Patient Subgroups and Predictors of Improvement in Chronic Neuropathic Pain: A Trajectory-Based Analysis

Area of Science:

• Pain Medicine
• Neurology
• Clinical Research

Background:

• Limited real-world evidence exists on predicting outcomes for chronic neuropathic pain (NP) in multidisciplinary tertiary care.
• Identifying patient subgroups with similar pain trajectories is crucial for effective management.

Purpose of the Study:

• To identify subgroups of chronic neuropathic pain patients with distinct pain trajectories.
• To evaluate factors associated with different pain trajectories and treatment responses.

Main Methods:

• Analysis of data from 912 chronic neuropathic pain patients (baseline pain ≥4/10) from the Quebec Pain Registry.
• Group-based trajectory modeling (GBTM) to identify pain intensity and interference trajectories.
• Multiple imputation for missing data, with results confirmed by group-mixture modeling and GBTM on complete data.

Main Results:

• A three-class trajectory model best described pain intensity and interference.
• Only 23.1% of patients showed significant pain intensity improvement, and 23.5% showed pain interference improvement.
• Lower baseline pain intensity/interference predicted better outcomes; strong opioid use was linked to persistent severe pain.

Conclusions:

• A minority of chronic neuropathic pain patients experience significant improvement with current multidisciplinary treatments.
• Findings highlight limitations in current NP management and the need for novel therapeutic approaches.
• Trajectory analysis is valuable for personalized NP management in multidisciplinary settings.