Ashby Kristin, Zhuang Wei, González-Jimenez Andres, Alvarez-Alvarez Ismael, Lucena M Isabel, Andrade Raúl J, Aithal Guruprasad P, Suzuki Ayako, Chen Minjun
Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA.
Bioinformatic Platform. Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga, Spain.
J Hepatol. 2021 Aug;75(2):333-341. doi: 10.1016/j.jhep.2021.03.021. Epub 2021 May 18.
BACKGROUND & AIMS: Although most drug-induced liver injury (DILI) cases resolve after the offending medication is discontinued, time to recovery varies among patients, with 6 -12% developing a chronic disease. Herein, we investigated clinical factors and drug properties as potential risk determinants that influence the time course for DILI recovery and developed a model to predict its trajectory.
We applied an accelerated failure time model to 294 cases collected by the International Drug-Induced Liver Network Consortium (iDILIC). Factors included in the multivariate recovery score model were selected through univariate analysis. The model was externally validated using 257 cases from the Spanish DILI Registry and 191 cases from the LiverTox database.
Higher serum bilirubin and alkaline phosphatase (ALP) at DILI onset, a longer time to onset, and non-significant drug metabolism were associated with a longer recovery and were included in the recovery score model. We defined high- and low-risk groups based on the scores assigned by the model. The estimated probability of recovery by 6 months was 0.46 (95% CI 0.26-0.61) for the high-risk group and 0.93 (95% CI 0.58-0.99) for the low-risk group in the iDILIC. Model performance was validated in both validation sets. The high- and low-risk cases identified by the model showed a significantly different time course for recovery, with a majority of low-risk cases recovering sooner.
The trajectory of biochemical recovery from DILI is predicted by the extent of drug metabolism, serum bilirubin and ALP at DILI onset. The model can be used to compute an estimated DILI recovery and, when a significant delay is predicted, clinicians may consider additional investigations such as histologic evaluation or extended follow-up.
In this study, we investigated whether drug properties and clinical factors are associated with the time it takes to recover from drug-induced liver injury (DILI). We found that total bilirubin, alkaline phosphatase level at DILI onset, time to onset, and extent of drug metabolism were consistently associated with recovery time. Using these factors, we built a model to predict the trajectory of recovery from DILI and validated this model in 2 independent cohorts. Our findings offer important insights into the factors influencing the trajectory of recovery from DILI. Additional investigations and longer follow-ups can be planned in those for whom a delayed recovery is predicted.
尽管大多数药物性肝损伤（DILI）病例在停用致病药物后可恢复，但患者的恢复时间各不相同，6%-12%的患者会发展为慢性疾病。在此，我们研究了临床因素和药物特性作为影响DILI恢复时间进程的潜在风险决定因素，并开发了一个模型来预测其恢复轨迹。
我们将加速失效时间模型应用于国际药物性肝损伤网络联盟（iDILIC）收集的294例病例。多变量恢复评分模型中纳入的因素通过单变量分析进行选择。该模型使用来自西班牙DILI注册中心的257例病例和来自LiverTox数据库的191例病例进行外部验证。
DILI发病时较高的血清胆红素和碱性磷酸酶（ALP）、较长的发病时间以及药物代谢不显著与较长的恢复时间相关，并被纳入恢复评分模型。我们根据模型分配的分数定义了高风险组和低风险组。在iDILIC中，高风险组6个月时的估计恢复概率为0.46（95%CI 0.26-0.61），低风险组为0.93（95%CI 0.58-0.99）。模型性能在两个验证集中均得到验证。模型识别出的高风险和低风险病例显示出明显不同的恢复时间进程，大多数低风险病例恢复得更快。
DILI生化恢复的轨迹可通过药物代谢程度、DILI发病时的血清胆红素和ALP来预测。该模型可用于计算DILI的估计恢复时间，当预测到明显延迟时，临床医生可考虑进行额外的检查，如组织学评估或延长随访。
在本研究中，我们调查了药物特性和临床因素是否与药物性肝损伤（DILI）的恢复时间相关。我们发现总胆红素、DILI发病时的碱性磷酸酶水平、发病时间和药物代谢程度与恢复时间始终相关。利用这些因素，我们建立了一个模型来预测DILI的恢复轨迹，并在2个独立队列中对该模型进行了验证。我们的研究结果为影响DILI恢复轨迹的因素提供了重要见解。对于预测恢复延迟的患者，可以计划进行额外的检查和更长时间的随访。
