Clinical Trial Designs to Evaluate Predictive Biomarkers: What’s Being Estimated?

  • Gene Pennello
  • Jingjing YeEmail author
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 218)


Predictive biomarkers are used to predict whether a patient is likely to receive benefits from a therapy that outweigh its risks. In practice, a predictive biomarker is measured with a diagnostic assay or test kit. Usually the test has some potential for measuring the biomarker with error. For qualitative tests indicating presence or absence of a biomarker, the probability of misclassification is usually not zero. Study designs to evaluate predictive biomarkers include the biomarker-stratified design, the biomarker-strategy design, the enrichment (or targeted) design, and the discordant risk randomization design. Many authors have reviewed the main strengths and weaknesses of these study designs. However, the estimand being used to evaluate the performance of the predictive biomarker is usually not provided explicitly. In this chapter, we provide explicit formulas for the estimands used in common study designs assuming that the misclassification error of the biomarker test is non-differential to outcome. The estimands are expressed as terms of the biomarker’s predictive capacity (differential in treatment effect between biomarker positive and negative patients when the biomarker is never misclassified) and the test’s predictive accuracy (e.g., positive and negative predictive values of the test for the biomarker). Upon inspection, the estimands reveal not only well-known strengths and weaknesses of the study designs, but other insights. In particular, for the biomarker-stratified design, the estimand is the product of the biomarker predictive capacity and an attenuation factor between 0 and 1 that increases with the test’s predictive accuracy. For other designs, the estimands illuminate important limitations in evaluating the clinical utility of the biomarker test. After presenting the theoretical estimands, we present and discuss estimand values for a hypothetical case study of Procalcitonin (PCT) as a biomarker in Procalcitonin-guided evaluation and management of subjects suspected of lower respiratory tract infection.


Estimand Predictive biomarkers Clinical trial design Clinical performance Attenuation factor 



The authors gratefully thank Drs. Qin Li from and Thomas Gwise from the Food and Drug Administration for the helpful discussions and the reviewers of our draft manuscript for their comments and suggestions.


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Copyright information

© This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2019

Authors and Affiliations

  1. 1.Division of BiostatisticsOffice of Surveillance and Biometrics, Center for Devices and Radiological Health, US Food and Drug AdministrationSilver SpringUSA
  2. 2.Division of Biometrics VOffice of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug AdministrationSilver SpringUSA

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