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With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of 'signature' protein profiles specific(More)
The prostate-specific antigen test has been a major factor in increasing awareness and better patient management of prostate cancer (PCA), but its lack of specificity limits its use in diagnosis and makes for poor early detection of PCA. The objective of our studies is to identify better biomarkers for early detection of PCA using protein profiling(More)
Discovery of "signature" protein profiles that distinguish disease states (eg, malignant, benign, and normal) is a key step towards translating recent advancements in proteomic technologies into clinical utilities. Protein data generated from mass spectrometers are, however, large in size and have complex features due to complexities in both biological(More)
BACKGROUND Mutations in the tyrosine kinase (TK) domain of the epidermal growth factor receptor (EGFR) gene in lung cancers are associated with increased sensitivity of these cancers to drugs that inhibit EGFR kinase activity. However, the role of such mutations in the pathogenesis of lung cancers is unclear. METHODS We sequenced exons 18-21 of the EGFR(More)
BACKGROUND Most studies that have evaluated the association between the body-mass index (BMI) and the risks of death from any cause and from specific causes have been conducted in populations of European origin. METHODS We performed pooled analyses to evaluate the association between BMI and the risk of death among more than 1.1 million persons recruited(More)
Consider a continuous marker for predicting a binary outcome. For example, the serum concentration of prostate specific antigen may be used to calculate the risk of finding prostate cancer in a biopsy. In this article, we argue that the predictive capacity of a marker has to do with the population distribution of risk given the marker and suggest a(More)
There are two popular statistical approaches to biomarker evaluation. One models the risk of disease (or disease outcome) with, for example, logistic regression. A marker is considered useful if it has a strong effect on risk. The second evaluates classification performance by use of measures such as sensitivity, specificity, predictive values, and receiver(More)
Group randomized trials (GRTs) in public health research typically use a small number of randomized groups with a relatively large number of participants per group. Two fundamental features characterize GRTs: a positive correlation of outcomes within a group, and the small number of groups. Appropriate consideration of these fundamental features is(More)
BACKGROUND Prostate-specific antigen (PSA) testing is the primary method used to diagnose prostate cancer in the United States. Methods to integrate other risk factors associated with prostate cancer into individualized risk prediction are needed. We used prostate biopsy data from men who participated in the Prostate Cancer Prevention Trial (PCPT) to(More)
Research methods for biomarker evaluation lag behind those for evaluating therapeutic treatments. Although a phased approach to development of biomarkers exists and guidelines are available for reporting study results, a coherent and comprehensive set of guidelines for study design has not been delineated. We describe a nested case-control study design that(More)