The use of multiattribute decision models in evaluating triptan treatment options in migraine

Abstract

Background: The physician treating patients with migraine is now able to choose from among seven triptans-almotriptan, eletriptan, frovatriptan, naratriptan, rizatriptan, sumatriptan and zolmitriptan. These differ, to greater or lesser degrees, on a range of clinical attributes important for treatment selection.

Objective: To outline the basic principles of Multiattribute Decision Making (MADM) and describe how one such method-TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution)-can be applied to evaluate the currently available triptans.

Methods: In an example application, summary data from a recent meta-analysis of 53 published and unpublished placebo-controlled trials of the oral triptans were combined in TOPSIS models with computer-generated attribute importance weights representing the entire range of possible values, That is, the relative performance of the triptans was explored across all logically possible combinations of relative importance of the treatment attributes available from the meta-analysis, and uncertainty was assessed based on the confidence intervals from the meta-analysis.

Results: When compared across the entire range of values for relative attribute importance, almotriptan, eletriptan and rizatriptan were more similar to a hypothetical ideal triptan and were more likely to appear in the top three closest to the hypothetical ideal, than were naratriptan, sumatriptan, and zolmitriptan.

Conclusion: Using the TOPSIS model, almotriptan, eletriptan and rizatriptan were more likely to appear in the top three closest to the hypothetical ideal triptan.