The use of multiattribute decision models in evaluating triptan treatment options in migraine
- First Online:
- 104 Downloads
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.
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.
In an example application, summary data from a recent meta–analysis of 53 published and unpublished placebo–controlled trials of the oral triptans were combined in TOPSIS models with computer–generated attribute importance weights representing the entire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.
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.
Using the TOPSIS model, almotriptan, eletriptan and rizatriptan were more likely to appear in the top three closest to the hypothetical ideal triptan.
Key wordsdecision model triptans migraine
Unable to display preview. Download preview PDF.
- 9.Yoon KP, Hwang CL (1995) Multiple Attribute Decision Making: An Introduction. Sage, Thousand Oaks, pp 38–40Google Scholar
- 11.Barron FH, Barrett BE (1996) Decision quality using ranked attribute weights. Manag Sci 42:1515–1523Google Scholar
- 13.von Winterfeldt D, Edwards W (1987) Decision Analysis and Behavioral Research. Cambridge University Press, Cambridge Google Scholar
- 14.Abi-Zeid I, Belanger M, Guitouni A, Martel JM, Jabeur K (1998) A Multicriteria Method for Evaluating Courses of Action in Canadian Airspace Violation Situations. Available at: http://www. dodccrp. org/Proceedings/ DOCS/wcd00000/wcd091. htm. Accessed 14 Jan 2003Google Scholar
- 15.Hwang CL, Yoon KP (1981) Multiattribute Decision Making: Methods and Applications. Springer, Berlin, pp 128–140Google Scholar
- 16.Azar F (2000) Multi-attribute decision making: use of three scoring methods to compare the performance of imaging techniques for breast cancer detection. Available at: http://www. seas. upenn. edu/be/Tech_Reports/fredazar_ rechreport_MS_BE_00_01. PDF. Accessed 21 Oct 2002Google Scholar
- 17.Alberto C, Carignano C, Fultot M (2000) Evaluacion de la eficinecia de los sistemas de salud publica provincial en Argentina. Available at: http://selene. uab. es/dep-economiaempresa/ documents/tema_2. rtf. Accessed 21 Oct 2002Google Scholar
- 18.Zeleny M (1982) Multiple Criteria Decision Making. McGraw Hill, New YorkGoogle Scholar
- 20.Dodick D, Cutrer FM, Ferrari M, et al. (2002) Prioritization of treatment attributes in selecting an oral triptan: a survey of US neurologists. Headache 42:392Google Scholar
- 21.Cutrer FM, Goadsby PJ, Ferrari M, et al. (2002) Prioritization of treatment attributes in selecting an oral triptan: a survey of US primary care physicians. Headache 42:392–393Google Scholar
- 22.Lipton RB, Liberman J, Goadsby PJ, et al. (2002) An assessment of the priorities of US migraineurs with respect to prespecified triptan treatment attributes. Headache 42:394–395Google Scholar
- 23.Hess G (2002) The use of multiattribute analyses, multi-dimensional scaling and pairwise comparisons for group decision-making. ISPOR News 8:4–6Google Scholar