Narrative review discusses Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis risks from various medications

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Frontiers in Medicine Published June 2, 2026 Medically reviewed June 2, 2026 DOI ↗ By Dr. Julia Lee, PhD · Oncology, Genomics & Drug Development

Key Takeaway

Note potential SJS/TEN risks with multiple medication classes in this narrative review.

This narrative review addresses the association between Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis and a broad range of medications. The scope includes antibiotics, antiepileptics, allopurinol, nonsteroidal anti-inflammatory drugs, proton pump inhibitors, immune checkpoint inhibitors, novel antiandrogens, carbonic anhydrase inhibitors, and antivirals. The authors synthesize existing knowledge regarding these potential adverse reactions without providing specific incidence rates or statistical analyses. The review does not report sample sizes, follow-up durations, or detailed safety data for the listed drug classes. Consequently, the conclusions remain qualitative and descriptive rather than quantitative. The authors note that specific adverse event rates and tolerability data were not reported in the source material. This lack of numerical detail limits the ability to assess the magnitude of risk for individual drugs. Clinicians should interpret these associations with caution given the absence of rigorous statistical evidence in this narrative format. The review serves to highlight potential safety concerns rather than to establish definitive causal links or provide precise risk estimates for clinical decision-making.

Study Details

Study typeSystematic review

EvidenceLevel 1

PublishedJun 2026

View Original Abstract ↓

Stevens-Johnson Syndrome (SJS) and Toxic Epidermal Necrolysis (TEN) are rare yet life-threatening severe cutaneous adverse drug reactions (SCARs), characterized by high mortality and substantial morbidity risks. Identifying potential high-risk drugs associated with SJS/TEN is crucial for guiding clinical preventive interventions, enabling early detection, and enhancing risk management. With the rapid advancement of data science, adverse drug reaction (ADR) database mining has emerged as a powerful tool for systematically investigating the drug-SJS/TEN association, effectively overcoming the limitations of traditional case reports and small-sample studies regarding data scale and conclusion generalizability. This review summarizes recent advances in identifying potential high-risk drugs for SJS/TEN based on ADR database mining, with all included studies retrieved from peer-reviewed journals and strictly focused on SJS/TEN. We classify and discuss the major potential high-risk drug categories, including antibiotics, antiepileptics, allopurinol, nonsteroidal anti-inflammatory drugs (NSAIDs), proton pump inhibitors (PPIs), immune checkpoint inhibitors (ICIs), novel antiandrogens, carbonic anhydrase inhibitors, antivirals, and others. We also summarize their associated genetic susceptibilities, median onset times, and underlying mechanisms. These findings provide valuable references for enhancing medication safety and mitigating severe adverse drug reactions in clinical practice.