Abstract
Liver injury in Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) is a multifaceted disorder, lacking cohort homogeneity due to a variety of potential causes, including drugs, arsenic and other heavy metals, glyphosate, infections, and ultraviolet radiation. The goals of this review were (1) to analyze the role of diagnostic algorithms in assessing causality for potential culprits involved in the development of liver injury associated with immune-mediated SJS and TEN, which represent immune-based variant disorders within a continuous spectrum. Milder forms are classified as SJS or SJS/TEN overlap, while TEN is known as the most serious form; and (2) to interpret the findings that allow for the characterization of the different types of these disorders. The manuscript is based on an extensive literature search for single case reports, case cohorts, and review articles. Search terms included: Stevens-Johnson Syndrome, Toxic Epidermal Necrolysis, and specific diagnostic algorithms such as the Roussel Uclaf Causality Assessment Method (RUCAM) and the Algorithm of Drug Causality for Epidermal Necrolysis (ALDEN). For the purpose of basic feature description, the uniform term SJS/TEN is used in the current analysis. SJS/TEN presents with five different cohort types: SJS/TEN type (1), which refers to a cohort of SJS/TEN caused by drugs, as assessed by both ALDEN and RUCAM; type (2), representing SJS/TEN due to drugs and assessed by ALDEN only, but not by RUCAM; type (3), which includes a cohort of SJS/TEN caused by drugs, assessed by non-ALDEN and non-RUCAM tools; type (4), which focuses on a cohort of SJS/TEN caused by non-drug culprits, assessed by various tools; and type (5), which considers a cohort of SJS/TEN caused by unknown culprits. Using this new SJS/TEN typology will help better characterize individual features, personalize treatment, and clarify pathogenetic specifics for each of the five disease types. This new SJS/TEN typology provides clarity by replacing issues of inhomogeneity with cohort homogeneity.