Development of a Bayesian Joint Logistic Model to Better Study the Association between Haplotypes and Disease

In 2011, there will be an estimated 1,596,670 new cancer cases and 571,950 cancer-related deaths in the US. With the ever-increasing applications of cancer genetics in epidemiology, there is great potential to identify genetic risk factors that would help identify individuals with increased genetic susceptibility to cancer, which could be used to develop interventions or targeted therapies that could hopefully reduce cancer risk and mortality. In this dissertation, I propose to develop a new statistical method to evaluate the role of haplotypes in cancer susceptibility and development. This model will be flexible enough to handle not only haplotypes of any size, but also a variety of covariates. I will then apply this method to three cancer-related data sets (Hodgkin Disease, Glioma, and Lung Cancer). I hypothesize that there is substantial improvement in the estimation of association between haplotypes and disease, with the use of a Bayesian mathematical method to infer haplotypes that uses prior information from known genetics sources. Analysis based on haplotypes using information from publically available genetic sources generally show increased odds ratios and smaller p-values in both the Hodgkin, Glioma, and Lung data sets. For instance, the Bayesian Joint Logistic Model (BJLM) inferred haplotype TC had a substantially higher estimated effect size (OR=12.16, 95% CI = 2.47-90.1 vs. 9.24, 95% CI = 1.81-47.2) and more significant p-value (0.00044 vs. 0.008) for Hodgkin Disease compared to a traditional logistic regression approach. Also, the effect sizes of haplotypes modeled with recessive genetic effects were higher (and had more significant p-values) when analyzed with the BJLM. Full genetic models with haplotype information developed with the BJLM resulted in significantly higher discriminatory power and a significantly higher Net Reclassification Index compared to those developed with haplo.stats for lung cancer. Future analysis for this work could be to incorporate the 1000 Genomes project, which offers a larger selection of SNPs can be incorporated into the information from known genetic sources as well. Other future analysis include testing non-binary outcomes, like the levels of biomarkers that are present in lung cancer (NNK), and extending this analysis to full GWAS studies.

Exploring a model of skillful engagement in nursing practice

Prominent challenges facing nurse leaders are the growing shortage of nurses and the increasingly complex care required by acutely ill patients. In organizations that shortage is exacerbated by turnover and intent to leave. Unsatisfactory working conditions are cited by nurses when they leave their current jobs. Disengagement from the job leads to plateaued performance, decreased organizational commitment, and increased turnover. Solutions to these challenges include methods both to retain and to increase the effectiveness of each nurse. ^ The specific aim of this study was to examine the relationships among organizational structures thought to foster the clinical development of the nurse, with indicators of the development of clinical expertise, resulting in outcomes of positive job attitudes and effectiveness. Causal loop modeling is incorporated as a systems tool to examine developmental cycles both for an organization and for an individual nurse to look beyond singular events and investigate deeper patterns that emerge over time. ^ The setting is an academic specialty-care institution, and the sample in this cross-sectional study consists of paired data from 225 RNs and their nurse managers. Two panels of survey instruments were created based on the model's theoretical variables, one completed by RNs and the other by their Nurse Managers. The RN survey panel examined the variables of structural empowerment, magnet essentials, knowledge as identified by the Benner developmental stage, psychological empowerment, job stage, engagement, intent to leave, job satisfaction and the early recognition of patient complications. The nurse manager survey panel examined the Benner developmental stage, job stage, and overall level of nursing performance. ^ Four regression models were created based on the outcome variables. Each model identified significant organizational and individual characteristics that predicted higher job satisfaction, decreased intent to leave, more effectiveness as measured by early recognition and acting upon subtle patient complications, and better job performance. ^ Implications for improving job attitudes and effectiveness focus on ways that nursing leaders can foster a more empowering and healthy work environment. ^

Advanced Protein Modeling Method: Benchmarking and Applications in Computer-Aided Drug Discovery

Development of homology modeling methods will remain an area of active research. These methods aim to develop and model increasingly accurate three-dimensional structures of yet uncrystallized therapeutically relevant proteins e.g. Class A G-Protein Coupled Receptors. Incorporating protein flexibility is one way to achieve this goal. Here, I will discuss the enhancement and validation of the ligand-steered modeling, originally developed by Dr. Claudio Cavasotto, via cross modeling of the newly crystallized GPCR structures. This method uses known ligands and known experimental information to optimize relevant protein binding sites by incorporating protein flexibility. The ligand-steered models were able to model, reasonably reproduce binding sites and the co-crystallized native ligand poses of the β2 adrenergic and Adenosine 2A receptors using a single template structure. They also performed better than the choice of template, and crude models in a small scale high-throughput docking experiments and compound selectivity studies. Next, the application of this method to develop high-quality homology models of Cannabinoid Receptor 2, an emerging non-psychotic pain management target, is discussed. These models were validated by their ability to rationalize structure activity relationship data of two, inverse agonist and agonist, series of compounds. The method was also applied to improve the virtual screening performance of the β2 adrenergic crystal structure by optimizing the binding site using β2 specific compounds. These results show the feasibility of optimizing only the pharmacologically relevant protein binding sites and applicability to structure-based drug design projects.

Thoracic radiotherapy treatment planning with cine PET/CT

Purpose: Respiratory motion causes substantial uncertainty in radiotherapy treatment planning. Four-dimensional computed tomography (4D-CT) is a useful tool to image tumor motion during normal respiration. Treatment margins can be reduced by targeting the motion path of the tumor. The expense and complexity of 4D-CT, however, may be cost-prohibitive at some facilities. We developed an image processing technique to produce images from cine CT that contain significant motion information without 4D-CT. The purpose of this work was to compare cine CT and 4D-CT for the purposes of target delineation and dose calculation, and to explore the role of PET in target delineation of lung cancer. Methods: To determine whether cine CT could substitute 4D-CT for small mobile lung tumors, we compared target volumes delineated by a physician on cine CT and 4D-CT for 27 tumors with intrafractional motion greater than 1 cm. We assessed dose calculation by comparing dose distributions calculated on respiratory-averaged cine CT and respiratory-averaged 4D-CT using the gamma index. A threshold-based PET segmentation model of size, motion, and source-to-background was developed from phantom scans and validated with 24 lung tumors. Finally, feasibility of integrating cine CT and PET for contouring was assessed on a small group of larger tumors. Results: Cine CT to 4D-CT target volume ratios were (1.05±0.14) and (0.97±0.13) for high-contrast and low-contrast tumors respectively which was within intraobserver variation. Dose distributions on cine CT produced good agreement (< 2%/1 mm) with 4D-CT for 71 of 73 patients. The segmentation model fit the phantom data with R2 = 0.96 and produced PET target volumes that matched CT better than 6 published methods (-5.15%). Application of the model to more complex tumors produced mixed results and further research is necessary to adequately integrate PET and cine CT for delineation. Conclusions: Cine CT can be used for target delineation of small mobile lesions with minimal differences to 4D-CT. PET, utilizing the segmentation model, can provide additional contrast. Additional research is required to assess the efficacy of complex tumor delineation with cine CT and PET. Respiratory-averaged cine CT can substitute respiratory-averaged 4D-CT for dose calculation with negligible differences.

A Coordinated and Systematic Model for Adopting, Implementing and Maintaining Effective Sexual Health Education Programs in Schools

Getting evidence-based sexual health education activities into schools can be a complicated process. Working models that assist our educational system in the selection, implementation, and maintenance of effective school-based adolescent health programs are needed. Replicating sexual health programs in school-based settings: A model for schools provides a comprehensive and applied approach that engages all of the important stakeholders within a school district. The results from this study hold much potential to inform Texas and the nation about how a coordinated and practical model can assist school districts to increase the use of evidence-based programs addressing teen pregnancy prevention and sexual health issues.

Youth empowerment evaluation to improve afterschool programming

Community-based participatory research necessitates that community members act as partners in decision making and mutual learning and discovery. In the same light, for programs/issues involving youth, youth should be partners in knowledge sharing and evaluation (Checkoway & Richards-Schuster, 2004). This study is a youth-focused empowerment evaluation for the Successful Youth program. Successful Youth is a multi-component youth development after-school program for Latino middle school youth, created with the goal of reducing teen pregnancy. An empowerment evaluation is collaborative and participatory (Balcazar and Harper 2003). The three steps of an empowerment evaluation are: (1) defining mission, (2) taking stock, and (3) planning for the future (Fetterman 2001).^ In a program where youth are developing leadership skills, making choices, and learning how to self reflect and evaluate, the empowerment evaluation could not be more aligned with promoting and enhancing these skills. In addition, an empowerment evaluation is designed to "foster improvement and self-determination" and "build capacity" (Fetterman 2001). Four empowerment groups were conducted with approximately 6-9 Latino 7th grade students per group. All participants were enrolled in the Successful Youth program. Results indicate points where students' perceptions of the program were aligned with the program's mission and where gaps were identified. Students offered recommendations for program improvements. Additionally, students enjoyed expressing their feelings about the program and appreciated that their opinions were valued. Youth recommendations will be brought to program staff; and, where possible, gaps will be addressed. Empowerment evaluations with youth will continue during the duration of the program so that youth involvement and input remains integral in the evaluation and to ascertain whether the program's goals are being met. ^

A community-based assessment of the spatiotemporal distribution of influenza in a U.S.-Mexico border county during the spring 2009 novel H1N1 swine-origin influenza A pandemic

This study retrospectively evaluated the spatial and temporal disease patterns associated with influenza-like illness (ILI), positive rapid influenza antigen detection tests (RIDT), and confirmed H1N1 S-OIV cases reported to the Cameron County Department of Health and Human Services between April 26 and May 13, 2009 using the space-time permutation scan statistic software SaTScan in conjunction with geographical information system (GIS) software ArcGIS 9.3. The rate and age-adjusted relative risk of each influenza measure was calculated and a cluster analysis was conducted to determine the geographic regions with statistically higher incidence of disease. A Poisson distribution model was developed to identify the effect that socioeconomic status, population density, and certain population attributes of a census block-group had on that area's frequency of S-OIV confirmed cases over the entire outbreak. Predominant among the spatiotemporal analyses of ILI, RIDT and S-OIV cases in Cameron County is the consistent pattern of a high concentration of cases along the southern border with Mexico. These findings in conjunction with the slight northward space-time shifts of ILI and RIDT cluster centers highlight the southern border as the primary site for public health interventions. Finally, the community-based multiple regression model revealed that three factors—percentage of the population under age 15, average household size, and the number of high school graduates over age 25—were significantly associated with laboratory-confirmed S-OIV in the Lower Rio Grande Valley. Together, these findings underscore the need for community-based surveillance, improve our understanding of the distribution of the burden of influenza within the community, and have implications for vaccination and community outreach initiatives.^

Determinants of CD4 cell count decline after treatment interruption

Patients who had started HAART (Highly Active Anti-Retroviral Treatment) under previous aggressive DHHS guidelines (1997) underwent a life-long continuous HAART that was associated with many short term as well as long term complications. Many interventions attempted to reduce those complications including intermittent treatment also called pulse therapy. Many studies were done to study the determinants of rate of fall in CD4 count after interruption as this data would help guide treatment interruptions. The data set used here was a part of a cohort study taking place at the Johns Hopkins AIDS service since January 1984, in which the data were collected both prospectively and retrospectively. The patients in this data set consisted of 47 patients receiving via pulse therapy with the aim of reducing the long-term complications. ^ The aim of this project was to study the impact of virologic and immunologic factors on the rate of CD4 loss after treatment interruption. The exposure variables under investigation included CD4 cell count and viral load at treatment initiation. The rates of change of CD4 cell count after treatment interruption was estimated from observed data using advanced longitudinal data analysis methods (i.e., linear mixed model). Using random effects accounted for repeated measures of CD4 per person after treatment interruption. The regression coefficient estimates from the model was then used to produce subject specific rates of CD4 change accounting for group trends in change. The exposure variables of interest were age, race, and gender, CD4 cell counts and HIV RNA levels at HAART initiation. ^ The rate of fall of CD4 count did not depend on CD4 cell count or viral load at initiation of treatment. Thus these factors may not be used to determine who can have a chance of successful treatment interruption. CD4 and viral load were again studied by t-tests and ANOVA test after grouping based on medians and quartiles to see any difference in means of rate of CD4 fall after interruption. There was no significant difference between the groups suggesting that there was no association between rate of fall of CD4 after treatment interruption and above mentioned exposure variables. ^

A path analysis of an after-school health and exercise program for elementary school children in El Paso, Texas

As schools are pressured to perform on academics and standardized examinations, schools are reluctant to dedicate increased time to physical activity. After-school exercise and health programs may provide an opportunity to engage in more physical activity without taking time away from coursework during the day. The current study is a secondary data analysis of data from a randomized trial of a 10-week after-school program (six schools, n = 903) that implemented an exercise component based on the CATCH physical activity component and health modules based on the culturally-tailored Bienestar health education program. Outcome variables included BMI and aerobic capacity, health knowledge and healthy food intentions as assessed through path analysis techniques. Both the baseline model (χ2 (df = 8) = 16.90, p = .031; RMSEA = .035 (90% CI of .010–.058), NNFI = 0.983 and the CFI = 0.995) and the model incorporating intervention participation proved to be a good fit to the data (χ2 (df = 10) = 11.59, p = .314. RMSEA = .013 (90% CI of .010–.039); NNFI = 0.996 and CFI = 0.999). Experimental group participation was not predictive of changes in health knowledge, intentions to eat healthy foods or changes in Body Mass Index, but it was associated with increased aerobic capacity, β = .067, p < .05. School characteristics including SES and Language proficiency proved to be significantly associated with changes in knowledge and physical indicators. Further effects of school level variables on intervention outcomes are recommended so that tailored interventions can be developed aimed at the specific characteristics of each participating school. ^

Community health workers: The critical link to sustainable, healthy societies in low-resource settings---A model for the Baylor Shoulder to Shoulder Foundation

Community health workers (CHWs) can serve as a bridge between healthcare providers and communities to positively impact social determinants of health and, thus, the overall health of the population. The potential to effect lasting change is particularly significant within resource-poor settings with limited access to formally trained health care providers such as the small, rural village of Santa Ana Intibucá, Honduras and surrounding areas—located on the geographically and politically isolated border of Honduras and El Salvador. The Baylor Shoulder to Shoulder Foundation (BSTS) works in conjunction with Santa Ana's volunteer health committee to bring a health brigade that has provided health care and public health projects to the area at least twice a year since 2001. They have also hired a full-time Honduran physician, a Honduran in-country administrative director, and built a clinic; yet, no community health worker program exists. This CHW program model is the response to a clear need for a CHW program within the area served by BSTS and presents a CHW program model specific to Santa Ana Intibucá and surrounding areas to be implemented by BSTS. Methods used to develop this model include reviewing the literature for recommendations from leading authorities as well as successfully implemented CHW programs in comparable regions. This information was incorporated into existing knowledge and materials currently being used in the area. Using the CHW model proposed here, each brigade, in conjunction with the communities served, can help develop new modules to respond to the specific health priorities of the region at that time, incorporating consistent modes of contact with the local physician and the CHWs to provide refresher courses, training in new topics of interest, and to be reminded of the importance of community health workers' role as the critical link to healthy societies. With cooperation, effort, and support, the brigade can continue to help integrate a sustainable CHW system in which communities may be able to maximize the care they receive while also learning to care for their own health and the future of their communities.^

The assumptions and effects of conservative procedures in low -dose risk assessment for setting safety standards

Conservative procedures in low-dose risk assessment are used to set safety standards for known or suspected carcinogens. However, the assumptions upon which the methods are based and the effects of these methods are not well understood.^ To minimize the number of false-negatives and to reduce the cost of bioassays, animals are given very high doses of potential carcinogens. Results must then be extrapolated to much smaller doses to set safety standards for risks such as one per million. There are a number of competing methods that add a conservative safety factor into these calculations.^ A method of quantifying the conservatism of these methods was described and tested on eight procedures used in setting low-dose safety standards. The results using these procedures were compared by computer simulation and by the use of data from a large scale animal study.^ The method consisted of determining a "true safe dose" (tsd) according to an assumed underlying model. If one assumed that Y = the probability of cancer = P(d), a known mathematical function of the dose, then by setting Y to some predetermined acceptable risk, one can solve for d, the model's "true safe dose".^ Simulations were generated, assuming a binomial distribution, for an artificial bioassay. The eight procedures were then used to determine a "virtual safe dose" (vsd) that estimates the tsd, assuming a risk of one per million. A ratio R = ((tsd-vsd)/vsd) was calculated for each "experiment" (simulation). The mean R of 500 simulations and the probability R $<$ 0 was used to measure the over and under conservatism of each procedure.^ The eight procedures included Weil's method, Hoel's method, the Mantel-Byran method, the improved Mantel-Byran, Gross's method, fitting a one-hit model, Crump's procedure, and applying Rai and Van Ryzin's method to a Weibull model.^ None of the procedures performed uniformly well for all types of dose-response curves. When the data were linear, the one-hit model, Hoel's method, or the Gross-Mantel method worked reasonably well. However, when the data were non-linear, these same methods were overly conservative. Crump's procedure and the Weibull model performed better in these situations. ^