Evaluating and comparing biomarkers with respect to the area under the receiver operating characteristics curve in two-phase case-control studies

Biostatistics
Ying Huang

Abstract

Two-phase sampling design, where biomarkers are subsampled from a phase-one cohort sample representative of the target population, has become the gold standard in biomarker evaluation. Many two-phase case-control studies involve biased sampling of cases and/or controls in the second phase. For example, controls are often frequency-matched to cases with respect to other covariates. Ignoring biased sampling of cases and/or controls can lead to biased inference regarding biomarkers' classification accuracy. Considering the problems of estimating and comparing the area under the receiver operating characteristics curve (AUC) for a binary disease outcome, the impact of biased sampling of cases and/or controls on inference and the strategy to efficiently account for the sampling scheme have not been well studied. In this project, we investigate the inverse-probability-weighted method to adjust for biased sampling in estimating and comparing AUC. Asymptotic properties of the estimator and its inference procedure are developed for both Bernoulli sampling and finite-population stratified sampling. In simulation studies, the weighted estimators provide valid inference for estimation and hypothesis testing, while the standard empirical es...Continue Reading

References

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Jun 26, 2012·Clinical Chemistry·Margaret Sullivan PepeZiding Feng

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Citations

Sep 14, 2018·Statistics in Medicine·Lu Wang, Ying Huang
Apr 12, 2020·Cancer Epidemiology, Biomarkers & Prevention : a Publication of the American Association for Cancer Research, Cosponsored by the American Society of Preventive Oncology·Parichoy Pal ChoudhuryNilanjan Chatterjee

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