Development and validation of prognostic models using novel inflammatory markers for drug reactions with eosinophilia and systemic symptoms: An international multicenter cohort study.
Journal
Journal of the American Academy of Dermatology
ISSN
1097-6787
Date Issued
2025-07-15
Author(s)
Hsieh, Tyng-Shiuan
Lee, Haur Yueh
Abe, Riichiro
Takei, Shingo
Hayashi, Ryota
Hama, Natsumi
Abstract
Background: Drug reaction with eosinophilia and systemic symptoms (DRESS) is a life-threatening disease that has received little attention focusing on its prognostic markers.
Objective: We evaluated the association between novel inflammatory markers and in-hospital mortality. We also proposed and validated a risk stratification model to aid early intervention.
Methods: This international multicenter, retrospective cohort study included 169 patients diagnosed with DRESS from Taiwan, Singapore, and Japan, collecting demographics and laboratory markers within 3 days of diagnosing DRESS. Inflammatory markers were calculated, and statistical analyses, including logistic regression and receiver operating characteristic curve analysis. Predictive models were developed with internal validation using leave-one-out cross-validation.
Results: Lower hemoglobin-to-red blood cell distribution width ratio, higher platelet-to-lymphocyte ratio, and lower monocyte count are identified as significant predictors of mortality in a multivariate analysis. A predictive model for DRESS-related mortality, incorporating the significant inflammatory markers and underlying disease (malignancy, autoimmune disease, and cardiovascular disease), demonstrated good discrimination ability and acceptable accuracy.
Limitation: The retrospective design, along with factors like interhospital transfers, and underlying malignancies are limitations.
Conclusion: The presence of these novel inflammatory markers and the development of risk stratification model may be of value to stratification of the severity of DRESS.
Subjects
drug reaction with eosinophilia and systemic symptom
novel inflammatory markers
prognostic models
risk stratification
severe cutaneous adverse reaction
SDGs
Type
journal article