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Proportion of Antiepileptic Drug-Associated Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis: A Meta-Analysis

Lee EY, Knox C, Sugumar C, Phillips EJ

JAMA dermatology, 2026

4,403 participants

Abstract

Importance: Antiepileptic drugs (AEDs) are frequently implicated in Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN), which are the most severe type of drug hypersensitivity reaction, with a mortality rate up to 50%. However, the overall proportion of these cases attributed to AEDs has not been systematically reviewed.

Objective: To evaluate the proportion of AED-associated SJS/TEN.

Data sources: The MEDLINE and Embase databases were searched from inception through March 17, 2026, with results limited to English-language publications and human participants.

Study selection: All experimental and observational studies that reported patient-level triggers of SJS/TEN were included.

Data extraction and synthesis: Two reviewers independently screened studies and extracted data using a predefined template. To estimate the proportion of AED-associated SJS/TEN, a random-effects meta-analysis was performed, calculating the pooled proportions with 95% CIs. Subgroup analyses by age group (children vs adults) and geographic region were performed to explore heterogeneity.

Main outcomes and measures: To estimate the proportion of AED-associated SJS/TEN.

Results: This systematic review and meta-analysis included 50 studies with 4403 patients that reported patient-level triggers of SJS/TEN. Single-drug triggers accounted for 88% (95% CI, 83-92) of cases. The pooled proportion of SJS/TEN cases attributed to AEDs was 23% (95% CI, 19-26). Nearly all AED-associated cases were…

How strong is the evidence?

Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 4,403 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

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