This paper considers some of the theoretical and practical problems of conducting cost-utility analyses alongside clinical trials. In order to measure utilities of different health states in a clinical trial a number of critical assumptions have to be made. Some of these assumptions are questionable on a theoretical level, others empirically invalid. The practical problems of measuring utilities are discussed. The standard gamble is shown to be the most validated method of utility measurement, but still based on very strong assumptions. The standard gamble instrument is also costly and difficult to administer in clinical trials. Other instruments are found to be less valid than the standard gamble. It is concluded that although cost-utility analysis seems relevant in some instances, investigators should avoid this assessment of utility and instead measure cost-effectiveness, cost-benefit and quality of life.

As campylobacteriosis is one of the most important foodborne infections, a European Union (EU)-27 level cost-effectiveness model has been developed on the socio-economic costs and benefits of applying certain control measures for the reduction of Campylobacter in broiler meat. This is expected to be a gold standard for food safety policymakers in the EU; hence, the validity of its modelling assumptions is essential. The authors of the present paper conducted an independent review of model input parameters on health and economic burden and found that the model most probably overestimated the burden of human campylobacteriosis. A discounted, quality-adjusted life year (QALY)-based European estimate has been developed for human campylobacteriosis and resulted in 15.23 QALY loss per 1000 human gastroenteritis cases. Country-specific cost of illness estimates have been developed for various countries in the EU-27. Based on these model adaptations, a selected Campylobacter control strategy was re-assessed and its high cost-effectiveness was confirmed at the EU level, and also in all but three Member States. Bacteriocin treatment or vaccination of the animals, two alternative control measures were also re-evaluated, and these strategies seemed to be far less cost-effective than the investigated strategy. Putative barriers to the rapid implementation of the investigated Campylobacter control strategy are discussed, and potential solutions are proposed. Further research is required on stakeholder perspectives pertaining to the realistic barriers and implementation opportunities.

Simulation models are used widely in pharmacology, epidemiology and health economics (HEs). However, there have been no attempts to incorporate models from these disciplines into a single integrated model. Accordingly, we explored this linkage to evaluate the epidemiological and economic impact of oseltamivir dose optimisation in supporting pandemic influenza planning in the USA. An HE decision analytic model was linked to a pharmacokinetic/pharmacodynamics (PK/PD) – dynamic transmission model simulating the impact of pandemic influenza with low virulence and low transmissibility and, high virulence and high transmissibility. The cost-utility analysis was from the payer and societal perspectives, comparing oseltamivir 75 and 150 mg twice daily (BID) to no treatment over a 1-year time horizon. Model parameters were derived from published studies. Outcomes were measured as cost per quality-adjusted life year (QALY) gained. Sensitivity analyses were performed to examine the integrated model's robustness. Under both pandemic scenarios, compared to no treatment, the use of oseltamivir 75 or 150 mg BID led to a significant reduction of influenza episodes and influenza-related deaths, translating to substantial savings of QALYs. Overall drug costs were offset by the reduction of both direct and indirect costs, making these two interventions cost-saving from both perspectives. The results were sensitive to the proportion of inpatient presentation at the emergency visit and patients’ quality of life. Integrating PK/PD–EPI/HE models is achievable. Whilst further refinement of this novel linkage model to more closely mimic the reality is needed, the current study has generated useful insights to support influenza pandemic planning.

The Tufts Cost-Effectiveness Analysis (CEA) Registry (www.cearegistry.org) is a publicly available comprehensive database of cost-utility analyses of health interventions published in the peer-reviewed medical and public health literature. This article discusses the database structure, methodology of data extraction, current trends in cost-utility analyses and impact of the Registry.

Objectives: To compare cost effectiveness models for the first-line treatment of multiple myeloma, and explore the differences between the models’ structure, parameters, assumptions and results.

Methods: Three cost effectiveness models for the treatment of multiple myeloma, were compared that had been developed to inform resource allocation in the UK for the chemotherapy regimens bortezomib, melphalan and prednisolone (BMP); and melphalan, prednisolone and thalidomide (MPT) versus melphalan and prednisolone (MP). The models used alternative approaches and assumptions to estimate the overall survival and progression-free survival for each of the interventions. Through the use of sensitivity analyses, the most influential parameters and assumptions of each of the models were identified.

Results: The models developed by the manufacturers gave conflicting results, with each manufacturer favouring their drug. The differences between the model results were determined by two parameters: the hazard ratio for overall survival for MPT vs. MP and the cost of bortezomib.

Conclusions: Using models developed for assessing treatments for multiple myeloma we demonstrated that it was feasible to compare models, which then aided decision makers in making reimbursement decisions.

Objectives: We studied the cost-effectiveness of tenofovir and entecavir in e antigen positive (CHBe+) and negative (CHBe-) chronic hepatitis B.

Methods: Using a multicenter survey including 544 patients we measured patient quality of life and attributable costs by clinical disease stage. Natural disease progression was studied in 278 patients in a single center. A Markov model was constructed to follow hypothetical cohorts of treated and untreated 40-year-old CHBe+ and CHBe- patients and 50-year-old patients with compensated cirrhosis.

Results: We did not find an improvement in quality of life when viral load was reduced under treatment. Transition rates to liver cirrhosis were found to be age-dependent. Assuming equal effectiveness, tenofovir dominates the entecavir strategy because of its lower price in Belgium. The incremental cost-effectiveness ratio (ICER) of tenofovir after 20 years is more favorable for treating Caucasian cirrhotic patients (mean ICER €29,000/quality-adjusted life-year [QALY]) compared with treating non-cirrhotic patients (mean ICER €110,000 and 131,000/QALY for CHB e+ and e-, respectively). Within the non-cirrhotic patients the ICER decreases with increasing cohort starting age from 30 to 50 years.

Conclusions: Results of long-term models for tenofovir or entecavir treatment of CHB need to be interpreted with caution as long-term trials with hard end points are lacking. Especially the effect on HCC remains highly uncertain. Based on cost-effectiveness considerations such antiviral treatment should be targeted at patients with cirrhosis or at risk of rapid progression to this disease stage.

Objectives: The aim of this study was to evaluate the long-term cost-utility of liraglutide versus glimepiride as add-on therapy to metformin in patients with type 2 diabetes mellitus (T2DM), based on the results of clinical trial conducted in Asian population.

Methods: The validated UKPDS Outcomes Model was used to project life expectancy, quality adjusted life-years (QALYs), incidence of diabetes-related complication and cost of complications in patients receiving those regimens. Baseline cohort characteristics and treatment effects were derived from an Asian study. China-specific complication costs and utility score were taken from local studies. Patients’ outcomes were modeled for 30 years and incremental cost-effectiveness ratios were calculated for liraglutide compared with glimepiride from the healthcare system perspective. Both future costs and clinical benefits were discounted at 3 percent. Sensitivity analyses were performed.

Results: Over a period of 30 years, compared with glimepiride, liraglutide 1.8 mg was associated with improvements in life expectancy (0.1 year) and quality adjusted life-year (0.168 QALY), and a reduced incidence of diabetes-related complications leading to an incremental cost-effectiveness ratio per QALY gained versus glimepiride of CNY 25,6871 (DEC 2010, 1 USD = 6.6227 CNY).

Conclusions: Long-term projections indicated that liraglutide was associated with increased life expectancy, QALYs, and reduced complication incidences comparing with glimepiride. When the UK cost of liraglutide was discounted by 38 percent, liraglutide would be a cost-effective option in China from the healthcare system perspective using the 3X GDP/capita per QALY as the WTP threshold.

Objectives: The aim of this study was to evaluate the cost-effectiveness of alemtuzumab (CAMPATH-1H) compared with conventional chemotherapy in people with T-cell prolymphocytic leukemia (T-PLL).

Methods: We developed a decision-analytic model to assess the costs and benefits of alemtuzumab or conventional therapy based on their effects on quality of life of patients. The main outcome was the incremental cost-effectiveness ratio incorporating costs per additional quality-adjusted life-year (QALY) gained over lifetime. Due to the limited data available, a large number of assumptions had to be made to construct the cost-utility model. One-way, multi-way, and probabilistic sensitivity analyses (PSA) were conducted to explore the impact of these uncertainties. Expected values of perfect information were also calculated for four specific scenarios.

Results: Depending on different key assumptions made, the PSA suggested distinct conclusions using a willingness-to-pay threshold of 30,000 GBP per QALY gained. Using this threshold, the probability that alemtuzumab would be cost-effective varies from 0 percent to 53 percent for the four modeled scenarios. Population expected value of perfect information analysis suggests that resolving the parameter uncertainty in the analysis for people with T-PLL in the United Kingdom would have considerable value—up to 5.3 million euro.

Conclusions: Alemtuzumab appears more likely to be cost-effective if used earlier in the course of T-PLL and where it replaces the use of multiple alternative therapies. However, cost-effectiveness is highly uncertain and future research is clearly justified. Nevertheless, our analysis demonstrates the feasibility of considering the cost-effectiveness of an agent despite the presence of significant uncertainty to provide appropriate assessment information to policy makers.

Objectives: To determine the cost-effectiveness (CE) and cost-utility (CU) of drug-eluting stents (DES) compared to bare metal stents (BMS) in Ontario using a large prospective “real-world” cohort study and determine the extent to which results vary by patient risk subgroups.

Methods: A field evaluation was conducted based on all stent procedures in the province of Ontario between December 1, 2003, and March 31, 2005, with a minimum subject follow-up of 1 year. Effectiveness data from the study using a propensity-score matched cohort were combined with resource utilization and cost data and quality of life (QOL) data from the published literature in a decision analytic modeling framework to determine 2-year cost-effectiveness (cost per revascularization avoided) and cost-utility (cost per quality-adjusted life-year ([QALY] gained). Stochastic model parameter uncertainty was expressed using probability distributions and analyzed using a probabilistic model. Modeling assumptions were assessed using traditional deterministic sensitivity analysis.

Results: Significant differences in revascularization rates were found for patients with two or more high risk factors. Despite these differences, the CE and CU of DES remained high (e.g., $419,000 per QALY gained in the most favorable patient risk subgroup). In sensitivity analysis, the difference in cost between DES and BMS had an impact on the CE and CU results. For example, at a price differential of $500, the CU of DES was $20,000/QALY for one patient subgroup and DES was dominant (i.e., less costly and more effective) in another.

Conclusions: At current prices, the CE/CU of DES compared with BMS is high even in patient high risk subgroups. As the relative price of DES decrease, the value for money attractiveness of DES increases, especially for selected high risk patients.

Objectives: The aim of this study was to assess the cost-effectiveness of screening for open-angle glaucoma (OAG) in the United Kingdom, given that OAG is an important cause of blindness worldwide.

Methods: A Markov model was developed to estimate lifetime costs and benefits of a cohort of patients facing, alternatively, screening or current opportunistic case finding strategies. Strategies, varying in how screening would be organized (e.g., invitation for assessment by a glaucoma-trained optometrist [GO] or for simple test assessment by a technician) were developed, and allowed for the progression of OAG and treatment effects. Data inputs were obtained from systematic reviews. Deterministic and probabilistic sensitivity analyses were performed.

Results: Screening was more likely to be cost-effective as prevalence increased, for 40 year olds compared with 60 or 75 year olds, when the re-screening interval was greater (10 years), and for the technician strategy compared with the GO strategy. For each age cohort and at prevalence levels of ≤1 percent, the likelihood that either screening strategy would be more cost-effective than current practice was small. For those 40 years of age, “technician screening” compared with current practice has an incremental cost-effectiveness ratio (ICER) that society might be willing to pay when prevalence is 6 percent to 10 percent and at over 10 percent for 60 year olds. In the United Kingdom, the age specific prevalence of OAG is much lower. Screening by GO, at any age or prevalence level, was not associated with an ICER < £30,000.

Conclusions: Population screening for OAG is unlikely to be cost-effective but could be for specific subgroups at higher risk.

Objectives: The diffusion of cost-utility analyses (CUAs) through the medical literature was examined, documenting visible patterns and determining how they correspond with expectations about the diffusion of process innovations.

Methods: This study used 539 CUAs from a registry. It includes data elements comprising year of publication, the research center in which the study was performed, the clinical area covered by the CUA, and the specific journal. Finally, each paper was assigned to a journal type that could be one of the three categories: health services research, general medicine, or clinical specialty.

Results: When the average number of publications is plotted against time, the plot reveals an S-shaped curve. It appears that, whereas CUAs initially were published more frequently in general medical or health services research journals, there was a clear increase in the diffusion of CUA into subspecialty journals over time. The concentration ratio for research centers as measured by the Herfindhal–Hirschman Index decreased over time.

Conclusions: The spread of CUA through the medical literature follows patterns identified for the diffusion of other new technologies and processes. Future research should focus on what impact this spread has had on the practice of medicine and formulation of health policy.

Objectives: We designed a model of diagnostic and therapeutic interventions applied in children with meningeal signs. Using this model, we determined in a cost-utility analysis the consequences for society of different diagnostic strategies in terms of quality-adjusted life-years (QALYs) and costs.

Methods: Data were used from 360 children (0.1–15 years) visiting the pediatric emergency department of the Sophia Children's Hospital Rotterdam, The Netherlands (1988–98) with meningeal signs. Model inputs included probabilities of meningitis and adverse outcome, QALYs for years lived with long-term sequelae, and costs of tests and treatments. Mean outcome measures were costs and effects of diagnostic and therapeutic interventions in children suspected of bacterial meningitis, key determinants of the model outcomes, and evaluation of alternative diagnostic strategies and two vaccination programs in an analysis.

Results: The population comprised 99 children with bacterial meningitis (adverse outcome in 10), 36 with serious other bacterial infections, and 225 with self-limiting diseases. Key determinants were the risk of bacterial meningitis or sequelae, costs of treatment, and long-term morbidity. Minimizing lumbar punctures and empirical treatments using a diagnostic decision rule, without missing a single case of meningitis, was a dominant strategy to actual practice. Vaccination strategies of Streptococcus pneumoniae and Neisseria meningitidis resulted in our model in incremental cost-utility ratios of 401,965 Euro dollar ()/QALY and 22,635/QALY, respectively.

Conclusions: Costs of long-term morbidity of bacterial meningitis largely outweigh diagnostic and treatment costs. Modeling interventions in children at risk of bacterial meningitis should include long-term consequences in terms of costs and QALYs.

Objectives: The study evaluated the extent to which quality-adjusted life-years (QALYs) and healthy-years equivalents (HYEs) were used in cost-utility studies over the past 20 years (1981–2000) as well as possible changes in the quality of journals reporting cost-utility studies.

Methods: Cost-utility studies were identified through an electronic search. For each study the journal name, date of publication, article's language and research origin, and the journal's impact factor were recorded.

Results: The number of published cost-utility studies increased in the last 20 years but has leveled off in 1997. Most studies were performed in the United States and were published in English. All studies except one used QALYs as an outcome measure. The mean journal's impact factor has changed slightly over the years.

Conclusions: Cost-utility studies would possibly gain more popularity if they were used as a vehicle in the decision-making process regarding healthcare budgets and were more visible in the scientific literature.

Objectives: Cost-effectiveness analysts often present cost-effectiveness results by age to help inform decisions about the use of an intervention. Yet it is not known how well studies model the risks and costs associated with age. We reviewed published studies to examine their modeling of age differences.

Methods: MEDLINE searches identified all cost-effectiveness analyses published between 1985 and 1997 that included adults 50 years of age and older, were based on data for developed countries, and compared cost-effectiveness ratios for adults of different ages or for initiation of an intervention at different ages; 36 articles met these criteria. They were reviewed to determine the extent to which they incorporated age-specific data. Studies that justified using the same data for all ages were counted as having varied the data element by age.

Results: All studies varied life expectancy by age. Most also varied the incidence/prevalence of the target condition and the case fatality rate. Only 36% varied the effectiveness rate of the intervention by age. Costs were usually assumed constant: 42% of studies varied the cost of treating adverse effects and 17% varied the cost of treating the target condition. Whether a data element was varied did not appear to be related to the pattern of cost-effectiveness ratios by age.

Conclusions: Many studies have not modeled age differences in sufficient detail to ensure that differences in cost-effectiveness ratios by age are accurate and a sound basis for decisions. As cost-effectiveness analysis becomes more widespread, analysts should strive to incorporate more complete age-specific data.

Objectives: Although cost-utility analysis (CUA) has been recommended by some experts as the preferred technique for economic evaluation, there is controversy regarding what costs should be included and how they should be measured. The purpose of this study was to: a) identify the cost components that have been included in published CUAs; b) catalogue the sources of valuation used; c) examine the methods employed for estimating costs; and d) explore whether methods have changed over time.

Methods: We conducted a comprehensive search of the published literature and systematically collected data on the cost estimation of CUAs. We audited the cost estimates in 228 CUAs.

Results: In most studies (99%), analysts included some direct healthcare costs. However, the inclusion of direct non-healthcare and time costs (17%) was generally lacking, as was productivity costs (8%). Only 6% of studies considered future costs in added life-years. In general, we found little evidence of change in methods over time. The most frequently used source for valuation of healthcare services was published estimates (73%). Few studies obtained utilization data from RCTs (10%) or relied on other primary data (23%). About two-thirds of studies conducted sensitivity analyses on cost estimates.

Conclusions: We found wide variations in the estimation of costs in published CUAs. The study underscores the need for more uniformity and transparency in the field, and continued vigilance over cost estimates in CUAs on the part of analysts, reviewers, and journal editors.

Objectives: To test the feasibility of obtaining a baseline level of quality of reporting for cost-utility analysis (CUA) studies using the British Medical Journal economic submissions checklist, test interrater reliability of this tool, and discuss its longer term implications.

Methods: CUA studies in peer-reviewed English language journals in 1996, assessed using the British Medical Journal checklist, a quality index, and interrater reliability correlations.

Results: Forty-three CUA studies were assessed, with 23 checklist items acceptable and 10 items inadequate. Lowest quality scores were reported in specialist medical journals. Proportional agreement between assessors was over 80%.

Conclusions: The British Medical Journal checklist is a feasible tool to collect baseline information on the quality of reporting in journals other than the British Medical Journal. Editors of specialist medical journals are in greatest need of economic guidance. If handled carefully, they might consider adopting the British Medical Journal checklist.