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Use of Bootstrapping to Evaluate Infrequent Genetic Abnormalities as Prognostic Factors for Survival in Human Acute Leukemias

  • David D. Lawrence
  • Peter A. Reese
  • Clara D. Bloomfield
Conference paper

Abstract

The distributional properties of a summary random variable in a two-sample test involving a small group can be investigated through bootstrapping. With data from a prospective Cancer and Leukemia Group B (CALGB 8461) study of the prognostic significance of cytogenetic abnormalities on human acute leukemias, survival data involving an infrequent genetic abnormality was bootstrapped using Cox’s proportional hazards regression model. Eight of 578 cases in the survival analysis exhibited trisomy 13 as the sole cytogenetic abnormality. Although the bootstrap results agree with the classical log-rank test, the distribution of bootstrap regression coefficients deviates from normality (P< 0.01, Kolmogorov-Smirnov). This bootstrap methodology can be of value for exploratory studies of survival involving a small group to assess the reasonableness of the log-rank statistic when the asymptotic assumption is questionable.

Keywords

Score Function Bootstrap Sample Partial Likelihood Regression Coefficient Estimate Bootstrap Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 1992

Authors and Affiliations

  • David D. Lawrence
    • 1
  • Peter A. Reese
    • 2
  • Clara D. Bloomfield
    • 1
  1. 1.Department of MedicineRoswell Park Cancer Institute, New York State Department of HealthBuffaloUSA
  2. 2.Department of BiomathematicsRoswell Park Cancer Institute, New York State Department of HealthBuffaloUSA

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