17 resultados para method of separating variables

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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The Houston region is home to arguably the largest petrochemical and refining complex anywhere. The effluent of this complex includes many potentially hazardous compounds. Study of some of these compounds has led to recognition that a number of known and probable carcinogens are at elevated levels in ambient air. Two of these, benzene and 1,3-butadiene, have been found in concentrations which may pose health risk for residents of Houston.^ Recent popular journalism and publications by local research institutions has increased the interest of the public in Houston's air quality. Much of the literature has been critical of local regulatory agencies' oversight of industrial pollution. A number of citizens in the region have begun to volunteer with air quality advocacy groups in the testing of community air. Inexpensive methods exist for monitoring of ozone, particulate matter and airborne toxic ambient concentrations. This study is an evaluation of a technique that has been successfully applied to airborne toxics.^ This technique, solid phase microextraction (SPME), has been used to measure airborne volatile organic hydrocarbons at community-level concentrations. It is has yielded accurate and rapid concentration estimates at a relatively low cost per sample. Examples of its application to measurement of airborne benzene exist in the literature. None have been found for airborne 1,3-butadiene. These compounds were selected for an evaluation of SPME as a community-deployed technique, to replicate previous application to benzene, to expand application to 1,3-butadiene and due to the salience of these compounds in this community. ^ This study demonstrates that SPME is a useful technique for quantification of 1,3-butadiene at concentrations observed in Houston. Laboratory background levels precluded recommendation of the technique for benzene. One type of SPME fiber, 85 μm Carboxen/PDMS, was found to be a sensitive sampling device for 1,3-butadiene under temperature and humidity conditions common in Houston. This study indicates that these variables affect instrument response. This suggests the necessity of calibration within specific conditions of these variables. While deployment of this technique was less expensive than other methods of quantification of 1,3-butadiene, the complexity of calibration may exclude an SPME method from broad deployment by community groups.^

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This research examined to what extent Health Belief Model (HBM) and socioeconomic variables were useful in explaining the choice whether or not more effective contraceptive methods were used among married fecund women intending no additional births. The source of the data was the 1976 National Survey of Family Growth conducted under the auspices of the National Center for Health Statistics. Using the HBM as a framework for multivariate analyses limited support was found (using available measures) that the HBM components of motivation and perceived efficacy influence the likelihood of more effective contraceptive method use. Support was also found that modifying variables suggested by the HBM can influence the effects of HBM components on the likelihood of more effective method use. Socioeconomic variables were found, using all cases and some subgroups, to have a significant additional influence on the likelihood of use of more effective methods. Limited support was found for the concept that the greater the opportunity costs of an unwanted birth the greater the likelihood of use of more effective contraceptive methods. This research supports the use of HBM and socioeconomic variables to explain the likelihood of a protective health behavior, use of more effective contraception if no additional births are intended.^

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Any functionally important mutation is embedded in an evolutionary matrix of other mutations. Cladistic analysis, based on this, is a method of investigating gene effects using a haplotype phylogeny to define a set of tests which localize causal mutations to branches of the phylogeny. Previous implementations of cladistic analysis have not addressed the issue of analyzing data from related individuals, though in human studies, family data are usually needed to obtain unambiguous haplotypes. In this study, a method of cladistic analysis is described in which haplotype effects are parameterized in a linear model which accounts for familial correlations. The method was used to study the effect of apolipoprotein (Apo) B gene variation on total-, LDL-, and HDL-cholesterol, triglyceride, and Apo B levels in 121 French families. Five polymorphisms defined Apo B haplotypes: the signal peptide Insertion/deletion, Bsp 1286I, XbaI, MspI, and EcoRI. Eleven haplotypes were found, and a haplotype phylogeny was constructed and used to define a set of tests of haplotype effects on lipid and apo B levels.^ This new method of cladistic analysis, the parametric method, found significant effects for single haplotypes for all variables. For HDL-cholesterol, 3 clusters of evolutionarily-related haplotypes affecting levels were found. Haplotype effects accounted for about 10% of the genetic variance of triglyceride and HDL-cholesterol levels. The results of the parametric method were compared to those of a method of cladistic analysis based on permutational testing. The permutational method detected fewer haplotype effects, even when modified to account for correlations within families. Simulation studies exploring these differences found evidence of systematic errors in the permutational method due to the process by which haplotype groups were selected for testing.^ The applicability of cladistic analysis to human data was shown. The parametric method is suggested as an improvement over the permutational method. This study has identified candidate haplotypes for sequence comparisons in order to locate the functional mutations in the Apo B gene which may influence plasma lipid levels. ^

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Ethnic violence appears to be the major source of violence in the world. Ethnic hostilities are potentially all-pervasive because most countries in the world are multi-ethnic. Public health's focus on violence documents its increasing role in this issue.^ The present study is based on a secondary analysis of a dataset of responses by 272 individuals from four ethnic groups (Anglo, African, Mexican, and Vietnamese Americans) who answered questions regarding variables related to ethnic violence from a general questionnaire which was distributed to ethnically diverse purposive, nonprobability, self-selected groups of individuals in Houston, Texas, in 1993.^ One goal was psychometric: learning about issues in analysis of datasets with modest numbers, comparison of two approaches to dealing with missing observations not missing at random (conducting analysis on two datasets), transformation analysis of continuous variables for logistic regression, and logistic regression diagnostics.^ Regarding the psychometric goal, it was concluded that measurement model analysis was not possible with a relatively small dataset with nonnormal variables, such as Likert-scaled variables; therefore, exploratory factor analysis was used. The two approaches to dealing with missing values resulted in comparable findings. Transformation analysis suggested that the continuous variables were in the correct scale, and diagnostics that the model fit was adequate.^ The substantive portion of the analysis included the testing of four hypotheses. Hypothesis One proposed that attitudes/efficacy regarding alternative approaches to resolving grievances from the general questionnaire represented underlying factors: nonpunitive social norms and strategies for addressing grievances--using the political system, organizing protests, using the system to punish offenders, and personal mediation. Evidence was found to support all but one factor, nonpunitive social norms.^ Hypothesis Two proposed that the factor variables and the other independent variables--jail, grievance, male, young, and membership in a particular ethnic group--were associated with (non)violence. Jail, grievance, and not using the political system to address grievances were associated with a greater likelihood of intergroup violence.^ No evidence was found to support Hypotheses Three and Four, which proposed that grievance and ethnic group membership would interact with other variables (i.e., age, gender, etc.) to produce variant levels of subgroup (non)violence.^ The generalizability of the results of this study are constrained by the purposive self-selected nature of the sample and small sample size (n = 272).^ Suggestions for future research include incorporating other possible variables or factors predictive of intergroup violence in models of the kind tested here, and the development and evaluation of interventions that promote electoral and nonelectoral political participation as means of reducing interethnic conflict. ^

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Cancer is a chronic disease that often necessitates recurrent hospitalizations, a costly pattern of medical care utilization. In chronically ill patients, most readmissions are for treatment of the same condition that caused the preceding hospitalization. There is concern that rather than reducing costs, earlier discharge may shift costs from the initial hospitalization to emergency center visits. ^ This is the first descriptive study to measure the incidence of emergency center visits (ECVs) after hospitalization at The University of M. D. Anderson Cancer Center (UTMDACC), to identify the risk factors for and outcomes of these ECVs, and to compare 30-day all-cause mortality and costs for episodes of care with and without ECVs. ^ We identified all hospitalizations at UTMDACC with admission dates from September 1, 1993 through August 31, 1997 which met inclusion criteria. Data were electronically obtained primarily from UTMDACC's institutional database. Demographic factors, clinical factors, duration of the index hospitalization, method of payment for care, and year of hospitalization study were variables determined for each hospitalization. ^ The overall incidence of ECVs was 18%. Forty-five percent of ECVs resulted in hospital readmission (8% of all hospitalizations). In 1% of ECVs the patient died in the emergency center, and for the remaining 54% of ECVs the patient was discharged home. Risk factors for ECVs were marital status, type of index hospitalization, cancer type, and duration of the index hospitalization. The overall 30-day all-cause mortality rate was 8.6% for hospitalizations with an ECV and 5.3% for those without an ECV. In all subgroups, the 30-day all-cause mortality rate was higher for groups with ECVs than for those without ECVs. The most important factor increasing cost was having an ECV. In all patient subgroups, the cost per episode of care with an ECV was at least 1.9 times the cost per episode without an ECV. ^ The higher costs and poorer outcomes of episodes of care with ECVs and hospital readmissions suggest that interventions to avoid these ECVs or mitigate their costs are needed. Further research is needed to improve understanding of the methodological issues involved in relation to health care issues for cancer patients. ^

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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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It is widely acknowledged in theoretical and empirical literature that social relationships, comprising of structural measures (social networks) and functional measures (perceived social support) have an undeniable effect on health outcomes. However, the actual mechanism of this effect has yet to be clearly understood or explicated. In addition, comorbidity is found to adversely affect social relationships and health related quality of life (a valued outcome measure in cancer patients and survivors). ^ This cross sectional study uses selected baseline data (N=3088) from the Women's Healthy Eating and Living (WHEL) study. Lisrel 8.72 was used for the latent variable structural equation modeling. Due to the ordinal nature of the data, Weighted Least Squares (WLS) method of estimation using Asymptotic Distribution Free covariance matrices was chosen for this analysis. The primary exogenous predictor variables are Social Networks and Comorbidity; Perceived Social Support is the endogenous predictor variable. Three dimensions of HRQoL, physical, mental and satisfaction with current quality of life were the outcome variables. ^ This study hypothesizes and tests the mechanism and pathways between comorbidity, social relationships and HRQoL using latent variable structural equation modeling. After testing the measurement models of social networks and perceived social support, a structural model hypothesizing associations between the latent exogenous and endogenous variables was tested. The results of the study after listwise deletion (N=2131) mostly confirmed the hypothesized relationships (TLI, CFI >0.95, RMSEA = 0.05, p=0.15). Comorbidity was adversely associated with all three HRQoL outcomes. Strong ties were negatively associated with perceived social support; social network had a strong positive association with perceived social support, which served as a mediator between social networks and HRQoL. Mental health quality of life was the most adversely affected by the predictor variables. ^ This study is a preliminary look at the integration of structural and functional measures of social relationships, comorbidity and three HRQoL indicators using LVSEM. Developing stronger social networks and forming supportive relationships is beneficial for health outcomes such as HRQoL of cancer survivors. Thus, the medical community treating cancer survivors as well as the survivor's social networks need to be informed and cognizant of these possible relationships. ^

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Purpose. Recent reports reveals that studies of decision aids reported concern about the balance and accuracy of information included in decision aids. This study explores measures of balance in patient decision aids through a review of prostate cancer screening decision aid studies and analysis of patients’ rating of a patient decision aid for prostate cancer screening. ^ Methods. A data-abstraction form was used to collect the key characteristics, pertaining to balance, of studies included in the review. The key characteristics included (1) sample characteristics (age, race, family history of prostate cancer, and education), (2) description of the decision aid and how it was implemented, and (3) if a measure of balance was used for process evaluation and the rating. A summary table was used to report the findings. Deidentified data was received from a decision aid control trial and logistic regression analysis was used to test the association between the dependent variable (balance) and the independent variables (age, family history, race, screening preference at baseline, education, health insurance status). ^ Conclusion. Three sociodemographic variables remained significant in the final regression model: African American race, education and PSA history. Further research is needed to determine if these variables can predict a man’s perception of balance in prostate cancer screening decision aids. If a patient’s perceptions of balance can be predicted based on specific characteristics, patient report may not be the most objective method of evaluating the acceptability of a decision.^

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Objective. Predictors of non-adherence to antiretroviral medications in a population of low-income, multiethnic, HIV-positive smokers were investigated. ^ Methods. A secondary analysis was conducted using baseline data collected from 326 patients currently prescribed antiretrovirals enrolled in a randomized clinical trial assessing smoking outcomes. Variables evaluated included demographics, stress, depression, nicotine dependence, illicit drug use and alcohol use. ^ Results. The average age of participants was 45.9 years (SD=7.6). The majority of participants were male (72.1%), Black (76.7%), reported sexual contact as the method of HIV exposure (heterosexual (43%) and MSM (27%)) and were antiretroviral adherent (60.4%). Results from unadjusted analyses indicated depression (OR=1.02; 95% CI=1.00-1.04), illicit drug use (OR=2.39; 95% CI=1.51-3.79) and alcohol consumption (OR=2.86; 95% CI=1.79-4.57) were associated with non-adherence. Multivariate analyses indicated nicotine dependence (OR=1.13; 95% CI=1.02-1.25), illicit drug use (OR=2.10; 95% CI=1.27-3.49) and alcohol use (OR=2.50; 95% CI=1.52-4.12) were associated with nonadherence. ^ Conclusions. Illicit drug use, alcohol use and nicotine dependence are formidable barriers to antiretroviral adherence in this population. Future research is needed to assess how to address these variables in the context of improving antiretroviral adherence for individuals living with HIV/AIDS.^

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Body fat distribution is a cardiovascular health risk factor in adults. Body fat distribution can be measured through various methods including anthropometry. It is not clear which anthropometric index is suitable for epidemiologic studies of fat distribution and cardiovascular disease. The purpose of the present study was to select a measure of body fat distribution from among a series of indices (those traditionally used in the literature and others constructed from the analysis) that is most highly correlated with lipid-related variables and is independent of overall fatness. Subjects were Mexican-American men and women (N = 1004) from a study of gallbladder disease in Starr County, Texas. Multivariate associations were sought between lipid profile measures (lipids, lipoproteins, and apolipoproteins) and two sets of anthropometric variables (4 circumferences and 6 skinfolds). This was done to assess the association between lipid-related measures and the two sets of anthropometric variables and guide the construction of indices.^ Two indices emerged from the analysis that seemed to be highly correlated with lipid profile measures independent of obesity. These indices are: 2*arm circumference-thigh skinfold in pre- and post-menopausal women and arm/thigh circumference ratio in men. Next, using the sum of all skinfolds to represent obesity and the selected body fat distribution indices, the following hypotheses were tested: (1) state of obesity and centrally/upper distributed body fat are equally predictive of lipids, lipoproteins and apolipoproteins, and (2) the correlation among the lipid-related measures is not altered by obesity and body fat distribution.^ With respect to the first hypothesis, the present study found that most lipids, lipoproteins and apolipoproteins were significantly associated with both overall fatness and anatomical location of body fat in both sex and menopausal groups. However, within men and post-menopausal women, certain lipid profile measures (triglyceride and HDLT among post-menopausal women and apos C-II, CIII, and E among men) had substantially higher correlation with body fat distribution as compared with overall fatness.^ With respect to the second hypothesis, both obesity and body fat distribution were found to alter the association among plasma lipid variables in men and women. There was a suggestion from the data that the pattern of correlations among men and post-menopausal women are more comparable. Among men correlations involving apo A-I, HDLT, and HDL$\sb2$ seemed greatly influenced by obesity, and A-II by fat distribution; among post-menopausal women correlations involving apos A-I and A-II were highly affected by the location of body fat.^ Thus, these data point out that not only can obesity and fat distribution affect levels of single measures, they also can markedly influence the pattern of relationship among measures. The fact that such changes are seen for both obesity and fat distribution is significant, since the indices employed were chosen because they were independent of one another. ^

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This study described home infusion techniques and practices, measured the perceived risk of HIV and hepatitis transmission to self and others, and measured the outcome expectancy of following risk reduction guidelines for 90 hemophilia patients and/or their infusion assistants. It also assessed general knowledge of HIV and hepatitis information for the same population.^ The study subjects were hemophilia patients or their infusion assistants from the Gulf States Hemophilia Center in Houston, the El Paso Satellite Hemophilia Clinic in El Paso, or Texas members of the Women Outreach Network of the National Hemophilia Foundation (WONN) group. Each subject was interviewed either by telephone or in person. The questionnaire used was developed for the study and consisted of 60 items. These items assessed general demographics for the patients and assistants, including questions about their training to do infusions as well as the actual practices, measured perceived personal risk for the transmission of HIV or hepatitis to the assistants, perceived risk of transmission of HIV or hepatitis to others for assistants and self-infusers, and the outcome expectancy for following recommended risk reduction guidelines also for both groups.^ The theoretical framework used assumed that perceived risk and outcome expectancy would be predictive of behavior. The findings did not support this theory. Instead, the findings suggest that infusion behavior is habitual in nature; most respondents perform exactly the same behavior for every infusion. Since none of the variables selected were predictive of the compliance behavior for home infusion the teaching method should be directed towards mastery learning, or learning that will incorporate the correct behavior into a habitual pattern of home infusion. ^

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This paper defines and compares several models for describing excess influenza pneumonia mortality in Houston. First, the methodology used by the Center for Disease Control is examined and several variations of this methodology are studied. All of the models examined emphasize the difficulty of omitting epidemic weeks.^ In an attempt to find a better method of describing expected and epidemic mortality, time series methods are examined. Grouping in four-week periods, truncating the data series to adjust epidemic periods, and seasonally-adjusting the series y(,t), by:^ (DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI)^ is the best method examined. This new series w(,t) is stationary and a moving average model MA(1) gives a good fit for forecasting influenza and pneumonia mortality in Houston.^ Influenza morbidity, other causes of death, sex, race, age, climate variables, environmental factors, and school absenteeism are all examined in terms of their relationship to influenza and pneumonia mortality. Both influenza morbidity and ischemic heart disease mortality show a very high relationship that remains when seasonal trends are removed from the data. However, when jointly modeling the three series it is obvious that the simple time series MA(1) model of truncated, seasonally-adjusted four-week data gives a better forecast.^