Low doses vs. high doses of the angiotensin converting-enzyme inhibitor lisinopril in chronic heart failure: a cost-effectiveness analysis based on the Assessment of Treatment with Lisinopril and Survival (ATLAS) study. The ATLAS Study Group

Pharmacological interventions for heart failure in people with chronic kidney disease

BACKGROUND

Approximately half of people with heart failure have chronic kidney disease (CKD). Pharmacological interventions for heart failure in people with CKD have the potential to reduce death (any cause) or hospitalisations for decompensated heart failure. However, these interventions are of uncertain benefit and may increase the risk of harm, such as hypotension and electrolyte abnormalities, in those with CKD.

OBJECTIVES

This review aims to look at the benefits and harms of pharmacological interventions for HF (i.e., antihypertensive agents, inotropes, and agents that may improve the heart performance indirectly) in people with HF and CKD.

SEARCH METHODS

We searched the Cochrane Kidney and Transplant Register of Studies through 12 September 2019 in consultation with an Information Specialist and using search terms relevant to this review. Studies in the Register are identified through searches of CENTRAL, MEDLINE, and EMBASE, conference proceedings, the International Clinical Trials Register (ICTRP) Search Portal and ClinicalTrials.gov.

SELECTION CRITERIA

We included randomised controlled trials of any pharmacological intervention for acute or chronic heart failure, among people of any age with chronic kidney disease of at least three months duration.

DATA COLLECTION AND ANALYSIS

Two authors independently screened the records to identify eligible studies and extracted data on the following dichotomous outcomes: death, hospitalisations, worsening heart failure, worsening kidney function, hyperkalaemia, and hypotension. We used random effects meta-analysis to estimate treatment effects, which we expressed as a risk ratio (RR) with 95% confidence intervals (CI). We assessed the risk of bias using the Cochrane tool. We applied the GRADE methodology to rate the certainty of evidence.

MAIN RESULTS

One hundred and twelve studies met our selection criteria: 15 were studies of adults with CKD; 16 studies were conducted in the general population but provided subgroup data for people with CKD; and 81 studies included individuals with CKD, however, data for this subgroup were not provided. The risk of bias in all 112 studies was frequently high or unclear. Of the 31 studies (23,762 participants) with data on CKD patients, follow-up ranged from three months to five years, and study size ranged from 16 to 2916 participants. In total, 26 studies (19,612 participants) reported disaggregated and extractable data on at least one outcome of interest for our review and were included in our meta-analyses. In acute heart failure, the effects of adenosine A1-receptor antagonists, dopamine, nesiritide, or serelaxin on death, hospitalisations, worsening heart failure or kidney function, hyperkalaemia, hypotension or quality of life were uncertain due to sparse data or were not reported. In chronic heart failure, the effects of angiotensin-converting enzyme inhibitors (ACEi) or angiotensin receptor blockers (ARB) (4 studies, 5003 participants: RR 0.85, 95% CI 0.70 to 1.02; I² = 78%; low certainty evidence), aldosterone antagonists (2 studies, 34 participants: RR 0.61 95% CI 0.06 to 6.59; very low certainty evidence), and vasopressin receptor antagonists (RR 1.26, 95% CI 0.55 to 2.89; 2 studies, 1840 participants; low certainty evidence) on death (any cause) were uncertain. Treatment with beta-blockers may reduce the risk of death (any cause) (4 studies, 3136 participants: RR 0.69, 95% CI 0.60 to 0.79; I² = 0%; moderate certainty evidence). Treatment with ACEi or ARB (2 studies, 1368 participants: RR 0.90, 95% CI 0.43 to 1.90; I² = 97%; very low certainty evidence) had uncertain effects on hospitalisation for heart failure, as treatment estimates were consistent with either benefit or harm. Treatment with beta-blockers may decrease hospitalisation for heart failure (3 studies, 2287 participants: RR 0.67, 95% CI 0.43 to 1.05; I² = 87%; low certainty evidence). Aldosterone antagonists may increase the risk of hyperkalaemia compared to placebo or no treatment (3 studies, 826 participants: RR 2.91, 95% CI 2.03 to 4.17; I² = 0%; low certainty evidence). Renin inhibitors had uncertain risks of hyperkalaemia (2 studies, 142 participants: RR 0.86, 95% CI 0.49 to 1.49; I² = 0%; very low certainty). We were unable to estimate whether treatment with sinus node inhibitors affects the risk of hyperkalaemia, as there were few studies and meta-analysis was not possible. Hyperkalaemia was not reported for the CKD subgroup in studies investigating other therapies. The effects of ACEi or ARB, or aldosterone antagonists on worsening heart failure or kidney function, hypotension, or quality of life were uncertain due to sparse data or were not reported. Effects of anti-arrhythmic agents, digoxin, phosphodiesterase inhibitors, renin inhibitors, sinus node inhibitors, vasodilators, and vasopressin receptor antagonists were very uncertain due to the paucity of studies.

AUTHORS' CONCLUSIONS

The effects of pharmacological interventions for heart failure in people with CKD are uncertain and there is insufficient evidence to inform clinical practice. Study data for treatment outcomes in patients with heart failure and CKD are sparse despite the potential impact of kidney impairment on the benefits and harms of treatment. Future research aimed at analysing existing data in general population HF studies to explore the effect in subgroups of patients with CKD, considering stage of disease, may yield valuable insights for the management of people with HF and CKD.

Evaluating Cost-Effectiveness Models for Pharmacologic Interventions in Adults with Heart Failure: A Systematic Literature Review

BACKGROUND

Heart failure (HF) is a well-recognized public health concern and imposes high economic and societal costs. Decision analytic models exist for evaluating the economic ramifications associated with HF. Despite this, studies that appraise these modelling approaches for augmenting best-practice decisions remain scarce.

OBJECTIVE

Our objective was to conduct a systematic literature review (SLR) of published economic models for the management of HF and describe their general and methodological features.

METHODS

This SLR employed a combination of relevant search terms associated with HF, which were used in a number of databases, including MEDLINE, Embase, the National Health Service Economic Evaluation Database, Cost-Effectiveness Analysis Registry, ScHARR Health Utilities Database and Cochrane Library Database. A number of model features (i.e. model structure, specification, outcomes assessed, scenario and sensitivity analysis, key model drivers) were extracted and subsequently summarized.

RESULTS

Of 64 publications retained, a selection of modelling approaches were identified, including Markov (n = 28), trial-based analytic (n = 22), discrete-event simulation (n = 6), survival analytic (n = 7) and decision-tree modelling (n = 1) approaches. The bulk of publications employed either a cost-utility (n = 27) or cost-effectiveness (n = 36) analysis and evaluated more than one study outcome, which typically included overall costs (n = 59), incremental cost-effectiveness ratios (n = 55), life-years gained (n = 48) and willingness-to-pay thresholds (n = 37). Most publications focused on patients with chronic HF (n = 40) and used New York Heart Association (NYHA) disease classifications to categorize patients and determine disease severity. Few (n = 19) publications documented the use of hospitalization states for modelling patient outcomes and associated costs. A quality assessment of the included publications revealed most articles demonstrated reasonable methodological value.

CONCLUSIONS

We identified numerous decision analytic modelling approaches for evaluating the cost effectiveness of pharmacologic treatments in HF. A Markov cohort model approach was most commonly used, and most models relied on NYHA classes as a proxy of HF severity, disease progression and prognosis.

Consensus recommendations for management of patients with type 2 diabetes mellitus and cardiovascular diseases

The recent American Diabetes Association and the European Association for the Study of Diabetes guideline mentioned glycaemia management in type 2 diabetes mellitus (T2DM) patients with cardiovascular diseases (CVDs); however, it did not cover the treatment approaches for patients with T2DM having a high risk of CVD, and treatment and screening approaches for CVDs in patients with concomitant T2DM. This consensus guideline undertakes the data obtained from all the cardiovascular outcome trials (CVOTs) to propose approaches for the T2DM management in presence of CV comorbidities. For patients at high risk of CVD, metformin is the drug of choice to manage the T2DM to achieve a patient specific HbA1c target. In case of established CVD, a combination of glucagon-like peptide-1 receptor agonist with proven CV benefits is recommended along with metformin, while for chronic kidney disease or heart failure, a sodium-glucose transporter proteins-2 inhibitor with proven benefit is advised. This document also summarises various screening and investigational approaches for the major CV events with their accuracy and specificity along with the treatment guidance to assist the healthcare professionals in selecting the best management strategies for every individual. Since lifestyle modification and management plays an important role in maintaining the effectiveness of the pharmacological therapies, authors of this consensus recommendation have also briefed on the patient-centric non-pharmacological management of T2DM and CVD.

The analysis of multinational cost-effectiveness data for reimbursement decisions: a critical appraisal of recent methodological developments

Evidence produced by multinational trial-based cost-effectiveness studies is often used to inform decisions concerning the adoption of new healthcare technologies. A key issue relating to the use of this type of evidence is the extent to which trial-wide economic results are applicable to every single country participating in the study. We consider what role cost-effectiveness analysis alongside multinational trials should have in assisting reimbursement decisions at jurisdiction and national levels. Using the proposed framework as a benchmark to evaluate their relative pros and cons, we then describe and review the statistical approaches used in the multinational trial-based cost-effectiveness literature. The results of the review are used to define the desirable characteristics a statistical method for the analysis of data collected from different jurisdictions should have in order to be consistent with the proposed framework. It is argued that Bayesian hierarchical models that use both patient- and country-level information are the most appropriate tool to analyse multinational trial-based cost-effectiveness data and facilitate the between-country generalizability assessment of the study findings. The merits of each approach are discussed, highlighting problems and limitations, in order to identify areas of future research.

Economic burden of heart failure in the elderly

Heart failure (HF) ranks among the most costly chronic diseases in developed countries. At present these countries devote 1-2% of all healthcare expenditures towards HF. In the US, these costs are estimated at $US30.2 billion for 2007. The burden of HF is greatest among the elderly, with 80% of HF hospitalizations and 90% of HF-related deaths in this cohort. As a result, approximately three-quarters of the resources for HF care are consumed by elderly patients. As demographic shifts increase the number of elderly individuals in both developed and developing nations, the resources devoted to HF care will likely further increase. Hospitalization accounts for roughly two-thirds of HF costs, but procedures, outpatient visits and medications also consume significant financial resources. HF also adversely impacts patient quality of life, and these relevant effects may not be captured in pure cost analyses. The cost effectiveness of several pharmacological interventions has been explored. In general, neurohormonal antagonists used for outpatient treatment of chronic HF are relatively cost effective, in part by reducing hospitalizations. Because HF poses such an enormous financial burden, efficient resource allocation for its management is a major societal and governmental challenge. In order to make informed decisions and allocate resources for HF care rationally, detailed data regarding costs and resource use will be essential. Further studies are needed to examine the impact of pharmacological and non-pharmacological interventions on costs and resource use in elderly individuals with HF.

Modelling downstream effects in the presence of technological change

Downstream effects are typically evaluated given current technology and current practice patterns rather than for technology and practice patterns that will be available at the time when downstream effects accrue. Where a relatively short time horizon can be expected to capture all relevant costs and effects, the current approach is unlikely to introduce substantial error into estimates of the costs and benefits attributed to an intervention; the estimates will remain valid so long as the context to which estimates relate remains unchanged. However, for longer time horizons, the magnitude of error associated with the current approach might be substantial. This paper describes three strategies for incorporating uncertainty associated with technological change into modeled economic evaluations: (i) discounting; (ii) within-trial analysis; and (iii) threshold/sensitivity analysis with horizon scanning. The appropriateness of each strategy for handling uncertainty associated with technological change is then considered under various possible situations defined over the characteristics of technological change (pace and whether technological change produces interventions that are dominant, cost increasing or cost saving) and the characteristics of downstream effects (proximity and the sensitivity of policy recommendations to their inclusion/exclusion). Selecting the appropriate strategy (or strategies) for the situation should permit estimation of more realistic upper and lower bounds around base-case estimates.

Cost-effectiveness analysis using data from multinational trials: the use of bivariate hierarchical modeling

Health care cost-effectiveness analysis (CEA) often uses individual patient data (IPD) from multinational randomized controlled trials. Although designed to account for between-patient sampling variability in the clinical and economic data, standard analytical approaches to CEA ignore the presence of between-location variability in the study results. This is a restrictive limitation given that countries often differ in factors that could affect the results of CEAs, such as the availability of health care resources, their unit costs, clinical practice, and patient case mix. The authors advocate the use of Bayesian bivariate hierarchical modeling to analyze multinational cost-effectiveness data. This analytical framework explicitly recognizes that patient-level costs and outcomes are nested within countries. Using real-life data, the authors illustrate how the proposed methods can be applied to obtain (a) more appropriate estimates of overall cost-effectiveness and associated measure of sampling uncertainty compared to standard CEA and (b) country-specific cost-effectiveness estimates that can be used to assess the between-location variability of the study results while controlling for differences in country-specific and patient-specific characteristics. It is demonstrated that results from standard CEA using IPD from multinational trials display a large degree of variability across the 17 countries included in the analysis, producing potentially misleading results. In contrast, "shrinkage estimates'' obtained from the modeling approach proposed here facilitate the appropriate quantification of country-specific cost-effectiveness estimates while weighting the results based on the level of information available within each country. The authors suggest that the methods presented here represent a general framework for the analysis of economic data collected from different locations.

Do economic evaluations have a role in decision-making in Medicine Management Committees? A qualitative study

OBJECTIVE

To explore pharmacists' perceptions on the use of economic evaluations in decision-making within Medicine Management Committees (MMCs), identify factors that influence the uptake of economic evidence and examine the usefulness of different presentations of economic evidence.

METHOD

This two-stage qualitative study was carried out in July and August 2004 in two hospitals in northwest England. First, a researcher observed the decision-making process at two MMCs. Handwritten notes were made during observation, which were later transcribed. Subsequently, in-depth semi-structured interviews were conducted with a purposive sample of pharmacists involved in the MMCs. The interviews explored pharmacists' views on the usefulness of economic evaluations in decision-making, the factors influencing the uptake of economic evidence by the MMCs, and the optimal presentation of economic results. The interviews were audiotaped and transcribed verbatim. All the transcribed data were thematically analysed using the constant comparison approach.

RESULTS

In all, six new drug applications were observed and ten pharmacists were interviewed. Pharmacists were observed to play an important role in decisions about drug formularies in hospitals. Although interviewees considered that timely economic evaluations would be useful in reviewing new medicines, the actual use of economic evidence in decision-making within MMCs was limited. The barriers to using economic evaluations included pharmacists' lack of initiative to search for and difficulty in understanding economic evaluations, and the perceived availability, credibility and transferability of economic studies. However, the main barrier to implementing economic evidence was the decision makers' concern about the impact of the medicines on the hospitals' drug budgets. Interviewees felt that they understood and trusted disaggregated economic results better than aggregated ones.

CONCLUSION

This study found the use of economic evidence in decision-making at both MMCs was limited. To improve the usefulness of economic evaluations in MMCs, members of MMCs will need more training in accessing, understanding and appraising economic evidence; researchers need to improve the credibility and transferability of economic studies, and present the results in clear and understandable ways. However, due to the restricted focus of local, short-term drug budgets, evidence-based decision-making remains a challenge for local MMCs.

Analytic considerations in economic evaluations of multinational cardiovascular clinical trials

OBJECTIVES

The growing number of economic evaluations that use data collected in multinational clinical trials raises numerous questions regarding their execution and interpretation. Although recommendations for conducting economic evaluations have been widely disseminated, relatively little guidance has been given for conducting economic evaluations alongside clinical trials, particularly multinational trials.

METHODS

Building on a literature review that was conducted in preparation for an expert workshop, we evaluated a subset of methodological issues related to conducting economic evaluations alongside multinational clinical trials.

RESULTS

We found wide variation in the types of costs included as part of the analyses and in the methods used to assign costs to hospitalization events. Furthermore, we found that the extrapolation of costs and survival outcomes beyond the trial period is an inconsistent practice and is often not dependent on whether a survival benefit was observed in the trial or on the epidemiology or practice patterns in the country to which the findings are directed.

CONCLUSIONS

Although the limited sample size precluded a quantitative analysis of trial characteristics and their associations with the methodologies employed, our findings highlight the need for more guidance to analysts regarding the execution of economic evaluations using data from multinational clinical trials. As the research community grapples with the complexities of methodological and logistical issues involved in multinational economic evaluations, the development of a standardized format to report the basic methodological characteristics of such studies would help to improve transparency and comparability for other analysts and decision-makers.

Whither trial-based economic evaluation for health care decision making?

The randomised controlled trial (RCT) has developed a central role in applied cost-effectiveness studies in health care as the vehicle for analysis. This paper considers the role of trial-based economic evaluation in this era of explicit decision making. It is argued that any framework for economic analysis can only be judged insofar as it can inform two key decisions and be consistent with the objectives of a health care system subject to its resource constraints. The two decisions are, firstly, whether to adopt a health technology given existing evidence and, secondly, an assessment of whether more evidence is required to support this decision in the future. It is argued that a framework of economic analysis is needed which can estimate costs and effects, based on all the available evidence, relating to the full range of possible alternative interventions and clinical strategies, over an appropriate time horizon and for specific patient groups. It must also enable the accumulated evidence to be synthesised in an explicit and transparent way in order to fully represent the decision uncertainty. These requirements suggest that, in most circumstances, the use of a single RCT as a vehicle for economic analysis will be an inadequate and partial basis for decision making. It is argued that RCT evidence, with or without economic content, should be viewed as simply one of the sources of evidence, which must be placed in a broader framework of evidence synthesis and decision analysis.

Economic burden of heart failure: a summary of recent literature

OBJECTIVE

We reviewed literature published from 1995 to 2002 to highlight findings on the economic burden of heart failure (HF). Methods A key-word search of literature indexes for relevant citations identified 54 articles that were then summarized for findings on HF economics.

RESULTS

Results were described in terms of burden of illness, cost-effectiveness analysis, and resource utilization and costs. Hospitalization of the elderly is the driving force behind HF costs. Interventions that decrease the frequency of hospital admissions while maintaining clinical and patient reported outcomes are considered a high priority among decision makers and clinicians. Although the cost-effectiveness of therapy with beta-adrenergic blocking agents has been well established in the literature, the cost-effectiveness of hospital- or home-based HF management programs is still under debate. The issues of payer status and physician specialty impact on decreased hospital admission and cost have been inconclusive.

CONCLUSIONS

Any intervention capable of decreasing even a small fraction of adverse outcomes, most notably hospital admission and length of stay, could trigger significant cost savings in the management of HF. Public policy makers, together with clinicians identifying cost saving or cost-effective interventions in their practice, are expected to increase their efforts to evaluate the cost-effectiveness and outcomes of medical and pharmacologic interventions in HF.

'Lost in translation': accounting for between-country differences in the analysis of multinational cost-effectiveness data

Cost-effectiveness analysis has gained status over the last 15 years as an important tool for assisting resource allocation decisions in a budget-limited environment such as healthcare. Randomised (multicentre) multinational controlled trials are often the main vehicle for collecting primary patient-level information on resource use, cost and clinical effectiveness associated with alternative treatment strategies. However, trial-wide cost effectiveness results may not be directly applicable to any one of the countries that participate in a multinational trial, requiring some form of additional modelling to customise the results to the country of interest. This article proposes an algorithm to assist with the choice of the appropriate analytical strategy when facing the task of adapting the study results from one country to another. The algorithm considers different scenarios characterised by: (a) whether the country of interest participated in the trial; and (b) whether individual patient-level data (IPD) from the trial are available. The analytical options available range from the use of regression-based techniques to the application of decision-analytic models. Decision models are typically used when the evidence base is available exclusively in summary format whereas regression-based methods are used mainly when the country of interest actively recruited patients into the trial and there is access to IPD (or at least country-specific summary data). Whichever method is used to reflect between-country variability in cost-effectiveness data, it is important to be transparent regarding the assumptions made in the analysis and (where possible) assess their impact on the study results.

Assessing generalisability by location in trial-based cost-effectiveness analysis: the use of multilevel models

Cost-effectiveness analysis (CEA) in health care is increasingly conducted alongside multicentre and multinational randomised controlled clinical trials (RCTs). The increased use of stochastic CEA is designed to account for between-patient sampling variability in cost-effectiveness data assuming that observations are independently distributed. However, between-location variability in cost-effectiveness may result if there is a hierarchical structure in the data; that is, if there is correlation in costs and outcomes between patients recruited in particular locations. This may be expected in multi-location trials given that centres and countries often differ in factors such as clinical practice, patient case-mix and the unit costs of delivering health care. A failure to acknowledge this feature may lead to misleading conclusions in a trial-based economic study. Multilevel modelling (MLM) is an analytical framework that can be used to handle hierarchical cost-effectiveness data. Using data from a recently conducted economic analysis, this paper shows how multilevel modelling can be used to obtain (a) more appropriate estimates of the population average incremental cost-effectiveness and associated standard errors compared to standard stochastic CEA; and (b) location-specific estimates of incremental cost-effectiveness which can be used to explore appropriately the variability between centres/countries of the cost-effectiveness results.

Conducting economic evaluations alongside multinational clinical trials: toward a research consensus

Demand for economic evaluations in multinational clinical trials is increasing, but there is little consensus about how such studies should be conducted and reported. At a workshop in Durham, North Carolina, we sought to identify areas of agreement about how the primary findings of economic evaluations in multinational clinical trials should be generated and presented. In this paper, we propose a framework for classifying multinational economic evaluations according to (a) the sources of an analyst's estimates of resource use and clinical effectiveness and (b) the analyst's method of estimating costs. We review existing studies in the cardiology literature in the context of the proposed framework. We then describe important methodological and practical considerations in conducting multinational economic evaluations and summarize the advantages and disadvantages of each approach. Finally, we describe opportunities for future research. Delineation of the various approaches to multinational economic evaluation may assist researchers, peer reviewers, journal editors, and decision makers in evaluating the strengths and limitations of particular studies.

A pharmacoeconomic evaluation of the Myocardial Ischaemia Reduction with Aggressive Cholesterol Lowering (MIRACL) study in the United Kingdom

OBJECTIVE

To determine the short-term healthcare costs associated with intensive lipid lowering with atorvastatin initiated within 24-96 hours of the occurrence of acute coronary syndrome (ACS) in patients in the UK.

METHODS

Patient-level clinical outcome data from the Myocardial Ischaemia Reduction with Aggressive Cholesterol Lowering (MIRACL) trial and standard cost data were used to compare the total expected 16-week cost per patient on atorvastatin 80 mg/day versus placebo. Clinical outcomes assessed included the following: death; cardiac arrest with resuscitation; nonfatal myocardial infarction; worsening angina pectoris with objective evidence of myocardial ischaemia requiring rehospitalisation; surgical or percutaneous coronary revascularisation; nonfatal stroke; hospitalisation for angina without objective evidence of myocardial ischaemia; and new or worsening congestive heart failure requiring rehospitalisation. All relevant direct medical costs from the perspective of the NHS were considered.

RESULTS

The total expected cost was pound 784.05 per patient in the placebo cohort and pound 851.59 per patient in the atorvastatin cohort, resulting in an incremental cost of pound 67.54 per patient in the atorvastatin group. The cost per event avoided was pound 1762.04. A third of the cost of atorvastatin treatment was offset within 16 weeks by the cost savings resulting from the reduction in the number of events in the atorvastatin cohort compared with the placebo cohort.

CONCLUSION

The clinical benefits of short-term intensive atorvastatin treatment administered after ACS is attainable through a marginal increase in 'upfront' costs.

Bayesian methods for design and analysis of cost-effectiveness trials in the evaluation of health care technologies

We review the development of Bayesian statistical methods for the design and analysis of randomized controlled trials in the assessment of the cost-effectiveness of health care technologies. We place particular emphasis on the benefits of the Bayesian approach; the implications of skew cost data; the need to model the data appropriately to generate efficient and robust inferences instead of relying on distribution-free methods; the importance of making full use of quantitative and structural prior information to produce realistic inferences; and issues in the determination of sample size. Several new examples are presented to illustrate the methods. We conclude with a discussion of the key areas for future research.

Present and future pharmacotherapy for heart failure

The pharmacotherapy currently recommended by the American College of Cardiology and the American Heart Association for heart failure (HF) is a diuretic, an angiotensin-converting enzyme inhibitor (ACEI), a beta-adrenoceptor antagonist and (usually) digitalis. This current treatment of HF may be improved by optimising the dose of ACEI used, as increasing the dose of lisinopril increases its benefits in HF. Selective angiotensin receptor-1 (AT(1)) antagonists are effective alternatives for those who cannot tolerate ACEIs. AT(1) antagonists may also be used in combination with ACEIs, as some studies have shown cumulative benefits for the combination. In addition to being used in Stage IV HF patients, in whom it has a marked benefit, spironolactone should be studied in less severe HF and in the presence of beta-blockers. The use of carvedilol, extended-release metoprolol and bisoprolol should be extended to severe HF patients as these agents have been shown to decrease mortality in this group. The ancillary properties of carvedilol, particularly antagonism at prejunctional beta -adrenoceptors, may give it additional benefits to selective beta(1)-adrenoceptor antagonists. Celiprolol and bucindolol are not the beta-blockers of choice in HF, as they do not decrease mortality. Although digitalis does not reduce mortality, it remains the only option for a long-term positive inotropic effect, as the long-term use of the phosphodiesterase inhibitors is associated with increased mortality. The calcium sensitising drug levosimendan may be useful in the hospital treatment of decompensated HF to increase cardiac output and improve dyspnoea and fatigue. The antiarrhythmic drug amiodarone should probably be used in patients at high risk of arrhythmic or sudden death, although this treatment may soon be superseded by the more expensive implanted cardioverter defibrillators, which are probably more effective and have fewer side effects. The natriuretic peptide nesiritide has recently been introduced for the hospital treatment of decompensated HF. Novel drugs that may be beneficial in the treatment of HF include the vasopeptidase inhibitors and the selective endothelin-A receptor antagonists but these require much more investigation. However, disappointing results have been obtained in a large clinical trial of the tumour necrosis factor alpha antagonist etanercept, where no likelihood of a difference between placebo and etanercept was observed. Small clinical trials with recombinant growth hormone to thicken ventricles in dilated cardiomyopathy have given variable results.

The probability of cost-effectiveness

BACKGROUND

The study of cost-effectiveness comparisons between competing medical interventions has led to a variety of proposals for quantifying cost-effectiveness. The differences between the various approaches can be subtle, and one purpose of this article is to clarify some important distinctions.

DISCUSSION

We discuss alternative measures in the framework of individual, patient-level, incremental net benefits. In particular we examine the probability of cost-effectiveness for an individual, proposed by Willan.

SUMMARY

We argue that this is a useful addition to the range of cost-effectiveness measures, but will be of secondary interest to most decision makers. We also demonstrate that Willan's proposed estimate of this probability is logically flawed.

Representing uncertainty: the role of cost-effectiveness acceptability curves

Decision-making in health care is inevitably undertaken in a context of uncertainty concerning the effectiveness and costs of health care interventions and programmes. One method that has been suggested to represent this uncertainty is the cost-effectiveness acceptability curve. This technique, which directly addresses the decision-making problem, has advantages over confidence interval estimation for incremental cost-effectiveness ratios. However, despite these advantages, cost-effectiveness acceptability curves have yet to be widely adopted within the field of economic evaluation of health care technologies. In this paper we consider the relationship between cost-effectiveness acceptability curves and decision-making in health care, suggest the introduction of a new concept more relevant to decision-making, that of the cost-effectiveness frontier, and clarify the use of these techniques when considering decisions involving multiple interventions. We hope that as a result we can encourage the greater use of these techniques.

Economics of chronic heart failure

Chronic heart failure (CHF) is now recognized as a major and escalating public health problem. The costs of this syndrome, both in economic and personal terms, are considerable. The prevalence of CHF is 1-2% and appears to be increasing, in part because of ageing of the population. Economic analyses of CHF should include both direct and indirect costs of care. Healthcare expenditure on CHF in developed countries consumes 1-2% of the total health care budget. The cost of hospitalization represents the greatest proportion of total expenditure. Optimization of drug therapy represents the most effective way of reducing costs. Recent economic analyses in the Netherlands and Sweden suggest the costs of care are rising.

A framework for cost-effectiveness analysis from clinical trial data

We present a general Bayesian framework for cost-effectiveness analysis (CEA) from clinical trial data. This framework allows for very flexible modelling of both cost and efficacy related trial data. A common CEA technique is established for this wide class of models through linking mean efficacy and mean cost to the parameters of any given model. Examples are given in which efficacy may be measured as a continuous, binary, ordinal or time-to-event outcome, and in which costs are modelled as distributed normally, log-normally, as a mixture or non-parametrically. A case study is presented, illustrating the methodology and illuminating the role of prior information.