5 resultados para Method of Averaging

em DigitalCommons@The Texas Medical Center


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A non-parametric method was developed and tested to compare the partial areas under two correlated Receiver Operating Characteristic curves. Based on the theory of generalized U-statistics the mathematical formulas have been derived for computing ROC area, and the variance and covariance between the portions of two ROC curves. A practical SAS application also has been developed to facilitate the calculations. The accuracy of the non-parametric method was evaluated by comparing it to other methods. By applying our method to the data from a published ROC analysis of CT image, our results are very close to theirs. A hypothetical example was used to demonstrate the effects of two crossed ROC curves. The two ROC areas are the same. However each portion of the area between two ROC curves were found to be significantly different by the partial ROC curve analysis. For computation of ROC curves with large scales, such as a logistic regression model, we applied our method to the breast cancer study with Medicare claims data. It yielded the same ROC area computation as the SAS Logistic procedure. Our method also provides an alternative to the global summary of ROC area comparison by directly comparing the true-positive rates for two regression models and by determining the range of false-positive values where the models differ. ^

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Approximately 200,000 African children are born with sickle-cell anemia each year. Research has shown that individuals with hemoglobin disorders, particularly sickle-cell anemia, have increased susceptibility to contracting malaria. Currently it is recommended that patients diagnosed with sickle-cell anemia undergo malaria chemoprophylaxis in order to decrease their chances of malarial infection. However, studies have shown that routine administration of these drugs increases the risk of drug resistance and could possibly impair the development of naturally acquired immunity. Clinical trials have shown intermittent preventive treatment (IPT) to be an effective method of protection against malaria. The objective of this report was to review previously conducted clinical trials that study the effects of intermittent preventive treatment on malaria and anemia in infants and children. Based on the review, implications for its appropriateness as a protective measure against malaria for infants and children diagnosed with sickle-cell disease were provided.^ The 18 studies reviewed were randomized controlled trials that focused on IPT’s effect on malaria (7 studies), anemia (1 study), or both (8 studies). In addition to these 16, one study looks at IPT’s effect on molecular resistance to malaria, and another study is a follow-up to a study in order to review IPT’s potential to cause a rebound effect. The 18 th study in this review specifically looks at IPT’s protective efficacy in children with SCA. The studies in this report were restricted to randomized controlled trials that have been performed from 2000 to 2010. Reports on anemia were included to illustrate possible added benefits of the use of IPT specific to burdens associated with SCA other than malaria susceptibility. The outcomes of these studies address several issues of concern involving the administration of IPT: protective efficacy (in reference to age, seasonal versus perennial malaria regions, and overall effectiveness against malaria and anemia), drug resistance, drug rebound effect, drug side-effects, and long-term effects. Overall, these showed that IPT has a significant level of protective efficacy against malaria and/or anemia in children. More specifically, the IPT study evaluating children diagnosed with sickle-cell anemia proved IPT to be a more effective method of protection than traditional chemoprophylaxis. ^

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Despite having been identified over thirty years ago and definitively established as having a critical role in driving tumor growth and predicting for resistance to therapy, the KRAS oncogene remains a target in cancer for which there is no effective treatment. KRas is activated b y mutations at a few sites, primarily amino acid substitutions at codon 12 which promote a constitutively active state. I have found that different amino acid substitutions at codon 12 can activate different KRas downstream signaling pathways, determine clonogenic growth potential and determine patient response to molecularly targeted therapies. Computer modeling of the KRas structure shows that different amino acids substituted at the codon 12 position influences how KRas interacts with its effecters. In the absence of a direct inhibitor of mutant KRas several agents have recently entered clinical trials alone and in combination directly targeting two of the common downstream effecter pathways of KRas, namely the Mapk pathway and the Akt pathway. These inhibitors were evaluated for efficacy against different KRAS activating mutations. An isogenic panel of colorectal cells with wild type KRas replaced with KRas G12C, G12D, or G12V at the endogenous loci differed in sensitivity to Mek and Akt inhibition. In contrast, screening was performed in a broad panel of lung cell lines alone and no correlation was seen between types of activating KRAS mutation due to concurrent oncogenic lesions. To find a new method to inhibit KRAS driven tumors, siRNA screens were performed in isogenic lines with and without active KRas. The knockdown of CNKSR1 (CNK1) showed selective growth inhibition in cells with an oncogenic KRAS. The deletion of CNK1 reduces expression of mitotic cell cycle proteins and arrests cells with active KRas in the G1 phase of the cell cycle similar to the deletion of an activated KRas regardless of activating substitution. CNK1 has a PH domain responsible for localizing it to membrane lipids making KRas potentially amenable to inhibition with small molecules. The work has identified a series of small molecules capable of binding to this PH domain and inhibiting CNK1 facilitated KRas signaling.

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Genetic anticipation is defined as a decrease in age of onset or increase in severity as the disorder is transmitted through subsequent generations. Anticipation has been noted in the literature for over a century. Recently, anticipation in several diseases including Huntington's Disease, Myotonic Dystrophy and Fragile X Syndrome were shown to be caused by expansion of triplet repeats. Anticipation effects have also been observed in numerous mental disorders (e.g. Schizophrenia, Bipolar Disorder), cancers (Li-Fraumeni Syndrome, Leukemia) and other complex diseases. ^ Several statistical methods have been applied to determine whether anticipation is a true phenomenon in a particular disorder, including standard statistical tests and newly developed affected parent/affected child pair methods. These methods have been shown to be inappropriate for assessing anticipation for a variety of reasons, including familial correlation and low power. Therefore, we have developed family-based likelihood modeling approaches to model the underlying transmission of the disease gene and penetrance function and hence detect anticipation. These methods can be applied in extended families, thus improving the power to detect anticipation compared with existing methods based only upon parents and children. The first method we have proposed is based on the regressive logistic hazard model. This approach models anticipation by a generational covariate. The second method allows alleles to mutate as they are transmitted from parents to offspring and is appropriate for modeling the known triplet repeat diseases in which the disease alleles can become more deleterious as they are transmitted across generations. ^ To evaluate the new methods, we performed extensive simulation studies for data simulated under different conditions to evaluate the effectiveness of the algorithms to detect genetic anticipation. Results from analysis by the first method yielded empirical power greater than 87% based on the 5% type I error critical value identified in each simulation depending on the method of data generation and current age criteria. Analysis by the second method was not possible due to the current formulation of the software. The application of this method to Huntington's Disease and Li-Fraumeni Syndrome data sets revealed evidence for a generation effect in both cases. ^

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This thesis project is motivated by the potential problem of using observational data to draw inferences about a causal relationship in observational epidemiology research when controlled randomization is not applicable. Instrumental variable (IV) method is one of the statistical tools to overcome this problem. Mendelian randomization study uses genetic variants as IVs in genetic association study. In this thesis, the IV method, as well as standard logistic and linear regression models, is used to investigate the causal association between risk of pancreatic cancer and the circulating levels of soluble receptor for advanced glycation end-products (sRAGE). Higher levels of serum sRAGE were found to be associated with a lower risk of pancreatic cancer in a previous observational study (255 cases and 485 controls). However, such a novel association may be biased by unknown confounding factors. In a case-control study, we aimed to use the IV approach to confirm or refute this observation in a subset of study subjects for whom the genotyping data were available (178 cases and 177 controls). Two-stage IV method using generalized method of moments-structural mean models (GMM-SMM) was conducted and the relative risk (RR) was calculated. In the first stage analysis, we found that the single nucleotide polymorphism (SNP) rs2070600 of the receptor for advanced glycation end-products (AGER) gene meets all three general assumptions for a genetic IV in examining the causal association between sRAGE and risk of pancreatic cancer. The variant allele of SNP rs2070600 of the AGER gene was associated with lower levels of sRAGE, and it was neither associated with risk of pancreatic cancer, nor with the confounding factors. It was a potential strong IV (F statistic = 29.2). However, in the second stage analysis, the GMM-SMM model failed to converge due to non- concaveness probably because of the small sample size. Therefore, the IV analysis could not support the causality of the association between serum sRAGE levels and risk of pancreatic cancer. Nevertheless, these analyses suggest that rs2070600 was a potentially good genetic IV for testing the causality between the risk of pancreatic cancer and sRAGE levels. A larger sample size is required to conduct a credible IV analysis.^