SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

Effects of exercise with oxygen prebreathe for decompression risk reduction

Astronauts performing extravehicular activities (EVA) are at risk for occupational hazards due to a hypobaric environment, in particular Decompression Sickness (DCS). DCS results from nitrogen gas bubble formation in body tissues and venous blood. Denitrogenation achieved through lengthy staged decompression protocols has been the mainstay of prevention of DCS in space. Due to the greater number and duration of EVAs scheduled for construction and maintenance of the International Space Station, more efficient alternatives to accomplish missions without compromising astronaut safety are desirable. ^ This multi-center, multi-phase study (NASA-Prebreathe Reduction Protocol study, or PRP) was designed to identify a shorter denitrogenation protocol that can be implemented before an EVA, based on the combination of adynamia and exercise enhanced oxygen prebreathe. Human volunteers recruited at three sites (Texas, North Carolina and Canada) underwent three different combinations (“PRP phases”) of intense and light exercise prior to decompression in an altitude chamber. The outcome variables were detection of venous gas embolism (VGE) by precordial Doppler ultrasound, and clinical manifestations of DCS. Independent variables included age, gender, body mass index, oxygen consumption peak, peak heart rate, and PRP phase. Data analysis was performed both by pooling results from all study sites, and by examining each site separately. ^ Ten percent of the subjects developed DCS and 20% showed evidence of high grade VGE. No cases of DCS occurred in one particular PRP phase with use of the combination of dual-cycle ergometry (10 minutes at 75% of VO2 peak) plus 24 minutes of light EVA exercise (p = 0.04). No significant effects were found for the remaining independent variables on the occurrence of DCS. High grade VGE showed a strong correlation with subsequent development of DCS (sensitivity, 88.2%; specificity, 87.2%). In the presence of high grade VGE, the relative risk for DCS ranged from 7.52 to 35.0. ^ In summary, a good safety level can be achieved with exercise-enhanced oxygen denitrogenation that can be generalized to the astronaut population. Exercise is beneficial in preventing DCS if a specific schedule is followed, with an individualized VO2 prescription that provides a safety level that can then be applied to space operations. Furthermore, VGE Doppler detection is a useful clinical tool for prediction of altitude DCS. Because of the small number of high grade VGE episodes, the identification of a high probability DCS situation based on the presence of high grade VGE seems justified in astronauts. ^

Second, do less harm: The state of states' medical error reporting programs

Statement of the problem and public health significance. Hospitals were designed to be a safe haven and respite from disease and illness. However, a large body of evidence points to preventable errors in hospitals as the eighth leading cause of death among Americans. Twelve percent of Americans, or over 33.8 million people, are hospitalized each year. This population represents a significant portion of at risk citizens exposed to hospital medical errors. Since the number of annual deaths due to hospital medical errors is estimated to exceed 44,000, the magnitude of this tragedy makes it a significant public health problem. ^ Specific aims. The specific aims of this study were threefold. First, this study aimed to analyze the state of the states' mandatory hospital medical error reporting six years after the release of the influential IOM report, "To Err is Human." The second aim was to identify barriers to reporting of medical errors by hospital personnel. The third aim was to identify hospital safety measures implemented to reduce medical errors and enhance patient safety. ^ Methods. A descriptive, longitudinal, retrospective design was used to address the first stated objective. The study data came from the twenty-one states with mandatory hospital reporting programs which report aggregate hospital error data that is accessible to the public by way of states' websites. The data analysis included calculations of expected number of medical errors for each state according to IOM rates. Where possible, a comparison was made between state reported data and the calculated IOM expected number of errors. A literature review was performed to achieve the second study aim, identifying barriers to reporting medical errors. The final aim was accomplished by telephone interviews of principal patient safety/quality officers from five Texas hospitals with more than 700 beds. ^ Results. The state medical error data suggests vast underreporting of hospital medical errors to the states. The telephone interviews suggest that hospitals are working at reducing medical errors and creating safer environments for patients. The literature review suggests the underreporting of medical errors at the state level stems from underreporting of errors at the delivery level. ^

Estimating parameters in Markov models for longitudinal studies with missing data or surrogate outcomes

The discrete-time Markov chain is commonly used in describing changes of health states for chronic diseases in a longitudinal study. Statistical inferences on comparing treatment effects or on finding determinants of disease progression usually require estimation of transition probabilities. In many situations when the outcome data have some missing observations or the variable of interest (called a latent variable) can not be measured directly, the estimation of transition probabilities becomes more complicated. In the latter case, a surrogate variable that is easier to access and can gauge the characteristics of the latent one is usually used for data analysis. ^ This dissertation research proposes methods to analyze longitudinal data (1) that have categorical outcome with missing observations or (2) that use complete or incomplete surrogate observations to analyze the categorical latent outcome. For (1), different missing mechanisms were considered for empirical studies using methods that include EM algorithm, Monte Carlo EM and a procedure that is not a data augmentation method. For (2), the hidden Markov model with the forward-backward procedure was applied for parameter estimation. This method was also extended to cover the computation of standard errors. The proposed methods were demonstrated by the Schizophrenia example. The relevance of public health, the strength and limitations, and possible future research were also discussed. ^

Racial disparities in CD4 counts at initial HIV-1 diagnosis: Analysis of the Adult Spectrum of HIV disease dataset and public health implications

Introduction. The HIV/AIDS disease burden disproportionately affects minority populations, specifically African Americans. While sexual risk behaviors play a role in the observed HIV burden, other factors including gender, age, socioeconomics, and barriers to healthcare access may also be contributory. The goal of this study was to determine how far down the HIV/AIDS disease process people of different ethnicities first present for healthcare. The study specifically analyzed the differences in CD4 cell counts at the initial HIV-1 diagnosis with respect to ethnicity. The study also analyzed racial differences in HIV/AIDS risk factors. ^ Methods. This is a retrospective study using data from the Adult Spectrum of HIV Disease (ASD), collected by the City of Houston Department of Health. The ASD database contains information on newly reported HIV cases in the Harris County District Hospitals between 1989 and 2000. Each patient had an initial and a follow-up report. The extracted variables of interest from the ASD data set were CD4 counts at the initial HIV diagnosis, race, gender, age at HIV diagnosis and behavioral risk factors. One-way ANOVA was used to examine differences in baseline CD4 counts at HIV diagnosis between racial/ethnic groups. Chi square was used to analyze racial differences in risk factors. ^ Results. The analyzed study sample was 4767. The study population was 47% Black, 37% White and 16% Hispanic [p<0.05]. The mean and median CD4 counts at diagnosis were 254 and 193 cells per ml, respectively. At the initial HIV diagnosis Blacks had the highest average CD4 counts (285), followed by Whites (233) and Hispanics (212) [p<0.001 ]. These statistical differences, however, were only observed with CD4 counts above 350 [p<0.001], even when adjusted for age at diagnosis and gender [p<0.05]. Looking at risk factors, Blacks were mostly affected by intravenous drug use (IVDU) and heterosexuality, whereas Whites and Hispanics were more affected by male homosexuality [ p<0.05]. ^ Conclusion. (1) There were statistical differences in CD4 counts with respect to ethnicity, but these differences only existed for CD4 counts above 350. These differences however do not appear to have clinical significance. Antithetically, Blacks had the highest CD4 counts followed by Whites and Hispanics. (2) 50% of this study group clinically had AIDS at their initial HIV diagnosis (median=193), irrespective of ethnicity. It was not clear from data analysis if these observations were due to failure of early HIV surveillance, HIV testing policies or healthcare access. More studies need to be done to address this question. (3) Homosexuality and bisexuality were the biggest risk factors for Whites and Hispanics, whereas for Blacks were mostly affected by heterosexuality and IVDU, implying a need for different public health intervention strategies for these racial groups. ^

Continuous safety screens for randomized controlled clinical trials with blinded treatment information

Standard methods for testing safety data are needed to ensure the safe conduct of clinical trials. In particular, objective rules for reliably identifying unsafe treatments need to be put into place to help protect patients from unnecessary harm. DMCs are uniquely qualified to evaluate accumulating unblinded data and make recommendations about the continuing safe conduct of a trial. However, it is the trial leadership who must make the tough ethical decision about stopping a trial, and they could benefit from objective statistical rules that help them judge the strength of evidence contained in the blinded data. We design early stopping rules for harm that act as continuous safety screens for randomized controlled clinical trials with blinded treatment information, which could be used by anyone, including trial investigators (and trial leadership). A Bayesian framework, with emphasis on the likelihood function, is used to allow for continuous monitoring without adjusting for multiple comparisons. Close collaboration between the statistician and the clinical investigators will be needed in order to design safety screens with good operating characteristics. Though the math underlying this procedure may be computationally intensive, implementation of the statistical rules will be easy and the continuous screening provided will give suitably early warning when real problems were to emerge. Trial investigators and trial leadership need these safety screens to help them to effectively monitor the ongoing safe conduct of clinical trials with blinded data.^

A comparative analysis of CHIP Perinatal policy in twelve states

The purpose of this comparative analysis of CHIP Perinatal policy (42 CFR § 457) was to provide a basis for understanding the variation in policy outputs across the twelve states that, as of June 2007, implemented the Unborn Child rule. This Department of Health and Human Services regulation expanded in 2002 the definition of “child” to include the period from conception to birth, allowing states to consider an unborn child a “targeted low-income child” and therefore eligible for SCHIP coverage. ^ Specific study aims were to (1) describe typologically the structural and contextual features of the twelve states that adopted a CHIP Perinatal policy; (2) describe and differentiate among the various designs of CHIP Perinatal policy implemented in the states; and (3) develop a conceptual model that links the structural and contextual features of the adopting states to differences in the forms the policy assumed, once it was implemented. ^ Secondary data were collected from publicly available information sources to describe characteristics of states’ political system, health system, economic system, sociodemographic context and implemented policy attributes. I posited that socio-demographic differences, political system differences and health system differences would directly account for the observed differences in policy output among the states. ^ Exploratory data analysis techniques, which included median polishing and multidimensional scaling, were employed to identify compelling patterns in the data. Scaled results across model components showed that economic system was most closely related to policy output, followed by health system. Political system and socio-demographic characteristics were shown to be weakly associated with policy output. Goodness-of-fit measures for MDS solutions implemented across states and model components, in one- and two-dimensions, were very good. ^ This comparative policy analysis of twelve states that adopted and implemented HHS Regulation 42 C.F.R. § 457 contributes to existing knowledge in three areas: CHIP Perinatal policy, public health policy and policy sciences. First, the framework allows for the identification of CHIP Perinatal program design possibilities and provides a basis for future studies that evaluate policy impact or performance. Second, studies of policy determinants are not well represented in the health policy literature. Thus, this study contributes to the development of the literature in public health policy. Finally, the conceptual framework for policy determinants developed in this study suggests new ways for policy makers and practitioners to frame policy arguments, encouraging policy change or reform. ^

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. ^

Secondary analysis of effectivness of tinidazole-containing-quadruple eradication therapy in asymptomatic H. pylori infected children in El Paso

Helicobacter pylori infection is frequently acquired during childhood. This microorganism is known to cause gastritis, and duodenal ulcer in pediatric patients, however most children remain completely asymptomatic to the infection. Currently there is no consensus in favor of treatment of H. pylori infection in asymptomatic children. The firstline of treatment for this population is triple medication therapy including two antibacterial agents and one proton pump inhibitor for a 2 week duration course. Decreased eradication rate of less than 75% has been documented with the use of this first-line therapy but novel tinidazole-containing quadruple sequential therapies seem worth investigating. None of the previous studies on such therapy has been done in the United States of America. As part of an iron deficiency anemia study in asymptomatic H. pylori infected children of El Paso, Texas, we conducted a secondary data analysis of study data collected in this trial to assess the effectiveness of this tinidazole-containing sequential quadruple therapy compared to placebo on clearing the infection. Subjects were selected from a group of asymptomatic children identified through household visits to 11,365 randomly selected dwelling units. After obtaining parental consent and child assent a total of 1,821 children 3-10 years of age were screened and 235 were positive to a novel urine immunoglobulin class G antibodies test for H. pylori infection and confirmed as infected using a 13C urea breath test, using a hydrolysis urea rate >10 μg/min as cut-off value. Out of those, 119 study subjects had a complete physical exam and baseline blood work and were randomly allocated to four groups, two of which received active H. pylori eradication medication alone or in combination with iron, while the other two received iron only or placebo only. Follow up visits to their houses were done to assess compliance and occurrence of adverse events and at 45+ days post-treatment, a second urea breath test was performed to assess their infection status. The effectiveness was primarily assessed on intent to treat basis (i.e., according to their treatment allocation), and the proportion of those who cleared their infection using a cut-off value >10 μg/min of for urea hydrolysis rate, was the primary outcome. Also we conducted analysis on a per-protocol basis and according to the cytotoxin associated gene A product of the H. pylori infection status. Also we compared the rate of adverse events across the two arms. On intent-to-treat and per-protocol analyses, 44.3% and 52.9%, respectively, of the children receiving the novel quadruple sequential eradication cleared their infection compared to 12.2% and 15.4% in the arms receiving iron or placebo only, respectively. Such differences were statistically significant (p<0.001). The study medications were well accepted and safe. In conclusion, we found in this study population, of mostly asymptomatically H. pylori infected children, living in the US along the border with Mexico, that the quadruple sequential eradication therapy cleared the infection in only half of the children receiving this treatment. Research is needed to assess the antimicrobial susceptibility of the strains of H. pylori infecting this population to formulate more effective therapies. ^

A systematic review of the evidence for use of herbal medicine for the treatment of acute diarrhea

Background. Acute diarrhea (AD) is an important cause of morbidity and mortality among both children and adults. An ideal antidiarrheal treatment should be safe, effective, compatible with Oral Rehydration Solution, and inexpensive. Herbal medicines, if effective, should fit these criteria as well or better than standard treatment. ^ Objective. The objective of the present study was to assess the effectiveness of plant preparations in patients with AD in reports of randomized and non-randomized controlled trials. ^ Aims. The aims of the present study were to identify effective antidiarrheal herbs and to identify potential antidiarrheal herbs for future studies of efficacy through well designed clinical trials in human populations. ^ Methods. Nineteen published studies of herbal management of AD were examined to identify effective plant preparations. Ten plant preparations including Berberine (Berberis aristata), tormentil root ( Potentialla tormentilla), baohauhau (from the baobaosan plant), carob (Ceratonia siliqua), pectin (Malus domestica), wood creosote (Creosote bush), guava (Psidium guajava L.), belladonna (Atropa belladonna), white bean (Phaseolis vulgaris), and wheat (Triticum aestivum) were identified. ^ Results. Qualitative data analysis of nineteen clinical trials indicated berberine’s potentially valuable antisecretory effects against diarrhea caused by Vibrio cholerae and enterotoxigenic Escherichia coli. Tormentil root showed significant efficacy against rotavirus-induced diarrhea; carob exhibited antidiarrheal properties not only by acting to detoxify and constipate but by providing a rich source of calories; guava and belladonna are antispasmodics and have been shown to relieve the symptoms of AD. Finally, white bean and wheat yielded favorable clinical and dietary outcomes in children with diarrhea. ^ Conclusion. The present study is the first to review the evidence for use of herbal compounds for treatment of AD. Future randomized controlled trials are needed to evaluate their efficacy and safety.^

Quality of life, symptom experience, and use of complementary and alternative medicine among women with ovarian cancer

The objectives of this dissertation were to determine the quality of life in women with ovarian cancer and the association of their physical and emotional well-being with the number of symptoms, duration of symptoms, and the scores of common symptoms of ovarian cancer; to study the prevalence of complementary and alternative medicine techniques for symptom relief and its association with the number of symptoms, age, education, insurance, comorbidity, and satisfaction with medical care they received, and their pre-diagnostic experience of symptoms.^ This study was based on a secondary data analysis of a study of early detection of ovarian cancer. A sample of 139 women with ovarian cancer was recruited and was administered a questionnaire comprised of questions on their quality of life, their symptoms and what they did about the symptoms, whether they used any complementary and alternative medicine techniques, and other medical conditions they had. Out of this sample, 53 patients underwent in-depth interviews relating to their symptoms before the diagnosis and their experiences with the health care system leading to the ovarian cancer diagnosis. ^ In article #1, ovarian cancer patients were observed to have significantly poorer quality of life on all subscales and summary scores except pain, compared to that of the general population of US women. Physical well-being scores were negatively associated with the number of symptoms before diagnosis and a significant negative association of comorbidity index was observed with physical well-being. Higher education and increase in time since diagnosis was found to have better physical scores. Emotional well-being scores showed marginally significant associations with number of symptoms and bloating. ^ In article #2, a thematic content analysis of the ovarian cancer patients’ interviews revealed that on recognition of their symptoms women first assumed their symptoms to be a normal transient occurrence due to a pre-existing disease condition, or due to some other disease. A series of misattributions of their symptoms on their and their doctors’ part impacted their health care seeking.In article #3, a significantly greater likelihood of CAM use with an increase in the number of symptoms was observed.^ Based on the foregoing results, it is important to educate women on possible signs of ovarian cancer and also to educate doctors about the results of current research regarding ovarian cancer diagnosis. This will help to avoid a delay in getting a diagnosis and improve women’s quality of life. It emphasizes the diagnosis of ovarian cancer in earlier stages by more sensitive screening techniques. This study emphasizes the importance of consideration of comorbidity in any quality of life research. Additionally, educating women in the safe use of CAM techniques carries immense significance because the efficacy and safety of many of the currently advertized CAM products has not been scientifically validated. Further research is needed to confirm the findings of this study. ^

Psychosocial factors and musculoskeletal symptoms in a vulnerable working population in Nicaragua

This research is a secondary data analysis of the CUPID-INCA Nicaragua study, a cross-sectional study comparing psychosocial and physical factors on musculoskeletal symptoms among nurses, office workers and maquiladoras in Nicaragua. There were three objectives for this thesis. (1) To describe the study population according to their socio-demographic, psychosocial (i.e. work organization and health beliefs) and physical factors. (2) To estimate the prevalence of musculoskeletal disorders (MSDs) in the study population (nurses, office workers and maquilas). (3) To analyze and compare the trends of association between psychosocial factors and MSDs to that of physical factors and MSDs in the study population. Trends of association between MSDs and psychosocial factors were also compared between nurses, office workers and maquilas. ^ Majority of the total study population were females, middle aged, non smokers and had been on the job for more than five years. Prevalence rates of low back pain and upper extremity pain were 28% and 37% respectively in nurses, 17% and 34% in office workers and 18% and 31% in maquilas. Workers' health belief was significantly associated with MSDs in all three occupational groups. Psychosocial factors were not consistently associated more with MSDs than physical factors. Maquilas had more psychosocial factors statistically significantly associated with musculoskeletal symptoms than nurses and office workers. ^ The findings of this research suggest that both psychosocial and physical risk factors play a role on the prevalence of musculoskeletal symptoms in the three working populations in Nicaragua. Future research in this area should explore further, the risk of developing MSDs from workers' exposure to psychosocial factors as well as physical factors.^

BEST SUBSET SELECTION FOR CATEGORICAL DATA

When choosing among models to describe categorical data, the necessity to consider interactions makes selection more difficult. With just four variables, considering all interactions, there are 166 different hierarchical models and many more non-hierarchical models. Two procedures have been developed for categorical data which will produce the "best" subset or subsets of each model size where size refers to the number of effects in the model. Both procedures are patterned after the Leaps and Bounds approach used by Furnival and Wilson for continuous data and do not generally require fitting all models. For hierarchical models, likelihood ratio statistics (G('2)) are computed using iterative proportional fitting and "best" is determined by comparing, among models with the same number of effects, the Pr((chi)(,k)('2) (GREATERTHEQ) G(,ij)('2)) where k is the degrees of freedom for ith model of size j. To fit non-hierarchical as well as hierarchical models, a weighted least squares procedure has been developed.^ The procedures are applied to published occupational data relating to the occurrence of byssinosis. These results are compared to previously published analyses of the same data. Also, the procedures are applied to published data on symptoms in psychiatric patients and again compared to previously published analyses.^ These procedures will make categorical data analysis more accessible to researchers who are not statisticians. The procedures should also encourage more complex exploratory analyses of epidemiologic data and contribute to the development of new hypotheses for study. ^

Descriptive analysis of Ben Taub Pediatric Weight Management Program

The purpose of this study is to descriptively analyze the current program at Ben Taub Pediatric Weight Management Program in Houston, Texas, a program designed to help overweight children ages three to eighteen to lose weight. In Texas, approximately one in every three children is overweight or obese. Obesity is seen at an even greater level within Ben Taub due to the hospital's high rate of service for underserved minority populations (Dehghan et al, 2005; Tyler and Horner, 2008; Hunt, 2009). The weight management program consists of nutritional, behavioral, physical activity, and medical counseling. Analysis will focus on changes in weight, BMI, cholesterol levels, and blood pressure from 2007–2010 for all participants who attended at least two weight management sessions. Recommendations will be given in response to the results of the data analysis.^

Motivational interviewing and feedback for college drinkers: Handling missing values with complete case analysis and multiple imputation

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