Abstract
Scrambler therapy is a noninvasive electroanalgesia technique designed to remodulate the pain system. Despite growing evidence of its efficacy in patients with neuropathic pain, little is known about the clinical factors associated with treatment outcome. We conducted a prospective, open-label, single-arm trial to assess the efficacy and safety of scrambler therapy in patients with chronic neuropathic pain of various etiologies. A post-hoc analysis was performed to investigate whether cluster analysis of the Neuropathic Pain Symptom Inventory (NPSI) profiles could identify a subgroup of patients regarding neuropathic pain phenotype and treatment outcome. Scrambler therapy resulted in a significant decrease in the pain numerical rating scale (NRS) score over 2 weeks of treatment (least squares mean of percentage change from baseline, − 15%; 95% CI − 28% to − 2.4%; p < 0.001). The mean score of Brief Pain Inventory (BPI) interference subdimension was also significantly improved (p = 0.022), while the BPI pain composite score was not. Hierarchical clustering based on the NPSI profiles partitioned the patients into 3 clusters with distinct neuropathic pain phenotypes. Linear mixed-effects model analyses revealed differential response to scrambler therapy across clusters (p = 0.003, pain NRS; p = 0.072, BPI interference subdimension). Treatment response to scrambler therapy appears different depending on the neuropathic pain phenotypes, with more favorable outcomes in patients with preferentially paroxysmal pain rather than persistent pain. Further studies are warranted to confirm that capturing neuropathic pain phenotypes can optimize the use of scrambler therapy.
Highlights
Complex mechanism-phenotype relationships, it would be useful to analyze the pattern of pain-related symptom profiles as a whole, rather than individual symptoms and signs
Using the validated symptom-based questionnaires or quantitative sensory testing (QST), researchers have identified subgroups of patients characterized by distinct neuropathic pain phenotypes, which might be related to specific pathophysiologic m echanisms[21,26]
A post-hoc cluster analysis was performed to investigate whether clustering based on the pain-related symptom profiles (NPSI) can identify distinct subgroups of patients with regard to neuropathic pain phenotype and response to scrambler therapy
Summary
Complex mechanism-phenotype relationships, it would be useful to analyze the pattern of pain-related symptom profiles as a whole, rather than individual symptoms and signs. A post-hoc cluster analysis was performed to investigate whether clustering based on the pain-related symptom profiles (NPSI) can identify distinct subgroups of patients with regard to neuropathic pain phenotype and response to scrambler therapy. P-value Cluster 1 (n = 8) Cluster 2 (n = 10) Cluster 3 (n = 9) P-value was significantly improved with scrambler therapy (p = 0.022 for the effect of time), whereas the composite score for the BPI pain subdimension (mean of the 4 pain items) did not change significantly (Table 2).
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