PharmacoEconomics最新文献

Background: The National Institute for Health and Care Excellence (NICE) may approve health technologies on condition of more evidence generated only in research (OiR) or only with research (OwR). NICE specifies the information needed to comply with its request, although it may not necessarily guarantee good quality and timely evidence for re-appraisal, before reaching a final decision.

Aim: This study aimed to critically appraise the methods, quality and risk of bias of evidence generated in response to NICE OiR and OwR technology appraisal (TA) and highly specialised technologies (HSTs) recommendations.

Methods: NICE TAs (between March 2000 and September 2020) and HST evaluations (to October 2023) of medicines were reviewed. Conditional recommendations were analysed to identify the evidence requested by NICE for re-appraisal. The new evidence was analysed for compliance with NICE's request and assessed using the Cochrane Collaboration's tools for risk of bias in randomised trials and the ROBINS-I tool for non-randomised evidence.

Results: NICE made 54 conditional recommendations from TAs (13 OiR and 41 OwR) and five conditional recommendations for HSTs (all OwR). Of these, 16 TAs presented additional evidence for re-appraisal (9 OiR [69%] and 7 OwR [17%]) and three HSTs (3 OwR [60%]). Two of the nine re-appraised TAs with OiR recommendation and four of the seven OwR complied fully with NICE's request for further evidence, while all three from the HSTs complied. The majority of re-appraised TAs and HSTs included evidence that was deemed to be at serious, high, moderate or unclear risk of bias. Among the 26 randomised controlled trials from TAs assessed, eight were categorised as having low risk of bias in all domains and ten had at least one domain as a high risk of bias. Reporting was unclear for the remainder. Twenty-two non-randomised studies, primarily single-arm studies, were susceptible to biases mostly due to the selection of participants and to confounding. Two HSTs provided evidence from randomised controlled trials which were classified as unclear or high risk of bias. All non-randomised evidence from HSTs were categorised as moderate or serious risk of bias.

Conclusions: There is widespread non-compliance with agreed data requests and important variation in the quality of evidence submitted in response to NICE conditional approval recommendations. Quality standards ought to be stipulated in respect to evidence contributing to re-appraisals following NICE conditional approval recommendations.

Objective: Chimeric antigen-receptor T-cell therapy (CAR-T) is characterised by early phase data at the time of registration, high upfront cost and a complex manufacturing and administration process compared with standard therapies. Our objective was to compare the performance of different models to assess the cost effectiveness of CAR-T using a state-transition model (STM), partitioned survival model (PSM) and discrete event simulation (DES).

Methods: Individual data for tisagenlecleucel for the treatment of young patients with acute lymphoblastic leukaemia (ALL) were used to populate the models. Costs and benefits were measured over a lifetime to generate a cost per quality-adjusted life-year (QALY). Model performance was compared quantitatively on the outcomes generated and a checklist developed summarising the components captured by each model type relevant to assessing cost effectiveness of CAR-T.

Results: Models generated similar results with base-case analyses ranging from an incremental cost per QALY of $96,074-$99,625. DES was the only model to specifically capture CAR-T wait time, demonstrating a substantial loss of benefit of CAR-T with increased wait time.

Conclusion: Although model type did not meaningfully impact base-case results, the ability to incorporate an outcome-based payment arrangement (OBA) and wait time are important elements to consider when selecting a model for CAR-T. DES provided greater flexibility compared with STM and PSM approaches to deal with the complex manufacturing and administration process that can lead to extended wait times and substantially reduce the benefit of CAR-T. This is an important consideration when selecting a model type for CAR-T, so major drivers of uncertainty are considered in funding decisions.

Background and objective: Accurately extrapolating survival beyond trial follow-up is essential in a health technology assessment where model choice often substantially impacts estimates of clinical and cost effectiveness. Evidence suggests standard parametric models often provide poor fits to long-term data from immuno-oncology trials. Palmer et al. developed an algorithm to aid the selection of more flexible survival models for these interventions. We assess the usability of the algorithm, identify areas for improvement and evaluate whether it effectively identifies models capable of accurate extrapolation.

Methods: We applied the Palmer algorithm to the CheckMate-649 trial, which investigated nivolumab plus chemotherapy versus chemotherapy alone in patients with gastroesophageal adenocarcinoma. We evaluated the algorithm's performance by comparing survival estimates from identified models using the 12-month data cut to survival observed in the 48-month data cut.

Results: The Palmer algorithm offers a systematic procedure for model selection, encouraging detailed analyses and ensuring that crucial stages in the selection process are not overlooked. In our study, a range of models were identified as potentially appropriate for extrapolating survival, but only flexible parametric non-mixture cure models provided extrapolations that were plausible and accurately predicted subsequently observed survival. The algorithm could be improved with minor additions around the specification of hazard plots and setting out plausibility criteria.

Conclusions: The Palmer algorithm provides a systematic framework for identifying suitable survival models, and for defining plausibility criteria for extrapolation validity. Using the algorithm ensures that model selection is based on explicit justification and evidence, which could reduce discordance in health technology appraisals.

Survival extrapolation often plays an important role in health technology assessment (HTA), and there are a range of different approaches available. Approaches that can leverage external evidence (i.e. data or information collected outside the main data source of interest) may be helpful, given the extent of uncertainty often present when determining a suitable survival extrapolation. One of these methods is the multi-parameter evidence synthesis (MPES) approach, first proposed for use in HTA by Guyot et al., and more recently by Jackson. While MPES has potential benefits over conventional extrapolation approaches (such as simple or flexible parametric models), it is more computationally complex and requires use of specialist software. This tutorial presents an introduction to MPES for HTA, alongside a user-friendly, publicly available operationalisation of Guyot's original MPES that can be executed using the statistical software package R. Through two case studies, both Guyot's and Jackson's MPES approaches are explored, along with sensitivity analyses relevant to HTA. Finally, the discussion section of the tutorial details important considerations for analysts considering use of an MPES approach, along with potential further developments. MPES has not been used often in HTA, and so there are limited examples of how it has been used and perceived. However, this tutorial may aid future research efforts exploring the use of MPES further.

Care as usual has failed to stem the tide of mental health challenges in children and young people. Transformed models of care and prevention are required, including targeting the social determinants of mental health. Robust economic evidence is crucial to guide investment towards prioritised interventions that are effective and cost-effective to optimise health outcomes and ensure value for money. Mental healthcare and prevention exhibit the characteristics of complex dynamic systems, yet dynamic simulation modelling has to date only rarely been used to conduct economic evaluation in this area. This article proposes an integrated decision-making and planning framework for mental health that includes system dynamics modelling, cost-effectiveness analysis, and participatory model-building methods, in a circular process that is constantly reviewed and updated in a 'living model' ecosystem. We describe a case study of this approach for mental health system policy and planning that synergises the unique attributes of a system dynamics approach within the context of economic evaluation. This kind of approach can help decision makers make the most of precious, limited resources in healthcare. The application of modelling to organise and enable better responses to the youth mental health crisis offers positive benefits for individuals and their families, as well as for taxpayers.

Background and objective: China has the highest number of hepatitis C virus (HCV) infections in the world. However, it is unclear what levels of screening and treatment are needed to achieve the WHO 2030 hepatitis C elimination targets. We aimed to evaluate the impact of scaling up interventions on the hepatitis C epidemic and determine how and at what cost these elimination targets could be achieved for the whole population in China.

Methods: We developed a compartmental model incorporating HCV transmission, disease progression, and care cascade for the whole population in China, calibrated with data on demographics, injecting drug use, HCV prevalence, and treatments. Five different scenarios were evaluated for effects and costs for 2022-2030. All costs were converted to 2021 US dollar (USD) and discounted at an annual rate of 5%. One-way sensitivity analyses were conducted to assess the robustness of the model.

Results: Under the status quo scenario, the incidence of hepatitis C is projected to increase from 60.39 (57.60-63.45) per 100,000 person-years in 2022 to 68.72 (65.3-73.97) per 100,000 person-years in 2030, and 2.52 million (1.94-3.07 million) infected patients are projected to die between 2022 and 2030, of which 0.76 (0.61-1.08) million will die due to hepatitis C. By increasing primary screening to 10%, conducting regular rescreening (annually for PWID and every 5 years for the general population) and treating 90% of patients diagnosed, the incidence would be reduced by 88.15% (86.61-89.45%) and hepatitis C-related mortality by 60.5% (52.62-65.54%) by 2030, compared with 2015 levels. This strategy would cost USD 52.78 (USD 43.93-58.53) billion.

Conclusions: Without changes in HCV prevention and control policy, the disease burden of HCV in China will increase dramatically. To achieve the hepatitis C elimination targets, China needs to sufficiently scale up screening and treatment.

Background: Psoriatic arthritis (PsA) is an inflammatory disease characterised by a variety of clinical manifestations. Considering the economic burden posed by PsA and the increasing number of treatment options, economic evaluations are required to better allocate available resources. This work aims to update a previous published literature review on PsA cost-of-illness and cost-effectiveness analysis.

Methods: A search was performed of English-language literature between January 2017 and March 20, 2024 in Medline/PubMed, Embase and Cochrane library using the terms 'psoriatic arthritis', 'cost of illness' and 'cost effectiveness'. Data on decision model, time horizon, population, treatment options, perspective, type of costs, relevant results and authors' conclusion were extracted from the reviewed articles. Finally, the quality of the included studies was evaluated.

Results: Twenty-seven studies met the inclusion criteria: 16 cost-of-illness and 11 cost-effectiveness/cost-utility analyses. PsA is characterised by high direct and indirect costs. Drug costs as well as hospitalisation and absenteeism were the major drivers of the observed costs. The cost-effectiveness analyses reported the dominance or the cost effectiveness of biologic therapies compared with non-biologic PsA treatment. Biological options like bimekizumab and ixekizumab have demonstrated a better cost-effectiveness profile in PsA patients compared with other treatments (i.e., other biological treatments).

Conclusions: There was an increased number of economic evaluations compared with the previous review. PsA is still associated with significant economic burden worldwide. The main cost was represented by therapies, specifically biological therapies. Amongst the biological therapies, bimekizumab and ixekizumab appear to provide the most economic benefit. Finally, new economic studies are needed to enrich knowledge on the economic burden of subgroups of PsA patients as well as early treatment of PsA with new therapies.

Objectives: The aim of the study was to develop and compare utility value sets for the EORTC QLU-C10D, a cancer-specific utility instrument based on the EORTC QLQ-C30, using the preferences of the general public and cancer patients in Singapore, and to assess their measurement properties.

Methods: A total of 600 individuals from the general public were recruited using a multi-stage random sampling, along with 626 cancer patients with clinically confirmed diagnoses from outpatient clinics of the largest tertiary cancer hospital. Each participant valued 16 pairs of EORTC QLU-C10D health states using a discrete choice experiment (DCE). Conditional logit models were used to analyze the DCE responses of the general public and cancer patients separately. Utility values were assessed for known-group validity and responsiveness in the cancer patients by comparing mean values across subgroups of patients and calculating standardized response means using longitudinal EORTC QLQ-C30 data, respectively.

Results: Physical functioning and pain had the most impact on utility for both cancer patients and general public groups. Worst health state utility values were -0.821 and -0.463 for the general public and cancer patients, respectively. Cancer patients' values were lower for mild-to-moderate health states but higher for moderately-to-highly impaired states compared with the general public's values. Both value sets discriminated between patients with differing characteristics and responded equally well to improved health status, but the cancer patients' value set was slightly more responsive to deteriorated health.

Conclusions: EORTC QLU-C10D value sets based on the preferences of the Singaporean general public and cancer patients exhibited differences in values but similar psychometric properties.

Background: Invasive meningococcal disease (IMD) is primarily associated with five Neisseria meningitidis serogroups: A, B, C, W, or Y. In the United States (US), available vaccines protect against serogroups B (MenB), A, C, W, and Y (MenACWY), and A, B, C, W, and Y (MenABCWY). The Advisory Committee on Immunization Practices is re-evaluating the adolescent meningococcal vaccination schedule with varying recommendation formats. This analysis aimed to predict which schedule could avert the most IMD cases and have the most positive public health impact (PHI).

Methods: An epidemiological model compared the 15-year PHI of vaccination schedules using MenB, MenACWY, and/or MenABCWY vaccines versus current US standard of care (SoC). Varying coverage rates reflected routine, shared clinical decision making, and risk-based recommendations. Sensitivity analyses assessed robustness of the results to different inputs/assumptions.

Results: The most positive PHI compared with SoC was observed with one dose of MenACWY at 11 years of age and two doses of MenABCWY (6 months apart) at 16 years of age, assuming routine recommendation and coverage reflecting real-world uptake of MenACWY. This strategy resulted in 123 IMD cases averted (MenB: 59, MenACWY: 64), 17 deaths prevented, 574 life-years saved, and 757 quality-adjusted life-years gained versus SoC. Eliminating MenACWY vaccination at 11 years was found to result in an additional IMD burden.

Conclusion: A routinely recommended two-dose pentavalent vaccine, with doses administered 6 months apart at 16 years of age, alongside the routinely recommended MenACWY vaccine at 11 years of age, would improve the PHI and benefits of IMD vaccination to society.

Background and objectives: Disorders of gut-brain interaction are highly prevalent and burdensome conditions for both patients and healthcare systems. Given the limited effectiveness of pharmacotherapy in treating disorders of gut-brain interaction, non-pharmacological interventions are increasingly used; however, the value for money of non-pharmacological treatments is uncertain. This is the first review to assess the economic evaluation evidence of non-pharmacological interventions for disorders of gut-brain interaction.

Methods: A scoping review was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. Reporting adhered to ISPOR's good practices for systematic reviews with cost and cost-effectiveness outcomes. Comprehensive searches were performed on 24 October, 2023, and an updated search was run on 18 May, 2024 in PubMed/MEDLINE, Embase, Web of Science, Scopus and the International HTA database, with two reviewers screening studies in parallel. The novel Criteria for Health Economic Quality Evaluation (CHEQUE) framework was used to assess methodological and reporting quality. Reporting quality was further assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022.

Results: Fifteen studies were included. Most studies examined treatments for irritable bowel syndrome. Cognitive behavioural therapy, dietary interventions and sacral neuromodulation were cost effective. Acupuncture and physiotherapy were not. CHEQUE assessment showed 12 studies met at least 70% of the methodological criteria, and 14 studies achieved 70% or more for reporting quality.

Conclusions: This review highlights gaps in the current evidence base, particularly in the robustness and generalisability of results due to methodological inconsistencies. Future research should incorporate longer follow-ups, comprehensive cost assessments, subgroup analyses, equity considerations and clearer justifications for modelling assumptions.