Sensory profiles of patients with neuropathic pain based on the neuropathic pain symptoms and signs.

Pain

Autonomic and Peripheral Nerve Laboratory, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA Division of Neurological Pain Research and Therapy, Department of Neurology, Christian-Albrechts University, Kiel, Germany INSERM U987, Centre d'Evaluation et de Traitement de la Douleur, Hôpital Ambroise Paré, Boulogne-Billancourt F-92100, France Université Versailles-Saint-Quentin, Versailles F-78035, France Department of Statistics and Biostatistics, Rutgers University, New Brunswick, NJ, USA Pfizer Inc, New York, NY, USA.

Published: February 2014

This manuscript aimed to characterize the clinical profile of various neuropathic pain (NeP) disorders and to identify whether patterns of sensory symptoms/signs exist, based on baseline responses on the Neuropathic Pain Symptom Inventory (NPSI) questionnaire and the quantitative sensory testing (QST). These post hoc analyses were based on data from 4 randomized, double-blind, placebo-controlled clinical studies of pregabalin (150-600mg/day) in patients with NeP syndromes: central poststroke pain, posttraumatic peripheral pain, painful HIV neuropathy, and painful diabetic peripheral neuropathy. The NPSI questionnaire includes 10 different pain symptom descriptors. QST was used to detect sensory thresholds of accurately calibrated sensory stimuli and to quantify the intensity of evoked sensation. To identify symptoms/signs clusters and select the number of clusters, a principal component analysis (PCA) and hierarchical clustering methods with clinical input were used. Analysis of the NPSI pain qualities and individual QST measures at baseline indicated no clear association between particular symptoms/signs profiles and etiologies. Based on NPSI symptoms, PCA identified 3 pain dimensions: provoked, deep, and pinpoint. A hierarchical cluster analysis identified 3 clusters with distinct pain characteristics profiles independent of NeP syndrome. Based on QST signs, PCA identified 2 pain dimensions: evoked by cold and evoked by touch. A hierarchical cluster analysis identified 4 clusters with distinct pain characteristics profiles. These "trans-etiological" profiles may reflect distinct pathophysiological mechanisms and therefore, potential differential responses to treatment.

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http://dx.doi.org/10.1016/j.pain.2013.10.023DOI Listing

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