Diagnostic and prognostic prediction using gene expression profiles in high-dimensional microarray data
2003

Using Gene Expression Profiles for Cancer Prediction

publication Evidence: moderate

Author Information

Author(s): Simon R

Primary Institution: National Cancer Institute

Hypothesis

Can gene expression profiles improve diagnostic and prognostic predictions in cancer treatment?

Conclusion

Gene expression profiling has the potential to enhance cancer diagnosis and treatment selection, but significant methodological challenges remain.

Supporting Evidence

  • Prognostic markers are often not reproducibly established in clinical practice.
  • Many studies do not evaluate the reproducibility of gene expression measurements.
  • Proper planning and statistical methods are crucial for developing reliable classifiers.

Takeaway

Scientists are trying to use tiny pieces of information from genes to help doctors figure out what kind of cancer someone has and how to treat it better.

Methodology

The study discusses the importance of planning and statistical methods in developing gene expression-based classifiers for cancer.

Potential Biases

The absence of structured analysis and protocols increases the risk of bias in results.

Limitations

Many studies lack proper protocols, leading to unreliable prognostic markers and classification systems.

Digital Object Identifier (DOI)

10.1038/sj.bjc.6601326

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