PharmacoEconomics最新文献

Background and objective: Economic evaluation of antimicrobial resistance (AMR) interventions is complicated by the multisectoral, inter-temporal and international aspects of the problem, further hindered by a lack of available data and theoretical understanding of the emergence and transmission of AMR. Despite the substantial global focus on the problem, there is a lack of comprehensive economic evaluation literature on AMR policies. The goal of this work is to review the available literature on the economic evaluation of AMR interventions focusing on methods used to quantify the effects on AMR and the associated health consequences and costs.

Methods: The studies included in the review were identified by a previous study by Painter et al. that included all full economic evaluations of AMR policies in the peer-reviewed and grey literature published between 2000 and 2020. The current review extracted additional information to (1) summarise the types and the key features of the AMR intervention economic evaluation literature available; (2) systemise the types of intervention effects on AMR quantified and describe these across the dimensions of AMR burden: time, space, wider pathogen pool and different sectors (One Health framework); and (3) categorise the methods used to derive these outcomes and how were these linked to health consequences and costs.

Results: Thirty-one studies were included within this review, of which 18 evaluated interventions that aimed to reduce infection rates and 11 evaluated interventions that aimed to optimise antimicrobial use. Almost all were conducted with a high-income and/or upper-middle income country perspective and focused on human health. Thirteen of 31 studies were cost-utility analyses. Fifteen of 31 and 7/31 studies estimated the AMR effects through decision tree and/or Markov models and transmission models, respectively. Transmission models and linkage of AMR outcomes to quality-adjusted life-years and costs were more common in evaluations of interventions aimed at reducing infection rates. Most of the included studies restricted the scope of evaluation to a short time horizon and a narrow geographical scope and did not consider the wider impact on other pathogens and other settings, potentially resulting in an incomplete capture of the effects of interventions.

Conclusions: This review found limited available literature that mainly focused on high-income countries and infection prevention/reduction strategies. Most evaluations used a narrow study scope, which might have prevented the full capture of the costs and outcomes associated with interventions. Finally, despite the known complexities associated with quantifying AMR effects, and the corresponding methodological challenges, the implications of these choices were rarely discussed explicitly.

Objective: The utilities elicited with the composite time trade-off (cTTO) method for health states worse-than-dead (WTD) often correlate poorly with other severity measures, indicating a poor sensitivity of cTTO. We aimed to explore modifications to cTTO to better understand this phenomenon and identify potential improvements.

Methods: A total of 480 respondents completed an online TTO interview, each valuing 12 EQ-5D-5L health states. The participants were randomized into four arms, A-D. Arm A followed the standard cTTO, serving as a reference. In arm B, we removed the sorting question comparing immediate death versus 10 years in a valued state. Arm C allowed for utility values $<-1$ by reducing the time in the valued state in the lead-time TTO (LT-TTO) part of cTTO. In arm D, we randomly selected the starting negative utility in LT-TTO. Utility value distributions, correlations between utilities and level sum score (LSS), and inconsistencies between Pareto-ordered states were analyzed.

Results: Arm A replicated the lack of significant correlation between LSS and the negative utility observed in previous work. Of the experimental arms, only arm B exhibited a significant negative correlation. Compared with arm A, arm B produced a higher proportion of WTD states ( $46.5\%$ versus  $26.3\%$ ), less negative utility for WTD states on average ( $-0.571$ versus  $-0.752$ ), and a lower mean censored utility for 55555 ( $-0.486$ versus  $-0.406$ ).

Conclusions: The observed lack of correlation between LSS and utility for WTD states appears linked to the use of comparison with immediate death in the sorting question. LT-TTO is capable of eliciting utility values in a way that is sensitive to severity. Modifying the initial questions in cTTO to identify whether health states are BTD or WTD should be considered.

Aim: This study aims to estimate the value of a statistical life (VSL) in the context of atherosclerotic cardiovascular disease (ASCVD) in Spain using a contingent valuation/standard gamble (CV/SG) chained approach.

Methods: The study employed a two-stage preference elicitation method that combined contingent valuation and a modified standard gamble technique. Specifically, willingness-to-pay and willingness-to-accept values were obtained for two health states depicting hypothetical outcomes following cardiovascular events. Subsequently, relative utility losses for the health states were derived using a modified standard gamble framing two risky choices. Chaining these elicited values allowed for VSL calculation without requiring direct valuation of small mortality risk reductions. The study was conducted through in-person interviews with a representative sample of 412 Spanish adults selected by stratified quotas.

Results: The estimated VSL range is from 1.59 to 2.06 million euros. Minor differences emerge between VSL figures on the basis of each of the two health states. These VSL estimates for ASCVD are congruent with the recent update of the official VSL estimated for Spain in the context of road traffic accidents, though the upper limit of the range is slightly higher (almost 9%).

Conclusions: VSL estimates align with existing ranges in other European countries, particularly in the context of road safety, where a significant portion of existing studies is concentrated. Comparisons with other contexts, involving cardiovascular diseases, also lend support to the estimates presented here.

Objective: Collective changes in healthcare practices are required to ensure real environmental gains. As patient-centred care is increasingly considered to enhance the ability of health systems to meet the expectations of the population, it is crucial for policymakers and health professionals to account for the preferences of the wider public regarding environmentally friendly healthcare. This article synthesises and appraises evidence from empirical studies to understand how people value environmental concerns when making decisions within medical-related or pharmaceutical sectors.

Methods: We conducted electronic searches of the PubMed, Scopus, and Embase literature databases. Studies were eligible if they conducted a quantitative experiment to understand participants' preferences regarding sustainability and green initiatives in the medical sector or for pharmaceuticals.

Results: Of the 1138 documents identified, 32 studies were deemed eligible. More than 60% were published since 2020. Different methods were used to elicit the revealed and/or stated preferences of participants. In most studies, respondents valued the environment positively and were willing to change their behaviour or practices to support sustainability. However, concerns such as disease severity or clinical effectiveness of medicines or medical interventions were often prioritised over environmental considerations. The wide heterogeneity in study participants emphasises the need to involve all stakeholders to achieve the transition to a greener and sustainable healthcare system.

Conclusion: The identified studies used various methods but were consistent in finding broad support for environmental considerations within the healthcare sector.

Objectives: This study aimed to assess the cost effectiveness of nirsevimab, a recently authorized monoclonal antibody (mAb) for the prevention of lower respiratory tract disease (LRTD) caused by respiratory syncytial virus (RSV), in comparison with the standard practice involving palivizumab for high-risk infants during their first RSV season in the Netherlands.

Methods: A static cost-effectiveness model was populated for the Netherlands to evaluate different immunization strategies for nirsevimab over a single RSV season from a societal perspective. The model considered the most recently published RSV incidence data (average incidence from 2006 to2018), costs (adjusted to the 2023 price year), and associated health effects. Extensive scenario analyses were conducted to explore various strategies, and sensitivity analysis was performed to assess the model's robustness.

Results: In the base-case scenario, all-infant protection-a strategy of in-season with catch-up immunization for all infants-nirsevimab has the potential to prevent numerous RSV-related cases, including 2333 hospitalizations and 150 intensive-care admissions, in the overall population compared with the standard of care. Nirsevimab appears to be cost effective under this strategy with an economically justifiable acquisition price for nirsevimab of €220 at a willingness-to-pay threshold of €50,000 per quality-adjusted life-year. Sensitivity analyses indicate a 52% probability that nirsevimab is cost effective at this threshold. Comparison of different vaccination strategies revealed that the all-infant protection approach was the one that prevented the higher number of cases.

Conclusions: This study indicates that universal infant immunization with nirsevimab has the potential to be cost effective and significantly reduces the burden of RSV among Dutch infants. These findings underscore the importance of implementing effective protective measures against RSV-LRTD, reducing the pressure on the healthcare system during the RSV season.

Background and objective: In Germany, all new drugs undergo an early benefit assessment (EBA) by the decision-making body (G-BA). Due to limited access to clinical data in pediatric healthcare since 2017, evidence transfer has allowed for data from adult studies to be used in the EBA of pediatric drugs. This study examines the acceptance of evidence transfer, aiming to understand its correlation with granted added benefit.

Methods: By searching the G-BA database, relevant EBAs were identified. In addition to descriptive statistics, agreement statistics regarding binary and ordinal extent of added benefit and binary logistic regression with and without intercept were performed to investigate acceptance of evidence transfer, juxtaposing it with manufacturers' claims, and to evaluate the impact of identified factors on evidence transfer.

Results: In 14 of 36 identified EBAs, the evidence transfer was accepted by the G-BA. They referred to four therapeutic areas, received a non-quantifiable added benefit and were subject to a pediatric investigation program. Non-quantifiable added benefit implies an added value in itself which can range from minor to major added benefit and is considering the genuine uncertainty mainly induced in theese EBAs due to evidence transfer, which is not allowing a quantification of an added benefit. The binary agreement between manufacturers' claims and G-BA's appraisals was less than by chance [kappa - 0.054 (- 0.158 to 0.050)] whereas the ordinal agreement became fair [kappa 0.333 (0.261-0.406)]. Congruence of the mechanism of action, alignment of disease pattern, transferability of efficacy and safety, and same comparator were fundamental for evidence transfer. Additionally, supportive evidence, therapeutic breakthroughs, and small-scale approval enhanced the acceptance of evidence transfer. The regression models yielded similar results showing different model fit and explained variance.

Conclusions: Evidence transfer hinges upon fulfilling various minimum criteria and additional supportive evidence. Availability of study data from adult or older patients and the pediatric group under evaluation is crucial.

Objective: This study aims to evaluate the financial implications of implementing various payment models, including outcome-based agreements (OBAs), volume-based rebates, and guaranteed rebates, for the newly approved gene therapies, exagamglogene autotemcel (exa-cel) and lovotibeglogene autotemcel (lovo-cel), in the treatment of sickle-cell disease (SCD) from the perspective of Colorado Medicaid. The analysis specifically examines the cost of standard of care (SoC) for severe SCD, the impact of different eligibility criteria based on vaso-occlusive events (VOEs), and the potential financial impacts associated with rebate structures.

Methods: Data from the Colorado Department of Health Care Policy & Financing (HCPF) database was used to estimate the annual costs for Medicaid-enrolled patients with severe SCD from 2018 to 2023. Patients were selected based on various eligibility criteria, including the number of VOEs, acute chest syndrome events, and stroke diagnoses. Three-state Markov models (SCD, stable, and dead) were constructed to compare the costs of SoC and gene therapies. The durability of gene therapy effectiveness and the financial impact of OBAs, volume-based rebates, and guaranteed rebates were evaluated over a 6-year contract period, with scenarios reflecting different VOE criteria and treatment durability.

Results: The average annual SoC cost for severe SCD patients (N = 138) was US$45,941 (SD US$59,653), with higher costs associated with more frequent VOEs. Gene therapies exa-cel and lovo-cel, with one-off list prices of US$2.2 million and US$3.1 million, respectively, exhibited high upfront costs, resulting in a negative cumulative balance averaging - US$2.11 million for exa-cel and - US$3.00 million for lovo-cel per patient over 6 years compared with SoC. Outcome-based rebates could potentially save Medicaid approximately US$260K (uncertainty interval 88K-772K) per patient on average for exa-cel and US$367K (uncertainty interval 122K-1111K) for lovo-cel after they pay the full up-front cost. Volume-based and guaranteed rebates also offered potential savings but varied in impact based on contract duration and effectiveness of gene therapy.

Conclusions: The study highlights critical considerations for Medicaid in negotiating OBAs for SCD gene therapies. Achieving budget neutrality over 6 years is unlikely due to low SoC costs. However, payment models can enhance value-based spending by linking high therapy costs and potential rebates to the health gains these treatments may offer. OBAs offer offsets contingent on therapy effectiveness durability and contract terms (such as length and price), while varying eligibility criteria impact budgets and outcomes. Medicaid real-world data is crucial for navigating complexities in defining eligible populations and structuring OBAs.