Joseph Arthur1, Kimberson Tanco2, Ali Haider2, Courtney Maligi2, Minjeong Park3, Diane Liu3, Eduardo Bruera2. 1. Department of Palliative Care & Rehabilitation Medicine, Unit 1414, The University of Texas MD Anderson Cancer, 1515 Holcombe Boulevard, Houston, TX, 77030, USA. jaarthur@mdanderson.org. 2. Department of Palliative Care & Rehabilitation Medicine, Unit 1414, The University of Texas MD Anderson Cancer, 1515 Holcombe Boulevard, Houston, TX, 77030, USA. 3. Department of Biostatistics, The University of Texas MD Anderson Cancer, Houston, TX, USA.
Abstract
PURPOSE: The Edmonton Classification System for Cancer Pain (ECS-CP) has been shown to predict pain management complexity based on five features: pain mechanism, incident pain, psychological distress, addictive behavior, and cognitive function. The main objective of our study was to explore the association between ECS-CP features and pain treatment outcomes among outpatients managed by a palliative care specialist-led interdisciplinary team. METHODS: Initial and follow-up clinical information of 386 eligible supportive care outpatients were retrospectively reviewed and analyzed. RESULTS: Between the initial consultation and the first follow-up visit, the median ESAS pain intensity improved from 6 to 4.5 (p < 0.0001) and the median total symptom distress score (0-100) improved from 38 to 31 (p < 0.0001). At baseline, patients with neuropathic pain (p < 0.001) and those with at least one ECS-CP feature (p = 0.006) used a higher number of adjuvant medications. At follow-up, patients with neuropathic pain were less likely to achieve their personalized pain goal (PPG) (29 vs 72%, p = 0.015). No statistically significant association was found between increasing sum of ECS-CP features and any of the pain treatment outcomes at follow-up. CONCLUSION: Neuropathy was found to be a poor prognostic feature in advanced cancer pain management. Increasing sum of ECS-CP features was not predictive of pain management complexity at the follow-up visit when pain was managed by a palliative medicine specialist. Further research is needed to further explore these observations.
PURPOSE: The Edmonton Classification System for Cancer Pain (ECS-CP) has been shown to predict pain management complexity based on five features: pain mechanism, incident pain, psychological distress, addictive behavior, and cognitive function. The main objective of our study was to explore the association between ECS-CP features and pain treatment outcomes among outpatients managed by a palliative care specialist-led interdisciplinary team. METHODS: Initial and follow-up clinical information of 386 eligible supportive care outpatients were retrospectively reviewed and analyzed. RESULTS: Between the initial consultation and the first follow-up visit, the median ESAS pain intensity improved from 6 to 4.5 (p < 0.0001) and the median total symptom distress score (0-100) improved from 38 to 31 (p < 0.0001). At baseline, patients with neuropathic pain (p < 0.001) and those with at least one ECS-CP feature (p = 0.006) used a higher number of adjuvant medications. At follow-up, patients with neuropathic pain were less likely to achieve their personalized pain goal (PPG) (29 vs 72%, p = 0.015). No statistically significant association was found between increasing sum of ECS-CP features and any of the pain treatment outcomes at follow-up. CONCLUSION:Neuropathy was found to be a poor prognostic feature in advanced cancer pain management. Increasing sum of ECS-CP features was not predictive of pain management complexity at the follow-up visit when pain was managed by a palliative medicine specialist. Further research is needed to further explore these observations.
Entities:
Keywords:
Cancer; Edmonton classification system for cancer pain; Neuropathic; Pain
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