Methods for Including Adverse Events in Economic Evaluations: Suggestions for Improvement.

OBJECTIVE: Inclusion of relevant effectiveness and safety outcomes in economic evaluation of health technologies is required to aid efficient healthcare decisions. Our objective was to identify the key issues related to the inclusion of adverse events (AEs) in economic evaluation and explore perspectives for good practice recommendations to handle these issues. METHODS: We focused on the frequently encountered methodological issues related to the integration of AEs in economic evaluations of health technologies. We distinguished the following elements: the incorporation of AEs in decision models, the terminology of AEs, the estimation of AEs consequences in terms of quality of life (QoL) and costs, and the exploration of the uncertainty related to the impact of AEs on the economic results. RESULTS: We illustrated and discussed each of the identified issues by giving health technology assessment examples. We focused on the extent to which the integration of AEs in decision models can be improved by dealing with the lack of relevant real-world safety data, estimating the consequences of AEs (eg, for costs and QoL loss), exploring the impacts of AEs that are not adequately captured in current measurement of health-related QoL, and identifying the need for development of a good terminology of relevant types of AEs to be incorporated in economic evaluation. CONCLUSION: Based on a reflection the key methodological issues related to the incorporation of adverse drug events in economic evaluations, we suggested several recommendations to serve a starting point for health technology assessment agencies and researchers to develop good research practices in this field.

Four Aspects Affecting Health Economic Decision Models and Their Validation.

Health care decision makers in many jurisdictions use cost-effectiveness analysis based on health economic decision models for policy decisions regarding coverage and price negotiation for medicines and medical devices. While validation of health economic decision models has always been considered important, many reviews of model-based cost-effectiveness studies report limitations regarding their validation. The current opinion paper discusses four aspects of current health economic decision modeling with relevance for future directions in model validation: increased use of complex models, international cooperation, open-source modeling, and stakeholder involvement. First, new, more complex clinical study designs and treatment strategies may require relatively complex model structures and/or input data analyses. Simultaneously, more widespread technical knowledge along with wider data availability have led to a broader range of model types. This puts extra requirements on model validation and transparency. Second, increased international cooperation of policy makers and, in particular, health technology assessment (HTA) authorities in performing model assessments is discussed in relation to the repeated use of health economic models (multi-use disease models). We argue such coordinated efforts may benefit model validity. Third, open-source modeling is discussed as one possible answer to increased transparency requirements. Finally, involvement of all relevant stakeholders throughout the whole decision process is an ongoing development that necessarily also includes health economic modeling. We argue this implies that model validity should be considered in a broader perspective, with more focus on conceptual modeling, model transparency, accuracy requirements, and choice of relevant model outcomes than previously.

Economic Evaluation of Sequences of Biological Treatments for Patients With Moderate-to-Severe Rheumatoid Arthritis and Inadequate Response or Intolerance to Methotrexate in France.

OBJECTIVES: Biologic disease-modifying antirheumatic drugs (bDMARDs) are prescribed sequentially in the treatment of rheumatoid arthritis (RA). Healthcare decision makers continue to debate their use, mainly because of their high costs. Our aim was to perform an economic evaluation for France of bDMARD sequences for treatment of moderate-to-severe RA after inadequate response or intolerance to conventional DMARDs (eg, methotrexate). METHODS: A discretely integrated condition event simulation was developed to track the course of patients from first bDMARD through switches to further lines in a sequence. The model included 11 events, 91 conditions, and 21 controlling equations. Inputs were obtained from a meta-analysis of clinical trials, a French registry, national drug lists, and databases. Survival, time with minimal activity, quality-adjusted life-years (QALYs), and total costs were output. Structural and probabilistic sensitivity analyses were conducted. RESULTS: Sequences starting with etanercept biosimilars (ETB) cost less, with ETB-abatacept-infliximab the least expensive: the mean lifetime discounted total cost was €116 912 per patient, with a mean of 11.166 QALYs. Most other strategies were dominated or led to small QALY gains (0.0008-0.0329). Only ETB-tocilizumab-abatacept made it onto the efficiency frontier, but at €955 778 per QALY gained. These results were confirmed in several scenarios and uncertainty analyses. CONCLUSION: Given minor differences in QALYs gained between bDMARD sequences with large cost differences, starting with biosimilars was more efficient than starting with branded products. Our model and findings should provide French and other decision makers with useful tools to address the challenges of comparing sequences of treatments for RA.

Value of Information Analytical Methods: Report 2 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force.

The allocation of healthcare resources among competing priorities requires an assessment of the expected costs and health effects of investing resources in the activities and of the opportunity cost of the expenditure. To date, much effort has been devoted to assessing the expected costs and health effects, but there remains an important need to also reflect the consequences of uncertainty in resource allocation decisions and the value of further research to reduce uncertainty. Decision making with uncertainty may turn out to be suboptimal, resulting in health loss. Consequently, there may be value in reducing uncertainty, through the collection of new evidence, to better inform resource decisions. This value can be quantified using value of information (VOI) analysis. This report from the ISPOR VOI Task Force describes methods for computing 4 VOI measures: the expected value of perfect information, expected value of partial perfect information (EVPPI), expected value of sample information (EVSI), and expected net benefit of sampling (ENBS). Several methods exist for computing EVPPI and EVSI, and this report provides guidance on selecting the most appropriate method based on the features of the decision problem. The report provides a number of recommendations for good practice when planning, undertaking, or reviewing VOI analyses. The software needed to compute VOI is discussed, and areas for future research are highlighted.

Value of Information Analysis for Research Decisions-An Introduction: Report 1 of the ISPOR Value of Information Analysis Emerging Good Practices Task Force.

Healthcare resource allocation decisions made under conditions of uncertainty may turn out to be suboptimal. In a resource constrained system in which there is a fixed budget, these suboptimal decisions will result in health loss. Consequently, there may be value in reducing uncertainty, through the collection of new evidence, to make better resource allocation decisions. This value can be quantified using a value of information (VOI) analysis. This report, from the ISPOR VOI Task Force, introduces VOI analysis, defines key concepts and terminology, and outlines the role of VOI for supporting decision making, including the steps involved in undertaking and interpreting VOI analyses. The report is specifically aimed at those tasked with making decisions about the adoption of healthcare or the funding of healthcare research. The report provides a number of recommendations for good practice when planning, undertaking, or reviewing the results of VOI analyses.

Economic Evaluations of Anticancer Drugs Based on Medico-Administrative Databases: A Systematic Literature Review.

BACKGROUND: Oncology is among the most active therapeutic fields in terms of new drug development projects, with increasingly expensive drugs. The expected clinical benefit and cost effectiveness of these treatments in clinical practice have yet to be fully confirmed. Health medico-administrative databases may be useful for assessing the value of anticancer drugs with real-world data. OBJECTIVE: The objectives of our systematic literature review (SLR) were to analyse economic evaluations of anticancer drugs based on health medico-administrative databases, to assess the quality of these evaluations, and to identify the inputs from such databases that can be used in economic evaluations of anticancer drugs. METHODS: We performed an SLR by using PubMed and Web of Science articles published from January 2008 to January 2019. The search strategy focused on anticancer drug cost-effectiveness analyses (CEAs)/cost-utility analyses (CUAs) that were entirely based on medico-administrative databases. The review reported the main choices of economic evaluation methods in the analyses. The quality of the articles was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) and risk of bias assessment checklists. RESULTS: Of the 306 records identified in PubMed, 12 articles were selected, and one additional article was identified through Web of Science. Ten of the 13 articles were CEAs and three were CUAs. Most of the analyses were carried out in North America (n = 11). The economic metric used was the cost per life-year gained (n = 10) or cost per quality-adjusted life-year (n = 3). Reporting of the target analysis population and strategies in the articles was in agreement with the CHEERS guidelines. The structural assumptions underpinning the economic models displayed the poorest reporting quality among the items analysed. Representativeness bias (n = 11) and the issue of censored medical costs (n = 8) were the most frequently analysed risks. CONCLUSION: A comparison of the economic results was not relevant due to the high heterogeneity of the selected studies. Our SLR highlighted the benefits and pitfalls related to the use of medico-administrative databases in the economic evaluations of anticancer drugs.

Systematic Literature Review of Economic Evaluations of Biological Treatment Sequences for Patients with Moderate to Severe Rheumatoid Arthritis Previously Treated with Disease-Modifying Anti-rheumatic Drugs.

OBJECTIVE: This systematic literature review (SLR) had two objectives: to analyse published economic evaluations of biological disease-modifying anti-rheumatic drugs (bDMARDs) for patients with moderate to severe rheumatoid arthritis (RA) previously treated with DMARDs and to assess the quality of those that included sequences of treatments. METHODS: We performed an SLR on PubMed, Central, Cochrane, and French databases from January 2000 to December 2018. The search focused on cost-effectiveness/utility/benefit analyses. We extracted data on treatment sequences, outcomes (e.g. quality-adjusted life year) and choices of economic evaluation methods (e.g. model type, type of analysis, and method of utility estimation). We analysed the improvement of methods by comparing two sub-periods (2000-2009 and 2010-2018). The quality of reporting and the quality of the methods were assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) and a set of eight key aspects for a reference case for economic evaluation of bDMARDs based on the Outcome Measures in Rheumatology (OMERACT) and Drummond checklists. Data extraction and study assessment were performed independently by two health economists. RESULTS: From the 824 records identified in the initial search, 51 publications were selected. Of these, 31 included sequences. Individual models such as discrete-event simulations were used in over two-fifths (22/51, 43%) of the selected studies. Few studies (7/51, 14%) used utility scores based on generic instruments (e.g. EQ-5D). Estimation of hospitalization costs was described in only approximately one-third of studies (19/51). Loss of quality of life (QoL) related to adverse events such as tuberculosis and pneumonia was included in one-tenth (5/51, 10%) of the studies. It was difficult to compare the results of the economic evaluations (i.e. incremental cost-effectiveness ratios) due to the high heterogeneity of studies in terms of disease stage, data sources, inputs, and methods of health outcome assessment used. For identified studies including sequences, the CHEERS assessment of reporting quality showed insufficient reporting of uncertainty analyses and utility weights in more than a third of the studies (11/31, 35%; 9/25, 36%). An in-depth assessment of the quality of the studies revealed that only seven, mostly conducted during the sub-period 2010-2018, addressed the majority of methodological quality assessment issues such as the simulation of patient sequence pathways, the use of systematic reviews and meta-analyses of comparative effectiveness, the choice of treatment sequence, and rules for switching. CONCLUSION: Our SLR identified a lack of high-quality evaluations assessing bDMARD sequences, although some improvements were made in the reporting and modelling of patients' pathways in studies published after 2010. In order to improve economic evaluations of RA, clear health technology assessment guidance on RA health-related QoL instruments must be provided, and data including long-term disease progression must be made available.

Rheumatoid arthritis treated with 6-months of first-line biologic or biosimilar therapy: an updated systematic review and network meta-analysis.

OBJECTIVES: The aim of this study was to estimate the effectiveness of first-line biologic disease modifying drugs(boDMARDs), and their approved biosimilars (bsDMARDs), compared with conventional (csDMARD) treatment, in terms of ACR (American College of Rheumatology) and EULAR (European League against Rheumatism) responses. METHODS: Systematic literature search, on eight databases to January 2017, sought ACR and EULAR data from randomized controlled trials (RCTs) of boDMARDs / bsDMARDs (in combination with csDMARDs, or monotherapy). Two adult populations: methotrexate (MTX)-naïve patients with severe active RA; and csDMARD-experienced patients with moderate-to-severe active RA. Network meta-analyses (NMA) were conducted using a Bayesian Markov chain Monte Carlo simulation using a random effects model with a probit link function for ordered categorical. RESULTS: Forty-six RCTs met the eligibility criteria. In the MTX-naïve severe active RA population, no biosimilar trials meeting the inclusion criteria were identified. MTX plus methylprednisolone (MP) was most likely to achieve the best ACR response. There was insufficient evidence that combination boDMARDs was superior to intensive (two or more) csDMARDs. In the csDMARD-experienced, moderate-to-severe RA population, the greatest effects for ACR responses were associated with tocilizumab (TCZ) monotherapy, and combination therapy (plus MTX) with bsDMARD etanercept (ETN) SB4, boDMARD ETN and TCZ. These treatments also had the greatest effects on EULAR responses. No clear differences were found between the boDMARDs and their bsDMARDs. CONCLUSIONS: In MTX-naïve patients, there was insufficient evidence that combination boDMARDs was superior to two or more csDMARDs. In csDMARD-experienced patients, boDMARDs and bsDMARDs were comparable and all combination boDMARDs / bsDMARDs were superior to single csDMARD.

Trusting the Results of Model-Based Economic Analyses: Is there a Pragmatic Validation Solution?

Models have become a nearly essential component of health technology assessment. This is because the efficacy and safety data available from clinical trials are insufficient to provide the required estimates of impact of new interventions over long periods of time and for other populations and subgroups. Despite more than five decades of use of these decision-analytic models, decision makers are still often presented with poorly validated models and thus trust in their results is impaired. Among the reasons for this vexing situation are the artificial nature of the models, impairing their validation against observable data, the complexity in their formulation and implementation, the lack of data against which to validate the model results, and the challenges of short timelines and insufficient resources. This article addresses this crucial problem of achieving models that produce results that can be trusted and the resulting requirements for validation and transparency, areas where our field is currently deficient. Based on their differing perspectives and experiences, the authors characterize the situation and outline the requirements for improvement and pragmatic solutions to the problem of inadequate validation.

The French National Authority for Health (HAS) Guidelines for Conducting Budget Impact Analyses (BIA).

BACKGROUND: Budget impact analysis (BIA) provides short- and medium-term estimates on changes in budgets and health outcomes resulting from the adoption of new health interventions. OBJECTIVE: The purpose of this study is to present the newly developed French National Authority for Health (HAS) guidelines on budget impact analysis as follows: process, literature review, recommendations and comparisons with other guidelines. METHODS: The development process of the HAS guidelines included a literature review (search dates: January 2000 to June 2016), a retrospective investigation of BIA previously submitted to HAS, a public consultation, international expert reviews and approval from the HAS Board and the Economic and Public Health Evaluation Committee of HAS. RESULTS: Documents identified in the literature review included 12 national guidelines, 5 recommendations for good practices developed by national and international society of health economics and 14 methodological publications including recommendations for conducting BIA. Based on its research findings, HAS developed its first BIA guidelines, which include recommendations on the following topics: BIA definition, perspective, populations, time horizon, compared scenarios, budget impact models, costing, discounting, choice of clinical data, reporting of results and uncertainty exploration. CONCLUSION: It is expected that the HAS BIA guidelines will enhance the usefulness, quality and transparency of BIA submitted by drug manufacturers to HAS. BIA is becoming an essential part of a comprehensive economic assessment of healthcare interventions in France, which also includes cost-effectiveness analysis and equity of access to healthcare.

[HAS budget impact analysis guidelines: A new decision-making tool]. / Le guide d'analyse d'impact budgétaire de la HAS : un nouvel outil d'aide à la décision.

INTRODUCTION: Budget impact analysis (BIA) provides short and medium-term estimates on changes in budgets and resources resulting from the adoption of new health interventions. OBJECTIVE: The objective of this article is to present the main messages of the newly developed French National Authority for Health (HAS) guidelines on budget impact analysis : issues, recommendations and perspectives. METHODS: The HAS guidelines development process was based on data derived from a literature review on BIA (search dates : January 2000 to June 2016), an HAS retrospective investigation, a public consultation, international expert advice, and approval from the HAS Board and the Economic and Public Health Evaluation Committee. RESULTS: Based on its research findings, HAS developed its first BIA guidelines, which include recommendations on the following topics : BIA definition, perspective, populations, time horizon, compared scenarios, budget impact models, costing, discounting, choice of clinical data, reporting of results and uncertainty analysis. CONCLUSION: The HAS BIA guidelines are expected to enhance the usefulness of BIA as an essential part of a comprehensive economic assessment of healthcare interventions, which itself includes cost-effectiveness analysis and equity of access to healthcare.

Health-state utility estimates for health technology assessment: a review of the manufacturers' submissions to the French National Authority for Health.

BACKGROUND: Our aim was to review the selection and methods used for deriving health state utility (HSU) estimates included in the cost-utility analyses (CUA) submitted by manufacturers to the National Authority for Health (HAS) during the first 2 years after the introduction of the economic evaluation for price setting in France. METHODS: We reviewed all manufacturers' submissions that included a CUA and were assessed by HAS by the end of October 2015 (N = 34). We reviewed the identification, selection, and methods used to estimate HSU and compared them with those recommended by HAS. RESULTS: A literature review to identify HSU was reported in only 13 (38%) submissions. The instruments for describing HSU were a preference-based generic instrument in 20 (59%) submissions; vignettes in five (15%); a condition-specific instrument in three (9%); and a combination of instruments in six (18%). The valuation perspective was the general population in 26 (76%) submissions; in only nine (26%) submissions, the valuation set was derived from the French general population. CONCLUSIONS: We identified numerous concerns in the selection, valuation and use of HSU, as well as a frequent lack of clarity in the methods used. Most submissions (79%) included HSU that did not meet HAS recommendations.

Exploring Uncertainty in Economic Evaluations of Drugs and Medical Devices: Lessons from the First Review of Manufacturers' Submissions to the French National Authority for Health.

OBJECTIVES: The objective of this paper was to evaluate how uncertainty has been accounted for in the cost-effectiveness analyses (CEAs) submitted by manufacturers to the French National Authority for Health (HAS) and to identify recurring concerns in these submissions. METHODS: We used a cross-sectional design to evaluate manufacturers' submissions from the beginning of the evaluation process in October 2013 to the end of May 2015 (n = 28). The sources of uncertainty attached to these CEAs were categorized and assessed. Relevant data were extracted independently by two assessors. RESULTS: Adherence to the HAS reference case was generally considered to be acceptable. Methodological uncertainty and parameter uncertainty were the sources of uncertainty that were most frequently explored by manufacturers. The quality of reporting of deterministic sensitivity analysis and probabilistic sensitivity analysis varied substantially across submissions, with a frequent lack of justification of the plausible range of parameter point estimates in 12 submissions (43 %). Structural uncertainty was explored much less frequently. Concerns related to omission of either important clinical events or relevant health states or extrapolation of the effects of the technology beyond the time horizon of the clinical trials were identified in 16 submissions (57 %). CONCLUSIONS: This study presented a characterization of the treatment of uncertainty for the first 28 manufacturers' submissions to the HAS. This work identified important concerns regarding the exploration of sources of uncertainty. The findings may help manufacturers to improve the quality of their submissions and may provide useful insights for extending guidelines on uncertainty analysis in CEAs submitted to the HAS.