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

Support Care Cancer. 2017 Sep;25(9):2863-2869. doi: 10.1007/s00520-017-3702-z. Epub 2017 Apr 6.

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.

Keywords: Cancer; Edmonton classification system for cancer pain; Neuropathic; Pain.

MeSH terms

  • Aged
  • Female
  • Humans
  • Male
  • Middle Aged
  • Neoplasms / complications*
  • Neoplasms / psychology
  • Pain / classification*
  • Pain Management / methods*
  • Prognosis
  • Retrospective Studies
  • Treatment Outcome