Clinical Trials Commons^™

C10: Oral Potentially Malignant Disorders Prevalence In The Orthodontic Clinic, Mark Greene

Annual Research Symposium

No abstract provided.

C8: Intravenous (Iv) Bolus Versus Iv Infusion As Initial Approach For Blood Pressure (Bp) In Acute Ischemic Stroke (Ais) Patients Receiving Tissue-Plasminogen Activator (Tpa), Alexander D. Bonca, Alana Whittaker

Annual Research Symposium

No abstract provided.

C4: Comparing The Sub-Gingival Levels Of Cytomegalovirus, Epstein-Barr Virus, Porphyromonas Gingivalis In Human Immunodeficiency Virus-1 Seropositive Patients With And Without Antiretroviral Therapy, Supriya Kheur

Annual Research Symposium

No abstract provided.

S3: Post-Covid-19 Recovery Care Plan For Older Adults With Continuing Symptoms Of Breathlessness And Fatigue, Nancy M. Bryan, Marie Wright-Rolf Edd, Msn, Rn, Siboney Zelaya Ph.D., Mph, Msn Ed, Rn, Justin Carbonel

Annual Research Symposium

Background:

The CDC research actively continues gathering information related to short and long-term symptoms that remain following the acute phase of Covid-19 diagnosis (CDC, 2020).

Fatigue and shortness of breath are listed among the most commonly reported long-term symptoms of Covid-19:

1. Fatigue
2. Shortness of Breath
3. Cough
4. Joint Pain
5. Chest Pain (CDC, 2020).

Evidence suggests that older adults over the age of 60 who have multiple comorbidities are more susceptible and are at a higher risk of contracting the Covid-19 virus thus potentially prolonging recovery time post diagnosis (Greenhalgh, Knight, A’Court, Buxton, & Husain, 2020).

The Agency for Healthcare Research and …

P14: Emerging Role Of Pharmacists In Treatment And Vaccination For Covid-19, Dwaynie Bacon Jr, Man Ha, Dr. Mandal

Annual Research Symposium

No abstract provided.

P5: Covid-19 Vaccine: Technology Platform, Efficacy And Immune Protection, Manas Mandal

Annual Research Symposium

Roseman Research Day Symposium.

P2: Characteristics Of Individuals With Oral Hpv Positive Results, Val Cheever, Eric Hon, Andrew J. Gross, Man Hung

Annual Research Symposium

No abstract provided.

O2: In-Silico Approach To Analyze Anticancer Activity Of Withania Somnifera In Oral Cancer, Gauri Kumbhar

Annual Research Symposium

No abstract provided.

Resident Heart Rate Variability During Cataract Surgery, Ahmad Baiyasi, Shibandri Das, Ferris Bayasi, Faisal Ridha Al-Timimi

Medical Student Research Symposium

Purpose: To evaluate ophthalmology resident anxiousness and cardiovascular response by tracking resident heart rate (HR) when performing cataract surgery during their last year of residency.

Methods: A prospective analysis of 31 cataract cases, completed by three residents (two females and one male), at the Kresge Eye Institute in August and September 2020 was performed. Inclusion criteria for cases included all cataract cases performed by PGY-4 residents at the Kresge Eye Institute who downloaded the Heart Graph app supported by iOS. Residents with android mobile devices were excluded from the study. Informed consent was obtained from all residents who utilized the …

Optimal Two-Stage Designs Based On Restricted Mean Survival Time For A Single-Arm Study, Guogen Shan

School of Public Health Faculty Research

© 2021 The Author(s) Restricted mean survival time is an alternative measure of treatment effect to hazard ratio in clinical trials with time-to-event outcome. The current methods have been focused on one-stage designs. In this article, we propose optimal two-stage designs for a single-arm study with the smallest expected sample size. We compare the performance of the new optimal two-stage designs with the existing one-stage design with regards to the expected sample size and the expected total study length. The simulation results indicate that the new two-stage designs can save the expected sample size substantially as compared to the one-stage …

Using Covid-19 Vaccine Efficacy Data To Teach One-Sample Hypothesis Testing, Frank Wang

Numeracy

In late November 2020, there was a flurry of media coverage of two companies’ claims of 95% efficacy rates of newly developed COVID-19 vaccines, but information about the confidence interval was not reported. This paper presents a way of teaching the concept of hypothesis testing and the construction of confidence intervals using numbers announced by the drug makers Pfizer and Moderna publicized by the media. Instead of a two-sample test or more complicated statistical models, we use the elementary one-proportion z-test to analyze the data. The method is designed to be accessible for students who have only taken a …

Novel Nonparametric Testing Approaches For Multivariate Growth Curve Data: Finite-Sample, Resampling And Rank-Based Methods, Ting Zeng

Theses and Dissertations--Statistics

Multivariate growth curve data naturally arise in various fields, for example, biomedical science, public health, agriculture, social science and so on. For data of this type, the classical approach is to conduct multivariate analysis of variance (MANOVA) based on Wilks' Lambda and other multivariate statistics, which require the assumptions of multivariate normality and homogeneity of within-cell covariance matrices. However, data being analyzed nowadays show marked departure from multivariate normal distribution and homoscedasticity. In this dissertation, we investigate nonparametric testing approaches for multivariate growth curve data from three aspects, i.e., finite-sample, resampling and rank-based methods.

The first project proposes an approximate …

Innovative Statistical Models In Cancer Immunotherapy Trial Design, Jing Wei

Theses and Dissertations--Statistics

A challenge arising in cancer immunotherapy trial design is the presence of non-proportional hazards (NPH) patterns in survival curves. We considered three different NPH patterns caused by delayed treatment effect, cure rate and responder rate of treatment group in this dissertation. These three NPH patterns would violate the proportional hazard model assumption and ignoring any of them in an immunotherapy trial design will result in substantial loss of statistical power.

In this dissertation, four models to deal with NPH patterns are discussed. First, a piecewise proportional hazards model is proposed to incorporate delayed treatment effect into the trial design consideration. …

Tricyclic Antidepressant Use And Risk Of Fractures: A Meta-Analysis Of Cohort Studies Through The Use Of Both Frequentist And Bayesian Approaches, Qing Wu, Yingke Xu, Yueyang Bao, Jovan Alvarez, Mikee Lianne Gonzales

School of Medicine Faculty Research

Background: Research findings regarding the association between tricyclic antidepressant (TCA) treatment and the risk of fracture are not consistent; we aimed to assess whether people who take TCAs are at an increased fracture risk. Methods: Relevant studies published through June 2020 were identified through database searches of MEDLINE, EMBASE, Scopus, PsycINFO, ISI Web of Science, WorldCat Dissertations and Theses from each database’s inception, as well as through manual searches of relevant reference lists. Two researchers independently performed literature searches, study selection, data abstraction and study appraisal by using a standardized protocol. Frequentist and Bayesian hierarchical random-effects models were used for …

Utility Of Inflammatory Markers To Predict Adverse Outcome In Acute Pancreatitis: A Retrospective Study In A Single Academic Center, Mohamad Mubder, Banreet Dhindsa, Danny Nguyen, Syed Saghir, Chad Cross, Ranjit Makar, Gordon Ohning

School of Medicine Faculty Research

Background/Aim: Acute pancreatitis (AP) is a commonly encountered emergency where early identification of complicated cases is important. Inflammatory markers like lymphocyte to monocyte ratio (LMR) and neutrophil to lymphocyte ratio (NLR) are simple and readily available markers. In this study, we evaluated the utility of these markers in the early identification of patients with complicated AP. Patients and Methods: All patients with a diagnosis of AP admitted to the University Medical Center in Las Vegas/Nevada between August 2015 and September 2018 were identified using ICD-10 codes. Medical records were reviewed retrospectively. Epidemiological measures and their associated confidence intervals were calculated …

Sensitivity Analysis For Incomplete Data And Causal Inference, Heng Chen

Statistical Science Theses and Dissertations

In this dissertation, we explore sensitivity analyses under three different types of incomplete data problems, including missing outcomes, missing outcomes and missing predictors, potential outcomes in \emph{Rubin causal model (RCM)}. The first sensitivity analysis is conducted for the \emph{missing completely at random (MCAR)} assumption in frequentist inference; the second one is conducted for the \emph{missing at random (MAR)} assumption in likelihood inference; the third one is conducted for one novel assumption, the ``sixth assumption'' proposed for the robustness of instrumental variable estimand in causal inference.

Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation., Arinjita Bhattacharyya

Electronic Theses and Dissertations

Generalized linear models have broad applications in biostatistics and sociology. In a regression setup, the main target is to find a relevant set of predictors out of a large collection of covariates. Sparsity is the assumption that only a few of these covariates in a regression setup have a meaningful correlation with an outcome variate of interest. Sparsity is incorporated by regularizing the irrelevant slopes towards zero without changing the relevant predictors and keeping the resulting inferences intact. Frequentist variable selection and sparsity are addressed by popular techniques like Lasso, Elastic Net. Bayesian penalized regression can tackle the curse of …

A Modular Framework For Early-Phase Seamless Oncology Trials, Philip S. Boonstra, Thomas M. Braun, Elizabeth C. Chase

The University of Michigan Department of Biostatistics Working Paper Series

Background: As our understanding of the etiology and mechanisms of cancer becomes more sophisticated and the number of therapeutic options increases, phase I oncology trials today have multiple primary objectives. Many such designs are now 'seamless', meaning that the trial estimates both the maximum tolerated dose and the efficacy at this dose level. Sponsors often proceed with further study only with this additional efficacy evidence. However, with this increasing complexity in trial design, it becomes challenging to articulate fundamental operating characteristics of these trials, such as (i) what is the probability that the design will identify an acceptable, i.e. safe …

Integrated Multiple Adaptive Design Involving Sample Size Re-Estimation And (Covariate-Adjusted) Response-Adaptive Randomization For Continuous And Binary Outcomes, Christine M. Orndahl

Theses and Dissertations

Historically, clinical trials have been performed based on decisions made prior to the start of the trial. Adaptive designs have been developed to provide increased flexibility, allowing pre-specified changes to occur based on interim data. Each adaptive design addresses a unique pitfall of a non-adaptive design, such as minimizing the chance of an under- or over-powered study by utilizing interim data to update the sample size estimate (sample size re-estimation) or increasing the ethical benefit of a trial by allocating more participants to the better performing treatment group ([covariate-adjusted] response-adaptive randomization). Additional benefit is attainable by combining more than one …

Estimation Of The Treatment Effect With Bayesian Adjustment For Covariates, Li Xu

Theses and Dissertations--Statistics

The Bayesian adjustment for confounding (BAC) is a Bayesian model averaging method to select and adjust for confounding factors when evaluating the average causal effect of an exposure on a certain outcome. We extend the BAC method to time-to-event outcomes. Specifically, the posterior distribution of the exposure effect on a time-to-event outcome is calculated as a weighted average of posterior distributions from a number of candidate proportional hazards models, weighing each model by its ability to adjust for confounding factors. The Bayesian Information Criterion based on the partial likelihood is used to compare different models and approximate the Bayes factor. …