Alan D. Hutson

PROGRESSIVE, SEVERE LUNG INJURY SECONDARY TO THE INTERACTION OF INSULTS IN GASTRIC ASPIRATION

This study examines lung injury and inflammation over 24 hours following intratracheal instillation of hydrochloric acid (acid), small nonacidic gastric particles (SNAP), or combined acid and small particles (CASP) in adult rats. The severity and duration of injury was significantly greater for CASP compared to acid or SNAP based on PaO2/FiO2, bronchoalveolar lavage (BAL) albumin, and BAL cell numbers. The inflammatory response associated with aspiration injury from CASP was distinct in several respects. Tumor necrosis factor (TNF)-alpha was greatly reduced in CASP compared to SNAP or acid, whereas interleukin (IL)-1beta was increased. Levels of cytokine-induced neutrophil chemoattractant (CINC)-1, monocyte chemoattractant protein (MCP)-1, and IL-10 in lavage were also significantly increased in animals injured with CASP compared to other forms of aspiration. Statistical analysis showed that BAL levels of IL-10 correlated most strongly with albumin leakage in aspiration-injured animals at 6 and 24 hours, followed by BAL levels of MCP-1. Additional cytokine cluster analyses indicated that levels of MCP-1 and CINC-1 in BAL from all injured animals were strongly correlated with inflammatory neutrophil numbers at 6 and 24 hours post aspiration, and that IL-10 levels in BAL were strongly correlated with inflammatory cell numbers at 24 hours. Preliminary blocking experiments showed that administration of anti-IL-10 antibody increased the albumin permeability index at 6 hours in SNAP and CASP animals, but anti-MCP-1 antibody did not affect the severity of injury. The results of this study support the possibility that different forms of aspiration are associated with identifiable cytokine profiles, and that specific cytokines, including IL-10 and MCP-1, may have utility as diagnostic or prognostic markers in clinical applications.□ This study examines lung injury and inflammation over 24 hours following intratracheal instillation of hydrochloric acid (acid), small nonacidic gastric particles (SNAP), or combined acid and small particles (CASP) in adult rats. The severity and duration of injury was significantly greater for CASP compared to acid or SNAP based on PaO2/FiO2, bronchoalveolar lavage (BAL) albumin, and BAL cell numbers. The inflammatory response associated with aspiration injury from CASP was distinct in several respects. Tumor necrosis factor (TNF)-α was greatly reduced in CASP compared to SNAP or acid, whereas interleukin (IL)-1β was increased. Levels of cytokine-induced neutrophil chemoattractant (CINC)-1, monocyte chemoattractant protein (MCP)-1, and IL-10 in lavage were also significantly increased in animals injured with CASP compared to other forms of aspiration. Statistical analysis showed that BAL levels of IL-10 correlated most strongly with albumin leakage in aspiration-injured animals at 6 and 24 hours, followed by BAL levels of MCP-1. Additional cytokine cluster analyses indicated that levels of MCP-1 and CINC-1 in BAL from all injured animals were strongly correlated with inflammatory neutrophil numbers at 6 and 24 hours post aspiration, and that IL-10 levels in BAL were strongly correlated with inflammatory cell numbers at 24 hours. Preliminary blocking experiments showed that administration of anti–IL-10 antibody increased the albumin permeability index at 6 hours in SNAP and CASP animals, but anti–MCP-1 antibody did not affect the severity of injury. The results of this study support the possibility that different forms of aspiration are associated with identifiable cytokine profiles, and that specific cytokines, including IL-10 and MCP-1, may have utility as diagnostic or prognostic markers in clinical applications.

Superimposed Gastric Aspiration Increases the Severity of Inflammation and Permeability Injury in a Rat Model of Lung Contusion

INTRODUCTION Lung contusion (LC) from blunt thoracic trauma is a clinically-prevalent condition that can progress to acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). Patients with LC are at risk for gastric aspiration at the time of trauma, but the combined insults have not been well-studied in animal models. This study tests the hypothesis that concurrent gastric aspiration (combined acid and small gastric particles, CASP) at the time of trauma significantly increases permeability injury and inflammation compared with LC alone, and also modifies the inflammatory response to include distinct features compared with the aspiration component of injury. MATERIALS AND METHODS Four groups of adult male Long-Evans rats were studied (LC, CASP, LC+CASP, uninjured controls). LC was induced in anesthetized rats at a fixed impact energy of 2.0 J, and CASP (1.2 mL/kg body weight, 40 mg particles/mL, pH=1.25) was instilled through an endotracheal tube. Lung injury and inflammation were assessed by arterial blood gases and levels of albumin, cells, and cytokines/chemokines in bronchoalveolar lavage (BAL) at 5 and 24 h. RESULTS Rats with LC+CASP had lower mean PaO(2)/FiO(2) ratios compared with LC alone at 24 h, and higher BAL albumin concentrations compared with either LC or CASP alone. Rats with LC+CASP versus LC had more severe inflammation based on higher levels of PMN in BAL at 5 h, increased whole lung myeloperoxidase (MPO) activity at 5 and 24 h, and increased levels of inflammatory mediators in BAL (TNFalpha, IL-1beta, and MCP-1 at 5 and 24 h; IL-10, MIP-2, and CINC-1 at 5 h). Rats with LC+CASP also had distinct aspects of inflammation compared with CASP alone, i.e., significantly higher levels of IL-10 (5 and 24 h), IL-1beta (24 h), CINC-1 (24 h), and MCP-1 (24 h), and significantly lower levels of MPO (5 h), MIP-2 (5 h), and CINC-1 (5 h). CONCLUSIONS Concurrent gastric aspiration can exacerbate permeability lung injury and inflammation associated with LC, and also generates a modified inflammatory response compared with aspiration alone. Unwitnessed gastric aspiration has the potential to contribute to more severe forms of LC injury associated with progression to ALI/ARDS and pneumonia in patients with thoracic trauma.

Likelihood testing populations modeled by autoregressive process subject to the limit of detection in applications to longitudinal biomedical data

Dependent and often incomplete outcomes are commonly found in longitudinal biomedical studies. We develop a likelihood function, which implements the autoregressive process of outcomes, incorporating the limit of detection problem and the probability of drop-out. The proposed approach incorporates the characteristics of the longitudinal data in biomedical research allowing us to carry out powerful tests to detect a difference between study populations in terms of the growth rate and drop-out rate. The formal notation of the likelihood function is developed, making it possible to adapt the proposed method easily for various different scenarios in terms of the number of groups to compare and a variety of growth trend patterns. Useful inferential properties for the proposed method are established, which take advantage of many well-developed theorems regarding the likelihood approach. A broad Monte-Carlo study confirms both the asymptotic results and illustrates good power properties of the proposed method. We apply the proposed method to three data sets obtained from mouse tumor experiments.

Exploration of the Relationship between Drinking Intensity and Quality of Life

This work explored the association between quality of life and drinking intensity in the Project MATCH sample. Tobit regression models were evaluated to assess the relationship between quality of life indicators (eg, measures of depression, adverse consequences, and others) and drinks per drinking day (DDD), and to assess modification or confounding of DDD by subject characteristics and treatment type. Each quality of life indicator improved with decreased DDD. Gender and ethnicity modified the DDD effect for some outcomes, with DDD exerting a greater influence on quality of life in women and non-Hispanic whites.

Group sequential control of overall toxicity incidents in clinical trials – non-Bayesian and Bayesian approaches

In some small clinical trials, toxicity is not a primary endpoint; however, it often has dire effects on patients’ quality of life and is even life-threatening. For such clinical trials, rigorous control of the overall incidence of adverse events is desirable, while simultaneously collecting safety information. In this article, we propose group sequential toxicity monitoring strategies to control overall toxicity incidents below a certain level as opposed to performing hypothesis testing, which can be incorporated into an existing study design based on the primary endpoint. We consider two sequential methods: a non-Bayesian approach in which stopping rules are obtained based on the ‘future’ probability of an excessive toxicity rate; and a Bayesian adaptation modifying the proposed non-Bayesian approach, which can use the information obtained at interim analyses. Through an extensive Monte Carlo study, we show that the Bayesian approach often provides better control of the overall toxicity rate than the non-Bayesian approach. We also investigate adequate toxicity estimation after the studies. We demonstrate the applicability of our proposed methods in controlling the symptomatic intracranial hemorrhage rate for treating acute ischemic stroke patients.

Modifying the Exact Test for a Binomial Proportion and Comparisons with Other Approaches

Abstract In this note we provide a simple continuity and tail-corrected approach to the standard exact test for a single binomial proportion commonly used in practice. We redefine the p-value for the two-sided alternative by noting the skewed distribution of the sample proportion under the null hypothesis. We illustrate that for both one and two-sided alternatives the coverage probabilities of the new methodology approaches more closely the desired type I error α and thus recommend these modifications to the applied statistician for consideration.

A generalized empirical likelihood approach for two-group comparisons given a U-statistic constraint

We investigate a generalized empirical likelihood (EL) approach in a two-group setting where the constraints on parameters have a form of U-statistics. In this situation, the summands that consist of the constraints for the EL are not independent, and a weight of each summand may not have a direct interpretation as a probability point mass, dissimilar to the common EL constraints based on independent summands. We show that the resulting EL ratio statistic has a weighted distribution in the univariate case and a combination of weighted distributions in the multivariate case. Through an extensive Monte-Carlo study, we show that the proposed methods applied for some well-known U-statistics have robust Type I error control under various underlying distributions including cases with a violation of exchangeability under null hypotheses. For the application, we employ the proposed methods to test hypotheses in crossover designs demonstrating an adaptability of the proposed methods in various hypothesis tests.

Easy and accurate variance estimation of the nonparametric estimator of the partial area under the ROC curve and its application

The receiver operating characteristic (ROC) curve is a popular technique with applications, for example, investigating an accuracy of a biomarker to delineate between disease and non-disease groups. A common measure of accuracy of a given diagnostic marker is the area under the ROC curve (AUC). In contrast with the AUC, the partial area under the ROC curve (pAUC) looks into the area with certain specificities (i.e., true negative rate) only, and it can be often clinically more relevant than examining the entire ROC curve. The pAUC is commonly estimated based on a U-statistic with the plug-in sample quantile, making the estimator a non-traditional U-statistic. In this article, we propose an accurate and easy method to obtain the variance of the nonparametric pAUC estimator. The proposed method is easy to implement for both one biomarker test and the comparison of two correlated biomarkers because it simply adapts the existing variance estimator of U-statistics. In this article, we show accuracy and other advantages of the proposed variance estimation method by broadly comparing it with previously existing methods. Further, we develop an empirical likelihood inference method based on the proposed variance estimator through a simple implementation. In an application, we demonstrate that, depending on the inferences by either the AUC or pAUC, we can make a different decision on a prognostic ability of a same set of biomarkers. Copyright

What is the Proper Sample Size for Studies of Periodontal Treatment

Small sample sizes are a common problem in biomedical research, and the periodontal literature is no exception. It is a problem leading to not only reduced statistical power but also an inappropriate statistical inference of a treatment effect. Using statistical methods with an insufficient sample size may give rise to an increased chance of falsely detecting treatment efficacy. This article provides some guidelines to cope with the small sample size problem. The authors discuss adequate sample sizes in several statistical tests and then suggest alternative statistical methods that are valid with a small sample size.