The Association Between Dextromethorphan/Bupropion with Alcohol and Substance Misuse: Reports to the Food and Drug Administration Adverse Event Reporting System (FAERS)
Bibliographic record
Abstract
OBJECTIVE: Dextromethorphan/bupropion (DXM/BUP) received Food and Drug Administration (FDA) approval for the treatment of adults with major depressive disorder (MDD) in August 2022. This combination is not known to have abuse liability and is not currently scheduled by the Drug Enforcement Administration (DEA). Notwithstanding, dextromethorphan is a drug of abuse. Herein, we sought to determine whether DXM/BUP has alcohol and/or substance misuse liability. METHODS: We evaluated spontaneous reports of terms such as "alcohol problem, alcoholism, alcohol abuse, substance dependence, substance use disorder (SUD), substance abuse, drug dependence, drug use disorder and drug abuse" in the FDA Adverse Event Reporting System (FAERS). The FAERS is a spontaneous reporting database of adverse events submitted to the FDA. RESULTS: We performed a comparative assessment of the alcohol and/or substance misuse liability of DXM/BUP since its market authorization in August 2022, using acetaminophen as the control. Dextromethorphan served as the upper-bound reference point. Our findings showed that, since August 2022, dextromethorphan had a significant reporting odds ratio (ROR) for "drug abuse." In contrast, DXM/BUP did not have a significant ROR for any of the categories of alcohol and/or substance misuse evaluated. Limitations of our findings derive largely from the limitations of the FAERS and its data capture method. CONCLUSION: The absence of alcohol or substance misuse reported to the FAERS with DXM/BUP accords with the lack of evidence of abuse liability prior to FDA approval and its non-scheduling by the DEA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".