| アブストラクト | 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. |
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