2003
DOI: 10.1046/j.1526-4637.2003.03027.x
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Multidimensional Subgroups in Migraine: Differential Treatment Outcome to a Pain Medicine Program

Abstract: This study questions the validity of the MPI subgroup classification algorithm. The results indicate that the K-clustering approach is more useful than the MPI in deriving meaningful patient clusters that differentially predict treatment outcome in a migraine population.

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Cited by 27 publications
(24 citation statements)
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“…In agreement with previous studies [19,21,22,26,66] three patient subtypes emerged which were significantly different for pain parameters and psychological profile. Cluster I subjects on average showed the lowest symptom burden as reflected by the Pain Inventory and Zerssen’s Complaint List.…”
Section: Discussionsupporting
confidence: 92%
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“…In agreement with previous studies [19,21,22,26,66] three patient subtypes emerged which were significantly different for pain parameters and psychological profile. Cluster I subjects on average showed the lowest symptom burden as reflected by the Pain Inventory and Zerssen’s Complaint List.…”
Section: Discussionsupporting
confidence: 92%
“…The increased use of cognitive control and the low avoidance scores may be related to the lower subjective pain stress. Thus, this subgroup resembles the type of patient referred to in literature as “uncomplicated” [19], “low impact” [26] or “good pain control” [66] with low levels of pain, impairment and dysfunction.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…For example, in microarray studies of cancer, a common objective is to identify cancer subtypes that are predictive of the prognosis (survival time) of cancer patients (Bhattacharjee et al, 2001; Sorlie et al, 2001; van ’t Veer et al, 2002; Rosenwald et al, 2002; Lapointe et al, 2004; Bullinger et al, 2004). In studies of chronic pain conditions, such as fibromyalgia or temporomandibular disorders (TMD), one may wish to develop a more precise case definition for the condition of interest by identifying subgroups of patients with similar clinical characteristics (Jamison et al, 1988; Bruehl et al, 2002; Davis et al, 2003; Hastie et al, 2005). However, conventional clustering methods (such as k -means clustering and hierarchical clustering) may produce unsatisfactory results when applied to these types of problems.…”
Section: Introductionmentioning
confidence: 99%
“…O bem-estar físico e o emocional, assim como as relações sociais, familiares e de trabalho, são extremamente afetados (Sorajjakool et al, 2006;Smith et al, 2001). A experiência da dor é mais bem entendida se uma construção multidimensional, incluindo aspectos físi-cos, biológicos, sociais, psicológicos e espirituais, for considerada (Davis et al, 2003). Além dos conceitos de nocicepção, sensitividade central e do componente neuropático da dor, numerosos estudos apontam fatores não-biológicos, como o suporte social e as estratégias de enfrentamento (coping), como fundamentais na percepção de dor dos pacientes (Keefe e Bonk, 1999;Lester et al, 1996;Kraaimaat et al, 1995).…”
Section: Introductionunclassified