Abstract
OBJECTIVES: People receiving medications for opioid use disorder often continue to experience opioid withdrawal, creating barriers to improved outcomes. Emerging evidence suggests the existence of distinct opioid withdrawal subtypes characterized by high and low levels of withdrawal severity, highlighting the need for personalized treatment approaches. To inform clinical practice, we identified subgroups of adults based on levels of opioid withdrawal over time during opioid use disorder (OUD) treatment. METHODS: We conducted a secondary analysis of the Clinical Trials Network (CTN-0051) Extended-Release Naltrexone versus Buprenorphine for Opioid Treatment trial using latent class growth analysis to identify subgroups of withdrawal. Four hundred and seventy-four participants in an OUD trial were randomized to receive extended-release naltrexone (XR-NTX) or sublingual buprenorphine-naloxone (BUP-NX). Withdrawal symptoms were measured using the Subjective Opiate Withdrawal Scale (SOWS) at 10 timepoints. We identified classes and compared their predictors of withdrawal and time to return to opioid use. RESULTS: Two distinct trajectories - low and high sustained opioid withdrawal - were identified in each treatment arm. Most participants were in the low withdrawal class (n = 176; 86 % XR-NTX and n = 241; 89 % BUP-NX) with fewer in the high sustained withdrawal class (n = 28; 14 % XR-NTX and n = 29; 11 % BUP-NX). Differences in lifetime history of anxiety and depression and in quality of life domains (mobility, usual activities, and pain/discomfort) were primarily observed among XR-NTX participants, with only one baseline mobility difference emerging between BUP-NX classes. In the XR-NTX arm, time to return to use was significantly shorter in the high sustained withdrawal class compared to the low withdrawal class, whereas BUP-NX classes did not differ on time to return to use. DISCUSSION AND CONCLUSIONS: Our findings demonstrate the existence of distinct high and low opioid withdrawal subtypes among individuals receiving XR-NTX and BUP-NX. These results underscore the importance of personalized withdrawal management strategies and highlight the need to consider individual withdrawal trajectories when optimizing treatments. Future research should focus on identifying predictors of withdrawal severity to improve clinical outcomes.