Shou Yanhong, Yang Lu, Yang Yongsheng, Zhu Xiaohua, Li Feng, Yin Bo, Zheng Yingyan, Xu Jinhua
Department of Dermatology, Huashan Hospital, Fudan University, Shanghai, 200040, China.
Department of Radiology, Huashan Hospital, Fudan University, Shanghai, 200040, China.
Front Med. 2021 Aug;15(4):585-593. doi: 10.1007/s11684-020-0817-2. Epub 2021 Mar 1.
Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare but severe diseases. This study aimed to validate the predictive ability of risk models in patients with SJS/TEN and propose possible refinement in China. Patients in the Department of Dermatology of Huashan Hospital from January 2008 to January 2019 were included. Results showed that the severity-of-illness score for TEN (SCORTEN) had a good discrimination (area under the receiver operating characteristic curve (AUC), 0.78), and it was superior to auxiliary score (AS) and ABCD-10, which indicates age, bicarbonate level, cancer, dialysis, and 10% involved body surface area (AUC, 0.69 and 0.68, respectively). The calibration of SCORTEN (Hosmer-Lemeshow goodness-of-fit test, P = 0.69) was also better than that of AS (P = 0.25) and ABCD-10 (P = 0.55). SCORTEN and ABCD-10 were similar (Brier score (BS), 0.04 and 0.04) in terms of accuracy of predictions. In addition, the imaging appearance of pulmonary consolidation on computed tomography was associated with high mortality. Refined models were formed using the variables and this imaging appearance. The refined AS and ABCD-10 models were similar in discrimination compared with the original SCORTEN (0.74 vs. 0.78, P = 0.23; 0.74 vs. 0.78, P = 0.30, respectively). Therefore, SCORTEN showed good discrimination performance, calibration, and accuracy, and refined AS or ABCD-10 model may be an option when SCORTEN variables are not available.
史蒂文斯-约翰逊综合征(SJS)和中毒性表皮坏死松解症(TEN)是罕见但严重的疾病。本研究旨在验证 SJS/TEN 患者风险模型的预测能力,并在中国提出可能的改进。纳入华山医院皮肤科 2008 年 1 月至 2019 年 1 月的患者。结果表明,TEN 严重程度评分(SCORTEN)具有良好的区分能力(接受者操作特征曲线下面积(AUC)为 0.78),优于辅助评分(AS)和 ABCD-10,分别为年龄、碳酸氢盐水平、癌症、透析和 10%体表面积(AUC 分别为 0.69 和 0.68)。SCORTEN 的校准(Hosmer-Lemeshow 拟合优度检验,P=0.69)也优于 AS(P=0.25)和 ABCD-10(P=0.55)。在预测准确性方面,SCORTEN 和 ABCD-10 的 Brier 得分(BS)相似(0.04 和 0.04)。此外,CT 上肺实变的影像学表现与高死亡率相关。使用这些变量和这种影像学表现形成了改良模型。改良后的 AS 和 ABCD-10 模型与原始 SCORTEN 相比在区分度上相似(0.74 与 0.78,P=0.23;0.74 与 0.78,P=0.30)。因此,SCORTEN 具有良好的区分性能、校准和准确性,当无法获得 SCORTEN 变量时,改良的 AS 或 ABCD-10 模型可能是一种选择。