The adoption of cost-effectiveness acceptability curves in cost-utility analyses.
BACKGROUND
Cost-effectiveness acceptability curves (CEACs) plot the probability that one health intervention is more cost-effective than alternatives, as a function of societal willingness to pay for additional units of health (e.g., life-years or quality-adjusted life-years gained).


OBJECTIVE
To quantify the adoption of CEACs in published cost-utility analyses (CUAs), and to identify factors associated with CEAC use.


METHODS
Data from the Tufts Medical Center Cost-Effectiveness Analysis Registry (www.cearegistry.org), a database with detailed information on approximately 1,400 CUAs published in the peer reviewed literature through 2006, was analyzed. The registry includes data on study origin, study methodology, reporting of results, whether CEACs were presented, and a subjective quality score. Univariate and multivariate logistic regression analyses were used to identify factors predicting CEAC use, from their introduction in 1994 through 2006.


RESULTS
Approximately 15% of CUAs published since 1994 present a CEAC. The use of CEACs has increased rapidly in recent years, from 2.1% of published CUAs in 2001 to 32.6% in 2006 (P < 0.0001). The most significant predictors of CEAC use were study quality (odds ratio [OR]: 2.26; 95% confidence interval [CI]: 1.80, 2.85), recent publication (OR: 1.99; 95% CI: 1.73, 2.29), and whether studies pertain to the UK (OR: 5.66; 95% CI: 3.67, 8.72) or Sweden (OR: 3.76; 95% CI: 1.67, 8.44).


CONCLUSIONS
CEAC use is increasing in the published cost-effectiveness literature, especially in UK-based studies.
Meckley
Lisa M
LM
Center for the Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts 02111, USA. lmeckley@tuftsmedicalcenter.org
Greenberg
Dan
D
Cohen
Joshua T
JT
Neumann
Peter J
PJ
D015706:Bibliometrics; D003362:Cost-Benefit Analysis / Q000379:methods*; D003365:Costs and Cost Analysis; D006801:Humans; D016015:Logistic Models; D015233:Models, Statistical; D010506:Periodicals as Topic; D019057:Quality-Adjusted Life Years; D012042:Registries; D012107:Research Design