Cancer Control (Oct 2024)

Prescription Opioid Use before and after Diagnosis of Cancer Among Older Cancer Survivors With Non-Cancer Chronic Pain Conditions (NCPCs): An Application of Group-Based Trajectory Modeling (GBTM)

  • Rudi Safarudin,
  • Traci LeMasters,
  • Salman Khan,
  • Usha Sambamoorthi

DOI
https://doi.org/10.1177/10732748241290769
Journal volume & issue
Vol. 31

Abstract

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Background Prescription opioids are essential in managing pain among adults with chronic pain conditions. However, persistent use over time can lead to negative health consequences. Identifying individuals with persistent use over time and their characteristics can inform clinical decision-making and aid in reducing the risk of abuse and overdose deaths. Objective This study aims to examine trajectories of prescription opioid use over time and factors associated with these trajectories among older cancer survivors with any non-cancer pain conditions (NCPC). Methods We conducted a retrospective cohort study design with longitudinal data of older (age at cancer diagnosis ≥67 years) cancer (incident breast, colorectal, and prostate cancers, or non-Hodgkin lymphoma) survivors with any NCPC. Data were derived from the 2007-2015 linked Surveillance, Epidemiology, and End Results (SEER)-Medicare dataset (N = 35,071). Group-Based Trajectory Modeling (GBTM) was used to identify homogeneous subgroups (distinct trajectories) of individuals based on every 90-day prescription opioid use during pre-cancer diagnosis (t 1 -t 4 ), acute cancer treatment (t 5 -t 8 ), and post-cancer treatment (t 9 -t 12 ) periods. Biological factors, social determinants of health (SDoH), physical and mental health, medication use, health care use, and external factors associated with a trajectory membership were analyzed with multivariable multinomial logistic regressions. Results Four distinct trajectories of opioid use were identified: (1) increase-decrease use (6.1%); (2) short-term use after cancer diagnosis (40.6%); (3) low-use (41.0%); and (4) persistent use (12.3%). In the fully-adjusted multinomial logistic regression, the SDoH such as Non-Hispanic Black [adjusted odds ratios (AOR) = 1.69; 95%CI = 1.48, 1.93)] and rural residence (AOR = 1.49; 95%CI = 1.15, 1.94)], comorbid anxiety (AOR = 1.33; 95%CI = 1.18, 1.51), and medication use (NSAIDs - AOR = 1.20; 95%CI = 1.10, 1.30) were associated with membership in the persistent use group. Persistent use was less likely among those with higher fragmented care index (AOR = 0.95, 95%CI = 0.93, 0.97) and those living in counties with higher Medicare advantage penetration (AOR = 0.96; 95%CI = 0.95, 0.97). Conclusions One in eight older adults had persistent opioid use over time. The profile characteristics of this group were different from the other trajectory groups. Policies and programs to reduce chronic opioid use need to consider the intra- and inter-individual variability to reduce opioid-related morbidity and mortality.