Disease Markers

Disease Markers / 2004 / Article

Open Access

Volume 20 |Article ID 726517 | https://doi.org/10.1155/2004/726517

Walter S. Liggett, Peter E. Barker, O. John Semmes, Lisa H. Cazares, "Measurement Reproducibility in the Early Stages of Biomarker Development", Disease Markers, vol. 20, Article ID 726517, 13 pages, 2004. https://doi.org/10.1155/2004/726517

Measurement Reproducibility in the Early Stages of Biomarker Development

Received18 Jan 2005
Accepted18 Jan 2005

Abstract

Biomarker discovery and development requires measurement reproducibility studies in addition to case-control studies. Parallel pursuit of reproducibility studies is especially important for emerging technologies such as protein biomarkers based on time-of-flight mass spectrometry, the case considered in this paper. For parallel studies, a way to improve reproducibility prior to identification of protein species is necessary. One approach is use of functional principal components analysis (PCA) as the basis for assessing measurement reproducibility. Reproducibility studies involve repeated measurement of a reference material such as a human serum standard. Measurement in our example is by SELDI-TOF (surface-enhanced laser desorption and ionization time-of-flight) mass spectrometry. Reproducibility is defined in reference to a source of variation, which in our example is associated with a type of commercially available protein biochip. We obtained spectra for 8 spots on each 11 chips. Two spectra are generally more alike when obtained from the same chip rather than different chips. Thus, our experiment indicates potential improvements from reducing variation in chip manufacture and chip handling during measurement. Our analysis involves careful registration of the spectra and characterization of the spectral differences. As shown by our example, a metrological analysis may enhance case-control studies by guiding optimization of the measurements underlying the biomarker.

Copyright © 2004 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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