23 resultados para P values


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Numerous studies have been carried out to try to better understand the genetic predisposition for cardiovascular disease. Although it is widely believed that multifactorial diseases such as cardiovascular disease is the result from effects of many genes which working alone or interact with other genes, most genetic studies have been focused on identifying of cardiovascular disease susceptibility genes and usually ignore the effects of gene-gene interactions in the analysis. The current study applies a novel linkage disequilibrium based statistic for testing interactions between two linked loci using data from a genome-wide study of cardiovascular disease. A total of 53,394 single nucleotide polymorphisms (SNPs) are tested for pair-wise interactions, and 8,644 interactions are found to be significant with p-values less than 3.5×10-11. Results indicate that known cardiovascular disease susceptibility genes tend not to have many significantly interactions. One SNP in the CACNG1 (calcium channel, voltage-dependent, gamma subunit 1) gene and one SNP in the IL3RA (interleukin 3 receptor, alpha) gene are found to have the most significant pair-wise interactions. Findings from the current study should be replicated in other independent cohort to eliminate potential false positive results.^

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Introduction. Cancer is the second most common cause of death in the USA (2). Studies have shown a coexistence of cancer and hypogonadism (9,31,13). The majority of patients with cancer develop cachexia, which cannot be solely explained by anorexia seen in these patients. Testosterone is a male sex hormone which is known to increase muscle mass and strength, maintain cancellous bone mass, and increase cortical bone mass, in addition to improving libido, sexual desire, and fantasy (14). If a high prevalence of hypogonadism is detected in male cancer patients, and a significant difference exists in testosterone levels in cancer patients with cachexia versus those without cachexia, testosterone may be administered in future randomized trials to help alleviate cachexia. Study group and design The study group consisted of male cancer patients and non-cancer controls aged between 40 and 70 years. The primary study design was cross-sectional with a sample size of 135. The present data analysis is done on a subset convenience sample of 72 patients recruited between November 2006 and January 2010. ^ Methods. Patients aged 40-70 years with or without a diagnosis of cancer were recruited into the study. All patients with a BMI over 35, significant edema, non-melanomatous skin cancer, current alcohol or illicit drug abuse, concomitant usage of medications interfering with gonadal axis, and anabolic agents, patients on tube feeds or parenteral nutrition within 3 months prior to enrollment were excluded from the study. The study was approved by the Institutional Review Board of Baylor College of Medicine and is being conducted at the Michael E. DeBakey Veterans Affairs Medical Center at Houston. My thesis is a pilot data analysis that employs a smaller subset convenience sample of 72 patients determined by using the data available for the 72 patients (of the intended sample of 135 patients) recruited between November 2006 and January 2010. The primary aim of this analysis is to compare the proportion of patients with hypogonadism in the male cancer and non-cancer control groups, and to evaluate if a significant difference exists with respect to testosterone levels in male cancer patients with cachexia versus those without cachexia. The procedures of the study relevant to the current data analysis included blood collection to measure levels of testosterone and measurement of body weight to categorize cancer patients into cancer cachexia and cancer non-cachexia sub-groups. ^ Results. After logarithmic transformation of data of cancer and control groups, the unpaired t test with unequal variances was done. The proportion of patients with hypogonadism in the male cancer and non-cancer control groups was 47.5% and 22.7% with a Pearson chi2 statistic of 1.6036 and a p value of 0.205. Comparing the mean calculated Bioavailable testosterone in male cancer patients and non-cancer controls resulted in a t statistic of 21.83 and a p value less than 0.001. When the cancer group alone was taken, the mean free testosterone, calculated bioavailable testosterone and total testosterone levels in the cancer non-cachexia sub-group were 3.93, 5.09, 103.51 respectively and in the cancer cachexia sub-group were 3.58, 4.17, 84.08 respectively. The unpaired t test with equal variances showed that the two sub-groups had p values of 0.2015, 0.1842, and 0.4894 with respect to calculated bioavailable testosterone, free testosterone, and total testosterone respectively. ^ Conclusions. The small sample size of this exploratory study, resulting in a small power, does not allow us to draw definitive conclusions. For the given sub-sample, the proportion of patients with hypogonadism in the cancer group was not significantly different from that of patients with hypogonadism in the control group. Inferences on prevalence of hypogonadism in male cancer patients could not be made in this paper as the sub-sample is small and therefore not representative of the general population. However, there was a statistically significant difference in calculated Bioavailable testosterone levels in male cancer patients versus non-cancer controls. Analysis of cachectic and non-cachectic patients within the male cancer group showed no significant difference in testosterone levels (total, free, and calculated bioavailable testosterone) between both sub-groups. However, to re-iterate, this study is exploratory and the results may change once the complete dataset is obtained and analyzed. It however serves as a good template to guide further research and analysis.^

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Interaction effect is an important scientific interest for many areas of research. Common approach for investigating the interaction effect of two continuous covariates on a response variable is through a cross-product term in multiple linear regression. In epidemiological studies, the two-way analysis of variance (ANOVA) type of method has also been utilized to examine the interaction effect by replacing the continuous covariates with their discretized levels. However, the implications of model assumptions of either approach have not been examined and the statistical validation has only focused on the general method, not specifically for the interaction effect.^ In this dissertation, we investigated the validity of both approaches based on the mathematical assumptions for non-skewed data. We showed that linear regression may not be an appropriate model when the interaction effect exists because it implies a highly skewed distribution for the response variable. We also showed that the normality and constant variance assumptions required by ANOVA are not satisfied in the model where the continuous covariates are replaced with their discretized levels. Therefore, naïve application of ANOVA method may lead to an incorrect conclusion. ^ Given the problems identified above, we proposed a novel method modifying from the traditional ANOVA approach to rigorously evaluate the interaction effect. The analytical expression of the interaction effect was derived based on the conditional distribution of the response variable given the discretized continuous covariates. A testing procedure that combines the p-values from each level of the discretized covariates was developed to test the overall significance of the interaction effect. According to the simulation study, the proposed method is more powerful then the least squares regression and the ANOVA method in detecting the interaction effect when data comes from a trivariate normal distribution. The proposed method was applied to a dataset from the National Institute of Neurological Disorders and Stroke (NINDS) tissue plasminogen activator (t-PA) stroke trial, and baseline age-by-weight interaction effect was found significant in predicting the change from baseline in NIHSS at Month-3 among patients received t-PA therapy.^

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Response to pharmacological treatment is variable among individuals. Some patients respond favorably to a drug while others develop adverse reactions. Early investigations showed evidence of variation in genes that code for drug receptors, drug transporters, and drug metabolizing enzymes; and pharmacogenetics appeared as the science that studies the relationship between drug response and genetic variation. Thiazide diuretics are the recommended first-line monotherapy for hypertension (i.e. SBP>140 or DBP>90). Even so, diuretics are associated with adverse metabolic side effects, such as hyperglycemia, which increase the risk of developing type 2 diabetes. Published approaches testing variation in candidate genes (e.g. the renin-angiotensin-aldosteron system (RAAS) and salt–sensitivity genes) have met with only limited success. We conducted the first genome wide association study to identify genes influencing hyperglycemia as an adverse effect of thiazide diuretics in non-Hispanic White hypertensive patients participating in the Genetic Epidemiology of Responses to Antihypertensives (GERA) and Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) clinical trials. No SNP reached the a priori defined threshold of statistical significance (p<5x10-8). We detected 50 SNPs in 9 genomic regions with suggestive p-values (p<1x10-5). Two of them, rs6870564 (p-value=3.28 X 10-6) and rs7702121 (p-value=5.09 X 10-6), were located close to biologic candidate genes, MYO and MGAT1, and one SNP in a genomic region in chromosome 6, rs7762018 (p-value=4.59 X 10-6) has been previously related to Insulin-Dependent Diabetes Mellitus (IDDM8). I conclude that 1) there are unlikely to be common SNPs with large effects on the adverse metabolic effects to hydrochlorothiazide treatment and 2) larger sample sizes are needed for pharmacogenetic studies of inter-individual variation in response to commonly prescribed medication.

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This issue of the Journal of Family Strengths is an opportunity for a fresh start, as the Family Preservation Journal is renewed and revived under a new name and a new format. Still keen on being a definitive record on developments in family strengths and parenting, the Journal is devoted to presenting theory, practice and evaluation articles on the strengths perspective in family preservation practice, all to assure and improve services and programs that promote and sustain family systems.

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The human colon tumor cell line, LS174T, has been shown to have four major components of the drug metabolizing system; cytochrome b$\sb5$ reductase, cytochrome b$\sb5$, cytochrome P450 reductase and cytochrome P450, by activity measurements, spectral studies and antibody cross-reactivity. Cytochrome P450IA1 is induced by benzanthracene in these cells as shown by activity with the specific substrate, ethoxyresorufin, cross-reactivity with rabbit antibodies to rat IA1, and by a hybridizing band on a Northern blot to a rat IA1 probe.^ Further, this system has proven responsive to various inducers and conditions of growth. The enzyme activities were found stable over limited cell passages with control values of 0.03 and 0.13 $\mu$mol/min/mg protein for NADPH and NADH cytochrome c (cyt c) reducing activity, 0.05 nmol cyt b$\sb5$ per milligram and 0.013 nmol cytochrome P450 per milligram of microsomal protein. Phenobarbital/hydrocortisone treatment showed a consistent, but not always significant increase in the NADPH and NADH cyt c reducing activity and benzanthracene treatment an increase in the NADH cyt c reducing activity. Delta-aminolevulinic acid (0.5mM) caused a significant decrease in the specific activity of all enzyme contents and activities tested.^ Finally, the cytochrome b$\sb5$ to cytochrome P450, by the coordinate induction of the cytochrome b$\sb5$ pathway by P450 inducers, by the high ratio of NADH to NADPH ethoxycoumarin deethylase activity in uninduced cell microsomes, and by the increase in NADH and NADPH ethoxycoumarin deethylase activity when the microsomes were treated with potassium cyanide, a desaturase inhibitor. ^

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The hydroxylation of N- and O-methyl drugs and a polycyclic hydrocarbon has been demonstrated in microsomes prepared from two transplantable Morris hepatomas (i.e., 7288C. t.c. and 5123 t.c.(H). The hydroxylation rates of the drug benzphetamine and the polycyclic hydrocarbon benzo {(alpha)} pyrene by tumor microsomes were inducible 2 to 3-fold and 2-fold, respectively by pretreatment of rats with phenobarbital/hydrocortisone. Hepatoma 5123t.c.(h) microsomal hydroxylation activities were more inducible after these pretreatments than hepatoma 7288C.t.c. Two chemotherapeutic drugs (cyclophosphamide and isophosphamide) were shown to be mutagenic after activation by the tumor hemogenate with the TA100 strain of Salmonella typhimurium bacteria. NADPH-cytochrome P-450 was purified from phenobarbital/hydrocortisone treated rat hepatoma 5123t.c.(H) microsomes 353-fold with a specific activity 63.6 nmol of cytochrome c reduced per min per mg of protein. The purified enzyme, has an apparent molecular weight of 79,500 daltons, and contained an equal molar ratio of FMN and FAD, with a total flavin content of 16.4 nmol per mg of protein. The purified enzyme also catalyzed electron transfer to artificial electron acceptors with the K(,m) values of the hepatoma reductase similar to those of purified liver reductase. The K(,m) value of the hepatoma reductase (13 uM) for NADPH was similar to that of purified liver reductase (5.0 uM). In addition the purified hepatoma reductase was immunochemically similar to the liver reductase.^ Hepatoma cytochrome P-450, the hemeprotein component of the hepatoma microsomes of rats pretreated with phenobarbital/hydrocortisone. The resolution of the six forms was achieved by the DE-53 ion-exchange chromatography, and further purified by hydroxyapatite. The six different fractions that contained P-450 activity, had specific contents from 0.47 to 1.75 nmol of cytochrome P-450 per mg of protein, and indicated a 2 to 9-fold purification as compared to the original microsomes. In addition, difference spectra, molecular weights and immunological results suggest there are at least six different forms of cytochrome P-450 in hepatoma 5123 t.c.(H). ^

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Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^