Comparison of multiple comparison methods for identifying differential gene expression in simulated and real papillary thyroid cancer microarray data

The difficulty of detecting differential gene expression in microarray data has existed for many years. Several correction procedures try to avoid the family-wise error rate in multiple comparison process, including the Bonferroni and Sidak single-step p-value adjustments, Holm's step-down correction method, and Benjamini and Hochberg's false discovery rate (FDR) correction procedure. Each multiple comparison technique has its advantages and weaknesses. We studied each multiple comparison method through numerical studies (simulations) and applied the methods to the real exploratory DNA microarray data, which detect of molecular signatures in papillary thyroid cancer (PTC) patients. According to our results of simulation studies, Benjamini and Hochberg step-up FDR controlling procedure is the best process among these multiple comparison methods and we discovered 1277 potential biomarkers among 54675 probe sets after applying the Benjamini and Hochberg's method to PTC microarray data.^

Regulation of estrogen receptor alpha by the tumor suppressor p53 in breast cancer cells

Estrogen receptor (ER) and the tumor suppressor p53 are key prognostic indicators in breast cancer. Estrogen signaling through its receptor (ER) controls proliferation of normal as well as transformed mammary epithelial cells, and the presence of ER is established as a marker of good prognosis and response to therapy. The p53 tumor suppressor gene is often referred to as the "cellular gatekeeper" due to its extensive control of cell proliferation and apoptosis. Loss of functional p53 is a negative prognostic indicator and is correlated with lack of response to antiestrogens, reduced disease-free interval and increased chance of disease recurrence. Clinical studies have demonstrated that tumors with mutated p53 tend to be ER negative, while ER positive tumors tend to have wild type p53. ^ Recent studies from our lab indicate that p53 genotype correlates with estrogen receptor expression in mammary tumors in vivo. We therefore hypothesized that p53 regulates ER expression in mammary cancer cells by recruitment of specific cofactors to the ER promoter. To test this, MCF-7 cells were treated with doxorubicin or ionizing radiation, both of which stimulated significant increases in p53 expression, as expected, but also increased ER expression in a p53-dependent manner. Furthermore, in cells treated with siRNA targeting p53, both p53 and ER protein levels were significantly reduced. P53 was also demonstrated to transcriptionally regulate the ER promoter in luciferase assays and chromatin immunoprecipitation assays showed that p53 was recruited to the ER promoter along with CARM1, CBP, c-Jun and Sp1 and that this multifactor complex was formed in a p53-dependent manner. The regulation of ER by p53 has therapeutic implications, as the treatment of breast cancer cells with doxorubicin sensitized these cells to tamoxifen treatment. Furthermore, response to tamoxifen as well as to estrogen was dependent on p53 expression in ER positive human breast cancer cells. Taken together, these data demonstrate that p53 regulates ER expression through transcriptional control of the ER promoter, accounting for their concordant expression in human breast cancer and identifying potentially beneficial therapeutic strategies for the treatment of ER positive breast cancers. ^

Nosocomial infections and their relationship to non-traditional risk factors in a medical intensive care unit

Background. Nosocomial infections are a source of concern for many hospitals in the United States and worldwide. These infections are associated with increased morbidity, mortality and hospital costs. Nosocomial infections occur in ICUs at a rate which is five times greater than those in general wards. Understanding the reasons for the higher rates can ultimately help reduce these infections. The literature has been weak in documenting a direct relationship between nosocomial infections and non-traditional risk factors, such as unit staffing or patient acuity.^ Objective. To examine the relationship, if any, between nosocomial infections and non-traditional risk factors. The potential non-traditional risk factors we studied were the patient acuity (which comprised of the mortality and illness rating of the patient), patient days for patients hospitalized in the ICU, and the patient to nurse ratio.^ Method. We conducted a secondary data analysis on patients hospitalized in the Medical Intensive Care Unit (MICU) of the Memorial Hermann- Texas Medical Center in Houston during the months of March 2008- May 2009. The average monthly values for the patient acuity (mortality and illness Diagnostic Related Group (DRG) scores), patient days for patients hospitalized in the ICU and average patient to nurse ratio were calculated during this time period. Active surveillance of Bloodstream Infections (BSIs), Urinary Tract Infections (UTIs) and Ventilator Associated Pneumonias (VAPs) was performed by Infection Control practitioners, who visited the MICU and performed a personal infection record for each patient. Spearman's rank correlation was performed to determine the relationship between these nosocomial infections and the non-traditional risk factors.^ Results. We found weak negative correlations between BSIs and two measures (illness and mortality DRG). We also found a weak negative correlation between UTI and unit staffing (patient to nurse ratio). The strongest positive correlation was found between illness DRG and mortality DRG, validating our methodology.^ Conclusion. From this analysis, we were able to infer that non-traditional risk factors do not appear to play a significant role in transmission of infection in the units we evaluated.^

Workers and respirators: What factors influence medical clearance? Experience in the petrochemical industry 2004--2008

This retrospective cohort study analyzed data from more than 2200 OSHA-mandated respirator medical evaluations performed between 2004 and 2008, with information initially obtained using an online questionnaire, to determine what factors influence medical clearance and the ability to safely wear respiratory protection in a large petrochemical company.^ The employees were mostly white males with a high school education, ranging in age from 25 to 60 years of age, who had been employed with the company an average of eight years. Their work was typically performed outdoors in a rural or offshore setting. Respirators were typically required for emergency response – escape or rescue only – and/or limited to less than four hours per month.^ Approximately 90% of the population achieved medical clearance by utilizing the online questionnaire. Of the remaining 10%, 66% were cleared after additional "hands-on" medical examination exam; 28% of the individuals' jobs were modified by their supervisor in order to not use a respirator, and 6% of the individuals (n=13) were excluded from wearing a respirator on the basis of the medical examination. The primary causes for exclusion from respirator use were cardiovascular (37.5%) and respiratory (31.3%) issues, followed by psychological (18.8%) and musculoskeletal (12.5%) concerns. Ultimately, over 99% of workers evaluated under this system were found capable of using respiratory protection safely. This questionnaire has proven to be an excellent health screening tool capable of initiating early detection and further investigation of potentially serious medical conditions within a large and diverse population in multiple locations. ^

Effects of congressional modernization laws on public access to innovative medical device technologies

The Federal Food and Drug Administration (FDA) and the Centers for Medicare and Medicaid (CMS) play key roles in making Class III, medical devices available to the public, and they are required by law to meet statutory deadlines for applications under review. Historically, both agencies have failed to meet their respective statutory requirements. Since these failures affect patient access and may adversely impact public health, Congress has enacted several “modernization” laws. However, the effectiveness of these modernization laws has not been adequately studied or established for Class III medical devices. ^ The aim of this research study was, therefore, to analyze how these modernization laws may have affected public access to medical devices. Two questions were addressed: (1) How have the FDA modernization laws affected the time to approval for medical device premarket approval applications (PMAs)? (2) How has the CMS modernization law affected the time to approval for national coverage decisions (NCDs)? The data for this research study were collected from publicly available databases for the period January 1, 1995, through December 31, 2008. These dates were selected to ensure that a sufficient period of time was captured to measure pre- and post-modernization effects on time to approval. All records containing original PMAs were obtained from the FDA database, and all records containing NCDs were obtained from the CMS database. Source documents, including FDA premarket approval letters and CMS national coverage decision memoranda, were reviewed to obtain additional data not found in the search results. Analyses were conducted to determine the effects of the pre- and post-modernization laws on time to approval. Secondary analyses of FDA subcategories were conducted to uncover any causal factors that might explain differences in time to approval and to compare with the primary trends. The primary analysis showed that the FDA modernization laws of 1997 and 2002 initially reduced PMA time to approval; after the 2002 modernization law, the time to approval began increasing and continued to increase through December 2008. The non-combined, subcategory approval trends were similar to the primary analysis trends. The combined, subcategory analysis showed no clear trends with the exception of non-implantable devices, for which time to approval trended down after 1997. The CMS modernization law of 2003 reduced NCD time to approval, a trend that continued through December 2008. This study also showed that approximately 86% of PMA devices do not receive NCDs. ^ As a result of this research study, recommendations are offered to help resolve statutory non-compliance and access issues, as follows: (1) Authorities should examine underlying causal factors for the observed trends; (2) Process improvements should be made to better coordinate FDA and CMS activities to include sharing data, reducing duplication, and establishing clear criteria for “safe and effective” and “reasonable and necessary”; (3) A common identifier should be established to allow tracking and trending of applications between FDA and CMS databases; (4) Statutory requirements may need to be revised; and (5) An investigation should be undertaken to determine why NCDs are not issued for the majority of PMAs. Any process improvements should be made without creating additional safety risks and adversely impacting public health. Finally, additional studies are needed to fully characterize and better understand the trends identified in this research study.^

Association of maternal sphinganine:sphingosine ratio and folate levels with neural tube defects along the South Texas border

Neural tube defects (NTDs) remain elevated in Hispanic women along the South Texas Border, despite folate supplementation and folate fortification of cereal products. Missmer et al. examined the relationships between fumonisins, a class of corn mycotoxin, and NTDs in Hispanic women who ate corn tortillas and found increased odds ratios with increasing exposure, as measured by serum sphinganine:sphingosine (sa:so) ratios. This study examined the interactions between categorized maternal serum folate levels and stratified sa:so ratios and the resultant odds ratios of NTDs, stratified by type (anencephaly and spina bifida). The hypothesis was that the above normal folate category would have lower odds ratios of NTDs at given sa:so ratio categories and that there would be a difference in odds ratio patterns for anencephaly and spina bifida. Methods. Data for 406 Hispanic women were obtained from the Missmer case-control study. Sa:so ratios were calculated and subjects were stratified into “below normal,” “normal,” and above normal range for folate. A logistic regression model was applied, controlling for BMI, serum B12, lab batch, and conception date. Results. While OR’s of NTDs increased for increasing sa:so ratios, OR’s for “above normal” folate were not decreased at any sa:so ratio and there was no statistically significant difference between OR’s of anencephaly and spina bifida. Conclusion. Folate does not appear to be protective against the potential teratogenic effect of fumonisins and did not differ in effect on OR’s of NTD by type. More research is necessary to determine the extent of fumonisin exposure in Hispanic women along the South Texas Border.^

Concordance between medical records and personal interview in ascertaining breast cancer and diabetes status: Analysis of the south Texas women's health project

Accurate ascertainment of risk factors and disease status is vital in public health research for proper classification of research subjects. The two most common ways of obtaining this data is by self-report and review of medical records (MRs). South Texas Women’s Health Project was a case-control study looking at interrelationships between hormones, diet, and body size and breast cancer among Hispanic women 30-79 years of age. History of breast cancer, diabetes mellitus (DM) and use of DM medications was ascertained from a personal interview. At the time of interview, the subject identified her major health care providers and signed the medical records release form, which was sent to the designated providers. The MRs were reviewed to confirm information obtained from the interview.^ Aim of this study was to determine the sensitivity and specificity between MRs and personal interview in diagnosis of breast cancer, DM and DM treatment. We also wanted to assess how successful our low-cost approach was in obtaining pertinent MRs and what factors influenced the quality of MR or interview data. Study sample was 721 women with both self-report and MR data available by June 2007. Overall response rate for MR requests was 74.5%. MRs were 80.9% sensitive and 100% specific in confirming breast cancer status. Prevalence of DM was 22.7% from the interviews and 16% from MRs. MRs did not provide definite information about DM status of 53.6% subjects. Sensitivity and specificity of MRs for DM status was 88.9% and 90.4% respectively. Disagreement on DM status from the two sources was seen in 15.9% subjects. This discordance was more common among older subjects, those who were married and were predominantly Spanish speaking. Income and level of education did not have a statistically significantly association with this disagreement.^ Both self-report and MRs underestimate the prevalence of DM. Relying solely on MRs leads to greater misclassification than relying on self-report data. MRs have good to excellent specificity and thus serve as a good tool to confirm information obtained from self-report. Self-report and MRs should be used in a complementary manner for accurate assessment of DM and breast cancer status.^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

Secondary data analysis of lead screening compliance in high-risk children

Introduction. Despite the ban of lead-containing gasoline and paint, childhood lead poisoning remains a public health issue. Furthermore, a Medicaid-eligible child is 8 times more likely to have an elevated blood lead level (EBLL) than a non-Medicaid child, which is the primary reason for the early detection lead screening mandate for ages 12 and 24 months among the Medicaid population. Based on field observations, there was evidence that suggested a screening compliance issue. Objective. The purpose of this study was to analyze blood lead screening compliance in previously lead poisoned Medicaid children and test for an association between timely lead screening and timely childhood immunizations. The mean months between follow-up tests were also examined for a significant difference between the non-compliant and compliant lead screened children. Methods. Access to the surveillance data of all childhood lead poisoned cases in Bexar County was granted by the San Antonio Metropolitan Health District. A database was constructed and analyzed using descriptive statistics, logistic regression methods and non-parametric tests. Lead screening at 12 months of age was analyzed separately from lead screening at 24 months. The small portion of the population who were also related were included in one analysis and removed from a second analysis to check for significance. Gender, ethnicity, age of home, and having a sibling with an EBLL were ruled out as confounders for the association tests but ethnicity and age of home were adjusted in the nonparametric tests. Results. There was a strong significant association between lead screening compliance at 12 months and childhood immunization compliance, with or without including related children (p<0.00). However, there was no significant association between the two variables at the age of 24 months. Furthermore, there was no significant difference between the median of the mean months of follow-up blood tests among the non-compliant and compliant lead screened population for at the 12 month screening group but there was a significant difference at the 24 month screening group (p<0.01). Discussion. Descriptive statistics showed that 61% and 56% of the previously lead poisoned Medicaid population did not receive their 12 and 24 month mandated lead screening on time, respectively. This suggests that their elevated blood lead level may have been diagnosed earlier in their childhood. Furthermore, a child who is compliant with their lead screening at 12 months of age is 2.36 times more likely to also receive their childhood immunizations on time compared to a child who was not compliant with their 12 month screening. Even though there was no statistical significant association found for the 24 month group, the public health significance of a screening compliance issue is no less important. The Texas Medicaid program needs to enforce lead screening compliance because it is evident that there has been no monitoring system in place. Further recommendations include a need for an increased focus on parental education and the importance of taking their children for wellness exams on time.^

A categorical data analysis approach to estimation of demographic characteristics for Texas county populations

The need for timely population data for health planning and Indicators of need has Increased the demand for population estimates. The data required to produce estimates is difficult to obtain and the process is time consuming. Estimation methods that require less effort and fewer data are needed. The structure preserving estimator (SPREE) is a promising technique not previously used to estimate county population characteristics. This study first uses traditional regression estimation techniques to produce estimates of county population totals. Then the structure preserving estimator, using the results produced in the first phase as constraints, is evaluated.^ Regression methods are among the most frequently used demographic methods for estimating populations. These methods use symptomatic indicators to predict population change. This research evaluates three regression methods to determine which will produce the best estimates based on the 1970 to 1980 indicators of population change. Strategies for stratifying data to improve the ability of the methods to predict change were tested. Difference-correlation using PMSA strata produced the equation which fit the data the best. Regression diagnostics were used to evaluate the residuals.^ The second phase of this study is to evaluate use of the structure preserving estimator in making estimates of population characteristics. The SPREE estimation approach uses existing data (the association structure) to establish the relationship between the variable of interest and the associated variable(s) at the county level. Marginals at the state level (the allocation structure) supply the current relationship between the variables. The full allocation structure model uses current estimates of county population totals to limit the magnitude of county estimates. The limited full allocation structure model has no constraints on county size. The 1970 county census age - gender population provides the association structure, the allocation structure is the 1980 state age - gender distribution.^ The full allocation model produces good estimates of the 1980 county age - gender populations. An unanticipated finding of this research is that the limited full allocation model produces estimates of county population totals that are superior to those produced by the regression methods. The full allocation model is used to produce estimates of 1986 county population characteristics. ^

Bayesian inference and its application to meta-analysis of epidemiologic data

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. ^

A SIMULATION STUDY OF THE SIZE AND POWER OF SOME TWO-SAMPLE TESTS FOR UNEQUALLY CENSORED SURVIVAL DATA (RANK TESTS, LOGRANK, PROPORTIONAL HAZARDS, WILCOXON TESTS, EXPONENTIAL DISTRIBUTION)

Sizes and power of selected two-sample tests of the equality of survival distributions are compared by simulation for small samples from unequally, randomly-censored exponential distributions. The tests investigated include parametric tests (F, Score, Likelihood, Asymptotic), logrank tests (Mantel, Peto-Peto), and Wilcoxon-Type tests (Gehan, Prentice). Equal sized samples, n = 18, 16, 32 with 1000 (size) and 500 (power) simulation trials, are compared for 16 combinations of the censoring proportions 0%, 20%, 40%, and 60%. For n = 8 and 16, the Asymptotic, Peto-Peto, and Wilcoxon tests perform at nominal 5% size expectations, but the F, Score and Mantel tests exceeded 5% size confidence limits for 1/3 of the censoring combinations. For n = 32, all tests showed proper size, with the Peto-Peto test most conservative in the presence of unequal censoring. Powers of all tests are compared for exponential hazard ratios of 1.4 and 2.0. There is little difference in power characteristics of the tests within the classes of tests considered. The Mantel test showed 90% to 95% power efficiency relative to parametric tests. Wilcoxon-type tests have the lowest relative power but are robust to differential censoring patterns. A modified Peto-Peto test shows power comparable to the Mantel test. For n = 32, a specific Weibull-exponential comparison of crossing survival curves suggests that the relative powers of logrank and Wilcoxon-type tests are dependent on the scale parameter of the Weibull distribution. Wilcoxon-type tests appear more powerful than logrank tests in the case of late-crossing and less powerful for early-crossing survival curves. Guidelines for the appropriate selection of two-sample tests are given. ^