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      Pretreatment data is highly predictive of liver chemistry signals in clinical trials

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          Abstract

          Purpose

          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.

          Patients and methods

          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.

          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.

          Conclusion

          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.

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          Author and article information

          Journal
          Drug Des Devel Ther
          Drug Des Devel Ther
          Drug Design, Development and Therapy
          Dove Medical Press
          1177-8881
          2012
          27 November 2012
          : 6
          : 359-369
          Affiliations
          [1 ]AstraZeneca Pharmaceuticals, Wilmington, DE, USA
          [2 ]AstraZeneca Pharmaceuticals, Södertälje, Sweden
          Author notes
          Correspondence: Zhaohui Cai, AstraZeneca Pharmaceuticals LP, FOC, NW1-053, 1800 Concord Pike, PO Box 15437, Wilmington, DE 19850-5437, USA, Tel +1 302 885 7495, Fax +1 302 886 4803, Email zhaohui.cai@ 123456astrazeneca.com
          [*]

          These authors contributed equally to this work

          Article
          dddt-6-359
          10.2147/DDDT.S34271
          3513908
          23226004
          © 2012 Cai et al, publisher and licensee Dove Medical Press Ltd.

          This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited.

          Categories
          Original Research

          Pharmacology & Pharmaceutical medicine

          baseline, prediction, alt, hy’s law, bilirubin, ggt

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