12 resultados para mistimed covariates
em Duke University
Resumo:
MOTIVATION: Technological advances that allow routine identification of high-dimensional risk factors have led to high demand for statistical techniques that enable full utilization of these rich sources of information for genetics studies. Variable selection for censored outcome data as well as control of false discoveries (i.e. inclusion of irrelevant variables) in the presence of high-dimensional predictors present serious challenges. This article develops a computationally feasible method based on boosting and stability selection. Specifically, we modified the component-wise gradient boosting to improve the computational feasibility and introduced random permutation in stability selection for controlling false discoveries. RESULTS: We have proposed a high-dimensional variable selection method by incorporating stability selection to control false discovery. Comparisons between the proposed method and the commonly used univariate and Lasso approaches for variable selection reveal that the proposed method yields fewer false discoveries. The proposed method is applied to study the associations of 2339 common single-nucleotide polymorphisms (SNPs) with overall survival among cutaneous melanoma (CM) patients. The results have confirmed that BRCA2 pathway SNPs are likely to be associated with overall survival, as reported by previous literature. Moreover, we have identified several new Fanconi anemia (FA) pathway SNPs that are likely to modulate survival of CM patients. AVAILABILITY AND IMPLEMENTATION: The related source code and documents are freely available at https://sites.google.com/site/bestumich/issues. CONTACT: yili@umich.edu.
Resumo:
Conventional hedonic techniques for estimating the value of local amenities rely on the assumption that households move freely among locations. We show that when moving is costly, the variation in housing prices and wages across locations may no longer reflect the value of differences in local amenities. We develop an alternative discrete-choice approach that models the household location decision directly, and we apply it to the case of air quality in US metro areas in 1990 and 2000. Because air pollution is likely to be correlated with unobservable local characteristics such as economic activity, we instrument for air quality using the contribution of distant sources to local pollution-excluding emissions from local sources, which are most likely to be correlated with local conditions. Our model yields an estimated elasticity of willingness to pay with respect to air quality of 0.34-0.42. These estimates imply that the median household would pay $149-$185 (in constant 1982-1984 dollars) for a one-unit reduction in average ambient concentrations of particulate matter. These estimates are three times greater than the marginal willingness to pay estimated by a conventional hedonic model using the same data. Our results are robust to a range of covariates, instrumenting strategies, and functional form assumptions. The findings also confirm the importance of instrumenting for local air pollution. © 2009 Elsevier Inc. All rights reserved.
Resumo:
We consider the problem of variable selection in regression modeling in high-dimensional spaces where there is known structure among the covariates. This is an unconventional variable selection problem for two reasons: (1) The dimension of the covariate space is comparable, and often much larger, than the number of subjects in the study, and (2) the covariate space is highly structured, and in some cases it is desirable to incorporate this structural information in to the model building process. We approach this problem through the Bayesian variable selection framework, where we assume that the covariates lie on an undirected graph and formulate an Ising prior on the model space for incorporating structural information. Certain computational and statistical problems arise that are unique to such high-dimensional, structured settings, the most interesting being the phenomenon of phase transitions. We propose theoretical and computational schemes to mitigate these problems. We illustrate our methods on two different graph structures: the linear chain and the regular graph of degree k. Finally, we use our methods to study a specific application in genomics: the modeling of transcription factor binding sites in DNA sequences. © 2010 American Statistical Association.
Resumo:
BACKGROUND: Patients with chronic hepatitis C virus (HCV) infection have high rates of alcohol consumption, which is associated with progression of fibrosis and lower response rates to HCV treatment. AIMS: This prospective cohort study examined the feasibility of a 24-week integrated alcohol and medical treatment to HCV-infected patients. METHODS: Patients were recruited from a hepatology clinic if they had an Alcohol Use Disorders Identification Test score >4 for women and >8 for men, suggesting hazardous alcohol consumption. The integrated model included patients receiving medical care and alcohol treatment within the same clinic. Alcohol treatment consisted of 6 months of group and individual therapy from an addictions specialist and consultation from a study team psychiatrist as needed. RESULTS: Sixty patients were initially enrolled, and 53 patients participated in treatment. The primary endpoint was the Addiction Severity Index (ASI) alcohol composite scores, which significantly decreased by 0.105 (41.7% reduction) between 0 and 3 months (P < 0.01) and by 0.128 (50.6% reduction) between 0 and 6 months (P < 0.01) after adjusting for covariates. Alcohol abstinence was reported by 40% of patients at 3 months and 44% at 6 months. Patients who did not become alcohol abstinent had reductions in their ASI alcohol composite scores from 0.298 at baseline to 0.219 (26.8% reduction) at 6 months (P = 0.08). CONCLUSION: This study demonstrated that an integrated model of alcohol treatment and medical care could be successfully implemented in a hepatology clinic with significant favorable impact on alcohol use and abstinence among patients with chronic HCV.
Resumo:
Previously we have shown that a functional nonsynonymous single nucleotide polymorphism (rs6318) of the 5HTR2C gene located on the X-chromosome is associated with hypothalamic-pituitary-adrenal axis response to a stress recall task, and with endophenotypes associated with cardiovascular disease (CVD). These findings suggest that individuals carrying the rs6318 Ser23 C allele will be at higher risk for CVD compared to Cys23 G allele carriers. The present study examined allelic variation in rs6318 as a predictor of coronary artery disease (CAD) severity and a composite endpoint of all-cause mortality or myocardial infarction (MI) among Caucasian participants consecutively recruited through the cardiac catheterization laboratory at Duke University Hospital (Durham, NC) as part of the CATHGEN biorepository. Study population consisted of 6,126 Caucasian participants (4,036 [65.9%] males and 2,090 [34.1%] females). A total of 1,769 events occurred (1,544 deaths and 225 MIs; median follow-up time = 5.3 years, interquartile range = 3.3-8.2). Unadjusted Cox time-to-event regression models showed, compared to Cys23 G carriers, males hemizygous for Ser23 C and females homozygous for Ser23C were at increased risk for the composite endpoint of all-cause death or MI: Hazard Ratio (HR) = 1.47, 95% confidence interval (CI) = 1.17, 1.84, p = .0008. Adjusting for age, rs6318 genotype was not related to body mass index, diabetes, hypertension, dyslipidemia, smoking history, number of diseased coronary arteries, or left ventricular ejection fraction in either males or females. After adjustment for these covariates the estimate for the two Ser23 C groups was modestly attenuated, but remained statistically significant: HR = 1.38, 95% CI = 1.10, 1.73, p = .005. These findings suggest that this functional polymorphism of the 5HTR2C gene is associated with increased risk for CVD mortality and morbidity, but this association is apparently not explained by the association of rs6318 with traditional risk factors or conventional markers of atherosclerotic disease.
Resumo:
Bullying is a common childhood experience that involves repeated mistreatment to improve or maintain one's status. Victims display long-term social, psychological, and health consequences, whereas bullies display minimal ill effects. The aim of this study is to test how this adverse social experience is biologically embedded to affect short- or long-term levels of C-reactive protein (CRP), a marker of low-grade systemic inflammation. The prospective population-based Great Smoky Mountains Study (n = 1,420), with up to nine waves of data per subject, was used, covering childhood/adolescence (ages 9-16) and young adulthood (ages 19 and 21). Structured interviews were used to assess bullying involvement and relevant covariates at all childhood/adolescent observations. Blood spots were collected at each observation and assayed for CRP levels. During childhood and adolescence, the number of waves at which the child was bullied predicted increasing levels of CRP. Although CRP levels rose for all participants from childhood into adulthood, being bullied predicted greater increases in CRP levels, whereas bullying others predicted lower increases in CRP compared with those uninvolved in bullying. This pattern was robust, controlling for body mass index, substance use, physical and mental health status, and exposures to other childhood psychosocial adversities. A child's role in bullying may serve as either a risk or a protective factor for adult low-grade inflammation, independent of other factors. Inflammation is a physiological response that mediates the effects of both social adversity and dominance on decreases in health.
Resumo:
OBJECTIVES: Identification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic cardioprotective phenotypes or highly responsive to protective interventions remain high-priority knowledge gaps. We sought to identify novel common genetic variants associated with perioperative MI in patients undergoing coronary artery bypass grafting using genome-wide association methodology. SETTING: 107 secondary and tertiary cardiac surgery centres across the USA. PARTICIPANTS: We conducted a stage I genome-wide association study (GWAS) in 1433 ethnically diverse patients of both genders (112 cases/1321 controls) from the Genetics of Myocardial Adverse Outcomes and Graft Failure (GeneMAGIC) study, and a stage II analysis in an expanded population of 2055 patients (225 cases/1830 controls) combined from the GeneMAGIC and Duke Perioperative Genetics and Safety Outcomes (PEGASUS) studies. Patients undergoing primary non-emergent coronary bypass grafting were included. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome variable was perioperative MI, defined as creatine kinase MB isoenzyme (CK-MB) values ≥10× upper limit of normal during the first postoperative day, and not attributable to preoperative MI. Secondary outcomes included postoperative CK-MB as a quantitative trait, or a dichotomised phenotype based on extreme quartiles of the CK-MB distribution. RESULTS: Following quality control and adjustment for clinical covariates, we identified 521 single nucleotide polymorphisms in the stage I GWAS analysis. Among these, 8 common variants in 3 genes or intergenic regions met p<10(-5) in stage II. A secondary analysis using CK-MB as a quantitative trait (minimum p=1.26×10(-3) for rs609418), or a dichotomised phenotype based on extreme CK-MB values (minimum p=7.72×10(-6) for rs4834703) supported these findings. Pathway analysis revealed that genes harbouring top-scoring variants cluster in pathways of biological relevance to extracellular matrix remodelling, endoplasmic reticulum-to-Golgi transport and inflammation. CONCLUSIONS: Using a two-stage GWAS and pathway analysis, we identified and prioritised several potential susceptibility loci for perioperative MI.
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© 2014 UICC.Cytokines such as Interleukin (IL)212p70 ("IL-12") and IL-23 can influence tumor progression. We tested the hypothesis that blood levels of IL-12p40, the common subunit of both cytokines, are associated with melanoma progression. Blood from 2,048 white melanoma patients were collected at a single institution between March 1998 and March 2011. Plasma levels of IL-12p40 were determined for 573 patients (discovery), 249 patients (Validation 1) and 244 patients (Validation 2). Per 10-unit change of IL-12p40 level was used to investigate associations with melanoma patient outcome among all patients or among patients with early or advanced stage. Among stage I/II melanoma patients in the pooled data set, after adjustment for sex, age, stage and blood draw time from diagnosis, elevated IL-12p40 was associated with melanoma recurrence [hazard ratio (HR)51.04 per 10-unit increase in IL-12p40, 95% CI 1.02-1.06, p58.48 × 10-5]; Elevated IL-12p40 was also associated with a poorer melanoma specific survival (HR51.06, 95% CI 1.03-1.09, p53.35 × 10-5) and overall survival (HR51.05, 95% CI 1.03-1.08, p58.78 × 10-7) in multivariate analysis. Among stage III/IV melanoma patients in the pooled data set, no significant association was detected between elevated IL-12p40 and overall survival, or with melanoma specific survival, with or without adjustment for the above covariates. Early stage melanoma patients with elevated IL-12p40 levels are more likely to develop disease recurrence and have a poorer survival. Further investigation with a larger sample size will be needed to determine the role of IL-12p40 in advanced stage melanoma patients.
Resumo:
New representations of tree-structured data objects, using ideas from topological data analysis, enable improved statistical analyses of a population of brain artery trees. A number of representations of each data tree arise from persistence diagrams that quantify branching and looping of vessels at multiple scales. Novel approaches to the statistical analysis, through various summaries of the persistence diagrams, lead to heightened correlations with covariates such as age and sex, relative to earlier analyses of this data set. The correlation with age continues to be significant even after controlling for correlations from earlier significant summaries.
Resumo:
PURPOSE: The role of PM10 in the development of allergic diseases remains controversial among epidemiological studies, partly due to the inability to control for spatial variations in large-scale risk factors. This study aims to investigate spatial correspondence between the level of PM10 and allergic diseases at the sub-district level in Seoul, Korea, in order to evaluate whether the impact of PM10 is observable and spatially varies across the subdistricts. METHODS: PM10 measurements at 25 monitoring stations in the city were interpolated to 424 sub-districts where annual inpatient and outpatient count data for 3 types of allergic diseases (atopic dermatitis, asthma, and allergic rhinitis) were collected. We estimated multiple ordinary least square regression models to examine the association of the PM10 level with each of the allergic diseases, controlling for various sub-district level covariates. Geographically weighted regression (GWR) models were conducted to evaluate how the impact of PM10 varies across the sub-districts. RESULTS: PM10 was found to be a significant predictor of atopic dermatitis patient count (P<0.01), with greater association when spatially interpolated at the sub-district level. No significant effect of PM10 was observed on allergic rhinitis and asthma when socioeconomic factors were controlled for. GWR models revealed spatial variation of PM10 effects on atopic dermatitis across the sub-districts in Seoul. The relationship of PM10 levels to atopic dermatitis patient counts is found to be significant only in the Gangbuk region (P<0.01), along with other covariates including average land value, poverty rate, level of education and apartment rate (P<0.01). CONCLUSIONS: Our findings imply that PM10 effects on allergic diseases might not be consistent throughout Seoul. GIS-based spatial modeling techniques could play a role in evaluating spatial variation of air pollution impacts on allergic diseases at the sub-district level, which could provide valuable guidelines for environmental and public health policymakers.
Resumo:
\abstract
This dissertation seeks to explain the role of governmental and non-governmental actors in increasing/reducing the emergence of intergroup conflict after war, when group differences have been a salient aspect of group mobilization. This question emerges from several interrelated branches of scholarship on self-enforcing institutions and power-sharing arrangements, group fragmentation and demographic change, collective mobilization for collectively-targeted violence, and conflict termination and the post-conflict quality of peace. This question is investigated through quantitative analyses performed at the sub-national, national, and cross-national level on the effect of elite competition on the likelihood of violence committed on the basis of group difference after war. These quantitative analyses are each accompanied by qualitative, case study analyses drawn from the American Reconstruction South, Iraq, and Cote d'Ivoire that illustrate and clarify the mechanisms evaluated through quantitative analysis.
Shared findings suggest the correlation of reduced political competition with the increased likelihood of violence committed on the basis of group difference. Separate findings shed light on how covariates related to control over rent extraction and armed forces, decentralization, and citizenship can lead to a reduction in violence. However, these same quantitative analyses and case study analysis suggest that the control of the state can be perceived as a threat after the end of conflict. Further, together these findings suggest the political nature of violence committed on the basis of group difference as opposed to ethnic identity or resource scarcity alone.
Together, these combined analyses shed light on how and why political identities are formed and mobilized for the purpose of committing political violence after war. In this sense, they shed light on the factors that constrain post-conflict violence in deeply divided societies, and contribute to relevant academic, policy, and normative questions.
Resumo:
© 2015.To determine the immunological profile most important for IRIS prediction, we evaluated 20 baseline plasma biomarkers in Acquired Immunodeficiency Syndrome (AIDS) patients initiating antiretroviral therapy (ART). Patients were enrolled in a randomized, placebo-controlled ART initiation trial in South Africa and Mexico to test whether maraviroc could prevent IRIS. Participants were classified prospectively as having IRIS within 6. months of ART initiation. Twenty plasma biomarkers were measured at study enrollment for 267 participants. Biomarkers were tested for predicting IRIS with adjustment for covariates chosen through forward stepwise selection. Sixty-two participants developed IRIS and of these 21 were tuberculosis (TB)-IRIS. Baseline levels of vitamin D and higher d-dimer, interferon gamma (IFNγ), and sCD14 were independently associated with risk of IRIS in multivariate analyses. TB-IRIS cases exhibited a distinct biosignature from IRIS related to other pathogens, with increased levels of C-reactive protein (CRP), sCD14, IFNγ, and lower levels of Hb that could be captured by a composite risk score. Elevated markers of Type 1 T helper (Th1) response, monocyte activation, coagulation and low vitamin D were independently associated with IRIS risk. Interventions that decrease immune activation and increase vitamin D levels warrant further study.