries (n = 27), followed by upper-middle-income (n = 10), and lower-middle-income (n = 4) settings. Life table models were the most common methodological approach adopted (n = 26), followed by dynamic models (n = 10). Studies focused on disease prevention (n = 21) outnumbered those addressing disease management (n = 18). Most studies accounted for both absenteeism and presenteeism (n = 30). Estimates of productivity loss per person using gross domestic product ranged from US$1137 to AU$217,983 annually.

Conclusions: PALYs have been utilised in diverse diseases and contexts, highlighting their utility in measuring societal health impacts. However, adding unpaid and informal work makes burden estimates more accurate. The increasing emphasis on prevention indicates a strategic change in health policy and economic assessment.

Background: Advances in the availability and regimen optimization of highly effective disease-modifying treatments (DMTs) for relapsing-remitting multiple sclerosis (RRMS) have led to questions about their comparative worth.

Objectives: This study evaluates the costs and effects of natalizumab versus other highly effective DMTs and the impact, in terms of times and costs, of the new subcutaneous natalizumab formulation versus the intravenous formulation in patients with RRMS in Italy.

Methods: This is a cost-consequence analysis from the Italian national health service and societal perspectives. A Markov model was developed to assess clinical and cost outcomes related to disease and DMTs. The model simulated two scenarios: one comparing natalizumab extended-dose regimen and ofatumumab and ocrelizumab, focusing on efficacy outcomes and costs, and one comparing intravenous and subcutaneous natalizumab with a focus on administration resource consumption, times, and costs. Model input data came from the literature.

Results: DMTs had similar clinical and social outcomes: natalizumab slightly reduced disease progression, increased quality-adjusted life-years, and reduced the impact on days of productivity loss and informal care. Natalizumab also resulted in statistically significant 5-year cost reductions compared with ocrelizumab and ofatumumab. Subcutaneous natalizumab improved resource consumption compared with intravenous natalizumab, saving the time of healthcare professionals, patients, and caregivers and reducing administration costs. The subcutaneous formulation was associated with statistically significant total direct and indirect cost reductions at 5 years.

Conclusion: 6-week dosing regimen of natalizumab showed a slight improvement of clinical and social outcomes and a statistically significant cost reduction compared with ocrelizumab and ofatumumab over a 5-year simulation. Moreover, subcutaneous administration reduced administration times and costs.

Objectives: Most medication errors occur in primary and long-term care, and a wide range of medication safety interventions have been implemented, but these are often expensive, with little evidence around cost-effectiveness. We report a systematic review of economic evaluations of these interventions within primary and long-term healthcare settings.

Methods: A comprehensive search was conducted in databases (Medline, Embase, Econlit and PsycINFO) for full economic evaluations of primary care interventions targeting all errors in the medication use process (January 2004 to September 2025). Methodological and reporting qualities were assessed using standard tools.

Results: From 8523 records, 44 studies evaluating interventions in general/family practice (22), community pharmacy (11) and nursing/care/residential homes (11) met the inclusion criteria, 24 of which were either pharmacy led (19) or multidisciplinary medication reviews (5). All but one study looked at prescribing or monitoring interventions only. A total of 12 studies included all patients, with 24 focusing on older adults (> 65 years) and 3 focusing on condition-specific groups. Most studies only included costs from a healthcare perspective (39). Outcomes ranged from prescribing errors (9), hospital utilisation (13) and health-related quality of life (15) to falls (6) and adverse drug events (6). In total, 21 studies carried out an incremental cost-effectiveness analysis (16 including the incremental cost per quality-adjusted life year gained), and 14 reported the intervention cost-effectiveness. Remaining studies were cost-consequence (18) and cost-benefit analyses (5). Study reporting quality varied considerably, with lack of transparency in the design of the decision-analytic model, varied reporting of costs, little consideration of indirect costs or the impact of loss of trust on future use of healthcare, limitations in handling of uncertainty or discounting and very little patient involvement around targeting patients or designing interventions. Of the ten studies using decision models, all scored poorly for model validation. The quality of studies has not improved over time.

Conclusions: While some interventions demonstrated cost-effectiveness, study quality was variable, with generally poorly validated models. Study heterogeneity precluded meaningful direct comparison between studies. Significant research gaps remain as studies focused mainly on prescribing and monitoring errors, there was little or no investigation of technology-based interventions and there was inadequate targeting of patients most vulnerable to harm.

This illustration uses the Scottish Cardiovascular Disease (CVD) Policy Model as a case study to provide a comprehensive, step-by-step guide to building a discrete event simulation (DES) model in R. It is specifically designed for practitioners who are familiar with constructing Markov models in R and wish to transition their theoretical knowledge of DES into practical implementation. The Scottish CVD Policy Model was originally developed as an Excel-based Markov model with a sophisticated structure: a primary Markov model for first events and nested sub-Markov models for subsequent events. Later replicated in R by Xin, Yiqiao et al., the model's source code was made publicly available on GitHub, underscoring its potential as a teaching tool. The intricate structure of this model presents several challenges in health economic modeling, making it an ideal candidate for demonstrating how DES techniques can address such complexities effectively. In this illustration, we deliberately avoid using R packages developed specifically for DES to enhance transparency. Instead, we rely on base R functions, and the tidyverse package for tidy data wrangling. This approach ensures that every step of the DES implementation is clear and reproducible. In addition to covering fundamental topics such as how to simulate a time to event according to an assumed distribution, and continuous discounting, the illustration also provides solutions to more advanced modeling challenges, such as handling piecewise-modeled cost and utility. By discussing both general principles and complex scenarios, this paper equips readers with the practical tools needed to transition from Markov to DES frameworks, enhancing the accuracy and flexibility of health economic evaluations.

Patient and public involvement (PPI) in health economics modelling is increasingly recommended, yet formal guidance for how to structure or evaluate it remains limited. The Values in Modelling (VIM) framework was developed to address this gap by helping teams identify and deliberate on value-laden decisions in modelling. Drawing on philosophical theory, the framework defines five steps to guide collaboration between modellers and transdisciplinary participators and to document their influence on decision making: (1) identify ethical issues and perspectives; (2) characterize modelling decisions; (3) select decision-making strategies; (4) deliberate 'open' decisions; and (5) report and evaluate. We applied the VIM framework in the Lifetime Exposures and Asthma Outcomes Projection (LEAP) model project, which models the cost effectiveness of high-efficiency particulate air (HEPA) filters for asthma prevention and management. In this application, the framework helped prioritize modelling decisions for PPI, supported transparent deliberation about uncertainty, and led to concrete methodological changes-including new sensitivity analyses and revised outcome measures. These results demonstrate how a theory-informed process can enhance PPI in modelling, improving transparency, justification, and adequacy-for-purpose in health economics research.

Objectives: Obstructive hypertrophic cardiomyopathy (oHCM) is a myocardial disease, characterised by left ventricular hypertrophy, hampering the ventricular blood outflow. Standard of care (SoC) includes medications such as beta-blockers (BB) and calcium channel blockers (CCB) and septal reduction therapies. Recently, mavacamten, a first-in-class myosin inhibitor, became available to oHCM patients. The objective was to develop a decision analytic model to evaluate the cost effectiveness of mavacamten compared with SoC in oHCM patients from a Dutch societal perspective.

Methods: A Markov model was developed in R based on the Decision Analysis in R for Technologies in Health framework with data from the EXPLORER-HCM trial. This trial compared mavacamten in combination with background therapy (BB and CCB) versus placebo, including oHCM patients (n = 251; mean age 59 years) in New York Heart Association (NYHA) functional classes II (72.9%) and III (27.1%). For the model, four health states were defined based on the NYHA classes, including NYHA I-NYHA III/IV and death. The model evaluated mavacamten with SoC versus SoC alone over a lifetime horizon with a cycle length of 4 weeks, following the most recent Dutch guidelines. Health state utilities and societal costs were derived from the AFFECT-HCM study, with utilities measured using the EQ-5D-5L. Outcomes included (incremental) societal costs, life years (LYs), quality-adjusted life years (QALYs) and the incremental cost-effectiveness ratio (ICER). The Dutch willingness-to-pay thresholds of €50,000 and €80,000 per QALY were applied. Uncertainty of parameters was assessed in deterministic and probabilistic sensitivity and scenario analyses.

Results: Results indicate mavacamten being more effective (Δ4.75 LYs; Δ3.36 QALYs) and more costly (Δ€235,951) compared with SoC with an ICER of €70,223 per QALY gained. Varying parameters by 20% showed that the utility value of patients in NYHA class I (ICER: €57,199; €111,506 per QALY) and drug costs (ICER: €53,985; €86,555 per QALY) were most sensitive. Mavacamten accumulated most LYs, QALYs and costs by patients improving to NYHA class I, compared with SoC, and patients remained longer in that state throughout the model. For men, incremental QALYs (Δ 3.36) and costs (Δ €239,743) were slightly higher compared with women. The probability of the intervention being cost effective at the willingness-to-pay thresholds €50,000 and €80,000 per QALY was 1.3% and 87.4%, respectively. Conclusion The results show that mavacamten increased LYs and QALYs compared with SoC, however, at substantial additional costs. The probability of mavacamten being cost effective depends on the selected willingness-to-pay threshold.

Background: Post-traumatic stress disorder (PTSD) is a debilitating condition that arises after exposure to a traumatic event and leads to significant impairment in daily functioning if left untreated. Economic evaluations are essential for understanding the comparative value of PTSD treatments and ultimately supporting their implementation. Several model-based economic evaluations exist in this area; however, these can differ in their methodological approaches and parameter inputs, which can influence conclusions drawn.

Objective: This systematic review aimed to explore model structures and parameter inputs employed in model-based economic evaluations of PTSD treatment.

Methods: A literature search was carried out in the following databases: MEDLINE, PsycINFO, SCOPUS, Econlit, CINAHL, Web of Science Core Collection, and Cochrane Collaboration Library between 1 January 2000 and 1 May 2025. Studies were eligible if they presented a full economic evaluation of a treatment for PTSD using a decision-analytic model. Data relating to the model structure and parameter inputs were extracted and quality assessment was conducted.

Results: This review identified 14 model-based studies, of which two used decision trees, six used a Markov model, four used a combined decision tree and Markov model, and two used an agent-based model. There was significant variation across model parameters, including in disease conceptualisation and progression, data sources utilised, assumptions reported, and costs included. The quality assessment revealed the following key areas of concern: insufficient consideration of methodological uncertainty and heterogeneity, internal consistency, and incorporation of relevant disease and intervention characteristics.

Conclusions: This paper highlights important variations in current model-based economic evaluations of PTSD treatment. Future work should seek to generate evidence to support consistency in future economic evaluations of PTSD treatment options.