Pharmacodynamic analysis of the analgesic effect of capsaicin 8% patch (QutenzaTM) in diabetic neuropathic pain patients: detection of distinct response groups
Christian Martini1,*, Ashraf Yassen2,*, Erik Olofsen1, Paul Passier2, Malcom Stoker3, Albert Dahan1
1Department of Anesthesiology, Leiden University Medical Center, Leiden, The Netherlands; 2Global Clinical Pharmacology and Exploratory Development, Astellas Pharma Global Development Europe, Leiderdorp, The Netherlands; 3Global Medical Sciences, Astellas Pharma Global Development Europe, Leiderdorp, The Netherlands
*These authors contributed equally to this work
Abstract: Treatment of chronic pain is associated with high variability in the response to pharmacological interventions. A mathematical pharmacodynamic model was developed to quantify the magnitude and onset/offset times of effect of a single capsaicin 8% patch application in the treatment of painful diabetic peripheral neuropathy in 91 patients. In addition, a mixture model was applied to objectively match patterns in pain-associated behavior. The model identified four distinct subgroups that responded differently to treatment: 3.3% of patients (subgroup 1) showed worsening of pain; 31% (subgroup 2) showed no change; 32% (subgroup 3) showed a quick reduction in pain that reached a nadir in week 3, followed by a slow return towards baseline (16% ± 6% pain reduction in week 12); 34% (subgroup 4) showed a quick reduction in pain that persisted (70% ± 5% reduction in week 12). The estimate of the response-onset rate constant, obtained for subgroups 1, 3, and 4, was 0.76 ± 0.12 week-1 (median ± SE), indicating that every 0.91 weeks the pain score reduces or increases by 50% relative to the score of the previous week (= t½). The response-offset rate constant could be determined for subgroup 3 only and was 0.09 ± 0.04 week-1 (t½ 7.8 weeks). The analysis allowed separation of a heterogeneous neuropathic pain population into four homogenous subgroups with distinct behaviors in response to treatment with capsaicin. It is argued that this model-based approach may have added value in analyzing longitudinal chronic pain data and allows optimization of treatment algorithms for patients suffering from chronic pain conditions.
Keywords: diabetic neuropathic pain, capsaicin 8%, modeling, mixture model
This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.Download Article [PDF] View Full Text [HTML][Machine readable]