Orphanet Journal of Rare Diseases (Sep 2012)

Toxic epidermal necrolysis, DRESS, AGEP: Do overlap cases exist?

  • Bouvresse Sophie,
  • Valeyrie-Allanore Laurence,
  • Ortonne Nicolas,
  • Konstantinou Marie,
  • Kardaun Sylvia H,
  • Bagot Martine,
  • Wolkenstein Pierre,
  • Roujeau Jean-Claude

DOI
https://doi.org/10.1186/1750-1172-7-72
Journal volume & issue
Vol. 7, no. 1
p. 72

Abstract

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Abstract Background Severe cutaneous adverse reactions to drugs (SCARs) include acute generalized exanthematous pustulosis (AGEP), drug reaction with eosinophilia and systemic symptoms (DRESS) and epidermal necrolysis (Stevens-Johnson syndrome–toxic epidermal necrolysis [SJS-TEN]). Because of the varied initial presentation of such adverse drug reactions, diagnosis may be difficult and suggests overlap among SCARs. Overlapping SCARs are defined as cases fulfilling the criteria for definite or probable diagnosis of at least 2 ADRs according to scoring systems for AGEP, DRESS and SJS-TEN. We aimed to evaluate the prevalence of overlap among SCARs among cases in the referral hospital in France. Methods We retrospectively analyzed data for 216 patients hospitalized in the referral centre over 7 years with a discharge diagnosis of AGEP (n = 45), DRESS (n = 47), SJS-TEN (n = 80) or “drug rash” (n = 44). Each case with detailed clinical data and a skin biopsy specimen was scored for AGEP, DRESS and SJS-TEN by use of diagnostic scores elaborated by the RegiSCAR group. Results In total, 45 of 216 cases (21%) had at least 2 possible diagnoses: 35 had a single predominant diagnosis (definite or probable), 7 had several possible diagnoses and 3 (2.1% of 145 confirmed SCARs) were overlap SCARs. Conclusions Despite ambiguities among SCARs, confirmed overlap cases are rare. This study did not avoid pitfalls linked to its retrospective nature and selection bias. In the acute stage of disease, early identification of severe ADRs can be difficult because of clinical or biologic overlapping features and missing data on histology, biology and evolution. Retrospectively analyzing cases by use of diagnostic algorithms can lead to reliable discrimination among AGEP, DRESS and SJS-TEN.

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