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EB Research - Methodological Research in Epidemiology
Biomarker/Analytical Development: Limit of Detection (LOD) and Measurement Error (ME)
The use of biomarkers has been, and will continue to be, an integral part of epidemiological research, making substantial contributions to our understanding of disease pathways and processes. New and emerging biomarkers are integral to this continued understanding. The laboratory and measurement processes behind these biomarkers often provide researchers with a less than true measurement of the intended biomarker. Reasons for this measurement error include intra-individual variability and instrument sensitivity among others. Acknowledging, evaluating, and adjusting for these errors is crucial for the correct assessment of individual, as well as population risk, as measurement error affects almost all biomarker measurement.
Researchers here have diligently investigated the sources of laboratory measurement errors by gaining a laboratory perspective on the measurement process ranging from sample storage and preparation to the calibrations and measurement processes of assay equipment. This understanding has provided insight to data issues commonly present yet ignored in epidemiological research. These issues have been the motivation for numerous papers as well as a collaborative effort funded by the American Chemistry Council with the goal of providing the methodological tools necessary to assess and address the issues of LOD and ME when using biomarkers.
Principal investigators
Enrique F. Schisterman, Ph.D. & Neil Perkins, Ph.D.
DESPR Collaborators
Selected Publications
- Special Issue of Epidemiology, July 2010 - Volume 21 - Supplement 4, pp: S1-S84.
- Pollack AZ, Perkins NJ, Mumford SL, Schisterman EF. (2013). Correlated biomarker measurement error: An important threat to inference in environmental epidemiology. American Journal of Epidemiology, 177(1):84-92. PMID: 23221725
- Schisterman EF, Vexler A, Mumford SL, & Perkins NJ. (2010). Hybrid pooled-unpooled design for cost-efficient measurement of biomarkers. Statistics in Medicine, 29, 597-613. PMID: 20049693
- Perkins NJ, Schisterman EF, & Vexler A. (2009). Generalized ROC curve inference for a biomarker subject to a limit of detection and measurement error. Statistics in Medicine, 28, 1841-1860. PMID: 19340817
- Schisterman EF, Vexler A, Whitcomb BW, & Liu A. (2006). The limitations due to exposure detection limits for regression models. American Journal of Epidemiology, 163, 374-383. PMID: 16394206