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Conditional estimation after a two-stage diagnostic biomarker study that allows early termination for futility
Joseph S Koopmeiners1, Ziding Feng, Margaret Sullivan Pepe
1Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. koopm007@umn.edu
Statistics in Medicine
|January 13, 2012
Summary
Group sequential designs allow early study termination for futility but can bias results. This study introduces conditional estimators to correct bias in biomarker validation studies, improving estimate accuracy.
Area of Science:
- Biostatistics
- Biomarker Discovery
- Clinical Trial Design
Background:
- Biomarker discovery often yields markers with poor validation performance.
- Group sequential designs permit early termination for futility, but can introduce bias in estimates.
Purpose of the Study:
- To develop and evaluate conditional estimators and confidence intervals for unbiased estimation in group sequential studies.
- To address bias introduced by early termination for futility in biomarker validation.
Main Methods:
- Proposed conditional estimators and confidence intervals assuming an independent increments covariance structure.
- Applied methods to conditional estimation of receiver operating characteristic (ROC) and positive predictive value (PPV) curves.
- Evaluated performance through simulation studies.
Main Results:
- Conditional estimators and confidence intervals effectively correct for bias from early termination.
- Demonstrated improved accuracy in estimating ROC and PPV curves in two-stage studies.
- Simulation results support the proposed methodology's validity.
Conclusions:
- Conditional estimation provides a robust approach to address bias in group sequential biomarker studies.
- The proposed methods enhance the reliability of biomarker performance estimates after early futility stopping.
- This work contributes to more accurate biomarker validation in clinical trials.
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