Yang Ruiyuan, Li Kexin, Zou Cailun, Wee Aileen, Liu Jimin, Liu Liwei, Li Min, Wu Ting, Wang Yu, Ma Zikun, Wang Yan, Liu Jingyi, Huang Ang, Sun Ying, Chang Binxia, Liang Qingsheng, Jia Jidong, Zou Zhengsheng, Zhao Xinyan
Liver Research Center, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Diseases, Beijing, China.
Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Front Pharmacol. 2022 Jul 22;13:934467. doi: 10.3389/fphar.2022.934467. eCollection 2022.
To develop, optimize, and validate a novel model using alanine aminotransferase (ALT) and total bilirubin (TB) dynamic evolution patterns in predicting acute liver failure (ALF) in drug-induced liver injury (DILI) patients. The demographics, clinical data, liver biopsy, and outcomes of DILI patients were collected from two hospitals. According to the dynamic evolution of ALT and TB after DILI onset, the enrolled patients were divided into ALT-mono-peak, TB-mono-peak, double-overlap-peak, and double-separate-peak (DSP) patterns and compared. Logistic regression was used to develop this predictive model in both discovery and validation cohorts. The proportion of ALF was significantly higher in patients with the DSP pattern than in the ALT-mono-peak pattern and DOP pattern (10.0 vs. 0.0% vs. 1.8%, < 0.05). The area under receiver operating characteristic curve (AUROC) of the DSP pattern model was 0.720 (95% CI: 0.682-0.756) in the discovery cohort and 0.828 (95% CI: 0.788-0.864) in the validation cohort in predicting ALF, being further improved by combining with international normalized ratio (INR) and alkaline phosphatase (ALP) (AUROC in the discovery cohort: 0.899; validation cohort: 0.958). Histopathologically, patients with the DSP pattern exhibited a predominantly cholestatic hepatitis pattern (75.0%, < 0.05) with a higher degree of necrosis (29.2%, = 0.084). DILI patients with the DSP pattern are more likely to progress to ALF. The predictive potency of the model for ALF can be improved by incorporating INR and ALP. This novel model allows for better identification of high-risk DILI patients, enabling timely measures to be instituted for better outcome.
利用丙氨酸氨基转移酶（ALT）和总胆红素（TB）的动态演变模式开发、优化并验证一种预测药物性肝损伤（DILI）患者急性肝衰竭（ALF）的新模型。从两家医院收集DILI患者的人口统计学资料、临床数据、肝活检及预后情况。根据DILI发病后ALT和TB的动态演变，将纳入患者分为ALT单峰型、TB单峰型、双峰重叠型和双峰分离型（DSP）模式并进行比较。在发现队列和验证队列中均使用逻辑回归开发此预测模型。DSP模式患者中ALF的比例显著高于ALT单峰型模式和双峰重叠型模式患者（10.0% 对0.0% 对1.8%，P<0.05）。在预测ALF方面，DSP模式模型在发现队列中的受试者工作特征曲线下面积（AUROC）为0.720（95%可信区间：0.682 - 0.756），在验证队列中为0.828（95%可信区间：0.788 - 0.864），通过结合国际标准化比值（INR）和碱性磷酸酶（ALP）可进一步改善（发现队列中的AUROC：0.899；验证队列：0.958）。组织病理学上，DSP模式患者主要表现为胆汁淤积性肝炎模式（75.0%，P<0.05），坏死程度更高（29.2%，P = 0.084）。具有DSP模式的DILI患者更易进展为ALF。通过纳入INR和ALP可提高该模型对ALF的预测效力。这种新模型能够更好地识别高危DILI患者，从而能够及时采取措施以获得更好的预后。
