Professor |
Malaysia |
Replied: 20 Mar 2018 at 23:37
Hi Levina
With the increasing collection of economic data alongside conduct of clinical trial, there is now indeed a growing concern in the power and sample size in economic evaluation. Most often, clinical trials are underpowered to detect differences in cost.
The most common approach is based on the net benefit confidence limit equation to test the hypothesis about expected cost effectiveness ratio or net monetary benefit e.g. hypothesized that the incremental ratio of therapy XX compared with therapy YY will be lower than W per QALY1-4. This approach test the hypothesis by assessing whether net benefit, calculated by use of W, is significantly different from 0. Information usually required for the calculation include the variance of cost, variance of effectiveness, society’s willingness to pay for a benefit gain, difference in cost, difference in effectiveness and the correlation between the difference in cost and effect. More details can be found in the reference list below.
The methods are applicable to both CEA and CUA though the estimated sample size is applicable to the chosen effect. Hence, it is recommended to calculate based on the primary outcome that is most relevant in the study.
1. Briggs AH, Gray AM. Power and sample size calculations for stochastic cost-effectiveness analysis. Med Decis Making. 1998;18(2 Suppl):S81-92.
2. Laska EM, Meisner M, Siegel C. Power and Sample Size in Cost- Effectiveness Analysis. Med Decis Making. 1999;19(3):339-343.
3. Walter SD, Gafni A, Birch S. Estimation, power and sample size calculations for stochastic cost and effectiveness analysis. Pharmacoeconomics. 2007;25:455-466.
4. Glick HA, Doshi JA, Sonnad SS, Polsky D. Economic evaluation in clinical trials. Oxford: Oxford University Press; 2007.
