Division of Dermatology, Department of Medicine, Faculty of Medicine, The Skin and Allergy Research Unit, Chulalongkorn University, Bangkok, Thailand.
Biostatistics Excellence Center, Research Affairs, Faculty of Medicine, The Skin and Allergy Research Unit, Chulalongkorn University, Bangkok, Thailand.
J Eur Acad Dermatol Venereol. 2023 Sep;37(9):1881-1890. doi: 10.1111/jdv.19222. Epub 2023 May 27.
At present, no predictive models are available to determine the probability of in-hospital mortality rates (HMRs) in all phenotypes of severe cutaneous adverse reactions (SCARs).
Our study explored whether simple clinical and laboratory assessments could help predict the HMRs in any phenotypes of SCAR patients.
Factors influencing HMRs in 195 adults diagnosed with different SCAR phenotypes were identified, and their optimal cut-offs were determined by Youden's index. Predictive equations for HMRs for all SCAR patients and Stevens-Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN) patients were determined using the exact logistic regression models.
Acute generalized exanthematous pustulosis (AGEP) patients were significantly older, with a short time from drug exposure to reaction, and higher neutrophil count compared to SJS/TEN and drug reaction with eosinophilia and systemic symptoms (DRESS, p < 0.001). Peripheral blood eosinophilia, atypical lymphocytosis and elevated liver transaminase enzymes were significantly higher in DRESS. SJS/TEN phenotype, age ≥ 71.5 years, neutrophil-to-lymphocyte ratio ≥ 4.08 (high NLR) and systemic infection were factors predicting in-hospital mortality in all SCAR subjects. The ALLSCAR model developed from these factors demonstrated high-diagnostic accuracy for predicting HMRs in all SCAR phenotypes (area under the receiver-operator curve (AUC) = 0.95). The risk of in-hospital death was significantly increased in SCAR patients with high NLR after adjusting for systemic infection. The model derived from high NLR, systemic infection and age yielded higher accuracy than SCORTEN (AUC = 0.77) for predicting the HMRs in SJS/TEN patients (AUC = 0.97).
Being older, having systemic infection, having a high NLR and SJS/TEN phenotype increases ALLSCAR scores, which in turn increases the risk of in-hospital mortality. These basic clinical and laboratory parameters can easily be obtained in any hospital setting. Despite its simple approach, further validation of the model is warranted.
目前，尚无预测模型可用于确定所有严重皮肤不良反应（SCAR）表型的院内死亡率（HMR）概率。
本研究探讨简单的临床和实验室评估是否有助于预测任何 SCAR 患者表型的 HMR。
确定了 195 例不同 SCAR 表型患者的 HMR 影响因素，并通过 Youden 指数确定其最佳截断值。使用精确逻辑回归模型确定所有 SCAR 患者和史蒂文斯-约翰逊综合征（SJS）/中毒性表皮坏死松解症（TEN）患者 HMR 的预测方程。
急性全身性发疹性脓疱病（AGEP）患者年龄明显较大，从药物暴露到反应的时间较短，中性粒细胞计数高于 SJS/TEN 和药物反应伴嗜酸性粒细胞增多和全身症状（DRESS，p < 0.001）。DRESS 外周血嗜酸性粒细胞、非典型淋巴细胞增多和肝转氨酶升高更为明显。SJS/TEN 表型、年龄≥71.5 岁、中性粒细胞与淋巴细胞比值≥4.08（高 NLR）和全身感染是所有 SCAR 患者住院死亡率的预测因素。从这些因素中开发的 ALLSCAR 模型对所有 SCAR 表型的 HMR 预测具有较高的诊断准确性（受试者工作特征曲线下面积（AUC）= 0.95）。在调整全身感染后，NLR 较高的 SCAR 患者的住院死亡风险显著增加。与 SCORTEN（AUC=0.77）相比，从高 NLR、全身感染和年龄得出的模型预测 SJS/TEN 患者 HMR 的准确性更高（AUC=0.97）。
年龄较大、有全身感染、高 NLR 和 SJS/TEN 表型会增加 ALLSCAR 评分，从而增加住院死亡率。这些基本的临床和实验室参数可以在任何医院环境中轻松获得。尽管方法简单，但仍需要进一步验证该模型。
