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Background: Value of information (VOI) analysis often requires modeling to characterize and propagate uncertainty. In collaboration with a cancer clinical trial group, we integrated a VOI approach to assessing trial proposals.Objective: This paper aims to explore the impact of modeling choices on VOI results and to share lessons learned from the experience.Methods: After selecting two proposals (A: phase III, breast cancer; B: phase II, pancreatic cancer) for in-depth evaluations, we categorized key modeling choices relevant to trial decision makers (characterizing uncertainty of efficacy, evidence thresholds to change clinical practice, and sample size) and modelers (cycle length, survival distribution, simulation runs, and other choices). Using a $150,000 per quality-adjusted life-year (QALY) threshold, we calculated the patient-level expected value of sample information (EVSI) for each proposal and examined whether each modeling choice led to relative change of more than 10% from the averaged base-case estimate. We separately analyzed the impact of the effective time horizon.Results: The base-case EVSI was $118,300 for Proposal A and $22,200 for Proposal B per patient. Characterizing uncertainty of efficacy was the most important choice in both proposals (e.g. Proposal A: $118,300 using historical data vs. $348,300 using expert survey), followed by the sample size and the choice of survival distribution. The assumed effective time horizon also had a substantial impact on the population-level EVSI.Conclusions: Modeling choices can have a substantial impact on VOI. Therefore, it is important for groups working to incorporate VOI into research prioritization to adhere to best practices, be clear in their reporting and justification for modeling choices, and to work closely with the relevant decision makers, with particular attention to modeling choices. [ABSTRACT FROM AUTHOR]

Introduction: Frequently, within economic evaluations, data are subject to censoring, and ignoring censored data will lead to an underestimation of mean total costs. Several techniques have been published that can be used to estimate mean total costs and standard errors, and allow for censoring within cost data. This paper reviews these techniques and compares the mean total costs estimates generated by each method for different types of censoring.Methods: Nine techniques were identified that can be used to estimate mean total costs and standard errors in the presence of censoring: ignoring censoring; ignoring censored costs; Lin's method--with and without cost histories; weighted cost method--with and without cost histories; Lin's regression method--with and without cost histories; and Carides' regression method. These methods are compared across four different censoring mechanisms--random censoring, end-of-study censoring, informative censoring and partial censoring--by simulating the censoring mechanisms from a complete cohort of patients included in the CELT (Cost Effectiveness of Liver Transplantation) study.Results: The observed mean cost and standard error from the CELT data were 36,045 pounds sterling and 1517 pounds sterling (1998 values). Estimates under informative censoring were the least accurate predictors of mean total costs and tended to overestimate mean costs by > 1000 pounds sterling. Carides' regression method predicted mean total costs to within 3 pounds sterling of the observed mean and represented one of the three most accurate methods for predicting mean total costs (together with the weighted cost method with known cost histories and Lin's method with unknown cost histories). Lin's method with known cost histories gave the least accurate estimates of mean total costs and underpredicted costs by 2137-4859 pounds sterling across censoring mechanisms. Carides' method did not predict uncertainty around the mean costs well, and the weighted cost method with known cost histories and ignoring censoring were the best methods to use for estimating the standard error of the mean cost.Conclusions: Further work should be carried out on other datasets to confirm the generalisability of these results. Although Carides' regression method and Lin's method with unknown cost histories were the best estimators of mean total costs across censoring mechanisms, the weighted cost method with known cost histories is the preferred method for obtaining an accurate estimate of the mean total cost alone and the uncertainty surrounding it; therefore, it should be used to estimate mean costs and standard errors when patient cost histories are known. [ABSTRACT FROM AUTHOR]

Background: The Pediatric Quality of Life Inventory™ 4.0 Short Form 15 Generic Core Scales (hereafter the PedsQL) and the Child Health Utility-9 Dimensions (CHU9D) are two generic instruments designed to measure health-related quality of life in children and adolescents in the general population and paediatric patient groups living with specific health conditions. Although the PedsQL is widely used among paediatric patient populations, presently it is not possible to directly use the scores from the instrument to calculate quality-adjusted life-years (QALYs) for application in economic evaluation because it produces summary scores which are not preference-based.Objective: This paper examines different econometric mapping techniques for estimating CHU9D utility scores from the PedsQL for the purpose of calculating QALYs for cost-utility analysis.Methods: The PedsQL and the CHU9D were completed by a community sample of 755 Australian adolescents aged 15-17 years. Seven regression models were estimated: ordinary least squares estimator, generalised linear model, robust MM estimator, multivariate factorial polynomial estimator, beta-binomial estimator, finite mixture model and multinomial logistic model. The mean absolute error (MAE) and the mean squared error (MSE) were used to assess predictive ability of the models.Results: The MM estimator with stepwise-selected PedsQL dimension scores as explanatory variables had the best predictive accuracy using MAE and the equivalent beta-binomial model had the best predictive accuracy using MSE.Conclusions: Our mapping algorithm facilitates the estimation of health-state utilities for use within economic evaluations where only PedsQL data is available and is suitable for use in community-based adolescents aged 15-17 years. Applicability of the algorithm in younger populations should be assessed in further research. [ABSTRACT FROM AUTHOR]

Purpose: Economic evaluation of health services commonly requires information regarding health-state utilities. Sometimes this information is not available but non-utility measures of quality of life may have been collected from which the required utilities can be estimated. This paper examines the possibility of mapping a non-utility-based outcome, the Sydney Asthma Quality of Life Questionnaire (AQLQ-S), onto five multi-attribute utility instruments: Assessment of Quality of Life 8 Dimensions (AQoL-8D), EuroQoL 5 Dimensions 5-Level (EQ-5D-5L), Health Utilities Index Mark 3 (HUI3), 15 Dimensions (15D), and the Short-Form 6 Dimensions (SF-6D).Methods: Data for 856 individuals with asthma were obtained from a large Multi-Instrument Comparison (MIC) survey. Four statistical techniques were employed to estimate utilities from the AQLQ-S. The predictive accuracy of 180 regression models was assessed using six criteria: mean absolute error (MAE), root mean squared error (RMSE), correlation, distribution of predicted utilities, distribution of residuals, and proportion of predictions with absolute errors <0.0.5. Validation of initial 'primary' models was carried out on a random sample of the MIC data.Results: Best results were obtained with non-linear models that included a quadratic term for the AQLQ-S score along with demographic variables. The four statistical techniques predicted models that performed differently when assessed by the six criteria; however, the best results, for both the estimation and validation samples, were obtained using a generalised linear model (GLM estimator).Conclusions: It is possible to predict valid utilities from the AQLQ-S using regression methods. We recommend GLM models for this exercise. [ABSTRACT FROM AUTHOR]

The National Institute for Health and Care Excellence (NICE) invited the manufacturer of lenalidomide (Celgene) to submit evidence of the clinical and cost effectiveness of the drug for treating adults with myelodysplastic syndromes (MDS) associated with deletion 5q cytogenetic abnormality, as part of the Institute's single technology appraisal (STA) process. Kleijnen Systematic Reviews Ltd (KSR), in collaboration with Erasmus University Rotterdam, was commissioned to act as the Evidence Review Group (ERG). This paper describes the company's submission, the ERG review, and the NICE's subsequent decisions. The ERG reviewed the evidence for clinical and cost effectiveness of the technology, as submitted by the manufacturer to the NICE. The ERG searched for relevant additional evidence and validated the manufacturer's decision analytic model to examine the robustness of the cost-effectiveness results. Clinical effectiveness was obtained from a three-arm, European, randomized, phase III trial among red blood cell (RBC) transfusion-dependent patients with low-/intermediate-1-risk del5q31 MDS. The primary endpoint was RBC independence for ≥26 weeks, and was reached by a higher proportion of patients in the lenalidomide 10 and 5 mg groups compared with placebo (56.1 and 42.6 vs 5.9 %, respectively; both p < 0.001). The option of dose adjustments after 16 weeks due to dose-limiting toxicities or lack of response made long-term effectiveness estimates unreliable, e.g. overall survival (OS). The de novo model of the manufacturer included a Markov state-transition cost-utility model implemented in Microsoft Excel. The base-case incremental cost-effectiveness ratio (ICER) of the manufacturer was £56,965. The ERG assessment indicated that the modeling structure represented the course of the disease; however, a few errors were identified and some of the input parameters were challenged. In response to the appraisal documentation, the company revised the economic model, which increased the ICER to £68,125 per quality-adjusted life-year. The NICE Appraisal Committee (AC) did not recommend lenalidomide as a cost-effective treatment. Subsequently, the manufacturer submitted a Patient Access Scheme (PAS) that provided lenalidomide free of charge for patients who remained on treatment after 26 cycles. This PAS improved the ICER to £25,300, although the AC considered the proportion of patients who received treatment beyond 26 cycles, and hence the ICER, to be uncertain. Nevertheless, the AC accepted a commitment from the manufacturer to publish, once available, data on the proportion of patients eligible for the PAS, and believed this provided reassurance that lenalidomide was a cost-effective treatment for low- or intermediate-1-risk MDS patients. [ABSTRACT FROM AUTHOR]

Objectives: In Australia, no therapeutic agents were subsidised for the treatment of idiopathic pulmonary artery hypertension (iPAH), a rare progressive and severe disease with short life expectancy, until 1 March 2004, when bosentan (a dual endothelin receptor antagonist of high cost) was listed on the Pharmaceutical Benefits Scheme (PBS). Bosentan, in addition to conventional therapy, has been shown to slow iPAH progression and improve clinical and haemodynamic status and symptomatology, compared with placebo and conventional therapy. The objective of this paper is to describe the process of the Australian Pharmaceutical Benefits Scheme listing for bosentan (Tracleer), which included a health economic model assessing the cost effectiveness of bosentan from a healthcare payer perspective, and a risk-sharing arrangement based on the establishment of a patient registry.Methods: The health economic model predicted the cost, hospitalisation and mortality rates of a population of iPAH patients treated with either the conventional therapy regimen used in Australia or bosentan plus the conventional therapy regimen. The model was implemented as a first-order Monte Carlo simulation with mortality modelled directly as the main clinical outcome. The impacts of proposed continuation criteria, restricting the ongoing use of the drug, were evaluated. Costs and outcomes were discounted at 5% and a sensitivity analysis examined the robustness of the key assumptions.Results: The model predicted that after 5, 10 and 15 years, the difference in average cumulative costs between bosentan plus conventional therapy and conventional therapy alone would be 116,929 Australian dollars (A dollars), A181,808 dollars and A216,331 dollars for each patient, respectively. There would be an associated increase in average life expectancy of 1.39, 2.93 and 3.87 years at 5, 10 and 15 years, respectively, with an incremental cost-effectiveness ratio at 15 years of A55,927 dollars for each life-year gained. Removing the continuation criteria from the model increased the incremental cost-effectiveness ratio to A62,267 dollars (1996-2002 values).Conclusions: Economic modelling based on improved survival suggests bosentan to be a potentially cost-effective treatment for iPAH. However, the structure of the model and its inputs should be reviewed and updated as more data become available. [ABSTRACT FROM AUTHOR]

Objective: To estimate the cost effectiveness (from the UK NHS and personal social services perspective) of the cholinesterase inhibitors donepezil, rivastigmine and galantamine compared with usual care in the treatment of mild to moderately severe Alzheimer's disease. Patients had a mean age of 74 years, a mean disease duration of 1 year and a mean Alzheimer's disease assessment scale-cognitive subscale score of 24.Methods: A pharmacoeconomic model was used to predict long-term outcomes over a 5-year time horizon and to estimate the cost effectiveness of cholinesterase inhibitors for the management of Alzheimer's disease. The model structure is informed by a systematic review of the literature on the clinical and cost effectiveness of cholinesterase inhibitors and a review of the literature on the costs and outcomes associated with treatment for Alzheimer's disease. The main outcome measure used was the cost per quality-adjusted life-year (QALY) gained. All healthcare costs (excluding cholinesterase inhibitor costs) were indexed to pounds sterling (2003 values). Drug costs are 2005 values. Multivariate probabilistic sensitivity analysis and scenario analysis were undertaken to assess uncertainty in the results.Results: The clinical benefits on cognition from treatment with cholinesterase inhibitors resulted in an incremental cost per QALY gained ranging from 53,780 pounds sterling to 74,735 pounds sterling, over 5 years (vs usual care). Uncertainty analysis suggests that the probability of any of these treatments having an incremental cost per QALY of < 30,000 pounds sterling is < 21%. The key determinants of cost effectiveness were the effectiveness of treatment, the mean treatment cost and the cost savings associated with an expected delay in disease progression.Conclusions: Results presented in this paper suggest that the use of cholinesterase inhibitors may not be a cost-effective use of NHS resources. Guidance from the National Institute for Health and Clinical Effectiveness (NICE) in the UK on their judgements surrounding the acceptability of technologies as an effective use of resources, indicates there would need to be special reasons for accepting cholinesterase inhibitors as a cost-effective use of NHS resources. [ABSTRACT FROM AUTHOR]

To date, decision trees and Markov models have been the most common methods used in pharmacoeconomic evaluations. Both of these techniques lack the flexibility required to appropriately represent clinical reality. In this paper an alternative, more natural, way to model clinical reality--discrete event simulation--is presented and its application is illustrated with a real world example.A discrete event simulation represents the course of disease very naturally, with few restrictions. Neither mutually exclusive branches nor states are required, nor is a fixed cycle. All relevant aspects can be incorporated explicitly and efficiently. Flexibility in handling perspectives and carrying out sensitivity analyses, including structural variations, is incorporated and the entire model can be presented very transparently. The main limitations are imposed by lack of data to fit realistic models. Discrete event simulation, though rarely employed in pharmacoeconomics today, should be strongly considered when carrying out economic evaluations, particularly those aimed at informing policy makers and at estimating the budget impact of a pharmaceutical intervention. [ABSTRACT FROM AUTHOR]

Model-based economic evaluations should capture the impact on all costs and outcomes relevant to the chosen study perspective and time horizon. This editorial defines what is meant by direct treatment disutility (DTD) and describes why it could be an important harm that those designing model-based evaluations should consider. Some existing estimates of DTD identified from the current literature are summarised in terms of the methods used to elicit the values and the size of the estimated DTD. Model-based studies that include DTDs are also summarised. It was found that the values used within model-based economic evaluations (ranging from 0.00384 to 0.02) were typically smaller than the directly elicited values from the existing literature (0-0.033). Yet even with conservative estimates of DTDs, cost-effectiveness results were sensitive to their inclusion. The editorial concludes by discussing future methodological and empirical research needed to estimate more robust DTD values. [ABSTRACT FROM AUTHOR]

Objectives: This study provides the results of a cost-effectiveness analysis of levetiracetam as an adjunctive treatment for refractory epilepsy from the Canadian Ministry of Health perspective. The main objective is to estimate the expected cost-effectiveness ratio expressed as the incremental cost per seizure-free day gained when using levetiracetam. In addition, this study examines the potential savings that might result by reducing the number of surgical evaluations and surgery when using levetiracetam.Methods: A 1-year dose escalation decision-tree model comparing levetiracetam plus standard therapy with standard therapy alone was designed in order to combine probability, resource use and unit cost data (1999 Canadian dollars [$Can]). The short-term outcomes were derived from three phase III randomised, double-blind, placebo-controlled trials performed in 904 patients, aged 16-70 years, with at least 1 year history of epilepsy, two to four partial seizures per month, and receiving a maximum of two classic antiepileptic drugs.Results: The average gain in seizure-free days attributed to levetiracetam was 19 days per patient per year and the incremental cost-effectiveness ratio (ICER) for levetiracetam add-on in the base-case scenario was $Can80.7 per seizure-free day gained per patient per year. Moreover, when surgical investigation and surgery are considered in the model, the use of levetiracetam may be dominant, with substantial savings to the overall healthcare budget. All univariate sensitivity analyses show that the model was robust to the assumptions made.Conclusions: The economic analysis presented in this paper suggests, given a wide range of assumptions, that the increased cost of treating patients (with refractory epilepsy) with levetiracetam may be partially offset by a reduction in other direct medical costs (from the Canadian Ministry of Health perspective), as a consequence of an increase in the number of seizure-free days. Moreover, potential cost savings may be foreseen when it is assumed that levetiracetam may reduce the number of candidates for surgical evaluation and surgery through a reduction of seizure frequency. [ABSTRACT FROM AUTHOR]

In schizophrenia, modelling techniques may be needed to estimate the long-term costs and effects of new interventions. However, it seems that a simple direct link between symptoms and costs does not exist. Decisions about whether a patient will be hospitalized or admitted to a different healthcare setting are based not only on symptoms but also on social and environmental factors. This paper describes the development of a model to assess the dependencies between a broad range of parameters in the treatment of schizophrenia. In particular, the model attempts to incorporate social and environmental factors into the decision-making process for the prescription of new drugs to patients. The model was used to analyse the potential benefits of improving compliance with medication by 20% in patients in the UK. A discrete event simulation (DES) model was developed, to describe a cohort of schizophrenia patients with multiple psychotic episodes. The model takes into account the patient's sex, disease severity, potential risk of harm to self and society, and social and environmental factors. Other variables that change over time include the number of psychiatric consultations, the presence of psychotic episodes, symptoms, treatments, compliance, side-effects, the lack of ability to take care of him/herself, care setting and risk of harm. Outcomes are costs, psychotic episodes and symptoms. Univariate and multivariate sensitivity analyses were performed. Direct medical costs were considered (year of costing 2002), applying a 6.0% discount rate for costs and a 1.5% discount rate for outcome. The timeframe of the model is 5 years. When 50% of the decisions about the patient care setting are based on symptoms, a 20% increase in compliance was estimated to save 16,147 pounds and to avoid 0.55 psychotic episodes per patient over 5 years. Sensitivity analysis showed that the costs savings associated with increased compliance are robust over a range of variations in parameters. DES offers a flexible structure for modelling a disease, taking into account how a patient's history affects the course of the disease over time. This approach is particularly pertinent to schizophrenia, in which treatment decisions are complex. The model shows that better compliance increases the time between relapses, decreases the symptom score, and reduces the requirement for treatment in an intensive patient care setting, leading to cost savings. The extent of the cost savings depends on the relative importance of symptoms and of social and environmental factors in these decisions. [ABSTRACT FROM AUTHOR]

Introduction: Health economics models are typically built in Microsoft Excel® owing to its wide familiarity, accessibility and perceived transparency. However, given the increasingly rapid and analytically complex decision-making needs of both the pharmaceutical industry and the field of health economics and outcomes research (HEOR), the demands of cost-effectiveness analyses may be better met by the programming language R.Objective: This case study provides an explicit comparison between Excel and R for contemporary cost-effectiveness analysis.Methods: We constructed duplicate cost-effectiveness models using Excel and R (with a user interface built using the Shiny package) to address a hypothetical case study typical of contemporary health technology assessment.Results: We compared R and Excel versions of the same model design to determine the advantages and limitations of the modelling platforms in terms of (i) analytical capability, (ii) data safety, (iii) building considerations, (iv) usability for technical and non-technical users and (v) model adaptability.Conclusions: The findings of this explicit comparison are used to produce recommendations for when R might be more suitable than Excel in contemporary cost-effectiveness analyses. We conclude that selection of appropriate modelling software needs to consider case-by-case modelling requirements, particularly (i) intended audience, (ii) complexity of analysis, (iii) nature and frequency of updates and (iv) anticipated model run time. [ABSTRACT FROM AUTHOR]

Background: Clinical trials often report intervention efficacy in terms of the reduction in all-cause mortality between the treatment and control arms (i.e., an overall hazard ratio [oHR]) instead of the reduction in disease-specific mortality (i.e., a disease-specific hazard ratio [dsHR]). Using oHR to reduce all-cause mortality beyond the time horizon of the trial may introduce bias if the relative proportion of other-cause mortality increases with age. We sought to quantify this oHR extrapolation bias and propose a new approach to overcome this bias.Methods: We simulated a hypothetical cohort of patients with a generic disease that increased background mortality by a constant additive disease-specific rate. We quantified the bias in terms of the percentage change in life expectancy gains with the intervention under an oHR compared with a dsHR approach as a function of the cohort start age, the disease-specific mortality rate, dsHR, and the duration of the intervention's effect. We then quantified the bias in a cost-effectiveness analysis (CEA) of implantable cardioverter-defibrillators based on efficacy estimates from a clinical trial.Results: For a cohort of 50-year-old patients with a disease-specific mortality of 0.05, a dsHR of 0.5, a calculated oHR of 0.55, and a lifetime duration of effect, the bias was 28%. We varied these key parameters over wide ranges and the resulting bias ranged between 3 and 140%. In the CEA, the use of oHR as the intervention's effectiveness overestimated quality-adjusted life expectancy by 9% and costs by 3%, biasing the incremental cost-effectiveness ratio by - 6%.Conclusions: The use of an oHR approach to model the intervention's effectiveness beyond the time horizon of the trial overestimates its benefits. In CEAs, this bias could decrease the cost of a QALY, overestimating interventions' cost effectiveness. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background and Objective: The extrapolation of estimated hazard functions can be an important part of cost-effectiveness analyses. Given limited follow-up time in the sample data, it may be expected that the uncertainty in estimates of hazards increases the further into the future they are extrapolated. The objective of this study was to illustrate how the choice of parametric survival model impacts on estimates of uncertainty about extrapolated hazard functions and lifetime mean survival.Methods: We examined seven commonly used parametric survival models and described analytical expressions and approximation methods (delta and multivariate normal) for estimating uncertainty. We illustrate the multivariate normal method using case studies based on four representative hypothetical datasets reflecting hazard functions commonly encountered in clinical practice (constant, increasing, decreasing, or unimodal), along with a hypothetical cost-effectiveness analysis.Results: Depending on the survival model chosen, the uncertainty in extrapolated hazard functions could be constant, increasing or decreasing over time for the case studies. Estimates of uncertainty in mean survival showed a large variation (up to sevenfold) for each case study. The magnitude of uncertainty in estimates of cost effectiveness, as measured using the incremental cost per quality-adjusted life-year gained, varied threefold across plausible models. Differences in estimates of uncertainty were observed even when models provided near-identical point estimates.Conclusions: Survival model choice can have a significant impact on estimates of uncertainty of extrapolated hazard functions, mean survival and cost effectiveness, even when point estimates were similar. We provide good practice recommendations for analysts and decision makers, emphasizing the importance of considering the plausibility of estimates of uncertainty in the extrapolated period as a complementary part of the model selection process. [ABSTRACT FROM AUTHOR]

Background: During the period from 1999 to 2016, more than 350,000 Americans died from overdoses related to the use of prescription opioids. To the extent that supply is directly related to overprescribing, policy interventions aimed at changing prescriber behavior, such as the recent Centers for Disease Control and Prevention guideline, are clearly warranted. Although these could plausibly reduce the prevalence of opioid overuse and dependency, little is known about their economic and health-related impacts.Objective: The aim of this study was to quantify the efficacy of a policy intervention aimed at reducing the length of initial opioid prescriptions.Study Design and Methods: A Markov decision process model was fitted on a retrospective cohort of 827,265 patients, and patient cost and health trajectories were simulated over a 24-month period. The model's parameters were based on patients who received short (≤ 3 days) or long (> 7 days) initial opioid prescriptions, matched using propensity score methods.Study Population: All active-duty US Army soldiers from 2011 to 2014; the data contained detailed medical and administrative information on over 11 million soldier-months corresponding to 827,265 individual soldiers.Main Outcome Measure: Overall costs of a policy change, quality-adjusted life-years (QALYs) gained, and $/QALY gained.Results: Over a 2-year horizon, a reassignment of 10,000 patients to short initial duration would generate a cost saving in the vicinity of $3.1 million (excluding program costs), and would also lead to an estimated 4451 additional opioid-free months, i.e. months without any opioid prescriptions.Conclusion: The analysis found that efforts to change prescriber behavior can be cost effective, and further studies into the implementation of such policies are warranted. [ABSTRACT FROM AUTHOR]

Background: Vedolizumab (VDZ) was approved by the Japanese Ministry of Health, Labor and Welfare in 2018 for the treatment of patients with moderate-to-severe active ulcerative colitis (UC). The comparative cost-effectiveness of VDZ compared with other biologics is unknown in Japan. This information could be useful for decision makers at the time of repricing biologics for the treatment of patients with moderate-to-severe UC.Objective: The aim was to assess the cost-effectiveness of VDZ versus other branded biologics for the treatment of patients with moderate-to-severe UC who were anti-tumor necrosis factor (TNF)-naïve, from the Japanese public healthcare payer perspective.Methods: A hybrid decision tree/Markov model was developed to predict the number of patients who achieved response and remission at the end of the induction phase and sustained it during the maintenance phase, translating this into quality-adjusted life-years (QALYs) and costs. Treatment-related adverse events, discontinuation and surgery, and their impact on QALYs and costs were also modeled. A systematic literature review and network meta-analysis were conducted to estimate the comparative efficacy of each treatment versus placebo. Rates of adverse events, surgery, surgery complications, and utilities were from the literature. Costs (2018 Japanese yen) were obtained from the Japanese National Health Insurance drug price list and medical fee table and local claims databases. Clinical and economic outcomes were projected over a lifetime and discounted at 2% annually.Results: Over a lifetime, VDZ yielded greater QALYs and cost savings compared with golimumab and was cost-effective compared with adalimumab and infliximab (incremental cost-effectiveness ratios ¥4,821,940 and ¥4,687,692, respectively). Deterministic and probabilistic analyses supported the robustness of the findings in the base-case analysis, indicating that VDZ was either dominant or cost-effective in most scenarios and replications. The main limitations of this analysis include excluding tofacitinib and infliximab biosimilar as comparators, health-state utility estimates were obtained from population studies in the United Kingdom, and the impact of subsequent (i.e., second-line) biologic treatment was not evaluated.Conclusion: Our analysis suggests that VDZ is dominant or cost-effective compared with other branded biologics for the treatment of anti-TNF-naïve patients with moderate-to-severe UC in Japan. [ABSTRACT FROM AUTHOR]

Objective: The nature of model-based cost-effectiveness analysis can lead to disputes in the scientific community. We propose an iterative and collaborative approach to model development by presenting a flexible open-source simulation model for rheumatoid arthritis (RA), accessible to both technical and non-technical end-users.Methods: The RA model is a discrete-time individual patient simulation with 6-month cycles. Model input parameters were estimated based on currently available evidence and treatment effects were obtained with Bayesian network meta-analysis techniques. The model contains 384 possible model structures informed by previously published models. The model consists of the following components: (i) modifiable R and C++ source code available in a GitHub repository; (ii) an R package to run the model for custom analyses; (iii) detailed model documentation; (iv) a web-based user interface for full control over the model without the need to be well-versed in the programming languages; and (v) a general audience web-application allowing those who are not experts in modeling or health economics to interact with the model and contribute to value assessment discussions.Results: A primary function of the initial version of RA model is to help understand and quantify the impact of parameter uncertainty (with probabilistic sensitivity analysis), structural uncertainty (with multiple competing model structures), the decision framework (cost-effectiveness analysis or multi-criteria decision analysis), and perspective (healthcare or limited societal) on estimates of value.Conclusion: In order for a decision model to remain relevant over time it needs to evolve along with its supporting body of clinical evidence and scientific insight. Multiple clinical and methodological experts can modify or contribute to the RA model at any time due to its open-source nature. [ABSTRACT FROM AUTHOR]

Background and Objectives: In economic evaluations in oncology, adjusted survival should be generated if imbalances in prognostic/predictive factors across treatment arms are present. To date, no formal guidance has been developed regarding how such adjustments should be made. We compared various covariate-adjusted survival modeling approaches, as applied to the ENDEAVOR trial in multiple myeloma that assessed carfilzomib plus dexamethasone (Cd) versus bortezomib plus dexamethasone (Vd).Methods: Overall survival (OS) data and baseline characteristics were used for a subgroup (bortezomib-naïve/one prior therapy). Four adjusted survival modeling approaches were compared: propensity score weighting followed by fitting a Weibull model to the two arms of the balanced data (weighted data approach); fitting a multiple Weibull regression model including prognostic/predictive covariates to the two arms to predict survival using the mean value of each covariate and using the average of patient-specific survival predictions; and applying an adjusted hazard ratio (HR) derived from a Cox proportional hazard model to the baseline risk estimated for Vd.Results: The mean OS estimated by the weighted data approach was 6.85 years (95% confidence interval [CI] 4.62-10.70) for Cd, 4.68 years (95% CI 3.46-6.74) for Vd, and 2.17 years (95% CI 0.18-5.06) for the difference. Although other approaches estimated similar differences, using the mean value of covariates appeared to yield skewed survival estimates (mean OS was 7.65 years for Cd and 5.40 years for Vd), using the average of individual predictions had limited external validity (implausible long-term OS predictions with > 10% of the Vd population alive after 30 years), and using the adjusted HR approach overestimated uncertainty (difference in mean OS was 2.03, 95% CI - 0.17 to 6.19).Conclusions: Adjusted survival modeling based on weighted or matched data approaches provides a flexible and robust method to correct for covariate imbalances in economic evaluations. The conclusions of our study may be generalizable to other settings.Trial Registration: ClinicalTrials.gov identifier NCT01568866 (ENDEAVOR trial). [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to develop an EQ-5D-5L value set reflecting the health preferences of the Malaysian adult population.Methods: Respondents were sampled with quotas for urbanicity, gender, age, and ethnicity to ensure representativeness of the Malaysian population. The study was conducted using a standardized protocol involving the EuroQol Valuation Technology (EQ-VT) computer-assisted interview system. Respondents were administered ten composite time trade-off (C-TTO) tasks and seven discrete choice experiment (DCE) tasks. Both linear main effects and constrained non-linear regression models of C-TTO-only data and hybrid models combining C-TTO and DCE data were explored to determine an efficient and informative model for value set prediction.Results: Data from 1125 respondents representative of the Malaysian population were included in the analysis. Logical consistency was present in all models tested. Using cross-validation, eight-parameter models for C-TTO only and C-TTO + DCE hybrid data displayed greater out-of-sample predictive accuracy than their 20-parameter, main-effect counterparts. The hybrid eight-parameter model was chosen to represent the Malaysian value set, as it displayed greater out-of-sample predictive accuracy over C-TTO data than the C-TTO-only model, and produced more precise estimates. The estimated value set ranged from - 0.442 to 1.Conclusions: The constrained eight-parameter hybrid model demonstrated the best potential in representing the Malaysian value set. The presence of the Malaysian EQ-5D-5L value set will facilitate its application in research and health technology assessment activities. [ABSTRACT FROM AUTHOR]

Background: Cystic fibrosis (CF) negatively impacts upon health-related quality of life and survival. Adherence to nebulised treatments is low; improving adherence is hypothesised to reduce rates of exacerbation requiring intravenous antibiotics and lung function decline.Objective: A state transition model was developed to assess the cost effectiveness of an intervention aimed at increasing patient adherence to nebulised and inhaled antibiotics compared with current CF care, in advance of the forthcoming CFHealthHub randomised controlled trial (RCT).Methods: The model estimated the costs and health outcomes for each option from the perspective of the UK National Health Service and Personal Social Services over a lifetime horizon. Health gains were valued in terms of quality-adjusted life-years (QALYs) gained. Forced expiratory volume in 1 second (FEV1) trajectories were predicted over three lung function strata: (1) FEV1 ≥70%, (2) FEV1 40-69% and (3) FEV1 <40%. Additional states were included to represent 'post-lung transplantation' and 'dead'. The model was populated using CF Registry data, literature and expert opinion. Costs were presented at 2016 values. Uncertainty was assessed using deterministic and probabilistic sensitivity analyses.Results: If effective, the adherence intervention is expected to produce an additional 0.19 QALYs and cost savings of £64,078 per patient. Across all analyses, the intervention dominated current care. Over a 5-year period, the intervention is expected to generate cost savings of £49.5 million for the estimated 2979 patients with CF with Pseudomonas aeruginosa currently aged ≥16 years in the UK. If applied to a broader population of adult patients with CF receiving any nebulised therapy, the expected savings could be considerably greater.Conclusions: If effective, the adherence intervention is expected to produce additional health gains at a lower cost than current CF care. However, the economic analysis should be revisited upon completion of the full RCT. More generally, the analysis suggests that considerable gains could be accrued through the implementation of adherence interventions that shift care from expensive hospital-based rescue to community-based prevention. [ABSTRACT FROM AUTHOR]

Background: Ulcerative colitis (UC) is the most common form of inflammatory bowel disease in the UK. Medical management aims to induce and maintain remission and to avoid complications and the necessity for surgical intervention. Colectomy removes the source of inflammation but is associated with morbidity and mortality. Newer anti-tumour necrosis factor (TNF)-α therapies may improve medical outcomes, albeit at an increased cost.Objective: Our objective was to assess the incremental cost effectiveness of infliximab, adalimumab and golimumab versus conventional therapy and surgery from a National Health Service (NHS) and Personal Social Services (PSS) perspective over a lifetime horizon.Methods: A Markov model was developed with health states defined according to whether the patient is alive or dead, current treatments received, history of colectomy and level of disease control. Transition probabilities were derived from network meta-analyses (NMAs) of trials of anti-TNF-α agents in the moderate-to-severe UC population. Health utilities, colectomy rates, surgical complications and resource use estimates were derived from literature. Unit costs were drawn from standard costing sources and literature and were valued at year 2013/2014 values.Results: For patients in whom surgery is an option, colectomy is expected to dominate all medical treatment options. For patients in whom colectomy is not an option, infliximab and golimumab are expected to be ruled out due to dominance, whilst the incremental cost-effectiveness ratio (ICER) for adalimumab versus conventional treatment is expected to be approximately £50,278 per quality-adjusted life-year (QALY) gained.Conclusions: Based on the NMAs, the ICERs for anti-TNF-α therapy versus conventional treatment or surgery are expected to be at best, in excess of £50,000 per QALY gained. The cost effectiveness of withdrawing biologic therapy upon remission and re-treating relapse is unknown. [ABSTRACT FROM AUTHOR]

Background: Trivalent influenza vaccines encompass one influenza B lineage; however, predictions have been unreliable on which of two antigenically distinct circulating lineages will dominate. Quadrivalent seasonal influenza vaccines contain strains from both lineages. This analysis assesses the cost effectiveness of switching from trivalent inactivated influenza vaccination (TIV) in Finland to quadrivalent vaccination, using inactivated (QIV) or live-attenuated (Q-LAIV) vaccines.Methods: A transmission model simulated the dynamics of influenza infection while accounting for indirect (herd) protection. Prior distributions for key transmission parameters were repeatedly sampled and simulations that fitted the available information on influenza in Finland were recorded. The resulting posterior parameter distributions were used in a probabilistic sensitivity analysis in which economic parameters were sampled, simultaneously encompassing uncertainty in the transmission and economic parameters. The cost effectiveness of a range of trivalent and quadrivalent vaccine policies over a 20-year time horizon was assessed from both a societal and payer perspective in 2014 Euros.Results: The simulated temporal incidence pattern of symptomatic infections corresponded well with case surveillance data. A switch from the current TIV to Q-LAIV in children (2 to <18 years) and to QIV in other ages was estimated to annually avert approximately 76,100 symptomatic infections (95 % range 36,700-146,700), 11,500 primary care consultations (6100-20,000), 540 hospitalisations (240-1180), and 72 deaths (32-160), and was cost-saving relative to TIV (€374 million averted [€161-€752], in 2014 Euros, discounted at 3 %). This scenario had the highest probability of being the most cost-effective scenario considered.Conclusions: This analysis demonstrates that quadrivalent vaccination is expected to be highly cost effective, reducing the burden of influenza-related disease. [ABSTRACT FROM AUTHOR]

Background: Discrete choice experiments (DCEs) have been proposed as a method to estimate utility weights for health states within utility instruments. However, the most appropriate method to anchor the utility values on the full health to dead quality-adjusted life year (QALY) scale remains uncertain. We test four approaches to anchoring in which dead is valued at zero and full health at one.Methods: We use data from two DCEs valuing EQ-5D-3L and EQ-5D-5L health states, which presented pairs of health profiles with an associated duration, and a dead option. The approaches to anchoring the results on the required scale were (1) using only preferences between non-dead health profiles; (2) including the dead data, treating it as a health profile with zero duration; (3) explicitly modelling both duration and dead; and (4) using the preferences regarding the dead health state as an external anchor subsequent to the estimation of approach 1.Results: All approaches lead to differences in the scale of utility decrements, but not the ranking of EQ-5D health states. The models differ in their ability to predict preferences around dead health states, and the characteristics of the value sets in terms of their range and the proportion of states valued as worse than dead.Discussion: Appropriate anchoring of DCEs with or without complementary time trade-off (TTO) data remains unresolved, and the method chosen will impact on health resource allocation decision making employing the value sets. [ABSTRACT FROM AUTHOR]

Background: A trade-off exists between building confidence in health-economic (HE) decision models and the use of scarce resources. We aimed to create a practical tool providing model users with a structured view into the validation status of HE decision models, to address this trade-off.Methods: A Delphi panel was organized, and was completed by a workshop during an international conference. The proposed tool was constructed iteratively based on comments from, and the discussion amongst, panellists. During the Delphi process, comments were solicited on the importance and feasibility of possible validation techniques for modellers, their relevance for decision makers, and the overall structure and formulation in the tool.Results: The panel consisted of 47 experts in HE modelling and HE decision making from various professional and international backgrounds. In addition, 50 discussants actively engaged in the discussion at the conference workshop and returned 19 questionnaires with additional comments. The final version consists of 13 items covering all relevant aspects of HE decision models: the conceptual model, the input data, the implemented software program, and the model outcomes.Conclusions: Assessment of the Validation Status of Health-Economic decision models (AdViSHE) is a validation-assessment tool in which model developers report in a systematic way both on validation efforts performed and on their outcomes. Subsequently, model users can establish whether confidence in the model is justified or whether additional validation efforts should be undertaken. In this way, AdViSHE enhances transparency of the validation status of HE models and supports efficient model validation. [ABSTRACT FROM AUTHOR]

Introduction: Health economic models are increasingly important in funding decisions but most are based on data, which may therefore not represent the general population. We sought to establish the potential of real-world data available within the Clinical Practice Research Datalink (CPRD) and linked Hospital Episode Statistics (HES) to determine comprehensive healthcare utilisation and costs as input variables for economic modelling.Methods: A cohort of patients with irritable bowel syndrome (IBS) who first saw a gastroenterologist in 2008 or 2009, and with 3 years of data before and after their appointment, was created in the CPRD. Primary care, outpatient, inpatient, prescription and colonoscopy data were extracted from the linked CPRD and HES. The appropriate cost to the NHS was attached to each event. Total and stratified annual healthcare utilisation rates and costs were calculated before and after the gastroenterology appointment with distribution parameters. Absolute differences were calculated with 95% confidence intervals.Results: Total annual healthcare costs over 3 years increase by £935 (95% CI £928-941) following a gastroenterology appointment for IBS. We derived utilisation and cost data with parameter distributions stratified by demographics and time. Women, older patients, smokers and patients with greater comorbidity utilised more healthcare resources, which generated higher costs.Conclusions: These linked datasets provide comprehensive primary and secondary care data for large numbers of patients, which allows stratification of outcomes. It is possible to derive input parameters appropriate for economic models and their distributions directly from the population of interest. [ABSTRACT FROM AUTHOR]

Commonly used decision-analytic models for cost-effectiveness analysis simulate time in discrete steps. Use of discrete-time steps can introduce errors when calculating cumulative outcomes such as costs and quality-adjusted life-years. There are a number of myths or misconceptions concerning how to correct these errors and the need to do so. This tutorial shows that, by neglecting to apply within-cycle (sometimes referred to as half-cycle or continuity) correction methods to the results of discrete-time models, the analyst may arrive at the wrong recommendation regarding the use of a technology. We show that the standard half-cycle correction method results in the same cumulative outcome as the trapezoidal rule and life-table method. However, the trapezoidal rule has the added advantage of applying the correction at each cycle, not just the initial and final cycle. We further show that the Simpson's 1/3 rule is more accurate than the trapezoidal rule. We recommend using the Simpson's 1/3 rule in the base-case analysis and, if needed, showing the results with other methods in the sensitivity analysis. We also demonstrate that both the trapezoidal and Simpson's rules can easily be implemented in commonly used software. [ABSTRACT FROM AUTHOR]

Ireland is one of the few countries worldwide to have an explicit cost-effectiveness threshold. In 2012, an agreement between government and the pharmaceutical industry that provided substantial savings on existing medications set the threshold at €45,000/quality-adjusted life-year (QALY). This replaced a previously unofficial threshold of €20,000/QALY. According to the agreement, drugs within the threshold will be granted reimbursement, whereas those exceeding it may still be approved following further negotiation. A number of drugs far exceeding the threshold have been approved recently. The agreement only applies to pharmaceuticals. There are four reasons for concern regarding Ireland's threshold. The absence of an explicit threshold for non-drug interventions leaves it unclear if there is parity in willingness to pay across all interventions. As the threshold resembles a price floor rather than a ceiling, in principle it only offers a weak barrier to cost-ineffective interventions. It has no empirical basis. Finally, it is probably too high given recent estimates of a threshold for the UK based on the cost effectiveness of services forgone of approximately £13,000/QALY. An excessive threshold risks causing the Irish health system unintended harm. The lack of an empirically informed threshold means the policy recommendations of cost-effectiveness analysis cannot be considered as fully evidence- based rational rationing. Policy makers should consider these issues and recent Irish legislation that defined cost effectiveness in terms of the opportunity cost of services forgone when choosing what threshold to apply once the current industry agreement expires at the end of 2015 [ABSTRACT FROM AUTHOR]

Background: Oseltamivir is effective in the treatment of influenza. Utilisation in The Netherlands is limited, but increasing.Objective: To estimate the cost effectiveness of oseltamivir treatment (vs symptom relief only) for patients with influenza-like illness (ILI) who are at increased risk for serious complications of influenza.Methods: A cost-effectiveness analysis was used, building on a previously developed model (decision tree) that was applied for evaluating influenza vaccination and pandemic preparedness plans. Three patient subgroups were assessed (elderly patients [aged > or = 65 years] without chronic disease, elderly patients with chronic disease, and chronically ill, non-elderly patients). Inputs for the model were taken from various sources including a meta-analysis. A societal perspective was adopted and costs were expressed in euro per life-year gained (year 2003 values). Life-years lost were discounted at 4% in accordance with Dutch guidelines. Deterministic and probabilistic sensitivity analyses were employed to assess the robustness of the results.Results: For chronically ill patients with ILI, visits to the GP for oseltamivir treatment were cost saving. For non-chronically ill elderly patients, incremental cost-effectiveness was estimated at 1759 euros per life-year gained. Cost savings and favourable cost effectiveness were robust in a deterministic and stochastic sensitivity analysis.Conclusion: Our model-based analysis suggests that at-risk people presenting with ILI to a GP could be offered oseltamivir at favourable cost effectiveness or even cost savings in the Dutch setting compared with symptom relief with analgesics only. [ABSTRACT FROM AUTHOR]

A comprehensive, multinational literature search was conducted of all articles published from 1993 to 2003 regarding the cost effectiveness of antidepressant drugs, with special emphasis on comparing third-generation antidepressants (TGAs) with tricyclic antidepressants (TCAs) and selective serotonin reuptake inhibitors (SSRIs). Information from the collected articles was entered into a database and then analysed to assess the different approaches to cost effectiveness comparisons for the various classes of antidepressants. Factors examined included direct and indirect costs, treatment endpoints, healthcare cost burden and productivity gains for patients successfully treated for depression. Most model-based studies published between 1993 and 2003 supported the cost effectiveness of TGAs compared with TCAs or SSRIs. While the purchase price of TGAs may be greater, cost savings in terms of direct and indirect costs were realised because of the reduced adverse effects of TGAs and subsequent improved patient compliance. Studies based on patient level cost data, however, were less conclusive about the economic benefits of TGAs compared with SSRIs or TCAs. While it may be premature to conclude that TGAs have a significant net economic benefit compared with other antidepressant classes, prescribers and payers may find it helpful when choosing antidepressants for depressed patients to consider that the higher drug prices for TGAs may be offset by savings, in terms of their greater compliance and resultant therapeutic success rates compared with TCAs or SSRIs. Additional research is needed to clarify how cost effectiveness is assessed in different patient populations, such as geriatric patients--who commonly have more co-morbidities and higher total healthcare costs than other patient populations. [ABSTRACT FROM AUTHOR]

Objective: To quantify direct costs of medication and cost of illness (according to functional capacity) for patients with rheumatoid arthritis (RA) in Germany, allowing further use in a health economic evaluation of sequential therapy with disease-modifying antirheumatic drugs (DMARDs) in specialised, i.e. rheumatological, care in Germany.Design and Setting: The analysis was conducted from the societal perspective in Germany using a modelling approach, which was based on secondary analysis of existing data and on data from a sample of 583 patients from the German rheumatological database of 1998. Functional capacity was defined by the Hannover Functional Ability Questionnaire (HFAQ) scores. Costs were calculated from resources utilised and patients' work capacity. Direct costs consisted of outpatient medical services, inpatient treatment, long-term care and rehabilitation treatment. Indirect costs incurred by sick leave and premature retirement were quantified according to the human-capital approach.Main Outcome Measures and Results: Average total direct costs (year 1998-2001 values) per patient per year for continuous treatment with the selected DMARDs comprising costs for drugs, monitoring and treatment of adverse drug reactions (ADRs) were highest for intramuscular gold (sodium aurothiomalate) [euro 2106 (euro 1 approximately equal to $US 0.91; average of the period from 2000 through 2001)] followed by leflunomide (euro 2010), azathioprine (euro 1878), sulfasalazine (euro 1190), oral methotrexate (euro 708), and lowest for the antimalarials chloroquine/hydroxychloroquine (euro 684). There were additional yearly costs for RA-related non-DMARD medication of euro 554 per patient, including management of ADRs. Mean cost of illness (year 1998 values) excluding medication cost amounted to euro 17,868 per RA patient per year. Annual costs increased with increasing disability, i.e. decreasing functional capacity, of RA patients from euro 6029 per patient with more than 94% of functional capacity to euro 28,509 per patient with <20% of functional capacity. In general, there was a predominance of indirect costs in each of the categories of functional capacity, ranging between 74% and 87% of total (direct and indirect) annual costs per RA patient. Annual direct costs increased from euro 811 to euro 7438 per patient with increasing disability. Inpatient treatment was the predominant component of direct costs. Patients in the worst category (<20%) of function experienced hospital costs that were 6.5 times higher than those of patients in the best category (>94%).Conclusions: On the basis of the data presented it can be concluded that the results of this investigation are typical for patients in rheumatological care in Germany and can therefore be used in a health economic analysis of different DMARD sequences aimed at changing disease progression over time. [ABSTRACT FROM AUTHOR]

Objective: To estimate the 3-year incremental cost effectiveness and cost utility of introducing leflunomide into sequential therapy, consisting of the most frequently used disease-modifying antirheumatic drugs (DMARDs), for patients with rheumatoid arthritis in specialised, i.e. rheumatological, care in Germany.Design and Setting: The analysis was conducted from the societal perspective in Germany using an existing 3-year simulation model, which was adapted to the German healthcare system after secondary analysis of relevant publications and data. DMARD sequences including leflunomide were compared with those excluding leflunomide. Costs comprised direct costs incurred by treatment and indirect costs incurred by loss of productivity (sick leave and premature retirement) of rheumatoid arthritis patients. Effectiveness parameters were given by response years gained (RYGs) according to the American College of Rheumatology (ACR) criteria for 20%, 50% and 70% improvement (ACR20/50/70RYGs) and by QALYs gained (QALYGs). Costs, effects and QALYs were discounted by 5% per annum. In the base-case analysis, average values of costs, response years and QALYs were applied. Costs were in 1998-2001 values (euro 1 approximately equal to $US 0.91, average of the period from the year 2000 through 2001).Main Outcome Measures and Results: After 3 years, adding leflunomide was less costly and more effective than the strategy excluding leflunomide when total (direct and indirect) costs were considered. There were savings of euro 271,777 and 8.1, 4.3, 5.1 and 4.9 ACR20RYGs, ACR50RYGs, ACR70RYGs and QALYGs per 100 patients, respectively, obtained through adding leflunomide. Focusing on direct costs, adding leflunomide was more costly and more effective compared with excluding leflunomide, with an incremental cost effectiveness of euro 5004 per ACR20RYG, euro 9535 per ACR50RYG, euro 7996 per ACR70RYG, and an incremental cost utility of euro8301 per QALYG, after 3 years. The robustness of the results was shown in comprehensive sensitivity analyses. In the analysis of extremes, different combinations of the limits of cost, effectiveness and utility parameters were investigated. Adding leflunomide to sequential DMARD therapy remained dominant in 79% of the possible cases, i.e. was less costly and more effective than the strategy excluding leflunomide. Focusing on direct costs, adding leflunomide became dominant in 29% and remained more costly and more effective in 50% of possible cases.Conclusions: Our analysis suggests, with its underlying data and assumptions, that having leflunomide as an additional option in a DMARD treatment sequence extends the time patients benefit from DMARD therapy at reasonable additional direct costs. Adding leflunomide may even be cost saving when total (direct and indirect) costs are considered. As data on DMARD effectiveness were extracted from the results of clinical trials, real-world data from observational studies would be needed to corroborate the findings of the present analysis. [ABSTRACT FROM AUTHOR]

Background and Objective: Asthma is a chronic-episodic disease characterised by acute, symptomatic episodes of varying severity. We developed a Markov model that can be used to estimate the cost effectiveness of alternative asthma treatments. Because of the costs they incur, asthma exacerbations ('attacks') requiring intervention by a healthcare professional were a central consideration in the development of the model.Methods: Treatment success was assessed as asthma control, a composite measure based on goals defined in world-wide asthma management guidelines and in terms of quality-adjusted life-years (QALYs). The data from which the transition probabilities were derived came from patients with asthma who received either salmeterol/fluticasone propionate combination (SFC) 50/100microg or fluticasone propionate (FP) 100microg, administered twice daily via an inhaler, in a 12-week, randomised, double-blind, clinical trial. Costs were estimated from resource profiles defined for each of the model states. A key aspect of the model was the use of probabilistic sensitivity analysis techniques to examine the uncertainty in the cost-effectiveness results. Distributions were fitted to transition probabilities and to cost input parameters and values were sampled at random from these distributions using a second order Monte Carlo simulation technique. This produced a distribution for incremental cost effectiveness that was employed to construct 95% uncertainty intervals and to construct cost effectiveness acceptability curves.Results: In this analysis, the model was run over a 12-week period using transition probabilities derived from the trial data. The results showed that treatment with SFC resulted in a higher proportion of successfully controlled weeks per patient than treatment with FP (66 vs 47%), and higher mean weekly direct asthma management costs (pound sterling 15.77 vs pound sterling 11.83; 2000 values). The average incremental cost per successfully controlled week with SFC was pound sterling 20.83. Probabilistic sensitivity analysis showed that the 95% uncertainty intervals for the incremental cost-effectiveness ratio was - pound sterling 64.94 to pound sterling 112.66. In approximately 25% of cases, SFC was dominant (more effective and less costly), but in the remaining cases, it was both more effective and more costly. It was shown that if decision makers are willing to pay approximately pound sterling 45 for an additional successfully controlled week, SFC will be the more cost-effective strategy in this patient population for 80% of the time.Conclusions: This is one of the first decision-analytic models of asthma to incorporate probabilistic sensitivity analysis techniques to explore uncertainty. The model's flexible yet standardised framework permits the cost effectiveness of alternative asthma management strategies in different healthcare settings to be established. [ABSTRACT FROM AUTHOR]

Objective: This work carries out an empirical evaluation of the impact of the main mechanism for regulating the prices of medicines in the UK [the Pharmaceutical Price Regulation Scheme (PPRS)] on a variety of pharmaceutical price indices. The article also discusses to what extent the rate-of-return (ROR) regulation has encouraged UK-based pharmaceutical firms with patented products to diversify into markets in which products face strong competition.Design and Setting: The article starts with some background on the PPRS and the way firms behave under ROR constraints. The article goes on to explain the cointegration methods used and the results obtained. Finally, it offers some discussion and some conclusions related to the evidence and the incentives of UK pharmaceutical firms under the PPRS constraint.Main Outcome Measures and Results: The results obtained show that, according to only some cointegration tests carried out, the aggregate price indices of medical preparations and the price index of some therapeutic areas are cointegrated with the time series of ROR caps between 1980 and 1994. Additionally, a 1% change in the ROR cap has produced only a 0.15% change on the aggregate medicine price index.Conclusions: These results suggest that changes in the ROR cap have had little or no impact on medicine prices and that, at best, the impact of the ROR has also differed significantly across major therapeutic areas. Finally, it is argues that the UK regulation of prices might have encouraged firms to diversify into competitive medicine-regulated markets and into uncontrolled markets. [ABSTRACT FROM AUTHOR]

Objective: Data from the Acute Infarction Ramipril Efficacy (AIRE) study were used in a cost-effectiveness analysis to determine the incremental cost per life-year gained (LYG) when the ACE inhibitor ramipril was added to conventional treatment in patients with heart failure after acute myocardial infarction. In the AIRE trial, the addition of ramipril significantly lowered rates of total mortality and rehospitalisation due to heart failure.Design and Setting: The cost-effectiveness analysis was conducted from the perspective of the Statutory Health Insurance (SHI) provider in Germany. A modelling approach was used which was based on secondary analysis of existing data, and costs were those incurred by SHI (i.e. expenses of SHI). In the base-case analysis, average case-related expenses of SHI were applied and LYG were quantified by the method of Kaplan and Meier.Main Outcome Measures and Results: The incremental cost-effectiveness ratios of ramipril varied between 2500 and 8300 deutschmarks (DM) per LYG (1993 values for inpatient and 1995 values for outpatient treatment; DM1 approximately $US0.70), according to the treatment periods of 3.8 years and 1 year, respectively. In the sensitivity analysis, the robustness of the model and its results was shown when the extent of influence of different model variables on the base-case results was investigated. First, survival probability and LYG were estimated according to the Weibull method. Second, the dependency of the target variable (i.e. incremental cost per LYG) on random variables was described in a simulation. Third, the influence of the model variables on the target variable was quantified using a deterministic model. The variance of the target variable was broad and the hospitalisation impact of adding ramipril to conventional treatment was an independent variable with much greater influence on the target variable than the parameter of clinical effectiveness, i.e. the number of LYG.Conclusion: Results of this evaluation showed that ramipril has a favourable incremental cost-effectiveness ratio for the treatment of heart failure in post myocardial infarction patients and can be considered an economical therapeutic agent from the perspective of SHI (third-party payer) in Germany. [ABSTRACT FROM AUTHOR]