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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.

journal of pain research

Pharmacodynamic analysis of the analgesic effect of capsaicin 8% patch (QutenzaTM) in diabetic neuropathic pain patients: detection of distinct response groups