Characterizing Relationships Between Daily Pain, Opioid Use, and Mood in Patients With Advanced Cancer Using Ecological Momentary Assessments

PURPOSE In advanced cancer, pain symptoms, opioid use, and cognitive-emotional processes fluctuate day to day and may mutually reinforce one another. We used 28-day ecological momentary assessments (EMAs) to quantify within-person associations between daily pain and (a) interference, (b) opioid use and perceived efficacy, and (c) mood, and to test whether variability in pain catastrophizing moderates these associations. METHODS Patients with advanced cancer receiving outpatient oncology care at a comprehensive cancer center completed once-daily EMAs for 28 days (N = 26 analyzed). Measures included worst/average/least pain, pain interference, short-acting opioid tablets (count) and perceived opioid efficacy, negative and positive affect, and daily catastrophizing. Multilevel models estimated same-day within-person associations, controlling for study day and between-person mean pain. Individuals' standard deviation of daily catastrophizing changes (catastrophizing variability) was tested as a moderator. RESULTS Across 477 daily assessments (median 21/28 per participant), higher-than-usual worst pain was consistently associated with worse pain interference, higher short-acting opioid use, lower perceived opioid efficacy, and higher negative affect (all P < .01); Average and least pain showed smaller or nonsignificant effects. Greater day-to-day variability in catastrophizing was associated with worse pain. Among individuals whose pain catastrophizing fluctuated more, there was a stronger relationship between pain severity and interference, affect, and perceived opioid efficacy (inverse; P ≤ .01). CONCLUSION Greater day-to-day fluctuations in pain catastrophizing were associated with magnified correspondence of pain severity with interference, mood disruption, and perceived opioid inefficacy. Routine monitoring of pain severity combined with tracking catastrophizing variability may help identify high-risk days and inform in-the-moment support to better personalize pain management.