Background: The extent to which clinical trials of medications for opioid use disorder (MOUD) are representative or not is unknown. Some patient characteristics modify MOUD effectiveness; if these same characteristics differ in distribution between the trial population and usual-care population, this could contribute to lack of generalizability-a discrepancy between trial and usual-care effectiveness. Our objective was to identify interpretable, multidimensional subgroups who were prescribed MOUD in substance use treatment programs in the US but who were not represented or under-represented by clinical trial participants.
Methods: This was a secondary descriptive analysis of trial and real-world data. The trial data included twenty-seven US opioid treatment programs in the National Drug Abuse Treatment Clinical Trials Network, N = 2,199 patients. The real-world data included US substance use treatment programs that receive public funding, N = 740,015 patients. We characterized real-world patient populations who were non-represented and under-represented in the trial data in terms of sociodemographic and clinical characteristics that could modify MOUD effectiveness.
Results: We found that 10.7% of MOUD patients in TEDS-A were not represented in the three clinical trials. As expected, pregnant MOUD patients (n = 19,490) were not represented. Excluding pregnancy, education and marital status from the characteristics, 2.6% of MOUD patients were not represented. Patients aged 65 years and older (n = 11,204), and those 50-64 years who identified as other (non-White, non-Black, and non-Hispanic) race/ethnicity or multi-racial (n = 7,281) were under-represented.
Conclusions: Quantifying and characterizing non- or under-represented subgroups in trials can provide the data necessary to improve representation in future trials and address research-to-practice gaps.
Keywords: Clinical Trials; External validity; Generalizability; MOUD; Trial representation.