Transdiagnostic factors predicting prescription opioid-use disorder severity: A 12-month prospective study in patients on long-term opioid therapy for chronic pain.

Abstract

Research has suggested that transdiagnostic factors related to reward, cognitive, and regulatory processes are involved in addictive behaviors and the experience of pain. However, studies of Prescription Opioid-Use Disorder (POUD) in a chronic pain population are scarce. This study aimed to analyze the predictive power of anticipatory pleasure experience, obsessive-compulsive behavior, cognitive control, emotion dysregulation, and sleep on POUD severity in chronic pain patients on long-term opioid therapy. A three-wave prospective study was conducted in a sample of 67 patients. Individual interviews were held to collect self-reported data on transdiagnostic factors, POUD, and sociodemographic and clinical variables. Statistical analysis included repeated measures multinomial mixed models, unadjusted and covariate-adjusted. Rates of moderate-severe POUD significantly increased at 6- and 12-month follow-ups compared to initial assessment. The inability to experience anticipatory pleasure (OR [95 %CI] = 0.93 [0.89-0.98]), emotion dysregulation (OR = 1.06 [1.03-1.10]), and poorer sleep quality (OR = 1.25 [1.07-1.45]) predicted moderate-severe POUD even in the adjusted models (p< 0.05). In contrast, obsessive-compulsive behavior (OR = 1.02 [0.99-1.06]) was no longer significant after adjustment for covariates (p> 0.05). In addition, cognitive control was the only factor that predicted both mild (OR = 0.96 [0.93-0.99]) and moderate-severe (OR = 0.94 [0.90-0.98]) disorder (p< 0.05). Furthermore, when all transdiagnostic factors were included in a single model, cognitive control and anticipatory pleasure experience emerged as the strongest predictors of POUD severity, respectively (p< 0.05). The identification of key transdiagnostic factors related to POUD severity allows for a more specific profiling of patients at increased risk, potentially leading to improved treatment targets for chronic pain population on opioid therapy.