THE USE OF MULTIVARIATE ANALYSIS OF COVARIANCE IN EVALUATING THE COMPARABILITY OF LABORATORY DETERMINATIONS IN COOPERATIVE STUDIES

The role of clinical chemistry has traditionally been to evaluate acutely ill or hospitalized patients. Traditional statistical methods have serious drawbacks in that they use univariate techniques. To demonstrate alternative methodology, a multivariate analysis of covariance model was developed and applied to the data from the Cooperative Study of Sickle Cell Disease.^ The purpose of developing the model for the laboratory data from the CSSCD was to evaluate the comparability of the results from the different clinics. Several variables were incorporated into the model in order to control for possible differences among the clinics that might confound any real laboratory differences.^ Differences for LDH, alkaline phosphatase and SGOT were identified which will necessitate adjustments by clinic whenever these data are used. In addition, aberrant clinic values for LDH, creatinine and BUN were also identified.^ The use of any statistical technique including multivariate analysis without thoughtful consideration may lead to spurious conclusions that may not be corrected for some time, if ever. However, the advantages of multivariate analysis far outweigh its potential problems. If its use increases as it should, the applicability to the analysis of laboratory data in prospective patient monitoring, quality control programs, and interpretation of data from cooperative studies could well have a major impact on the health and well being of a large number of individuals. ^

Analysis of interval -censored events in hypertension studies: Evaluation of treatment of coronary heart disease

Many statistical studies feature data with both exact-time and interval-censored events. While a number of methods currently exist to handle interval-censored events and multivariate exact-time events separately, few techniques exist to deal with their combination. This thesis develops a theoretical framework for analyzing a multivariate endpoint comprised of a single interval-censored event plus an arbitrary number of exact-time events. The approach fuses the exact-time events, modeled using the marginal method of Wei, Lin, and Weissfeld, with a piecewise-exponential interval-censored component. The resulting model incorporates more of the information in the data and also removes some of the biases associated with the exclusion of interval-censored events. A simulation study demonstrates that our approach produces reliable estimates for the model parameters and their variance-covariance matrix. As a real-world data example, we apply this technique to the Systolic Hypertension in the Elderly Program (SHEP) clinical trial, which features three correlated events: clinical non-fatal myocardial infarction, fatal myocardial infarction (two exact-time events), and silent myocardial infarction (one interval-censored event). ^

An analysis of the shortage of registered nurses (RNs) in acute care hospitals in El Paso, Texas

The purpose of this analysis of the shortage of Registered Nurses (RNs) in acute care hospitals in El Paso, Texas, was to evaluate twenty-two specific organizational and/or patient care unit (nursing unit) characteristics that effect the retention and turnover of professional nurses. Vacancy Rates were used to measure the level of the shortage in each hospital and nursing unit in the study. Vacancy Rates are a function of both RN retention and RN turnover. Seventy-three patient care units in five acute care hospitals were included in the study population.^ Fredrick Herzberg's motivational - hygiene theory was used to explain the types of characteristics or factors that can effect worker dissatisfaction. Dissatisfiers (hygiene factors) are those work place characteristics that influence workers to leave the job. The twenty-two potentially dissatisfying work place characteristics were either organizational or patient care unit specific in nature. The focus of the study was to evaluate high vacancy rates caused by both low retention of RNs and high turnover rates. Retention and turnover are a function of workers (RNs) not staying in their jobs, therefore hygiene factors were appropriate characteristics to study.^ Various multivariate analysis techniques were used to assess both the individual and combined effects of the hygiene factors on Vacancy Rates, Retention and Turnover. Results suggest that certain organizational and patient care unit characteristics are associated with and have a statistically significant effect on vacancy rates, and the retention and turnover of RNs. The type of Hospital was of particular interest in this regards. For-Profit facilities were less effected by most of the study variables than the Not-for-Profits. ^

Application of stellar photometry to the analysis of microarray images

Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^

Bayesian generalized linear models for meta-analysis of diagnostic tests

With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

Analysis of prognostic factors for the development of metastases and survival in renal cell carcinoma patients

Introduction and objective. A number of prognostic factors have been reported for predicting survival in patients with renal cell carcinoma. Yet few studies have analyzed the effects of those factors at different stages of the disease process. In this study, different stages of disease progression starting from nephrectomy to metastasis, from metastasis to death, and from evaluation to death were evaluated. ^ Methods. In this retrospective follow-up study, records of 97 deceased renal cell carcinoma (RCC) patients were reviewed between September 2006 to October 2006. Patients with TNM Stage IV disease before nephrectomy or with cancer diagnoses other than RCC were excluded leaving 64 records for analysis. Patient TNM staging, Furhman Grade, age, tumor size, tumor volume, histology and patient gender were analyzed in relation to time to metastases. Time from nephrectomy to metastasis, TNM staging, Furhman Grade, age, tumor size, tumor volume, histology and patient gender were tested for significance in relation to time from metastases to death. Finally, analysis of laboratory values at time of evaluation, Eastern Cooperative Oncology Group performance status (ECOG), UCLA Integrated Staging System (UISS), time from nephrectomy to metastasis, TNM staging, Furhman Grade, age, tumor size, tumor volume, histology and patient gender were tested for significance in relation to time from evaluation to death. Linear regression and Cox Proportional Hazard (univariate and multivariate) was used for testing significance. Kaplan-Meier Log-Rank test was used to detect any significance between groups at various endpoints. ^ Results. Compared to negative lymph nodes at time of nephrectomy, a single positive lymph node had significantly shorter time to metastasis (p<0.0001). Compared to other histological types, clear cell histology had significant metastasis free survival (p=0.003). Clear cell histology compared to other types (p=0.0002 univariate, p=0.038 multivariate) and time to metastasis with log conversion (p=0.028) significantly affected time from metastasis to death. A greater than one year and greater than two year metastasis free interval, compared to patients that had metastasis before one and two years, had statistically significant survival benefit (p=0.004 and p=0.0318). Time from evaluation to death was affected by greater than one year metastasis free interval (p=0.0459), alcohol consumption (p=0.044), LDH (p=0.006), ECOG performance status (p<0.001), and hemoglobin level (p=0.0092). The UISS risk stratified the patient population in a statistically significant manner for survival (p=0.001). No other factors were found to be significant. ^ Conclusion. Clear cell histology is predictive for both time to metastasis and metastasis to death. Nodal status at time of nephrectomy may predict risk of metastasis. The time interval to metastasis significantly predicts time from metastasis to death and time from evaluation to death. ECOG performance status, and hemoglobin levels predicts survival outcome at evaluation. Finally, UISS appropriately stratifies risk in our population. ^

Risk factors for encephalitis and death from West Nile virus infection: An analysis of hospitalized cases in Houston, Texas from 2002--2008

We conducted a nested case-control study to determine the significant risk factors for developing encephalitis from West Nile virus (WNV) infection. The purpose of this research project was to expand the previously published Houston study of 2002–2004 patients to include data on Houston patients from four additional years (2005–2008) to determine if there were any differences in risk factors shown to be associated with developing the more severe outcomes of WNV infection, encephalitis and death, by having this larger sample size. A re-analysis of the risk factors for encephalitis and death was conducted on all of the patients from 2002–2008 and was the focus of this proposed research. This analysis allowed for the determination to be made that there are differences in the outcome in the risk factors for encephalitis and death with an increased sample size. Retrospective medical chart reviews were completed for the 265 confirmed WNV hospitalized patients; 153 patients had encephalitis (WNE), 112 had either viral syndrome with fever (WNF) or meningitis (WNM); a total of 22 patients died. Univariate logistic regression analyses on demographic, comorbidities, and social risk factors was conducted in a similar manner as in the previously conducted study to determine the risk factors for developing encephalitis from WNV. A multivariate model was developed by using model building strategies for the multivariate logistic regression analysis. The hypothesis of this study was that there would be additional risk factors shown to be significant with the increase in sample size of the dataset. This analysis with a greater sample size and increased power supports the hypothesis in that there were additional risk factors shown to be statistically associated with the more severe outcomes of WNV infection (WNE or death). Based on univariate logistic regression results, these data showed that even though age of 20–44 years was statistically significant as a protecting effect for developing WNE in the original study, the expanded sample lacked significance. This study showed a significant WNE risk factor to be chronic alcohol abuse, when it was not significant in the original analysis. Other WNE risk factors identified in this analysis that showed to be significant but were not significant in the original analysis were cancer not in remission > 5 years, history of stroke, and chronic renal disease. When comparing the two analyses with death as an outcome, two risk factors that were shown to be significant in the original analysis but not in the expanded dataset analysis were diabetes mellitus and immunosuppression. Three risk factors shown to be significant in this expanded analysis but were not significant in the original study were illicit drug use, heroin or opiate use, and injection drug use. However, with the multiple logistic regression models, the same independent risk factors for developing encephalitis of age and history of hypertension including drug induced hypertension were consistent in both studies.^

A GENETIC MARKER STUDY OF NON - INSULIN DEPENDENT DIABETICS IN THE MEXICAN-AMERICAN COMMUNITY FROM STARR COUNTY, TEXAS (PLASMA GLUCOSE, HEMOGLOBIN ANALYSIS)

Diabetes mellitus occurs in two forms, insulin-dependent (IDDM, formerly called juvenile type) and non-insulin dependent (NIDDM, formerly called adult type). Prevalence figures from around the world for NIDDM, show that all societies and all races are affected; although uncommon in some populations (.4%), it is common (10%) or very common (40%) in others (Tables 1 and 2).^ In Mexican-Americans in particular, the prevalence rates (7-10%) are intermediate to those in Caucasians (1-2%) and Amerindians (35%). Information about the distribution of the disease and identification of high risk groups for developing glucose intolerance or its vascular manifestations by the study of genetic markers will help to clarify and solve some of the problems from the public health and the genetic point of view.^ This research was designed to examine two general areas in relation to NIDDM. The first aims to determine the prevalence of polymorphic genetic markers in two groups distinguished by the presence or absence of diabetes and to observe if there are any genetic marker-disease association (univariate analysis using two by two tables and logistic regression to study the individual and joint effects of the different variables). The second deals with the effect of genetic differences on the variation in fasting plasma glucose and percent glycosylated hemoglobin (HbAl) (analysis of Covariance for each marker, using age and sex as covariates).^ The results from the first analysis were not statistically significant at the corrected p value of 0.003 given the number of tests that were performed. From the analysis of covariance of all the markers studied, only Duffy and Phosphoglucomutase were statistically significant but poor predictors, given that the amount they explain in terms of variation in glycosylated hemoglobin is very small.^ Trying to determine the polygenic component of chronic disease is not an easy task. This study confirms the fact that a larger and random or representative sample is needed to be able to detect differences in the prevalence of a marker for association studies and in the genetic contribution to the variation in glucose and glycosylated hemoglobin. The importance that ethnic homogeneity in the groups studied and standardization in the methodology will have on the results has been stressed. ^

Retrospective analysis of Methicillin-Resistant Staphylococcus Aureus (MRSA) skin and Soft-Tissue Infections (SSTI) in a university hospital emergency department (ED)

Study Objective: Identify the most frequent risk factors of Community Acquired-MRSA (CA-MRSA) Skin and Soft-tissue Infections (SSTIs) using a case series of patients and characterize them by age, race/ethnicity, gender, abscess location, druguse and intravenous drug-user (IVDU), underlying medical conditions, homelessness, treatment resistance, sepsis, those whose last healthcare visit was within the last 12 months, and describe the susceptibility pattern from this central Texas population that have come into the University Medical Center Brackenridge (UMCB) Emergency Department (ED). ^ Methods: This study was a retrospective case-series medical record review involving a convenience sample of patients in 2007 from an urban public hospital's ED in Texas that had a SSTI that tested positive for MRSA. All positive MRSA cultures underwent susceptibility testing to determine antibiotic resistance. The demographic and clinical variables that were independently associated with MRSA were determined by univariate and multivariate analysis using logistic regression to calculate odds ratios (OR), 95% confidence intervals, and significance (p≤ 0.05). ^ Results: In 2007, there were 857 positive MRSA cultures. The demographics were: males 60% and females 40%, with the average age of 36.2 (std. dev. =13) the study population consisted of non-Hispanic white (42%), Hispanics (38%), and non-Hispanic black (18.8%). Possible risk factors addressed included using recreational drugs (not including IVDU) (27%) homelessness (13%), diabetes status (12.6%) or having an infectious disease, and IVDU (10%). The most frequent abscess location was the leg (26.6%), followed by the arm and torso (both 13.7%). Eighty-three percent of patients had one prominent susceptibility pattern that had a susceptibility rate for the following antibiotics: trimethoprim/sulfamethoxazole (TMP-SMX) and vancomycin had 100%, gentamicin 99%, clindamycin 96%, tetracycline 96%, and erythromycin 56%. ^ Conclusion: The ED is becoming an important area for disease transmission between the sterile hospital environment and the outside environment. As always, it is important to further research in the ED in an effort to better understand MRSA transmission and antibiotic resistance, as well as to keep surveillance for the introduction of new opportunistic pathogens into the population. ^