PharmacoEconomics最新文献

Objectives: The clinical pathway for patients with moderate-to-severe Crohn's disease (CD) typically includes sequential pharmacologic treatment as well as surgery, but positioning of different therapies within these sequences remains challenging. Cost-utility analysis rarely captures these sequences and does not incorporate registry data on long-term effectiveness. In this study, we aim to overcome these limitations.

Methods: We developed an individual state transition model with four health states (active disease, remission, and remission due to surgery and death), five sequential treatment lines, and surgery. Efficacy data from network meta-analyses (NMA) for biologic naive and biologic exposed patients were combined with Dutch registry data to forecast long-term benefit, calculate costs, and estimate utilities. Analyses had a Dutch societal perspective with a lifetime time horizon. Costs were reported in 2023 euros and discounted with 3%. Effects were reported in quality-adjusted life years (QALYs) and discounted with 1.5%. The cost-per-QALY threshold was €20,000. Deterministic analyses for the base case, three scenarios (including recently published trials or price declines for ustekinumab), and one-way sensitivity analysis were run with 30,000 patients. The probabilistic sensitivity analysis was conducted by sampling 1000 patients in 1000 model runs.

Results: When opting for step-up sequences, the most cost-effective sequence (out of 156 sequences) starts with either azathiopurine/6-mp or methotrexate and is followed by combination therapy (infliximab + azathioprine) when patients discontinue their first line owing to disease activity or discontinuation. The most cost-effective top-down sequence (out of 72) starts with combination therapy (infliximab + azathioprine). After two lines of treatment, differences in cost-effectiveness between biologics become smaller. To be equally cost-effective as anti-tumor necrosis factor (TNF) combination therapy, a price decline for ustekinumab (biosimilars) of 81% is required or 50% to become the preferred option after combination therapy. Validation against external data suggested good predictive capabilities of the model.

Conclusions: Integrating NMA and registry data improves the quality of cost-effectiveness models for treatment sequences in CD. This open-source model can be easily updated for future therapies and holds the potential to become a standard model for use in clinical guideline development and the economic evaluation of new drugs.

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.

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.

Cardiovascular disease (CVD) is a major contributor to the health and economic burden of disease globally. In this paper we discuss the literature on the health economics of the prevention and early intervention in CVD. We reveal the large economic impact of CVD and provide the economic argument supporting the calls for early detection and diagnosis of CVD outlined in the Global Heart Hub's patient-led Manifesto for Change. Many challenges in conducting cost-effectiveness analyses of interventions for CVD prevention are identified, as well as the emerging statistical and economic methods to help overcome these issues. Lastly, we acknowledge the profound disparities in cardiovascular health faced by minority or underserved populations, and the important role that prevention and early intervention can play in improving health equity.

Objective: We aimed to compare EQ-5D-Y-5L health state preferences among children, adolescents, and adults in Canada using a discrete choice experiment (DCE), and to explore the feasibility of a rescaling latent DCE using anchoring tasks collected from adolescents.

Methods: An online survey was conducted to elicit preferences for EQ-5D-Y-5L health states from children (aged 12-15 years), adolescents (aged 16-17 years), and adults (aged ≥ 18 years). All respondents completed 12 latent DCE tasks. Adults and adolescents were randomly assigned to three additional anchoring tasks using a DCE with duration or with dead. The tasks were framed from the perspective of a 10-year-old child for adults and their own perspective for children and adolescents. Respondents provided feedback on the difficulty of latent DCE tasks. Mixed logit models were used to analyze latent DCE data. Anchored DCE models using duration/dead tasks were estimated and compared between adults and adolescents.

Results: Overall, 546 children, 508 adolescents, and 908 adults were included in the analyses. A higher proportion of children indicated it easy to complete DCE tasks compared with adolescents and adults. Monotonicity of coefficients were observed in latent DCE models among adults but not among children and adolescents. Anchored DCE modeling performed better in adults than in adolescents regarding monotonicity and statistical significance of coefficients, and the DCE with duration performed slightly better than the DCE with dead.

Conclusions: There were differences in health state preferences elicited using DCEs between children/adolescents and adults. Anchoring tasks appeared feasible for adolescents, with a DCE with duration performing slightly better than a DCE with dead.

Background and objective: Health technology assessment (HTA) of haemato-oncology therapies typically requires extrapolation of long-term survival beyond a trial's follow-up. Health technology assessment agencies must balance caution around uncertainty in early follow-up trial data whilst aiming to provide timely access. This study qualitatively and quantitatively assessed how eight HTA agencies considered maturing data and external evidence.

Methods: The eight HTA appraisals were based on ZUMA-7, a phase III trial for axicabtagene ciloleucel (axi-cel) for second-line diffuse large B-cell lymphoma. ZUMA-7 survival data were submitted with either a 25-month ('Interim') or 47-month ('Primary') follow-up. To inform axi-cel Interim survival extrapolations, external evidence was available from a prior mature single-arm trial for third-line or later diffuse large B-cell lymphoma (ZUMA-1). A qualitative assessment of eight different submissions to HTA agencies was undertaken to determine key discussion points. The value and cost of waiting for evidence to mature between Interim and Primary analyses were quantified using value of information methods to evaluate the impact of waiting for further evidence collection on population health.

Results: Agencies used varied approaches to account for uncertainty in survival extrapolations in both Interim and Primary analyses. No agency considered external evidence fully during Interim submissions; one used it partially to inform clinical plausibility; four did not consider it. Health technology assessment agencies that did not consider the relevance of ZUMA-1 were more inclined to wait for more mature evidence to mitigate uncertainty. When ZUMA-1 aided in determining a plausible range for Interim extrapolations, the less valuable more mature evidence became, with the cost of waiting for Primary analysis results exceeding the value conferred.

Conclusions: There was limited consideration of external evidence during the included HTA submissions. In the future, it is recommended that external evidence should be considered to a greater degree by both manufacturers and HTA agencies when extrapolating survival to ensure appropriate and timely HTA decisions that minimise the undue burden on healthcare systems.

Background: Bayesian cost-effectiveness analysis (CEA) requires the specification of prior distributions for all parameters to be empirically estimated via Bayes' rule. When costs are modelled via Log-Normal distributions, Uniform prior distributions are commonly applied on the logarithm-scale standard deviations for costs due to the ease of implementation. However, the consequences of placing wide Uniform priors on standard deviations of log costs for the interpretation of original-scale CEA results remain unclear. The purpose of our study is to explore the impact of using Uniform priors for the standard deviations of cost data on CEA conclusions when costs are assumed to be log-normally distributed.

Methods: The analysis has been performed using individual-level cost-utility data from a randomised controlled trial. Costs are initially jointly modelled with quality-adjusted life years (QALYs) using Log-Normal and Beta distributions, respectively. Uniform prior distributions with different upper bounds are applied to log-scale standard deviations in the cost Log-Normal model. We compare the performance of Uniform priors under the Log-Normal distribution with other distributional assumptions for costs. A simulation study has then been conducted to explore the impact of these models and prior choices on cost estimates in CEAs.

Results: Results show that the choice of Uniform priors on standard deviations of log costs in a Log-Normal model can substantially induce large fluctuations in cost estimates, and thus potentially affect the final estimates of the intervention being cost-effective compared with other distributional assumptions. This is potentially driven by the occurrence of zero values in cost data.

Conclusion: Bayesian CEAs may be sensitive to the choice of upper bounds of the Uniform priors for the standard deviations of log costs in Log-Normal models, particularly when data contain zero values. Our results suggest that caution should be taken when Uniform distributions with large upper bounds are used.