Immune Checkpoint Inhibitor-Related Epidermal Necrosis: Terminology, Pathology, and Clinical Implications

Immune checkpoint inhibitors (ICIs) can trigger severe cutaneous adverse reactions that mimic Stevens-Johnson syndrome/toxic epidermal necrolysis. Reports describe a wide spectrum of cutaneous reactions, including epidermal necrosis, raising questions about whether this represents a distinct clinicopathologic entity.

To review the literature on ICI-related epidermal necrosis (ICIREN), examining terminology, histopathologic features, clinical course, pathophysiology, the pathologist's role in diagnosis, and implications for management.

A systematic literature search of PubMed and relevant conference proceedings was conducted. Key sources include case series, retrospective reviews, and mechanistic studies detailing ICIREN.

ICIs have transformed cancer therapy but are associated with a spectrum of immune-related adverse events, notably cutaneous toxicities. Among the most severe is ICIREN, a reaction that can clinically resemble Stevens-Johnson syndrome and toxic epidermal necrolysis but may follow a distinct, more indolent course. Emerging terminology, including progressive immunotherapy-related mucocutaneous eruption, reflects growing recognition that not all cases fit the paradigm of classic drug-induced Stevens-Johnson syndrome/toxic epidermal necrolysis. ICIREN often presents with delayed onset, variable progression, limited mucosal involvement, and distinct histopathologic features such as lichenoid interface dermatitis and adnexal involvement. Understanding these differences is crucial, as early recognition and management may allow patients to safely continue ICI therapy. The underlying pathogenesis involves checkpoint blockade-driven T-cell activation with potential amplification by additional drug exposures. This review aims to equip pathologists and clinicians with a structured approach to the diagnosis, reporting, and multidisciplinary management of ICIREN, emphasizing the need for clinicopathologic correlation to optimize patient outcomes.