Fourier Transform Infrared (FTIR) has been use to discriminate different pathogens by signals from cells infected with these versus normal cells as references. To do the statistical analysis, Partial Least Square Regression (PLSR) was utilized to distinguish any two kinds of virus‐infected cells and normal cells. Validation using Bootstrap method and Cross‐validations were employed to calculate the shrinkages of Area Under the ROC Curve (AUC) and specificities corresponding to 80%, 90%, and 95% sensitivities. The result shows that our procedure can significantly discriminate these pathogens when we compare infected cells with the normal cells. On the height of this success, PLSR was applied again to simultaneously compare two kinds of virus‐infected cells and the normal cells. The shrinkage of Volume Under the Surface (VUS) was calculated to do the evaluation of model diagnostic performance. The high value of VUS demonstrates that our method can effectively differentiate virus‐infected cells and normal cells.

The increasing numbers of genetic tests in clinical settings have identified many variants of uncertain significance (VUS) in genes associated with inherited cardiac arrhythmias and inherited cardiomyopathies. Evaluation of clinical practices including counseling strategies and medical management recommendations for patients and their families is important to improve patient outcomes and prevent over- or under-treatment that may result in morbidity or fatality. The purpose of this study is to describe provider practices related to VUS results including how they conduct risk assessments and ascertain what information and medical management recommendations they provide to patients with VUS results and the patients’ family members. Additionally, we aim to describe providers’ concerns and informational needs related to counseling about a VUS. An anonymous online survey was developed for the current study and distributed to genetic counselors through the National Society of Genetic Counselors (NSGC) listerv and to cardiologists via emails obtained from publicly available resources. The survey explored healthcare providers’ confidence in counseling about a VUS, explanation of a VUS to patients, topics covered before and after genetic testing, and recommendations for patients with a VUS and their families using clinical vignettes. Providers (N=102) who completed the survey included 29 cardiovascular genetic counselors, 50 genetic counselors from other specialties, and 23 cardiologists. A hypothetical clinical scenario was used in which a young adult patient had a VUS in a gene causing Arrhythmogenic Right Ventricular Cardiomyopathy, but did not meet clinical diagnostic criteria for the condition. The patient’s only concerning issues included a personal history of fainting during exercising and sudden death of a 45 year old first-degree relative. Nearly 9% of all providers incorrectly described the VUS as likely pathogenic, while 15% would downplay the finding by indicating the VUS is more likely to eventually be reclassified as benign. Genetic counselors feel more confident about counseling about VUS results (p<0.001). Both cardiovascular genetic counselors and cardiologists feel confident in making medical management recommendations; however, cardiologists are more likely to recommend treatment with beta-blockers and exercise limitation for the patient. Compared to cardiac genetic counselors, other genetic counselors (p=0.001) and cardiologists (p=0.014) were more likely to recommend clinical testing for family members even though testing is expected to be uninformative, especially given the absence of any clinical diagnosis in the family. These findings highlight the expertise of different providers in different specialty area and suggest the need for interdisciplinary clinics that include cardiologists, cardiac genetic counselors, nurses, geneticists, psychologists and others to optimize care for challenging cases where VUS results create uncertainty.

No description available.

Receiver operating characteristic (ROC) curves have been widely used in evaluation of the goodness of the diagnostic method in many study fields, such as disease diagnosis in medicine. The area under the ROC curve (AUC) naturally became one of the most used variables in gauging the goodness of the diagnosis (Mossman, Somoza 1991). Since medical diagnosis often is not dichotomous, the ROC curve and AUC need to be generalized to a multi-dimensional case. The generalization of AUC to multi-class case has been studied by many researchers in the past decade. Most recently, Nakas & Yiannoutsos (2004) considered the ordered d classes ROC analysis by only considering the sensitivities of each class. Hence, their dimension is only d. Cha (2005) considered more types of mis-classification in the ordered multiple-class case, but reduced the dimension of Ferri, at.el. from d(d-1) to 2(d-1). In this dissertation we are trying to adjust and calculate the VUS for an ordered multipleclass with Cha’s 2(d-1)-dimension method. Our methodology of finding the VUS is introduced. We present the method of adjusting and calculating VUS and their statistical inferences for the 2(d-1)-dimension. Some simulation results are included and a real example will be presented. Intellectual outcomes in pediatric brain-tumor patients were investigated in a prospective longitudinal study. The Standard-Binet Intelligence Scale-Fourth Edition (SB-IV) Standard Age Score (SAS) and Composite intelligence quotient (IQ) score are examined as cognitive outcomes in pediatric brain-tumor patients. Treatment factors, patient factors and time since diagnosis are taken into account as the risk factors. Hierarchical linear/quadratic models and Gompertz based hierarchical nonlinear growth models were applied to build linear and nonlinear longitudinal curves. We use PRESS and Volume Under the Surface (VUS) as the criterions to compare these two methods. Some model interpretations are presented in this dissertation.