Noninferiority testing in cost-minimization studies: Practical issues concerning power analysis.
OBJECTIVE
In cost-minimization studies, it is important to establish noninferiority in the clinical effect of the treatments under investigation. The relationship between the proportion of patients reaching the end point in a study, equivalence limit (delta), and power is investigated in the context of cost-minimization studies with dichotomous clinical end points. Two formulations of the null-hypothesis, absolute and relative formulations of delta, will be explored.


METHODS
Sensitivity analysis was performed, in which the effect of the predicted proportions and delta on the power in a noninferiority setting was investigated. The patterns found are discussed in terms of the practical relevance within the cost-minimization framework.


RESULTS
Sensitivity analyses show different patterns of results for both null-hypotheses. The differences in these results originate from the way delta is expressed. By expressing delta as absolute difference, power grows quite fast when sample proportions are smaller than expected. In the case of a proportional delta at small sample proportions, the power to establish noninferiority remains low.


CONCLUSIONS
To obtain valid results from a cost-minimization study, care has to be taken to adapt the correct methodology for noninferiority testing in clinical outcomes. Defining delta in terms of absolute differences between treatments can lead to obscured results. Although conservative, the expression of delta as a proportion of the effectiveness of the treatment as usual is found to be closer to clinical practice. The inflated delta, resulting from smaller clinical effects than expected when absolute formulation is applied, thus can be avoided.
Span
Mark M
MM
Office of Medical Technology Assessment, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. M.M.Span@rug.nl
TenVergert
Elisabeth M
EM
van der Hilst
Christian S
CS
Stolk
Ronald P
RP
D003363:Cost Control; D017059:Models, Econometric; D017063:Outcome Assessment, Health Care / Q000191:economics* / Q000706:statistics & numerical data*; D012680:Sensitivity and Specificity