Modeling Agreement between Binary Classifications of Multiple Raters in R and SAS

Cancer screening and diagnostic tests often are classified using a binary outcome such as diseased or not diseased. Recently large-scale studies have been conducted to assess agreement between many raters. Measures of agreement using the class of generalized linear mixed models were implemented efficiently in four recently introduced R and SAS packages in large-scale agreement studies incorporating binary classifications. Simulation studies were conducted to compare the performance across the packages and apply the agreement methods to two cancer studies

Multiple Imputation When Rate of Change Is The Outcome of Interest

Little research has been devoted to multiple imputation (MI) of derived variables. We investigated various MI approaches for the outcome, rate of change, when the analysis model is a two-stage linear regression. Our simulations showed that competitive approaches depended on the missing data mechanism and presence of auxiliary terms

Trends in Anemia Care in Older Patients Approaching End-Stage Renal Disease in the United States (1995-2010)

Anemia is common in patients with advanced chronic kidney disease. While the treatment of anemia in patients with end-stage renal disease (ESRD) has attracted considerable attention, relatively little is known about patterns and trends in the anemia care received by patients before initiating maintenance dialysis or pre-emptive kidney transplantation

Guidelines for generating right-censored outcomes from a cox model extended to accommodate time-varying covariates

Simulating studies with right-censored outcomes as functions of time-varying covariates is discussed. Guidelines on the use of an algorithm developed by Zhou and implemented by Hendry are provided. Through simulation studies, the sensitivity of the method to user inputs is considered

Comparative outcomes of predominant facility-level use of ferumoxytol versus other intravenous iron formulations in incident hemodialysis patients

Ferumoxytol was first approved for clinical use in 2009 solely based on data from trial comparisons with oral iron on biochemical anemia efficacy end points. To compare the rates of important patient outcomes (infection, cardiovascular events and death) between facilities predominantly using ferumoxytol versus iron sucrose (IS) or ferric gluconate (FG) in patients with end-stage renal disease (ESRD)-initiating hemodialysis (HD)

Longer-term Outcomes of Darbepoetin Alfa Versus Epoetin Alfa in Patients With ESRD Initiating Hemodialysis: A Quasi-experimental Cohort Study

Adequately-powered studies directly comparing hard clinical outcomes of darbepoetin alfa (DPO) versus epoetin alfa (EPO) in patients undergoing dialysis are lacking

A robust measure of correlation between two genes on a microarray

<p>Abstract</p> <p>Background</p> <p>The underlying goal of microarray experiments is to identify gene expression patterns across different experimental conditions. Genes that are contained in a particular pathway or that respond similarly to experimental conditions could be co-expressed and show similar patterns of expression on a microarray. Using any of a variety of clustering methods or gene network analyses we can partition genes of interest into groups, clusters, or modules based on measures of similarity. Typically, Pearson correlation is used to measure distance (or similarity) before implementing a clustering algorithm. Pearson correlation is quite susceptible to outliers, however, an unfortunate characteristic when dealing with microarray data (well known to be typically quite noisy.)</p> <p>Results</p> <p>We propose a resistant similarity metric based on Tukey's biweight estimate of multivariate scale and location. The resistant metric is simply the correlation obtained from a resistant covariance matrix of scale. We give results which demonstrate that our correlation metric is much more resistant than the Pearson correlation while being more efficient than other nonparametric measures of correlation (e.g., Spearman correlation.) Additionally, our method gives a systematic gene flagging procedure which is useful when dealing with large amounts of noisy data.</p> <p>Conclusion</p> <p>When dealing with microarray data, which are known to be quite noisy, robust methods should be used. Specifically, robust distances, including the biweight correlation, should be used in clustering and gene network analysis.</p

Survey design and analysis considerations when utilizing misclassified sampling strata

Abstract Background A large multi-center survey was conducted to understand patients’ perspectives on biobank study participation with particular focus on racial and ethnic minorities. In order to enrich the study sample with racial and ethnic minorities, disproportionate stratified sampling was implemented with strata defined by electronic health records (EHR) that are known to be inaccurate. We investigate the effect of sampling strata misclassification in complex survey design. Methods Under non-differential and differential misclassification in the sampling strata, we compare the validity and precision of three simple and common analysis approaches for settings in which the primary exposure is used to define the sampling strata. We also compare the precision gains/losses observed from using a disproportionate stratified sampling scheme compared to using a simple random sample under varying degrees of strata misclassification. Results Disproportionate stratified sampling can result in more efficient parameter estimates of the rare subgroups (race/ethnic minorities) in the sampling strata compared to simple random sampling. When sampling strata misclassification is non-differential with respect to the outcome, a design-agnostic analysis was preferred over model-based and design-based analyses. All methods yielded unbiased parameter estimates but standard error estimates were lowest from the design-agnostic analysis. However, when misclassification is differential, only the design-based method produced valid parameter estimates of the variables included in the sampling strata. Conclusions In complex survey design, when the interest is in making inference on rare subgroups, we recommend implementing disproportionate stratified sampling over simple random sampling even if the sampling strata are misclassified. If the misclassification is non-differential, we recommend a design-agnostic analysis. However, if the misclassification is differential, we recommend using design-based analyses

Trends in Anemia Care in Older Patients Approaching End-Stage Renal Disease in the United States (1995-2010)

Anemia is common in patients with advanced chronic kidney disease. While the treatment of anemia in patients with end-stage renal disease (ESRD) has attracted considerable attention, relatively little is known about patterns and trends in the anemia care received by patients before initiating maintenance dialysis or pre-emptive kidney transplantation