Literature DB >> 22991423

Adaptive Bayesian analysis of serum creatinine as a marker for drug-induced renal impairment in an early-phase clinical trial.

Pierre-Edouard Sottas1, Gordon F Kapke, Jean-Marc Leroux.   

Abstract

BACKGROUND: A concern with using creatinine for the identification of drug-induced renal impairment is that small changes in serum creatinine (SCr) that frequently are perceived as measurement bias or imprecision translate into important changes in the glomerular filtration rate. Important drug-generated changes in creatinine are difficult to detect because they are frequently observed within the reference interval. The design of a crossover drug protocol is an opportunity to use study participants as their own control to identify these small but important changes.
METHODS: Twenty individuals participating in a phase I clinical trial were evaluated for SCr changes beyond those expected for biological variation according to individual Z scores derived from an adaptive Bayesian model. After 2 screening tests, participants were administered either drug (n = 11) or placebo (n = 9) during the first dosing interval. A washout period followed, and drug was then administered to the group that initially received placebo, and vice versa (10 visits total per participant).
RESULTS: Although all creatinine values fell within the reference interval, 8 participants individually showed increased concentrations (Z scores >2.33). These 8 participants were confirmed at unblinding to have received the drug in the identified dosing period, with 1 exception.
CONCLUSIONS: The ability to identify a drug effect on an individual-participant basis in early-phase studies permits drug developers to recognize issues early in development and rapidly engage in risk-benefit analysis. These results suggest that SCr monitoring is able to detect early kidney dysfunction when individual-based reference intervals are used.

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Year:  2012        PMID: 22991423     DOI: 10.1373/clinchem.2012.193698

Source DB:  PubMed          Journal:  Clin Chem        ISSN: 0009-9147            Impact factor:   8.327


  3 in total

1.  Adaptive Bayesian approach to clinical trial renal impairment biomarker signal from urea and creatinine.

Authors:  Pierre-Edouard Sottas; Gordon F Kapke; Jean-Marc Leroux
Journal:  Int J Biol Sci       Date:  2013-01-26       Impact factor: 6.580

2.  A bedside clinical tool using creatinine kinetics to predict worsening renal injury and early recovery.

Authors:  Maurice I Khayat; Jonathan M Deeth; Jonathan A Sosnov
Journal:  Clin Kidney J       Date:  2018-07-31

3.  The Effects of CYP2C19 genotype on the susceptibility for nephrosis in cardio-cerebral vascular disease treated by anticoagulation.

Authors:  Kai Chang; Zhongyong Jiang; Chenxia Liu; Junlong Ren; Ting Wang; Jie Xiong
Journal:  Medicine (Baltimore)       Date:  2016-09       Impact factor: 1.889

  3 in total

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