Definition, interpretation and calculation of cost-effectiveness acceptability curves

Löthgren, Mickael; Zethraeus, Niklas

doi:10.1002/1099-1050(200010)9:7<623::aid-hec539>3.0.co;2-v

Cited by 258 publications

(181 citation statements)

References 13 publications

Supporting

Mentioning

175

Contrasting

Order By: Relevance

“…Instead, frequentist inference involves determining the probability (p-value) of attaining the data observed (or data more extreme than that observed) given a hypothesis regarding the parameter. It has been shown that the p-value curve, which plots the one-sided p-value on a test of positive incremental net benefit over a range of values of l is the mirror image of the CEAC [19,26,32,33]. The p-value curve intersects the yaxis at one minus the one-sided p-value on a test of differences between costs, and asymptotes to the one-sided p-value on a test of differences between effectiveness [26,32].…”

Section: Some Additional Issues With Ceacsmentioning

confidence: 99%

“…The CEAC is derived from the joint density of incremental costs (DC) and incremental effects (DE) for the intervention of interest, and represents the proportion of the density where the intervention is cost-effective for a range of values of l. Parametric estimation is possible by assuming a parametric functional form for the joint density (DC, DE) (for example, the joint normal distribution assumed by Van Hout [18]). The CEAC is then either determined directly by integrating the joint density [18][19][20] or estimated indirectly via parametric bootstrapping of the distribution [18]. Alternatively, the joint density can be generated by non-parametric bootstrapping [21,22], when patient level data are available for re-sampling, or by Monte Carlo simulation [23].…”

Section: De¢nition Of the Ceacsmentioning

confidence: 99%

See 1 more Smart Citation

Cost‐effectiveness acceptability curves – facts, fallacies and frequently asked questions

2004

View full text Add to dashboard Cite

Cost‐effectiveness acceptability curves (CEACs) have been widely adopted as a method to quantify and graphically represent uncertainty in economic evaluation studies of health‐care technologies. However, there remain some common fallacies regarding the nature and shape of CEACs that largely result from the ‘textbook’ illustration of the CEAC. This ‘textbook’ CEAC shows a smooth curve starting at probability 0, with an asymptote to 1 for higher money values of the health outcome (λ). But this familiar ‘ogive’ shape which makes the ‘textbook’ CEAC look like a cumulative distribution function is just one special case of the CEAC. The reality is that the CEAC can take many shapes and turns because it is a graphic transformation from the cost‐effectiveness plane, where the joint density of incremental costs and effects may ‘straddle’ quadrants with attendant discontinuities and asymptotes. In fact CEACs: (i) do not have to cut the y‐axis at 0; (ii) do not have to asymptote to 1; (iii) are not always monotonically increasing in λ; and (iv) do not represent cumulative distribution functions (cdfs). Within this paper we present a ‘gallery’ of CEACs in order to identify the fallacies and illustrate the facts surrounding the CEAC. The aim of the paper is to serve as a reference tool to accompany the increased use of CEACs within major medical journals. Copyright © 2004 John Wiley & Sons, Ltd.

show abstract

Section: Some Additional Issues With Ceacsmentioning

confidence: 99%

Section: De¢nition Of the Ceacsmentioning

confidence: 99%

Cost‐effectiveness acceptability curves – facts, fallacies and frequently asked questions

2004

View full text Add to dashboard Cite

show abstract

“…To summarize the whole distribution of cost-effectiveness results, a so-called costeffectiveness acceptability curve (CEAC) can be constructed (8). This gives an estimate of the proportion of the simulated distribution of cost and effect pairs that lie below a given threshold (the maximum value a decision maker is prepared to pay for a unit of effect -K ) or, more simply, the proportion that generate positive net (monetary) benefits.…”

Section: Cost-effectiveness Analysismentioning

confidence: 99%

Counseling Versus Antidepressant Therapy for the Treatment of Mild to Moderate Depression in Primary Care

Miller

Chilvers

Dewey

et al. 2003

Int J Technol Assess Health Care

View full text Add to dashboard Cite

Objective: To compare the cost-effectiveness of generic psychological therapy (counseling) with routinely prescribed antidepressant drugs in a naturalistic general practice setting for a follow-up period of 12 months. Methods: Economic analysis alongside a randomized clinical trial with patient preference arm. Comparison of depression-related health service costs at 12 months. Cost-effectiveness analysis of bootstrapped trial data using net monetary benefits and acceptability curves. Results: No significant difference between the mean observed costs of patients randomized to antidepressants or to counseling (£342 vs £302, p = .56 [t test]). If decision makers are not willing to pay more for additional benefits (value placed on extra patient with good outcome, denoted by K , is zero), then we find little difference between the treatment modalities in terms of cost-effectiveness. If decision makers do place value on additional benefit (K > £0), then the antidepressant group becomes more likely to be cost-effective. This likelihood is in excess of 90% where decision makers are prepared to pay an additional £2,000 or more per additional patient with a good global outcome. The mean values for incremental net monetary benefits (INMB) from antidepressants are substantial for higher values ofConclusion: For a small proportion of patients, the counseling intervention (as specified in this trial) is a dominant cost-effective strategy. For a larger proportion of patients, the antidepressant intervention (as specified in this trial) is the dominant cost-effective strategy. For the remaining group of patients, cost-effectiveness depends on the value of K . Since we cannot observe K , acceptability curves are a useful way to inform decision makers.

show abstract

“…The acceptability curve illustrates the statistical uncertainty in our study due to our sample and provides policy relevant information (Briggs, 2001;Fenwick et al, 2001;Lothgren and Zethraeus, 2000). Finally, we conduct sensitivity analyses on several key parameters to assess how the ICERs would likely change if MIEDAR had been implemented under different realistic conditions.…”

Section: Incrementalmentioning

confidence: 99%

Cost-effectiveness of prize-based incentives for stimulant abusers in outpatient psychosocial treatment programs

Olmstead

Sindelar

Petry

2007

Drug and Alcohol Dependence

View full text Add to dashboard Cite

Objective-To evaluate the cost-effectiveness of a prize-based intervention as an addition to usual care for stimulant abusers.Methods-This cost-effectiveness analysis is based on a randomized clinical trial implemented within the National Drug Abuse Treatment Clinical Trials Network. The trial was conducted at eight community-based outpatient psychosocial drug abuse treatment clinics. 415 stimulant abusers were assigned to usual care (n = 206) or usual care plus abstinence-based incentives (n=209) for 12 weeks. Participants randomized to the incentive condition earned the chance to draw for prizes for submitting substance negative samples; the number of draws earned increased with continuous abstinence time. Incremental cost-effectiveness ratios were estimated to compare prize-based incentives relative to usual care. The primary patient outcome was longest duration of confirmed stimulant abstinence (LDA). Unit costs were obtained via surveys administered at the eight participating clinics. Resource utilizations and patient outcomes were obtained from the clinical trial. Acceptability curves are presented to illustrate the uncertainty due to the sample and to provide policy relevant information.Results-The incremental cost to lengthen the LDA by one week was $258 (95% confidence interval, $191 -$401). Sensitivity analyses on several key parameters show that this value ranges from $163 to $269.Conclusions-Compared with the usual care group, the incentive group had significantly longer LDAs and significantly higher costs.

show abstract

Definition, interpretation and calculation of cost-effectiveness acceptability curves

Cited by 258 publications

References 13 publications

Cost‐effectiveness acceptability curves – facts, fallacies and frequently asked questions

Cost‐effectiveness acceptability curves – facts, fallacies and frequently asked questions

Counseling Versus Antidepressant Therapy for the Treatment of Mild to Moderate Depression in Primary Care

Cost-effectiveness of prize-based incentives for stimulant abusers in outpatient psychosocial treatment programs

Contact Info

Product

Resources

About