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[Prognostic value of a continuous variable and an optimal cutoff point]

C Hill1

  • 1Département de biostatistique et d'épidémiologie, Institut Gustave-Roussy, Villejuif, France.

Bulletin Du Cancer
|August 1, 1993
PubMed
Summary

The current method for determining optimal cutoff points for continuous prognostic factors like cathepsin D in breast cancer is statistically flawed. Researchers should divide patients into more than two groups to accurately assess survival relationships.

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Area of Science:

  • Oncology
  • Biostatistics

Context:

  • Accurate prognostic factor assessment is crucial in breast cancer research.
  • Continuous variables, such as cathepsin D levels, pose challenges for survival analysis.
  • Existing methods for identifying optimal cutoff points are statistically problematic.

Purpose:

  • To highlight the statistical inaccuracies of the optimized cutoff point method for continuous prognostic factors.
  • To propose a statistically sound approach for analyzing continuous prognostic variables in survival studies.
  • To ensure biologically and statistically interpretable results in cancer prognostication.

Summary:

  • The optimized cutoff point method, used to dichotomize continuous variables like cathepsin D for breast cancer prognosis, is statistically incorrect.

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  • This method yields non-interpretable and variable results across patient groups.
  • A corrected approach involves dividing the population into more than two groups, examining the shape of the survival relationship without relying on observed survival for group definition.

    • Impact:

    • Provides a statistically valid methodology for analyzing continuous prognostic factors in oncology.
    • Improves the reliability and interpretability of survival analyses in breast cancer.
    • Facilitates more accurate patient stratification and treatment decisions based on continuous biomarkers.