OBJECTIVES: It is often unclear what the relative efficacies of available treatments are due to lack of head-to-head clinical trial evidence. Indirect treatment comparison (ITC) constitutes the standard method for comparing the relative efficacies of treatments in the absence of head-to-head trial evidence. This study sought to examine the difference in cost-effectiveness results between a series of decision analyses compared to synthesising the clinical evidence with adjusted indirect comparisons. METHODS: Cost-effectiveness analyses (CEA) of hypothetical Drug A versus Drug B for three different scenarios were performed using a Markov model. Three assumptions were made regarding the relative efficacies of these drugs: 1) Drug A = Drug B; 2) Drug B 10% worse than Drug A and; 3) Drug B 20% worse than Drug A. ITCs were undertaken for each scenario and the results were compared to the results from the cost-effectiveness analysis. RESULTS: For Assumption 1, the ITC showed a difference of up to 12%, whereas the CEA showed an almost perfect overlay of the two scatterplots and the acceptability curves. In Assumption 2, the ITC difference was up to 13%, while the scatterplots for the CEA were overlapping and the acceptability curves clearly represented two different treatments with only a small overlap at the upper range of the threshold. In Assumption 3, statistical superiority of Drug A was demonstrated through the ITC, and the acceptability curves of the CEA did not overlap. CONCLUSIONS: The methodology introduced in this paper is an alternative for decision makers to further examine the relative effectiveness of two treatments when no head-to-head clinical trial data are available. A major limitation of this method is that detailed inputs (such as cost and quality of life data) need to be readily available for the various treatments being compared.