A Budget Impact and Cost Per Additional Responder Analysis for Baricitinib for the Treatment of Moderate-to-Severe Rheumatoid Arthritis in Patients with an Inadequate Response to Tumor Necrosis Factor Inhibitors in the USA Due to a single error in the annual cost of sarilumab the following needs to be corrected in the article.

Development and Validation of the TRansparent Uncertainty ASsessmenT (TRUST) Tool for Assessing Uncertainties in Health Economic Decision Models Abstract Background An increasing number of technologies are obtaining marketing authorisation based on sparse evidence, which causes growing uncertainty and risk within health technology reimbursement decision making. To ensure that uncertainty is considered and addressed within health technology assessment (HTA) recommendations, uncertainties need to be identified, included in health economic models, and reported. Objective Our objective was to develop the TRansparent Uncertainty ASsessmenT (TRUST) tool for systematically identifying, assessing, and reporting uncertainties in decision models, with the aim of making uncertainties and their impact on cost effectiveness more explicit and transparent. Methods TRUST was developed by drawing on the uncertainty and risk assessment literature. To develop and validate this tool, we conducted HTA stakeholder discussion meetings and interviews and applied it in six real-world HTA case studies in the Netherlands and the UK. Results The TRUST tool enables the identification and categorisation of uncertainty according to its source (transparency issues, methodology issues, and issues with evidence: imprecision, bias and indirectness, and unavailability) in each model aspect. The source of uncertainty determines the appropriate analysis. The impact of uncertainties on cost effectiveness is also assessed. Stakeholders found using the tool to be feasible and of value for transparent uncertainty assessment. TRUST can be used during model development and/or model review. Conclusion The TRUST tool enables systematic identification, assessment, and reporting of uncertainties in health economic models and may contribute to more informed and transparent decision making in the face of uncertainty.

Fluocinolone Acetonide Intravitreal Implant for Treating Recurrent Non-infectious Uveitis: An Evidence Review Group Perspective of a NICE Single Technology Appraisal Abstract The National Institute for Health and Care Excellence (NICE) invited Alimera Sciences, the company manufacturing fluocinolone acetonide intravitreal implant (FAc) 0.19 mg (tradename ILUVIEN®), to submit evidence on the clinical and cost-effectiveness of FAc for treating recurrent non-infectious uveitis. Kleijnen Systematic Reviews Ltd, in collaboration with Maastricht University Medical Centre + , was commissioned to act as the independent Evidence Review Group (ERG). This paper contains a summary of the clinical and cost-effectiveness evidence submitted by the company, the ERG’s critique on the submitted evidence, and the guidance issued by the NICE Appraisal Committee (AC). The company submission (CS) was mainly informed by the PSV-FAI-001 trial in which FAc was compared with (limited) current practice [(L)CP], which was not considered to be representative of UK clinical practice by the ERG. There was no comparison of FAc to any treatment listed in the final scope, and especially to the dexamethasone intravitreal implant (dexamethasone), which was considered to be a relevant comparator by the AC. The primary outcome of the PSV-FAI-001 was recurrence of uveitis in the treated eye. Most of the events for the primary outcome were imputed during the PSV-FAI-001 trial, which probably led to an overestimation of the number of recurrences of disease, and a biased estimate of the relative effectiveness of FAc versus (L)CP. Finally, the place of FAc in the treatment pathway was not clearly defined by the company. Substantial uncertainty surrounded the cost-effectiveness results due to the shortcomings of the clinical evidence. Additionally, the quality of life of patients was not measured during the PSV-FAI-001 trial and long-term effectiveness data of FAc were lacking. The ERG adjusted several issues identified in the CS and added dexamethasone as a comparator in the decision analytic model. The ERG presented multiple analyses as base-cases because several elements of the assessment remained uncertain. The fully incremental ERG results ranged from dexamethasone (extendedly) dominating FAc (when assuming a hazard ratio of 1 or 0.7 for dexamethasone versus FAc) to an incremental cost-effectiveness ratio (ICER) of £30,153 per quality-adjusted life-year (QALY) gained for FAc versus (L)CP [when assuming a hazard ratio of 0.456 for dexamethasone versus (L)CP]. The ICER of FAc versus (L)CP ranged from £12,325 to £30,153 per QALY gained. After a second AC meeting where alternative company scenarios comparing FAc with dexamethasone were considered by the AC, the AC concluded that “the results of the company’s analyses ranged from the fluocinolone acetonide implant being dominant (that is, it was more effective and costs less), to an ICER of £29,461 per QALY gained, and most of the ICERs were below £20,000 per QALY gained”. Therefore, the AC recommended FAc as a cost-effective use of National Health Service (NHS) resources for treating recurrent non-infectious uveitis affecting the posterior segment of the eye in the final TA590 guidance (published July 2019).

Cost-Effectiveness of Tenofovir Alafenamide for Treatment of Chronic Hepatitis B in Canada Abstract Background/Aim Tenofovir alafenamide (TAF) has been approved for treating chronic hepatitis B (CHB) due to a proposed better safety profile in comparison with current therapies. We evaluated the cost effectiveness of TAF and other available treatment options for hepatitis B envelope antigen (HBeAg)-positive and HBeAg-negative CHB patients from a Canadian provincial Ministry of Health perspective. Methods A state-transition model based on the published literature was developed to compare treatment strategies involving entecavir (ETV), tenofovir disoproxil fumarate (TDF), and TAF. It adopted a lifetime time horizon. Outcomes measured were predicted number of liver-related deaths, costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs). Results For HBeAg-positive patients, TAF followed by ETV generated an additional 0.16 QALYs/person at an additional cost of Can$14,836.18 with an ICER of Can$94,142.71/QALY compared with TDF followed by ETV. Of the iterations, 28.7% showed that it is the optimal strategy with a Can$50,000 willingness-to-pay threshold. For HBeAg-negative patients, ETV followed by TAF would prevent an additional 13 liver-related deaths per 1000 CHB patients compared with TDF, followed by ETV. It generated an additional 0.13 QALYs/person at an additional cost of Can$59,776.53 with an ICER of Can$461,162.21/QALY compared with TDF, followed by ETV. TAF-containing strategies are unlikely to be a rational choice in either case. The results were sensitive to the HBeAg seroconversion rates and viral suppression rates of the treatments. Conclusions Our analysis suggests that TAF is not cost effective at its current cost. A 33.4% reduction in price would be required to make it cost effective for HBeAg-positive patients with a Can$50,000 willingness-to-pay threshold.

Acknowledgement to Referees

Correction to: Publication of Decision Model Source Code: Attitudes of Health Economics Authors The article Artificial recharge of a shallow hard rock aquiferas a climate change mitigation method.

Publication of Decision Model Source Code: Attitudes of Health Economics Authors

Improving Transparency in Decision Models: Current Issues and Potential Solutions

Can You Repeat That? Exploring the Definition of a Successful Model Replication in Health Economics Abstract The International Society for Pharmacoeconomics and Outcomes Research (ISPOR) modelling taskforce suggests decision models should be thoroughly reported and transparent. However, the level of transparency and indeed how transparency should be assessed are yet to be defined. One way may be to attempt to replicate the model and its outputs. The ability to replicate a decision model could demonstrate adequate reporting transparency. This review aims to explore published definitions of replication success across all scientific disciplines and to consider how such a definition should be tailored for use in health economic models. A literature review was conducted to identify published definitions of a ‘successful replication’. Using these as a foundation, several definitions of replication success were constructed, to be applicable to replications of economic decision models, with the associated strengths and weaknesses of such definitions discussed. A substantial body of literature discussing replicability was found; however, relatively few studies, ten, explicitly defined a successful replication. These definitions varied from subjective assessments to expecting exactly the same results to be reproduced. Whilst the definitions that have been found may help to construct a definition specific to health economics, no definition was found that completely encompassed the unique requirements for decision models. Replication is widely discussed in other scientific disciplines; however, as of yet, there is no consensus on how replicable models should be within health economics or what constitutes a successful replication. Replication studies can demonstrate how transparently a model is reported, identify potential calculation errors and inform future reporting practices. It may therefore be a useful adjunct to other transparency or quality measures.

Developing Open-Source Models for the US Health System: Practical Experiences and Challenges to Date with the Open-Source Value Project Abstract The Innovation and Value Initiative started the Open-Source Value Project with the aim to improve the credibility and relevance of model-based value assessment in the context of the US healthcare environment. As a core activity of the Open-Source Value Project, the Innovation and Value Initiative develops and provides access to flexible open-source economic models that are developed iteratively based on public feedback and input. In this article, we describe our experience to date with the development of two currently released, Open-Source Value Project models, one in rheumatoid arthritis and one in epidermal growth factor receptor-positive non-small-cell lung cancer. We developed both Open-Source Value Project models using the statistical programming language R instead of spreadsheet software (i.e., Excel), which allows the models to capture multiple model structures, model sequential treatment with individual patient simulations, and improve integration with formal evidence synthesis. By developing the models in R, we were also able to use version control systems to manage changes to the source code, which is needed for iterative and collaborative model development. Similarly, Open-Source Value Project models are freely available to the public to provide maximum transparency and facilitate collaboration. Development of the rheumatoid arthritis and non-small-cell lung cancer model platforms has presented multiple challenges. The development of multiple components of the model platform tailored to different audiences, including web interfaces, required more resources than a cost-effectiveness analysis for a publication would. Furthermore, we faced methodological hurdles, in particular related to the incorporation of multiple competing model structures and novel elements of value. The iterative development based on public feedback also posed some challenges during the review phase, where methodological experts did not always understand feedback from clinicians and vice versa. Response to the Open-Source Value Project by the modeling community and patient organizations has been positive, but feedback from US decision makers has been limited to date. As we progress with this project, we hope to learn more about the feasibility, benefits, and challenges of an open-source and collaborative approach to model development for value assessment.