77 resultados para SAMPLE SIZE


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Health departments, research institutions, policy-makers, and healthcare providers are often interested in knowing the health status of their clients/constituents. Without the resources, financially or administratively, to go out into the community and conduct health assessments directly, these entities frequently rely on data from population-based surveys to supply the information they need. Unfortunately, these surveys are ill-equipped for the job due to sample size and privacy concerns. Small area estimation (SAE) techniques have excellent potential in such circumstances, but have been underutilized in public health due to lack of awareness and confidence in applying its methods. The goal of this research is to make model-based SAE accessible to a broad readership using clear, example-based learning. Specifically, we applied the principles of multilevel, unit-level SAE to describe the geographic distribution of HPV vaccine coverage among females aged 11-26 in Texas.^ Multilevel (3 level: individual, county, public health region) random-intercept logit models of HPV vaccination (receipt of ≥ 1 dose Gardasil® ) were fit to data from the 2008 Behavioral Risk Factor Surveillance System (outcome and level 1 covariates) and a number of secondary sources (group-level covariates). Sampling weights were scaled (level 1) or constructed (levels 2 & 3), and incorporated at every level. Using the regression coefficients (and standard errors) from the final models, I simulated 10,000 datasets for each regression coefficient from the normal distribution and applied them to the logit model to estimate HPV vaccine coverage in each county and respective demographic subgroup. For simplicity, I only provide coverage estimates (and 95% confidence intervals) for counties.^ County-level coverage among females aged 11-17 varied from 6.8-29.0%. For females aged 18-26, coverage varied from 1.9%-23.8%. Aggregated to the state level, these values translate to indirect state estimates of 15.5% and 11.4%, respectively; both of which fall within the confidence intervals for the direct estimates of HPV vaccine coverage in Texas (Females 11-17: 17.7%, 95% CI: 13.6, 21.9; Females 18-26: 12.0%, 95% CI: 6.2, 17.7).^ Small area estimation has great potential for informing policy, program development and evaluation, and the provision of health services. Harnessing the flexibility of multilevel, unit-level SAE to estimate HPV vaccine coverage among females aged 11-26 in Texas counties, I have provided (1) practical guidance on how to conceptualize and conduct modelbased SAE, (2) a robust framework that can be applied to other health outcomes or geographic levels of aggregation, and (3) HPV vaccine coverage data that may inform the development of health education programs, the provision of health services, the planning of additional research studies, and the creation of local health policies.^

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Prevalence and mortality rates for non-insulin dependent (Type II) diabetes mellitus are two to five times greater in the Mexican-American population than in the general U.S. population. Diabetes has been associated with risk factors which increases the likelihood of developing atherosclerosis. Relatives of noninsulin dependent diabetic probands are at increased risk of developing diabetes; and offspring of diabetic parents are at greater risk. Elevation in risk factor levels clearly began to develop prior to adulthood. Therefore an excess of these risk factors are expected among offspring and relatives of diabetics.^ The purposes of this study were to describe levels of risk factors within a group of Mexican American children who were identified through a diabetic proband, and to determine if there was a relationship between risk factor levels and heritability. Data from three hundred and seventy-six children and adolescents between the ages of 7 and 13 years, inclusively, were analyzed. These children were identified through a diabetic proband who participated in the Diabetes Alert Study. This study group was compared to a representative sample of Mexican American children, who participated in the Hispanic Health and Nutrition Examination Survey.^ For females, there were statistically significant associations between upper body fat distribution and increased systolic and diastolic blood pressure after adjusting for age and measures of fatness. Body mass index was positively related to and explained a significant portion of the variability in systolic blood pressure, total cholesterol, and HDL-cholesterol, for males only. No relationship was found between degree of relationship to the diabetic proband and risk factor levels. The most likely explanations for this were insufficient sample size to detect differences, and/or incomplete ascertainment of pedigree information.^ Although there was evidence that these Mexican American children are fatter and have more central fat distribution than non-Hispanic children, there is no evidence of increased risk for diabetes and/or cardiovascular disease at these ages. ^

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In Part One, the foundations of Bayesian inference are reviewed, and the technicalities of the Bayesian method are illustrated. Part Two applies the Bayesian meta-analysis program, the Confidence Profile Method (CPM), to clinical trial data and evaluates the merits of using Bayesian meta-analysis for overviews of clinical trials.^ The Bayesian method of meta-analysis produced similar results to the classical results because of the large sample size, along with the input of a non-preferential prior probability distribution. These results were anticipated through explanations in Part One of the mechanics of the Bayesian approach. ^

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African-Americans make up twelve percent of the United States population, yet they experience morbidity and mortality at a rate that, in some cases, is disproportionate to their numbers. There are numerous health areas, including cancer, in which disparities exist. There are also numerous reasons which have been suggested to explain the high rates of cancer morbidity and mortality experienced by African-Americans. Among the reasons given to explain these differences are lack of knowledge and lack of access to medical care (1). This study sought to increase the knowledge, attitudes, and behavioral intentions of African-American women attending a Baptist church in Houston with regard to cervical cancer, breast cancer, Pap smear, and mammography. It was hypothesized that a church-based cancer education program would produce the desired change in knowledge, attitudes, and behavioral intentions.^ The quasi-experimental design of the study was untreated control group with pretest and posttest and untreated control group with posttest only. Female members of Mount Ararat Baptist Church took part in an eight-week, cancer education program based on social cognitive theory. Baseline data were collected before the start of the program at Mount Ararat and at Solid Rock Baptist Church, control group one. At the end of the program, the follow-up survey was administered at the program church, control church one, and in a third church, Damascus Missionary Baptist Church, which served as the posttest only group. The data were analyzed by Fisher's exact and paired t-test to determine if the program supported the project's hypotheses.^ Results of data analyses supported the major study hypotheses, the exception being behavioral intention to have Pap smear performed. Although the program appeared to have generally influenced changes in the desired direction, the results are limited due to the quasi-experimental design and small sample size. Longer term studies with larger sample sizes are needed to more fully develop and evaluate programs which impact the health of African-Americans. ^

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Purpose. This project was designed to describe the association between wasting and CD4 cell counts in HIV-infected men in order to better understand the role of wasting in progression of HIV infection.^ Methods. Baseline and prevalence data were collected from a cross-sectional survey of 278 HIV-infected men seen at the Houston Veterans Affairs Medical Center Special Medicine Clinic, from June 1, 1991 to January 1, 1994. A follow-up study was conducted among those at risk, to investigate the incidence of wasting and the association between wasting and low CD4 cell counts. Wasting was described by four methods. Z-scores for age-, sex-, and height-adjusted weight; sex-, and age-adjusted mid-arm muscle circumference (MAMC); and fat-free mass; and the ratio of extra-cellular mass (ECM) to body-cell mass (BCM) $>$ 1.20. FFM, ECM, and BCM were estimated from bioelectrical impedance analysis. MAMC was calculated from triceps skinfold and mid-arm circumference. The relationship between wasting and covariates was examined with logistic regression in the cross-sectional study, and with Poisson regression in the follow-up study. The association between death and wasting was examined with Cox's regression.^ Results. The prevalence of wasting ranged from 5% (weight and ECM:BCM) to almost 14% (MAMC and FFM) among the 278 men examined. The odds of wasting, associated with baseline CD4 cell count $<$200, was significant for each method but weight, and ranged from 4.6 to 12.7. Use of antiviral therapy was significantly protective of MAMC, FFM and ECM:BCM (OR $\approx$ 0.2), whereas the need for antibacterial therapy was a risk (OR 3.1, 95% CI 1.1-8.7). The average incidence of wasting ranged from 4 to 16 per 100 person-years among the approximately 145 men followed for 160 person-years. Low CD4 cell count seemed to increase the risk of wasting, but statistical significance was not reached. The effect of the small sample size on the power to detect a significant association should be considered. Wasting, by MAMC and FFM, was significantly associated with death, after adjusting for baseline serum albumin concentration and CD4 cell count.^ Conclusions. Wasting by MAMC and FFM were strongly associated with baseline CD4 cell counts in both the prevalence and incidence study and strong predictors of death. Of the two methods, MAMC is convenient, has available reference population data, may be the most appropriate for assessing the nutritional status of HIV-infected men. ^

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In geographical epidemiology, maps of disease rates and disease risk provide a spatial perspective for researching disease etiology. For rare diseases or when the population base is small, the rate and risk estimates may be unstable. Empirical Bayesian (EB) methods have been used to spatially smooth the estimates by permitting an area estimate to "borrow strength" from its neighbors. Such EB methods include the use of a Gamma model, of a James-Stein estimator, and of a conditional autoregressive (CAR) process. A fully Bayesian analysis of the CAR process is proposed. One advantage of this fully Bayesian analysis is that it can be implemented simply by using repeated sampling from the posterior densities. Use of a Markov chain Monte Carlo technique such as Gibbs sampler was not necessary. Direct resampling from the posterior densities provides exact small sample inferences instead of the approximate asymptotic analyses of maximum likelihood methods (Clayton & Kaldor, 1987). Further, the proposed CAR model provides for covariates to be included in the model. A simulation demonstrates the effect of sample size on the fully Bayesian analysis of the CAR process. The methods are applied to lip cancer data from Scotland, and the results are compared. ^

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Investigation into the medical care utilization of elderly Medicare enrollees in an HMO (Kaiser - Portland, Oregon): The specific research topics are: (1) The utilization of medical care by selected determinants such as: place of service, type of service, type of appointment, physician status, physician specialty and number of associated morbidities. (2) The attended prevalence of 3 chronic diseases: hypertension, diabetes and arthritis in addition to pneumonias as an example of acute diseases. The selection of these examples was based on their importance in morbidity/or mortality results among the elderly. The share of these diseases in outpatient and inpatient contacts was examined as an example of the relation between morbidity and medical care utilization. (3) The tendency of individual utilization patterns to persist in subsequent time periods. The concept of contagion or proneness was studied in a period of 2 years. Fitting the negative binomial and the Poisson distributions was applied to the utilization in the 2nd year conditional on that in the 1st year as regards outpatient and inpatient contacts.^ The present research is based on a longitudinal study of 20% random sample of elderly Medicare enrollees. The sample size is 1683 individuals during the period from August 1980-December 1982.^ The results of the research were: (1) The distribution of contacts by selected determinants did not reveal a consistent pattern between sexes and age groups. (2) The attended prevalence of hypertension and arthritis showed excess prevalence among females. For diabetes and pneumonias no female excess was noticed. Consistent increased prevalence with increasing age was not detected.^ There were important findings pertaining to the relatively big share of the combined 3 chronic diseases in utilization. They accounted for 20% of male outpatient contacts vs. 25% of female outpatients. For inpatient contacts, they consumed 20% in case of males vs. 24% in case of females. (3) Finding that the negative binomial distribution fit the utilization experience supported the research hypothesis concerning the concept of contagion in utilization. This important finding can be helpful in estimating liability functions needed for forecasting future utilization according to previous experience. Such information has its relevance to organization, administration and planning for medical care in general. (Abstract shortened with permission of author.) ^

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This study was designed to identify some of the factors related to patterns of physician visits to nursing home residents. The relationship of ten resident and organizational characteristics to patterns of physician visits was investigated through secondary analysis of data abstracted from the 1973-74 National Nursing Home Survey of the National Center for Health Statistics. The study sample was composed of 11,135 of the 19,013 nursing home residents who participated in the survey.^ The analytic results revealed that all ten variables had a statistically significant relationship to patterns of physician visits, mainly due to the large sample size. The degrees of association between the variables, measured by the Cramer's V statistic, ranged from moderate to very weak.^ Certification status of the nursing home under Medicare and/or Medicaid was shown to be most strongly related to patterns of physician visits, followed by primary source of payment for nursing home care, and residence prior to nursing home admission. Several variables thought to be related to patterns of physician visits were found to have a very weak relationship: age of the resident, marital status, length of stay, primary diagnosis, number of chronic conditions, activities of daily living status, and levels of care.^ In order to get a more precise picture of the relative influence of certification status and primary source of payment when the other variables were statistically controlled, these two variables were combined into a single variable. The results revealed that the combined effects of certification status and primary source of payment were sustained, regardless of differences in the residents' personal, utilization, and health status characteristics, and the levels of care that they received. The results also indicated that the five groups created by combining the two variables differed in patterns of physician visits. For example, private pay residents in intermediate care facilities (ICF's) and non-certified facilities were more likely to receive unscheduled visits than private pay residents in skilled nursing homes (SNH's), residents in SNH's supported by Medicare or Medicaid, and residents in ICF's supported by Medicaid. ^

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This study establishes the extent and relevance of bias of population estimates of prevalence, incidence, and intensity of infection with Schistosoma mansoni caused by the relative sensitivity of stool examination techniques. The population studied was Parcelas de Boqueron in Las Piedras, Puerto Rico, where the Centers for Disease Control, had undertaken a prospective community-based study of infection with S. mansoni in 1972. During each January of the succeeding years stool specimens from this population were processed according to the modified Ritchie concentration (MRC) technique. During January 1979 additional stool specimens were collected from 30 individuals selected on the basis of their mean S. mansoni egg output during previous years. Each specimen was divided into ten 1-gm aliquots and three 42-mg aliquots. The relationship of egg counts obtained with the Kato-Katz (KK) thick smear technique as a function of the mean of ten counts obtained with the MRC technique was established by means of regression analysis. Additionally, the effect of fecal sample size and egg excretion level on technique sensitivity was evaluated during a blind assessment of single stool specimen samples, using both examination methods, from 125 residents with documented S. mansoni infections. The regression equation was: Ln KK = 2.3324 + 0.6319 Ln MRC, and the coefficient of determination (r('2)) was 0.73. The regression equation was then utilized to correct the term "m" for sample size in the expression P ((GREATERTHEQ) 1 egg) = 1 - e('-ms), which estimates the probability P of finding at least one egg as a function of the mean S. mansoni egg output "m" of the population and the effective stool sample size "s" utilized by the coprological technique. This algorithm closely approximated the observed sensitivity of the KK and MRC tests when these were utilized to blindly screen a population of known parasitologic status for infection with S. mansoni. In addition, the algorithm was utilized to adjust the apparent prevalence of infection for the degree of functional sensitivity exhibited by the diagnostic test. This permitted the estimation of true prevalence of infection and, hence, a means for correcting estimates of incidence of infection. ^

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The study focused on the relationship between antisocial personality syndrome in boys ages 8-15 and parental alcohol/drug dependency. The population studied was case records of 101 boys coming to a private psychiatrist from 1966 through 1979. The boys were predominantly white and from middle to upper income families.^ A boy was determined to have antisocial personality syndrome if he exhibited antisocial behaviors in four or five major categories, did not exhibit a brain syndrome, and did not exhibit a thought disorder. The five major behavior categories were: (1) self-control (i.e., temper tantrums or hyperactivity), (2) behavior at home (i.e., disobedience or lying), (3) behavior at school (i.e., truancy or cheating), (4) behavior toward peers (i.e., bullying, fighting, or tattling), and (5) behavior against property (i.e., destructiveness or stealing). A boy was determined to be a control if he exhibited antisocial behaviors in two or less behavior categories.^ A parent was determined to have alcohol/drug dependency if s/he exhibited a score above the established threshold (1) for the MacAndrew Alcoholism Scale (28 or above), and (2) for the Holmes Alcoholism Scale (35 or above) which are used with the MMPI. A parent was classified not alcohol/drug dependent if s/he had scores below set thresholds (22 on the MacAndrew Alcoholism Scale and 28 on the Holmes Alcoholism Scale).^ For the final sample (N = 10), there was no reason to believe a relationship exists between antisocial personality syndrome in boys ages 8-15 and parental alcohol/drug dependency (Fisher's Exact Test {FET} P = 1.0). The small sample size primarily occurred as a result of 88.12% of the parents being classified in a questionable category in terms of alcohol/drug dependency.^ The sample was suggestive of a relationship between the fathers' Psychopathic Deviate (Pd) Scale scores as a measure of antisocial tendencies and the boy having antisocial personality syndrome (N = 75; P = .12). There was no evidence of such a relationship for mothers (N = 75; P = .97). ^

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Background: Helicobacter pylori infection among Native Americans is more prevalent than any other minority group in the United States. Few studies involving Helicobacter pylori have been conducted on Native Americans and no previous studies have been conducted in the Ysleta del Sur Pueblo population. Therefore we wanted to explore the prevalence and risk factors of Helicobacter pylori within this community. We also explored whether household transmission is occurring. ^ Materials and Methods: We conducted a cross-section study on the prevalence of Helicobacter pylori in the Ysleta del Sur Pueblo community. Main household caregivers were interviewed on household conditions, hygiene practices, and household sociodemographics. All household members were tested for IgG urine antibodies against Helicobacter pylori using RAPIRUN test kits. 13C urea breath testing using BREATHTEK kits was provided to study participants that had positive antibody results and utilized as confirmatory results of infection. ^ Results: Prevalence of Ysleta del Sur Pueblo was determined to be 27.4%. When comparing for ethnicity, Native Americans had increased prevalence of infection then Mexican-Americans living on the Pueblo. That prevalence increased from 1.6 to 3.3 when taking account only United States born study participants. The household secondary prevalence rate was found to be 23.8%. Helicobacter pylori infection rates increased with increasing age and decreasing income. ^ Conclusions: Native Americans had an increased risk of infection. As expected risk factors for Helicobacter pylori correlated with previous studies, but we found evidence of limited current transmission within households. However, due to the limited sample size (n=62) and power, we were not able to find statistical significance for some risk factors. A statistical association was found with age where increasing prevalence corresponded with increasing age suggesting that the birth cohort may be in effect within this population.^

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Lung cancer is the leading cause of cancer-related mortality in the US. Emerging evidence has shown that host genetic factors can interact with environmental exposures to influence patient susceptibility to the diseases as well as clinical outcomes, such as survival and recurrence. We aimed to identify genetic prognostic markers for non-small cell lung cancer (NSCLC), a major (85%) subtype of lung cancer, and also in other subgroups. With the fast evolution of genotyping technology, genetic association studies have went through candidate gene approach, to pathway-based approach, to the genome wide association study (GWAS). Even in the era of GWAS, pathway-based approach has its own advantages on studying cancer clinical outcomes: it is cost-effective, requiring a smaller sample size than GWAS easier to identify a validation population and explore gene-gene interactions. In the current study, we adopted pathway-based approach focusing on two critical pathways - miRNA and inflammation pathways. MicroRNAs (miRNA) post-transcriptionally regulate around 30% of human genes. Polymorphisms within miRNA processing pathways and binding sites may influence patients’ prognosis through altered gene regulation. Inflammation plays an important role in cancer initiation and progression, and also has shown to impact patients’ clinical outcomes. We first evaluated 240 single nucleotide polymorphisms (SNPs) in miRNA biogenesis genes and predicted binding sites in NSCLC patients to determine associations with clinical outcomes in early-stage (stage I and II) and late-stage (stage III and IV) lung cancer patients, respectively. First, in 535 early-stage patients, after correcting multiple comparisons, FZD4:rs713065 (hazard ratio [HR]:0.46, 95% confidence interval [CI]:0.32-0.65) showed a significant inverse association with survival in early stage surgery-only patients. SP1:rs17695156 (HR:2.22, 95% CI:1.44-3.41) and DROSHA:rs6886834 (HR:6.38, 95% CI:2.49-16.31) conferred increased risk of progression in the all patients and surgery-only populations, respectively. FAS:rs2234978 was significantly associated with improved survival in all patients (HR:0.59, 95% CI:0.44-0.77) and in the surgery plus chemotherapy populations (HR:0.19, 95% CI:0.07-0.46).. Functional genomics analysis demonstrated that this variant creates a miR-651 binding site resulting in altered miRNA regulation of FAS, providing biological plausibility for the observed association. We then analyzed these associations in 598 late-stage patients. After multiple comparison corrections, no SNPs remained significant in the late stage group, while the top SNP NAT1:rs15561 (HR=1.98, 96%CI=1.32-2.94) conferred a significantly increased risk of death in the chemotherapy subgroup. To test the hypothesis that genetic variants in the inflammation-related pathways may be associated with survival in NSCLC patients, we first conducted a three-stage study. In the discovery phase, we investigated a comprehensive panel of 11,930 inflammation-related SNPs in three independent lung cancer populations. A missense SNP (rs2071554) in HLA-DOB was significantly associated with poor survival in the discovery population (HR: 1.46, 95% CI: 1.02-2.09), internal validation population (HR: 1.51, 95% CI: 1.02-2.25), and external validation (HR: 1.52, 95% CI: 1.01-2.29) population. Rs2900420 in KLRK1 was significantly associated with a reduced risk for death in the discovery (HR: 0.76, 95% CI: 0.60-0.96) and internal validation (HR: 0.77, 95% CI: 0.61-0.99) populations, and the association reached borderline significance in the external validation population (HR: 0.80, 95% CI: 0.63-1.02). We also evaluated these inflammation-related SNPs in NSCLC patients in never smokers. Lung cancer in never smokers has been increasingly recognized as distinct disease from that in ever-smokers. A two-stage study was performed using a discovery population from MD Anderson (411 patients) and a validation population from Mayo Clinic (311 patients). Three SNPs (IL17RA:rs879576, BMP8A:rs698141, and STK:rs290229) that were significantly associated with survival were validated (pCD74:rs1056400 and CD38:rs10805347) were borderline significant (p=0.08) in the Mayo Clinic population. In the combined analysis, IL17RA:rs879576 resulted in a 40% reduction in the risk for death (p=4.1 × 10-5 [p=0.61, heterogeneity test]). We also validated a survival tree created in MD Anderson population in the Mayo Clinic population. In conclusion, our results provided strong evidence that genetic variations in specific pathways that examined (miRNA and inflammation pathways) influenced clinical outcomes in NSCLC patients, and with further functional studies, the novel loci have potential to be translated into clinical use.

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Purpose. The measurement of quality of life has become an important topic in healthcare and in the allocation of limited healthcare resources. Improving the quality of life (QOL) in cancer patients is paramount. Cataract removal and lens implantation appears to improve patient well-being of cancer patients, though a formal measurement has never been published in the US literature. In this current study, National Eye Institute Visual Functioning Questionnaire (NEI-VFQ-25), a validated vision quality of life metric, was used to study the change in vision-related quality of life in cancer patients who underwent cataract extraction with intraocular lens implantation. ^ Methods. Under an IRB approved protocol, cancer patients who underwent cataract surgery with intraocular lens implantation (by a single surgeon) from December 2008 to March 2011, and who had completed a pre- and postoperative NEI-VFQ-25 were retrospectively reviewed. Post-operative data was collected at their routine 4-6 week post-op visit. Patients' demographics, cancer history, their pre and postoperative ocular examinations, visual acuities, and NEI-VFQ-25 with twelve components were included in the evaluation. The responses were evaluated using the Student t test, Spearman correlation and Wilcoxon signed rank test. ^ Results. 63 cases of cataract surgery (from 54 patients) from the MD Anderson Cancer Center were included in the study. Cancer patients had a significant improvement in the visual acuity (P<0.0001) postoperatively, along with a significant increase in vision-related quality of life (P<0.0001). Patients also had a statistically significant improvement in ten of the twelve subcategories which are addressed in the NEI-VFQ-25. ^ Conclusions. In our study, cataract extraction and intraocular implantation showed a significant impact on the vision-related quality of life in cancer patients. Although this study includes a small sample size, it serves as a positive pilot study to evaluate and quantify the impact of a surgical intervention on QOL in cancer patients and may help to design a larger study to measure vision related QOL per dollar spent for health care cost in cancer patients.^

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Complex diseases, such as cancer, are caused by various genetic and environmental factors, and their interactions. Joint analysis of these factors and their interactions would increase the power to detect risk factors but is statistically. Bayesian generalized linear models using student-t prior distributions on coefficients, is a novel method to simultaneously analyze genetic factors, environmental factors, and interactions. I performed simulation studies using three different disease models and demonstrated that the variable selection performance of Bayesian generalized linear models is comparable to that of Bayesian stochastic search variable selection, an improved method for variable selection when compared to standard methods. I further evaluated the variable selection performance of Bayesian generalized linear models using different numbers of candidate covariates and different sample sizes, and provided a guideline for required sample size to achieve a high power of variable selection using Bayesian generalize linear models, considering different scales of number of candidate covariates. ^ Polymorphisms in folate metabolism genes and nutritional factors have been previously associated with lung cancer risk. In this study, I simultaneously analyzed 115 tag SNPs in folate metabolism genes, 14 nutritional factors, and all possible genetic-nutritional interactions from 1239 lung cancer cases and 1692 controls using Bayesian generalized linear models stratified by never, former, and current smoking status. SNPs in MTRR were significantly associated with lung cancer risk across never, former, and current smokers. In never smokers, three SNPs in TYMS and three gene-nutrient interactions, including an interaction between SHMT1 and vitamin B12, an interaction between MTRR and total fat intake, and an interaction between MTR and alcohol use, were also identified as associated with lung cancer risk. These lung cancer risk factors are worthy of further investigation.^

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An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^