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Related Experiment Videos

Clinical trial design for microarray predictive marker discovery and assessment.

L Pusztai1, K R Hess

  • 1Department of Breast Medical Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, TX 77030-4009, USA. lpusztai@mdanderson.org

Annals of Oncology : Official Journal of the European Society for Medical Oncology
|November 20, 2004
PubMed
Summary
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Gene-expression profiling offers a powerful clinical research tool for discovering novel outcome predictors. Validating these multigene predictors in prospective clinical trials is crucial for assessing their true accuracy and clinical value.

Area of Science:

  • Genomics
  • Clinical Diagnostics
  • Biomarker Discovery

Background:

  • Transcriptional profiling measures thousands of mRNA species, advancing beyond traditional methods like PCR.
  • Gene-expression profiling platforms are nearing clinical readiness.
  • Novel outcome predictors may differ significantly from single-gene markers.

Purpose of the Study:

  • To review methodological and statistical considerations for clinical trials.
  • To guide the discovery and validation of multigene predictors for therapy response.
  • To assess the clinical utility of gene-expression profiling in diagnostics.

Main Methods:

  • Utilizing machine learning algorithms trained on large sample sets.
  • Developing multigene predictors by integrating expression data with mathematical models.

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  • Designing prospective clinical trials for validation.

    • Main Results:

    • Gene-expression profiling enables the discovery of novel, multigene-based outcome predictors.
    • Machine learning algorithms can improve diagnostic test performance with more data.
    • Sequential generations of tests with increasing accuracy are anticipated.

    Conclusions:

    • Gene-expression profiling is a promising tool for clinical research and potential diagnostics.
    • Prospective validation in clinical trials is essential to establish the accuracy and value of multigene predictors.
    • Further development is needed to integrate these technologies into routine clinical practice.