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Abstract: Neuropathic pain highly affects quality of life, well-being, and function. It has recently been shown based on cluster analysis studies that most patients with neuropathic pain may be categorized into 1 of 3 sensory phenotypes: sensory loss, mechanical hyperalgesia, and thermal hyperalgesia. If these phenotypes reflect underlying pathophysiological mechanisms, they may be more relevant for patient management than underlying neurological diagnosis or pain intensity. The aim of this study was thus to examine the impact of these sensory phenotypes on mental health, functionality, and quality of life. Data of 433 patients from the IMI/EuroPain network database were analyzed, and results of HADS-D/A, Pain Catastrophizing Scale, Euro Quality of Life 5D/-VAS, Brief Pain Inventory, and Graded Chronic Pain Scale between the sensory phenotypes were compared using multiple regression analysis. There was no difference in chronic pain grade, pain intensity, depression, or anxiety scores between phenotypes. Pain interference (Brief Pain Inventory) was higher (P = 0.002); self-reported health state lower (Euro Quality of Life 5D VAS, P = 0.02); and problems regarding mobility (P = 0.008), usual activities (P = 0.004), and self-care (P = 0.039) more prominent (EQ5-D) in the sensory loss compared with the thermal hyperalgesia phenotype. Patients with sensory loss also showed higher pain catastrophizing scores (P = 0.006 and 0.022, respectively) compared with the 2 other groups. Sensory phenotype is associated with the impact of neuropathic pain conditions on well-being, daily functionality, and quality of life but is less associated with pain intensity. These results suggest that the somatosensory phenotype should be considered for personalized pain management., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Association for the Study of Pain.)

In a recent cluster analysis, it has been shown that patients with peripheral neuropathic pain can be grouped into 3 sensory phenotypes based on quantitative sensory testing profiles, which are mainly characterized by either sensory loss, intact sensory function and mild thermal hyperalgesia and/or allodynia, or loss of thermal detection and mild mechanical hyperalgesia and/or allodynia. Here, we present an algorithm for allocation of individual patients to these subgroups. The algorithm is nondeterministic-ie, a patient can be sorted to more than one phenotype-and can separate patients with neuropathic pain from healthy subjects (sensitivity: 78%, specificity: 94%). We evaluated the frequency of each phenotype in a population of patients with painful diabetic polyneuropathy (n = 151), painful peripheral nerve injury (n = 335), and postherpetic neuralgia (n = 97) and propose sample sizes of study populations that need to be screened to reach a subpopulation large enough to conduct a phenotype-stratified study. The most common phenotype in diabetic polyneuropathy was sensory loss (83%), followed by mechanical hyperalgesia (75%) and thermal hyperalgesia (34%, note that percentages are overlapping and not additive). In peripheral nerve injury, frequencies were 37%, 59%, and 50%, and in postherpetic neuralgia, frequencies were 31%, 63%, and 46%. For parallel study design, either the estimated effect size of the treatment needs to be high (>0.7) or only phenotypes that are frequent in the clinical entity under study can realistically be performed. For crossover design, populations under 200 patients screened are sufficient for all phenotypes and clinical entities with a minimum estimated treatment effect size of 0.5.

Patients with neuropathic pain are heterogeneous in etiology, pathophysiology, and clinical appearance. They exhibit a variety of pain-related sensory symptoms and signs (sensory profile). Different sensory profiles might indicate different classes of neurobiological mechanisms, and hence subgroups with different sensory profiles might respond differently to treatment. The aim of the investigation was to identify subgroups in a large sample of patients with neuropathic pain using hypothesis-free statistical methods on the database of 3 large multinational research networks (German Research Network on Neuropathic Pain (DFNS), IMI-Europain, and Neuropain). Standardized quantitative sensory testing was used in 902 (test cohort) and 233 (validation cohort) patients with peripheral neuropathic pain of different etiologies. For subgrouping, we performed a cluster analysis using 13 quantitative sensory testing parameters. Three distinct subgroups with characteristic sensory profiles were identified and replicated. Cluster 1 (sensory loss, 42%) showed a loss of small and large fiber function in combination with paradoxical heat sensations. Cluster 2 (thermal hyperalgesia, 33%) was characterized by preserved sensory functions in combination with heat and cold hyperalgesia and mild dynamic mechanical allodynia. Cluster 3 (mechanical hyperalgesia, 24%) was characterized by a loss of small fiber function in combination with pinprick hyperalgesia and dynamic mechanical allodynia. All clusters occurred across etiologies but frequencies differed. We present a new approach of subgrouping patients with peripheral neuropathic pain of different etiologies according to intrinsic sensory profiles. These 3 profiles may be related to pathophysiological mechanisms and may be useful in clinical trial design to enrich the study population for treatment responders., Competing Interests: Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.