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Cathepsin S as a biomarker of low-grade inflammation, insulin resistance, and cardiometabolic disease riskJobs, Elisabeth January 2014 (has links)
Cathepsin S is a protease important in major histocompatibility complex (MHC) class II antigen presentation and also in degrading the extracellular matrix. Studies, most of them experimental, have shown that cathepsin S is involved in different pathological conditions such as obesity, inflammation, atherosclerosis, diabetes, and cancer. The overall hypothesis of this report is that high levels of circulating cathepsin S, is a biomarker that reflects pathology induced by inflammation and obesity. The overall aim of this report was to investigate possible associations between circulating cathepsin S, inflammation, glucometabolic disturbance, and its associated diseases in the community. As cathepsin S appears to be a novel risk marker for several pathological conditions, we also wanted to examine the effect of dietary intervention on circulating cathepsin S concentrations. This thesis is based on data from three community-based cohorts, the Uppsala longitudinal study of adult men (ULSAM), the prospective investigation of the vasculature in Uppsala seniors (PIVUS), and a post-hoc study from the randomized controlled NORDIET trial. In the first study, we identified a cross-sectional positive association between serum cathepsin S and two markers of cytokine-mediated inflammation, CRP and IL-6. These associations were similar in non-obese individuals. In longitudinal analyses, higher cathepsin S at baseline was associated with higher CRP and IL-6 levels after six years of follow-up. In the second study, we identified a cross-sectional association between increased serum levels of cathepsin S and reduced insulin sensitivity. These associations were similar in non-obese individuals. No significant association was observed between cathepsin S and insulin secretion. In longitudinal analysis, higher cathepsin S levels were associated with an increased risk of developing diabetes during the six-year follow-up. In the third study, we found that higher serum levels of cathepsin S were associated with increased mortality risk. Moreover, in the ULSAM cohort, serum cathepsin S was independently associated with cause-specific mortality from cardiovascular disease and cancer. In the fourth study, we identified that adherence to an ad libitum healthy Nordic diet for 6 weeks slightly decreased the levels of plasma cathepsin S in normal or marginally overweight individuals, relative to the control group. Changes in circulating cathepsin S concentrations were correlated with changes in body weight, LDL-C, and total cholesterol. Conclusion: This thesis shows that circulating cathepsin S is a biomarker that independently reflects inflammation, insulin resistance, the risk of developing diabetes, and mortality risk. Furthermore, a Nordic diet moderately reduced cathepsin S levels in normal-weight and overweight men and women. This effect may be partially mediated by diet-induced weight loss and possibly by reduced LDL-C concentrations.
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Cancer Mortality Rates in Appalachia: Descriptive Epidemiology and an Approach to Explaining Differences in OutcomesBlackley, David, Behringer, Bruce, Zheng, Shimin 01 August 2012 (has links)
Cancer is a leading cause of death in the Appalachian region of the United States. Existing studies compare regional mortality rates to those of the entire nation. We compare cancer mortality rates in Appalachia to those of the nation, with additional comparisons of Appalachian and non-Appalachian counties within the 13 states that contain the Appalachian region. Lung/bronchus, colorectal, female breast and cervical cancers, as well as all cancers combined, are included in analysis. Linear regression is used to identify independent associations between ecological socioeconomic and demographic variables and county-level cancer mortality outcomes. There is a pattern of high cancer mortality rates in the 13 states containing Appalachia compared to the rest of the United States. Mortality rate differences exist between Appalachian and non-Appalachian counties within the 13 states, but these are not consistent. Lung cancer is a major problem in Appalachia; most Appalachian counties within the 13 states have significantly higher mortality rates than in-state, non-Appalachian counterparts. Mortality rates from all cancers combined also appear to be worse overall within Appalachia, but part of this disparity is likely driven by lung cancer. Education and income are generally associated with cancer mortality, but differences in the strength and direction of these associations exist depending on location and cancer type. Improving high school graduation rates in Appalachia could result in a meaningful long term reduction in lung cancer mortality. The relative importance of household income level to cancer outcomes may be greater outside the Appalachian regions within these states.
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Association Between Altitude and Bronchopulmonary CancerChing, Hung 01 January 2018 (has links)
As a validation study, this study addressed an under-researched area of bronchopulmonary cancer mortality and incidence. The association between altitude and bronchopulmonary cancer mortality and incidence was investigated using data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research. The theoretical framework for my study was Bronfenbrenner's ecological model. This model emphasizes the relevance of social and physical environments that influence patterns of disease and injury and shape responses to these patterns of disease and injury. The age-adjusted bronchopulmonary cancer mortality and incidence rates per 100,000 people in the highest elevation and lowest elevation states were investigated. The data used in this study spans from 2006 to 2014. In this study, bivariate statistics were used to analyze the data. The relevant technique of performing an unpaired t-test was used. After performing age, gender, and race-stratified analysis, no significant difference in cancer mortality and incidence was found within the following three groups: Black or African American, Asian or Pacific Islander, and American Indian or Alaska Native. This was a new finding, as previous studies did not stratify for race. Cancer mortality and incidence were found to be lower in both the male and female groups for the highest elevation states. Cancer mortality and incidence were also found to be lower in all age categories for the highest elevation states. A positive social change impact of this study is that this research provides the groundwork for future studies to probe what in the environment is lowering the bronchopulmonary cancer mortality and incidence for the White population.
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Trend Analysis and Modeling of Health and Environmental Data: Joinpoint and Functional ApproachKafle, Ram C. 04 June 2014 (has links)
The present study is divided into two parts: the first is on developing the statistical analysis and modeling of mortality (or incidence) trends using Bayesian joinpoint regression and the second is on fitting differential equations from time series data to derive the rate of change of carbon dioxide in the atmosphere.
Joinpoint regression model identifies significant changes in the trends of the incidence, mortality, and survival of a specific disease in a given population. Bayesian approach of joinpoint regression is widely used in modeling statistical data to identify the points in the trend where the significant changes occur. The purpose of the present study is to develop an age-stratified Bayesian joinpoint regression model to describe mortality trends assuming that the observed counts are probabilistically characterized by the Poisson distribution. The proposed model is based on Bayesian model selection criteria with the smallest number of joinpoints that are sufficient to explain the Annual Percentage Change (APC). The prior probability distributions are chosen in such a way that they are automatically derived from the model index contained in the model space. The proposed model and methodology estimates the age-adjusted mortality rates in different epidemiological studies to compare the trends by accounting the confounding effects of age. The future mortality rates are predicted using the Bayesian Model Averaging (BMA) approach.
As an application of the Bayesian joinpoint regression, first we study the childhood brain cancer mortality rates (non age-adjusted rates) and their Annual Percentage Change (APC) per year using the existing Bayesian joinpoint regression models in the literature. We use annual observed mortality counts of children ages 0-19 from 1969-2009 obtained from Surveillance Epidemiology and End Results (SEER) database of the National Cancer Institute (NCI). The predictive distributions are used to predict the future mortality rates. We also compare this result with the mortality trend obtained using joinpoint software of NCI, and to fit the age-stratified model, we use the cancer mortality counts of adult lung and bronchus cancer (25-85+ years), and brain and other Central Nervous System (CNS) cancer (25-85+ years) patients obtained from the Surveillance Epidemiology and End Results (SEER) data base of the National Cancer Institute (NCI).
The second part of this study is the statistical analysis and modeling of noisy data using functional data analysis approach. Carbon dioxide is one of the major contributors to Global Warming. In this study, we develop a system of differential equations using time series data of the major sources of the significant contributable variables of carbon dioxide in the atmosphere. We define the differential operator as data smoother and use the penalized least square fitting criteria to smooth the data. Finally, we optimize the profile error sum of squares to estimate the necessary differential operator. The proposed models will give us an estimate of the rate of change of carbon dioxide in the atmosphere at a particular time. We apply the model to fit emission of carbon dioxide data in the continental United States. The data set is obtained from the Carbon Dioxide Information Analysis Center (CDIAC), the primary climate-change data and information analysis center of the United States Department of Energy.
The first four chapters of this dissertation contribute to the development and application of joinpiont and the last chapter discusses the statistical modeling and application of differential equations through data using functional data analysis approach.
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The impact of POSSUM score on long-term outcome of patients with colorectal cancerCheung, Him-chun, Horace., 張謙俊. January 2010 (has links)
published_or_final_version / Medicine / Master / Master of Medical Sciences
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Prognostic factors for long-term survival in patients with cancer of the gastric cardiaChen, Tzu-hsin, Clement., 陳梓欣. January 2004 (has links)
published_or_final_version / Medical Sciences / Master / Master of Medical Sciences
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Cathepsin S as a Biomarker of Low-grade Inflammation, Insulin Resistance, and Cardiometabolic Disease RiskJobs, Elisabeth January 2014 (has links)
Cathepsin S is a protease important in major histocompatibility complex (MHC) class II antigen presentation and also in degrading the extracellular matrix. Studies, most of them experimental, have shown that cathepsin S is involved in different pathological conditions such as obesity, inflammation, atherosclerosis, diabetes, and cancer. The overall hypothesis of this report is that high levels of circulating cathepsin S, is a biomarker that reflects pathology induced by inflammation and obesity. The overall aim of this report was to investigate possible associations between circulating cathepsin S, inflammation, glucometabolic disturbance, and its associated diseases in the community. As cathepsin S appears to be a novel risk marker for several pathological conditions, we also wanted to examine the effect of dietary intervention on circulating cathepsin S concentrations. This thesis is based on data from three community-based cohorts, the Uppsala longitudinal study of adult men (ULSAM), the prospective investigation of the vasculature in Uppsala seniors (PIVUS), and a post-hoc study from the randomized controlled NORDIET trial. In the first study, we identified a cross-sectional positive association between serum cathepsin S and two markers of cytokine-mediated inflammation, CRP and IL-6. These associations were similar in non-obese individuals. In longitudinal analyses, higher cathepsin S at baseline was associated with higher CRP and IL-6 levels after six years of follow-up. In the second study, we identified a cross-sectional association between increased serum levels of cathepsin S and reduced insulin sensitivity. These associations were similar in non-obese individuals. No significant association was observed between cathepsin S and insulin secretion. In longitudinal analysis, higher cathepsin S levels were associated with an increased risk of developing diabetes during the six-year follow-up. In the third study, we found that higher serum levels of cathepsin S were associated with increased mortality risk. Moreover, in the ULSAM cohort, serum cathepsin S was independently associated with cause-specific mortality from cardiovascular disease and cancer. In the fourth study, we identified that adherence to an ad libitum healthy Nordic diet for 6 weeks slightly decreased the levels of plasma cathepsin S in normal or marginally overweight individuals, relative to the control group. Changes in circulating cathepsin S concentrations were correlated with changes in body weight, LDL-C, and total cholesterol. Conclusion: This thesis shows that circulating cathepsin S is a biomarker that independently reflects inflammation, insulin resistance, the risk of developing diabetes, and mortality risk. Furthermore, a Nordic diet moderately reduced cathepsin S levels in normal-weight and overweight men and women. This effect may be partially mediated by diet-induced weight loss and possibly by reduced LDL-C concentrations.
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TARGETING BREAST CANCER TRANSCRIPTION-DRIVEN SIGNALING PATHWAYS TO IMPROVE THERAPEUTIC RESPONSE IN TRIPLE NEGATIVE BREAST CANCERRoberts, Melyssa Susann 02 June 2020 (has links)
No description available.
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Prognostic Modeling in the Presence of Competing Risks: an Application to Cardiovascular and Cancer Mortality in Breast Cancer SurvivorsLeoce, Nicole Marie January 2016 (has links)
Currently, there are an estimated 2.8 million breast cancer survivors in the United States. Due to modern screening practices and raised awareness, the majority of these cases will be diagnosed in the early stages of disease where highly effective treatment options are available, leading a large proportion of these patients to fail from causes other than breast cancer. The primary cause of death in the United States today is cardiovascular disease, which can be delayed or prevented with interventions such as lifestyle modifications or medications. In order to identify individuals who may be at high risk for a cardiovascular event or cardiovascular mortality, a number of prognostic models have been developed. The majority of these models were developed on populations free of comorbid conditions, utilizing statistical methods that did not account for the competing risks of death from other causes, therefore it is unclear whether they will be generalizable to a cancer population remaining at an increased risk of death from cancer and other causes. Consequently, the purpose of this work is multi-fold. We will first summarize the major statistical methods available for analyzing competing risk data and include a simulation study comparing them. This will be used to inform the interpretation of the real data analysis, which will be conducted on a large, contemporary cohort of breast cancer survivors. For these women, we will categorize the major causes of death, hypothesizing that it will include cardiovascular failure. Next, we will evaluate the existing cardiovascular disease risk models in our population of cancer survivors, and then propose a new model to simultaneously predict a survivor's risk of death due to her breast cancer or due to cardiovascular disease, while accounting for additional competing causes of death. Lastly, model predicted outcomes will be calculated for the cohort, and evaluation methods will be applied to determine the clinical utility of such a model.
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Estudo sobre mortalidade, co-morbidades, adesão ao tratamento e sobrevida de pacientes portadores de câncer bucal em Campina Grande PB.Carvalho, Sérgio Henrique Gonçalves de 11 December 2009 (has links)
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Previous issue date: 2009-12-11 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Introduction: Oral cancer is a public health problem in Brazil, taking into consideration the high incidence and co-morbidities, mainly due to aggressive surgery to treat advanced tumors. Objectives: To determine the mortality, co-morbidities, treatment adherence and survival of patients with mouth malignant neoplasm seen at the Center for Oral Cancer Prevention from the Oncology Center Ulisses Pinto, FAP Hospital - Campina Grande-PB between 1999 and 2008. Materials and Methods: it was performed data collection from medical records of all patients with mouth malignant neoplasm diagnosed between 1999 and 2008. Data were analyzed by descriptive statistics and the chi-square and Pearson correlation were applied considering significant p values ≤ 0.05. Results: Of the total sample of 473 oral cancer cases, it was observed that 62.71% were males, 65.5 ± 13 mean age and 59.96% were Caucasian. Squamous cell carcinoma was the most prevalent histological type (86.2%) and tongue (29.6%) was the main anatomical site affected. Most injuries were diagnosed in clinical stages III and IV. It was observed 25.42% mortality rate, with median overall prevalent survival among 6-12 months. Co-morbidities occurred in 51.69% of patients, the most prevalent were hypertension, diabetes and depression. Oral co-morbidities occurred in 52.54% of patients, xerostomia was the most prevalent with 32%, followed by mucositis (27.1%) and dysphagia (19.5%). Regarding treatment adherence, it was observed that 82.63% adhered to treatment. There was statistically significant association between the following variables: mortality and TNM classification (p = 0.026), type of treatment (p = 0.027), survival (p = 0.000) and treatment adherence (p = 0.000); the overall co-morbidity rate was significantly associated with gender (p = 0.034) and age (p = 0.040); and the adherence to treatment was associated with age (p = 0.009) and mortality (p = 0.000). The survival rate was significantly associated with TNM classification (p = 0.026) and mortality p = 0.000. Conclusion: Considering the results it is concluded that oral cancer has high mortality rate and low survival rate, being influenced by treatment and TNM classification; there was high prevalence of overall co-morbidities: hypertension, diabetes and depression were the most prevalent; The prevalence of oral co-morbidities was high, being the xerostomia, mucositis and dysphagia the most frequent; most individuals adhered to treatment and this variable influenced the mortality rate and patient survival; survival of patients was influenced by mortality and TNM classification. / Introdução: O câncer de boca é um problema de saúde pública no Brasil, tendo em vista a alta incidência e as co-morbidades, decorrentes principalmente de cirurgias agressivas para tratar tumores avançados. Objetivos: Determinar o índice de mortalidade, co-morbidades, adesão ao tratamento e sobrevida de pacientes portadores de neoplasia maligna de boca atendidos no Núcleo de Prevenção ao Câncer Bucal do Centro de Cancerologia Ulisses Pinto no Hospital da FAP Campina Grande-PB, durante o período compreendido entre 1999 e 2008. Materiais e Métodos: Foi realizada coleta de dados em prontuários de todos os pacientes portadores de neoplasia maligna de boca, diagnosticadas entre 1999 e 2008. Os dados foram submetidos à análise estatística descritiva e aplicado teste qui-quadrado e de correlação de Pearson, considerando significantes valores de p≤0,05.Resultados: Do total da amostra de 473 casos de câncer bucal foi observado que 62,71% eram do gênero masculino, com idade média de 65,5±13 e 59,96% dos indivíduos eram leucodermas (59,96%). O carcinoma espinocelular foi o tipo histológico mais prevalente (86,2%), tendo a língua (29,6%) como principal localização anatômica acometida. A maioria das lesões foi diagnosticada em estádios clínicos III e IV. Foi observada taxa de mortalidade de 25,42%, com tempo de sobrevida médio prevalente entre 6-12 meses. As co-morbidades ocorreram em 51,69% dos pacientes, sendo as mais prevalentes a hipertensão, o diabetes e a depressão. As co-morbidades bucais ocorreram em 52,54% dos pacientes, sendo a xerostomia a mais prevalente com 32%, seguida de mucosite (27,1%) e disfagia (19,5%). Quanto à adesão ao tratamento observou-se que 82,63% aderiram ao tratamento. Houve associação estatisticamente significativos entre as seguintes variáveis: mortalidade e classificação TNM (p=0,026), tipo de tratamento (p=0,027), sobrevida (p=0,000) e com adesão ao tratamento (p=0,000); A taxa de co-morbidade geral teve associação estatisticamente significante com gênero (p=0,034) e com idade (p=0,040); e a adesão ao tratamento teve com idade(p=0,009) e mortalidade (p=0,000). A taxa de sobrevida teve associação estatisticamente significante com a classificação TNM (p=0,026) e mortalidade p=0,000. Conclusão: Diante dos resultados conclui-se que o câncer bucal apresenta elevada taxa de mortalidade e baixa média de sobrevida, sofrendo influência da classificação de tratamento e da classificação TNM; verificou-se elevada prevalência de co-morbidades gerais, sendo hipertensão, diabetes e depressão as mais prevalentes; A prevalência de co-morbidades bucais foi elevada, sendo a xerostomia, a mucosite e a disfagia as mais freqüentes; a maioria dos indivíduos aderiram ao tratamento e esta variável influenciou da taxa de mortalidade e de sobrevida dos pacientes; o tempo de sobrevida dos pacientes sofreu influência das variáveis taxa de mortalidade e classificação TNM.
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