Antidepressant drug–drug–drug interactions associated with unintentional traumatic injury: Screening for signals in real‐world data

Abstract

Antidepressants are associated with traumatic injury and are widely used with other medications. It remains unknown how drug–drug–drug interactions (3DIs) between antidepressants and two other drugs may impact potential injury risks associated with antidepressants. We aimed to generate hypotheses regarding antidepressant 3DI signals associated with elevated injury rates. Using 2000–2020 Optum's de‐identified Clinformatics Data Mart, we performed a self‐controlled case series study for each drug triad consisting of an antidepressant + codispensed drug (base‐pair) with a candidate interacting medication (precipitant). We included persons aged greater than or equal to 16 years who (1) experienced an injury and (2) used a candidate precipitant, during base‐pair therapy. We compared injury rates during observation time exposed to the drug triad versus the base‐pair only, adjusting for time‐varying covariates. We calculated adjusted rate ratios (RRs) using conditional Poisson regression and accounted for multiple comparisons via semi‐Bayes shrinkage. Among 147,747 eligible antidepressant users with an injury, we studied 120,714 antidepressant triads, of which 334 (0.3%) were positively associated with elevated injury rates and thus considered potential 3DI signals. Adjusted RRs for signals ranged from 1.31 (1.04–1.65) for sertraline + levothyroxine with tramadol (vs. without tramadol) to 6.60 (3.23–13.46) for escitalopram + simvastatin with aripiprazole (vs. without aripiprazole). Nearly half of the signals (137, 41.0%) had adjusted RRs greater than or equal to 2, suggesting strong associations with injury. The identified signals may represent antidepressant 3DIs of potential clinical concern and warrant future etiologic studies to test these hypotheses.

Screening of dermatology drugs for aberrant use‐patterns: An application of epidemiologic estimates and measures of inequality in drug use

“…databases containing information on individual drug users are increasingly used for screening and evaluating unknown drug effects. [4][5][6][7][8] In addition, evaluating drug utilization patterns by epidemiological measures and by assessment of inequality in drug use may be an important tool for identifying inappropriate or unexpected drug use.…”

“…Occasionally, suboptimal or wrongful use is less obvious and may only be discovered by intentional efforts such as surveillance or screening 3 . Real‐world healthcare databases containing information on individual drug users are increasingly used for screening and evaluating unknown drug effects 4–8 . In addition, evaluating drug utilization patterns by epidemiological measures and by assessment of inequality in drug use may be an important tool for identifying inappropriate or unexpected drug use.…”