Assessing the prognostic features of a pain classification system in advanced cancer patients

作者：Arthur Joseph^*; Tanco Kimberson; Haider Ali; Maligi Courtney; Park Minjeong; Liu Diane; Bruera Eduardo

来源：Supportive Care in Cancer, 2017, 25(9): 2863-2869.

DOI：10.1007/s00520-017-3702-z

• Cancer
• Pain
• Neuropathic
• Edmonton classification system for cancer pain

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.

• 出版日期2017-9