Pretreatment data is highly predictive of liver chemistry signals in clinical trials.
Pretreatment data is highly predictive of liver chemistry signals in clinical trials.
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DOI：
10.2147/dddt.s34271
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Furlong ST
中科院分区：
文献类型：
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作者：
Cai Z;Bresell A;Steinberg MH;Silberg DG;Furlong ST
这项回顾性分析的目的是评估预测模型如何根据治疗前（基线）信息确定哪些患者将在临床试验期间产生肝脏化学信号。基于来自24项后期临床试验的数据，开发了分类模型，以使用基线信息（包括人口统计学、病史、合并用药和基线实验室结果）预测肝脏化学结局。使用基线数据的预测模型预测了哪些患者将在试验期间产生肝脏信号，平均验证准确率约为80%。个体肝化学检查的基线水平对于预测试验期间自身的升高最为重要。基线时胆红素水平高并不罕见，并且与发生生化海氏法则病例的高风险相关。基线γ-谷氨酰转移酶（GGT）水平似乎具有一定的预测价值，但除了使用已建立的肝脏化学检查外，并未增加可预测性。使用治疗前（基线）数据可以预测哪些患者出现肝脏化学信号的风险较高。从此类预测中获得的知识可能有助于进行主动和有针对性的风险管理，并且本文描述的分析类型可以帮助确定新的生物标志物是否比现有生物标志物提供更好的性能。
The goal of this retrospective analysis was to assess how well predictive models could determine which patients would develop liver chemistry signals during clinical trials based on their pretreatment (baseline) information. Based on data from 24 late-stage clinical trials, classification models were developed to predict liver chemistry outcomes using baseline information, which included demographics, medical history, concomitant medications, and baseline laboratory results. Predictive models using baseline data predicted which patients would develop liver signals during the trials with average validation accuracy around 80%. Baseline levels of individual liver chemistry tests were most important for predicting their own elevations during the trials. High bilirubin levels at baseline were not uncommon and were associated with a high risk of developing biochemical Hy’s law cases. Baseline γ-glutamyltransferase (GGT) level appeared to have some predictive value, but did not increase predictability beyond using established liver chemistry tests. It is possible to predict which patients are at a higher risk of developing liver chemistry signals using pretreatment (baseline) data. Derived knowledge from such predictions may allow proactive and targeted risk management, and the type of analysis described here could help determine whether new biomarkers offer improved performance over established ones.