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Sample-size formula for the proportional-hazards regression model.

D A Schoenfeld

    Biometrics
    |June 1, 1983
    PubMed
    Summary

    This study provides a formula for calculating the necessary sample size in clinical trials when incorporating patient data to compare survival distributions. This method enhances trial design for diverse patient groups.

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    A simple algorithm for designing group sequential clinical trials.

    Biometrics·2001

    Area of Science:

    • Biostatistics
    • Clinical Trial Design
    • Survival Analysis

    Background:

    • Comparing survival distributions is crucial in clinical research.
    • Existing methods for sample size calculation may not fully utilize available patient data.
    • Heterogeneous patient populations present unique challenges in trial design.

    Purpose of the Study:

    • To derive a formula for determining sample size when comparing two survival distributions with concomitant information.
    • To extend existing asymptotic power calculations to include covariates.
    • To quantify the efficiency loss from ignoring relevant patient data.

    Main Methods:

    • Extension of Schoenfeld's (1981) asymptotic power formula.
    • Application of the proportional-hazards model.
    • Derivation of a sample size formula incorporating covariates.

    Main Results:

    • A formula is presented for sample size determination in survival analysis with covariates.
    • The study quantifies the loss in statistical efficiency when ignoring concomitant variables.
    • The derived formula is applicable to clinical trials with heterogeneous patient populations.

    Conclusions:

    • The new formula aids in designing more efficient clinical trials by utilizing all available patient information.
    • Incorporating concomitant variables improves the accuracy of survival distribution comparisons.
    • This work provides a valuable tool for optimizing resource allocation in clinical studies.

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