Group sequential testing of the predictive accuracy of a continuous biomarker with unknown prevalence

Joe Koopmeiners, Ziding Feng

Research output: Contribution to journalArticle

Abstract

Group sequential testing procedures have been proposed as an approach to conserving resources in biomarker validation studies. Previously, we derived the asymptotic properties of the sequential empirical positive predictive value (PPV) and negative predictive value (NPV) curves, which summarize the predictive accuracy of a continuous marker, under case-control sampling. A limitation of this approach is that the prevalence cannot be estimated from a case-control study and must be assumed known. In this paper, we consider group sequential testing of the predictive accuracy of a continuous biomarker with unknown prevalence. First, we develop asymptotic theory for the sequential empirical PPV and NPV curves when the prevalence must be estimated, rather than assumed known in a case-control study. We then discuss how our results can be combined with standard group sequential methods to develop group sequential testing procedures and bias-adjusted estimators for the PPV and NPV curve. The small sample properties of the proposed group sequential testing procedures and estimators are evaluated by simulation, and we illustrate our approach in the context of a study to validate a novel biomarker for prostate cancer.

Original languageEnglish (US)
Pages (from-to)1267-1280
Number of pages14
JournalStatistics in Medicine
Volume35
Issue number8
DOIs
StatePublished - Apr 15 2016

Fingerprint

Sequential Testing
Group Sequential
Group Testing
Biomarkers
Unknown
Case-control Study
Case-Control Studies
Curve
Validation Studies
Estimator
Sequential Methods
Case-control
Prostate Cancer
Asymptotic Theory
Prostatic Neoplasms
Small Sample
Asymptotic Properties
Resources
Simulation

Keywords

  • Diagnostic biomarkers
  • Group sequential methods
  • PPV curve
  • Prostate cancer

Cite this

Group sequential testing of the predictive accuracy of a continuous biomarker with unknown prevalence. / Koopmeiners, Joe; Feng, Ziding.

In: Statistics in Medicine, Vol. 35, No. 8, 15.04.2016, p. 1267-1280.

Research output: Contribution to journalArticle

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