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Related Experiment Videos

An epidemiologic perspective on biomarkers

A Schatzkin1, L Freedman, M Schiffman

  • 1National Cancer Institute, Bethesda, Maryland.

Journal of Internal Medicine
|January 1, 1993
PubMed
Summary
This summary is machine-generated.

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Biological markers, or biomarkers, can serve as valid surrogates for diseases in epidemiological studies. Using these intermediate end-points can make studies, like those for cancer, shorter, smaller, and more cost-effective.

Area of Science:

  • Epidemiology
  • Biomarker Research
  • Public Health

Background:

  • Biomarkers are crucial for understanding disease etiology and progression.
  • Integrating biomarkers into large-scale studies enhances observational and intervention research.
  • An intermediate end-point is a biomarker on the causal pathway between exposure and disease.

Purpose of the Study:

  • To define and evaluate the utility of intermediate end-points as surrogates for disease outcomes in epidemiological research.
  • To explore the conditions under which a biomarker can serve as a valid surrogate.
  • To discuss the statistical methodologies for validating biomarkers as surrogates.

Main Methods:

  • Discussion of three study designs for biomarker validation: exposure-marker, marker-disease, and exposure-marker-disease studies.

Related Experiment Videos

  • Analysis of statistical considerations for each study type.
  • Review of examples from cancer, colorectal, and cervical cancer research.

    • Main Results:

    • A biomarker is a valid surrogate if exposure affects it and the disease similarly.
    • Surrogate end-points can significantly reduce the size, duration, and cost of studies.
    • Examples illustrate the application of biomarkers in diverse research areas.

    Conclusions:

    • Biomarkers, when validated as intermediate end-points, offer efficient alternatives to traditional disease outcomes.
    • The use of surrogate end-points can accelerate etiological research and intervention development.
    • Rigorous statistical approaches are essential for validating biomarkers in epidemiological studies.