Medicine and Health Sciences Commons^™

Improved Peak Detection And Quantification Of Mass Spectrometry Data Acquired From Surface-Enhanced Laser Desorption And Ionization By Denoising Spectra With The Undecimated Discrete Wavelet Transform, Kevin R. Coombes, Spiros Tsavachidis, Jeffrey S. Morris, Keith A. Baggerly, Henry M. Kuerer

Jeffrey S. Morris

Background: Mass spectrometry, especially surface enhanced laser desorption and ionization (SELDI) is increasingly being used to find disease-related proteomic patterns in complex mixtures of proteins derived from tissue samples or from easily obtained biological fluids such as serum, urine, or nipple aspirate fluid. Questions have been raised about the reproducibility and reliability of peak quantifications using this technology. For example, Yasui and colleagues opted to replace continuous measures of the size of a peak by a simple binary indicator of its presence or absence in their analysis of a set of spectra from prostate cancer patients.

Methods: We collected nipple …

Pooling Information Across Different Studies And Oligonucleotide Microarray Chip Types To Identify Prognostic Genes For Lung Cancer., Jeffrey S. Morris, Guosheng Yin, Keith A. Baggerly, Chunlei Wu, Li Zhang

Jeffrey S. Morris

Our goal in this work is to pool information across microarray studies conducted at different institutions using two different versions of Affymetrix chips to identify genes whose expression levels offer information on lung cancer patients’ survival above and beyond the information provided by readily available clinical covariates. We combine information across chip types by identifying “matching probes” present on both chips, and then assembling them into new probesets based on Unigene clusters. This method yields comparable expression level quantifications across chips without sacrificing much precision or significantly altering the relative ordering of the samples. We fit a series of multivariable …

Accounting For Missing Data In End-Of-Life Research, Paula Diehr, Laura Lee Johnson

Paula Diehr

End-of-life studies are likely to have missing data because sicker persons are less likely to provide information and because measurements cannot be made after death. Ignoring missing data may result in data that are too favorable, because the sickest persons are effectively dropped from the analysis. In a comparison of two groups, the group with the most deaths and missing data will tend to have the most favorable data, which is not desirable. Results based on only the available data may not be generalizable to the original study population. If most of the missing data are absent because of death, …

Methods For Incorporating Death Into Health-Related Variables In Longitudinal Studies, Paula Diehr

Paula Diehr

BACKGROUND AND OBJECTIVES: Longitudinal studies of health over time may be misleading if some people die. Self-rated health (excellent to poor) and the SF-36 profile scores have been transformed to incorporate death. We applied the same approaches to incorporate death into activities of daily living difficulties (ADLs), IADLs, mini-mental state examination, depressive symptoms, blocks walked per week, bed days, the timed walk, body mass index and blood pressure. STUDY DESIGN AND SETTING: The Cardiovascular Health Study of 5,888 older adults, was followed up to 9 years. Mean age was 73 at baseline, and 658 had an incident stroke during follow-up. …

Matlab Code For Bayesian Fitting Of Adaptive P-Splines In Regression, Veera Baladandayuthapani

Veera Baladandayuthapani

No abstract provided.

Serum Proteomics Profiling: A Young Technology Begins To Mature, Kevin R. Coombes, Jeffrey S. Morris, Jianhua Hu, Sarah R. Edmondson, Keith A. Baggerly

Jeffrey S. Morris

No abstract provided.

Signal In Noise: Evaluating Reported Reproducibility Of Serum Proteomic Tests For Ovarian Cancer, Keith A. Baggerly, Jeffrey S. Morris, Sarah R. Edmonson, Kevin R. Coombes

Jeffrey S. Morris

Proteomic profi ling of serum initially appeared to be dramatically effective for diagnosis of early-stage ovarian cancer, but these results have proven diffi cult to reproduce. A recent publication reported good classifi cation in one dataset using results from training on a much earlier dataset, but the authors have since reported that they did not perform the analysis as described. We examined the reproducibility of the proteomic patterns across datasets in more detail. Our analysis reveals that the pattern that enabled successful classifi cation is biologically implausible and that the method, properly applied, does not classify the data accurately. We …

Reliability, Effect Size, And Responsiveness Of Health Status Measures In The Design Of Randomized And Cluster-Randomized Trials, Paula Diehr

Paula Diehr

BACKGROUND: New health status survey instruments are often described by their psychometric (measurement) properties, such as Validity, Reliability, Effect Size, and Responsiveness. For cluster-randomized trials, another important statistic is the Intraclass Correlation (ICC) for the instrument within clusters. Studies using better instruments can be performed with smaller sample sizes, but better instruments may be more expensive in terms of dollars, opportunity cost, or poorer data quality due to the response burden of longer instruments. METHODS: We defined the psychometric statistics in terms of a mathematical model, and examined the power of a two-sample test as a function of the test-retest …

"Rassling The Hog": The Influence Of Correlated Item Error On Internal Consistency, Classical Reliability, And Congeneric Reliability, Joseph F. Lucke

Joseph Lucke

The properties of internal consistency ($\alpha$), classical reliability ($\rho$), and congeneric reliability ($\omega$) for a composite test with correlated item error were analytically investigated. Possible sources of correlated item error are contextual effects, item bundles, and item models that ignore additional attributes or higher-order attributes. The relation between reliability and internal consistency is determined by the deviance from true-score equivalence. Reliability (classical or congeneric) is internal consistency plus the relative deviance from true-score equivalence. The influence of correlated item error on $\alpha$, $\rho$, and $\omega$ is conveyed strictly through the total item error covariance. As the total item error covariance …