Biostatistics Commons^™

Design, Analysis, And Interpretation Of Treatment Response Heterogeneity In Personalized Nutrition And Obesity Treatment Research, Roger S. Zoh, Bridget H. Esteves, Xiaoxin Yu, Amanda J. Fairchild, Ana I. Vazquez, Andrew G. Chapple, Andrew W. Brown, Brandon George, Derek Gordon, Douglas Landsittel, Gary L. Gadbury, Greg Pavela, Gustavo De Los Campos, Luis M. Mestre, David B. Allison

School of Public Health Faculty Publications

It is increasingly assumed that there is no one-size-fits-all approach to dietary recommendations for the management and treatment of chronic diseases such as obesity. This phenomenon that not all individuals respond uniformly to a given treatment has become an area of research interest given the rise of personalized and precision medicine. To conduct, interpret, and disseminate this research rigorously and with scientific accuracy, however, requires an understanding of treatment response heterogeneity. Here, we define treatment response heterogeneity as it relates to clinical trials, provide statistical guidance for measuring treatment response heterogeneity, and highlight study designs that can quantify treatment response …

Differences In Clinical Presentation At First Hospitalization And The Impact On Involuntary Admissions Among First-Generation Migrant Groups With Non-Affective Psychotic Disorders., Kelly K Anderson, Rebecca Rodrigues

Epidemiology and Biostatistics Publications

BACKGROUND: Some migrant and ethnic minority groups have a higher risk of coercive pathways to care; however, it is unclear whether differences in clinical presentation contribute to this risk. We sought to assess: (i) whether there were differences in clinician-rated symptoms and behaviours across first-generation immigrant and refugee groups at the first psychiatric hospitalization after psychosis diagnosis, and (ii) whether these differences accounted for disparities in involuntary admission.

METHODS: Using population-based health administrative data from Ontario, Canada, we constructed a sample (2009-2013) of incident cases of non-affective psychotic disorder followed for two years to identify first psychiatric hospitalization. We compared …

Construction And Performance Optimization Of Bioconjugated Nanosensors For Early Detection Of Breast Cancer And Pro-Inflammatory Diseases, Pooja Gaikwad

Dissertations, Theses, and Capstone Projects

In recent years, nanosensors have emerged as a tool with strong potential in medical diagnostics. Single-walled carbon nanotube (SWCNT) based optical nanosensors have notably garnered interest due to the unique characteristics of their near-infrared fluorescence emission, including tissue transparency, photostability, and various chiralities with discrete absorption and fluorescence emission bands. Additionally, the optoelectronic properties of SWCNT are sensitive to the surrounding environment, which makes them suitable for in vitro and in vivo biosensing. Single-stranded (ss) DNA-wrapped SWCNTs have been reported as optical nanosensors for cancers and metabolic diseases. Breast cancer and cardiovascular diseases are the most common causes of death …

Healthy Lifestyle Behaviors And Sociodemographic Characteristics Among Medical Students In Indonesia During The New Normal Era: A Cross-Sectional Study, Sharren Shera Vionnetta, Tommy Nugroho Tanumihardja, Kevin Kristian

Kesmas

This study aimed to identify medical students’ healthy lifestyle behaviors during the new normal era and to determine its relationship with sociodemographic factors, bearing in mind that, as future physicians and health role models, medical students play an important role in adopting and promoting healthy lifestyle behaviors to reduce the risk of future health problems as well as optimize communities’ health status. This cross-sectional study was conducted at the School of Medicine and Health Sciences of Universitas Katolik Indonesia Atma Jaya, with 111 medical students selected through stratified random sampling. Data were collected using sociodemographic characteristics (sex, residence, year of …

Prediction Of Factors For Patients With Hypertension And Dyslipidemia Using Multilayer Feedforward Neural Networks And Ordered Logistic Regression Analysis: A Robust Hybrid Methodology, Wan Muhamad Amir W Ahmad, Mohamad Nasarudin Bin Adnan, Norhayati Yusop, Hazik Bin Shahzad, Farah Muna Mohamad Ghazali, Nor Azlida Aleng, Nor Farid Mohd Noor

Makara Journal of Health Research

Background: Hypertension is characterized by abnormally high arterial blood pressure and is a public health problem with a high prevalence of 20%–30% worldwide. This research combined multiple logistic regression (MLR) and multilayer feedforward neural networks to construct and validate a model for evaluating the factors linked with hypertension in patients with dyslipidemia.

Methods: A total of 1000 data entries from Hospital Universiti Sains Malaysia and advanced computational statistical modeling methodologies were used to evaluate seven traits associated with hypertension. R-Studio software was utilized. Each sample's statistics were calculated using a hybrid model that included bootstrapping.

Results: Variable …

Characteristics And Source-Specific Health Risks Of Ambient Pm2.5-Bound Pahs In An Urban City Of Northern Taiwan, Yu-Chieh Ting, Chun-Hung Ku, Yu-Xuan Zou, Kai-Hsien Chi, Jhy-Charm Soo, Chin-Yu Hsu, Yu-Cheng Chen

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Polycyclic aromatic hydrocarbons (PAHs) with highly toxic compounds mainly exist in small-sized particles and can induce considerable human health risks. Studies on PM2.5-bound PAHs and their source-specific human health risks still remain scarce. Daily PM2.5 samples (n = 119) were collected every three days from 2016 to 2017 in Taipei city, Taiwan. Fifteen PAHs in PM2.5 were analyzed via gas chromatography tandem mass spectrometry (GC/MS-MS). We utilized a positive matrix factorization (PMF) model, diagnostic ratios, and potential source contribution function (PSCF) to identify the origins of PM2.5-bound PAHs. The annual concentration of total PAHs (TPAH) was 0.79 ± 0.67 ng …

Modeling Biphasic, Non-Sigmoidal Dose-Response Relationships: Comparison Of Brain- Cousens And Cedergreen Models For A Biochemical Dataset, Venkat D. Abbaraju, Tamaraty L. Robinson, Brian P. Weiser

Rowan-Virtua School of Osteopathic Medicine Departmental Research

Biphasic, non-sigmoidal dose-response relationships are frequently observed in biochemistry and pharmacology, but they are not always analyzed with appropriate statistical methods. Here, we examine curve fitting methods for “hormetic” dose-response relationships where low and high doses of an effector produce opposite responses. We provide the full dataset used for modeling, and we provide the code for analyzing the dataset in SAS using two established mathematical models of hormesis, the Brain-Cousens model and the Cedergreen model. We show how to obtain and interpret curve parameters such as the ED50 that arise from modeling, and we discuss how curve parameters might change …

Statistical Inference On Lung Cancer Screening Using The National Lung Screening Trial Data., Farhin Rahman

Electronic Theses and Dissertations

This dissertation consists of three research projects on cancer screening probability modeling. In these projects, the three key modeling parameters (sensitivity, sojourn time, transition density) for cancer screening were estimated, along with the long-term outcomes (including overdiagnosis as one outcome), the optimal screening time/age, the lead time distribution, and the probability of overdiagnosis at the future screening time were simulated to provide a statistical perspective on the effectiveness of cancer screening programs. In the first part of this dissertation, a statistical inference was conducted for male and female smokers using the National Lung Screening Trial (NLST) chest X-ray data. A …

Statistical Modeling Approaches For The Inference Of Cancer Mechanisms, Licai Huang

Dissertations and Theses (Open Access)

The aim of this study was to explore the potential of integrating multi-platform genomic datasets to improve our understanding of the biological mechanisms behind cancer. By merging clinical outcomes with the data obtained from multi-platform genomic studies, we can gain insight into the biological mechanisms behind a patient’s response to treatment. Additionally, the evaluation of the correlations between genetic variations and gene expression provides a better understanding of the functional significance of these variations. Such knowledge has the potential to revolutionize cancer diagnosis and treatment. This thesis describes methods developed to address two related aims. Aim 1: We have developed …

Statistical Approaches To Estimate Bidirectional And Time-Varying Causal Effects Using Mendelian Randomization, Jinhao Zou

Dissertations and Theses (Open Access)

Mendelian Randomization (MR) is an epidemiological framework using genetic variants as instrumental variables (IVs) to examine the causal effect of an exposure on an outcome. It is widely used to detect causal factors of diseases and provide insight into the biological pathway of diseases. Current methods under the MR framework are built to estimate the unidirectional causal effects of exposures on outcomes and neglect the potential bidirectional causal effects. However, a bidirectional causal effect creates a feedback loop that biases the casual inference in MR studies. Furthermore, current MR methods estimate the causal effect as a single value using cross-sectional …

Development Of A Metapgs For Accurate Prediction Of Osteoporotic Fracture, Xiangxue Xiao

UNLV Theses, Dissertations, Professional Papers, and Capstones

Introduction: Early identification of individuals at high-risk for osteoporotic fractures who may benefit from preventive intervention is essential. However, the predictive accuracy of the currently used fracture risk assessment tool remains suboptimal. The first aim of this research is to construct genome-wide polygenic scores for the femoral neck (PGS_FNBMD_idpred) and total body BMD (PGS_TBBMD_idpred) and to estimate their potential in identifying individuals with a high risk of osteoporotic fractures. The second aim is to validate the predictive performance of two previously established PGSs (PGS_FNBMD_idpred and PGS_TBBMD_idpred) in an external cohort …

Polygenic Risk Score Development And Validation For Early Detection And Risk Stratification Of Rheumatoid Arthritis And Osteoarthritis In Postmenopausal Women, Yingke Xu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Introduction: Around one in four adults worldwide suffer from arthritis. There are more than one hundred different forms of arthritis; the two most common forms of arthritis are rheumatoid arthritis (RA) and osteoarthritis (OA). RA is an autoimmune disease that can cause joint inflammation. Around 1.3 million adults in the US suffer from RA, representing 0.6%–1% of the population. The RA diagnosis in its early stages is difficult since its signs and symptoms are similar to other arthritis. OA is the most common form of arthritis. In the US, around 30.8 million people are affected by this disease. However, OA …

Editorial, Al Asyary

Kesmas

No abstract provided.

Approaches To Detecting And Modeling Over-And Underdispersion In Alternative Count Data Distributions And An Application Of Logistic Regression And Random Forest Modeling To Improve Screening Tools For Tic Disorders In Children, Rebecca C. Wardrop

Theses and Dissertations

This dissertation focuses on theory and application of discrete data methods, particularly approaches to over- and underdispersion relative to the Poisson distribution and an application of random forest and logistic regression modeling. The first chapter derives a score test for over- and underdispersion in the heaped generalized Poisson distribution. Equi-, over-, and underdispersed heaped generalized Poisson and heaped negative binomial data are simulated to evaluate the performance of the score test by comparing the power it achieves to that of Wald and likelihood ratio tests. We find that the score test we derive performs comparably to both the Wald and …

Statistical Methods For Single Cell Sequencing Data Analysis, Fei Qin

Theses and Dissertations

The recent emergence of single cell sequencing (SCS) technology has provided us with single-cell DNA or RNA sequencing (scDNA/RNA-seq) information to investigate cellular evolutionary relationships. Despite many analysis methods have been developed to infer intra-tumor genetic heterogeneity, cluster cellular subclones, detect genetic mutations, and investigate spatially variable (SV) genes, exploring SCS data remains statistically challenging due to its noisy nature.

To identify subclones with scDNA-seq data, many existing studies use an independent statistical model to detect copy number profile in the first step, followed by classical clustering methods for subclone identification in downstream analyses. However, spurious results might be generated …

A Bayesian Spatial Scan Statistic For Normal Data, Laasya Velamakanni

Theses and Dissertations

Scan statistics are useful methods for detecting spatial clustering. While they were initially developed to detect regions with an excess of binomial or Poisson events, spatial scan statistics have been extended to detect hotspots in other types of data including continuous data. They have many applications in different fields such as epidemiology (e.g. detecting disease outbreaks), sociology (e.g. detecting crime hotspots), and environmental health (e.g. detecting high-pollution areas). Spatial scan statistics identify a ‘most likely cluster’ and then use a likelihood ratio test to determine if this cluster is statistically significant. Spatial scan statistics have been extended to the Bayesian …

Statistical Methods For Semi-Competing And Competing Risks Data With Missing Event Types, Ruiqian Wu

Theses & Dissertations

There is a growing interest in modeling multiple event data in biomedical and public health investigations. Competing and semi-competing risks data are two special types of multiple event data. Statistical modeling of semi-competing risks data involves an intermediate event and a terminal event and emphasizes the investigation of the effect of the intermediate event on the terminal event. The investigation of the semi-competing risks data model not only enables us to determine if a disease episode is associated with mortality but also provides a toolkit for predicting death if the episode occurred at a particular time. Meanwhile, the interpretation of …

Unraveling The Neural Basis Of Emotions: Advancing Understanding With Ecologically Valid Paradigms And High-Resolution Intracranial Eeg, Tiankang Xie

Dartmouth College Ph.D Dissertations

Background

Emotion arises from integrating information about the external world with memories of past experiences, current homeostatic states, and future goals. They play a vital role in regulating our thoughts, feelings and behaviors, significantly impacting our mental health. Thus, it is important to understand the neurobiological mechanisms that give rise to emotions. While there has been considerable work investigating the neural basis of emotions, progress has been hampered by several methodological limitations. For example, prior work has relied on relatively simple and isolated stimuli, which often fail to effectively capture the dynamic and multifaceted nature of emotional experiences in real-life …

Exposure Levels Of Airborne Fungi, Bacteria, And Antibiotic Resistance Genes In Cotton Farms During Cotton Harvesting And Evaluations Of N95 Respirators Against These Bioaerosols, Atin Adhikari, Pratik Banerjee, Taylor Thornton, Daleniece Higgins, Caleb Adeoye, Sonam Sherpa

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

The USA is the third-leading cotton-producing country worldwide and cotton farming is common in the state of Georgia. Cotton harvest can be a significant contributor to airborne microbial exposures to farmers and nearby rural communities. The use of respirators or masks is one of the viable options for reducing organic dust and bioaerosol exposures among farmers. Unfortunately, the OSHA Respiratory Protection Standard (29 CFR Part 1910.134) does not apply to agricultural workplaces and the filtration efficiency of N95 respirators was never field-tested against airborne microorganisms and antibiotic resistance genes (ARGs) during cotton harvesting. This study addressed these two information gaps. …

Childhood Asthma-Management Practices In Rural Nigeria: Exploring The Knowledge, Attitude, And Practice Of Caregivers In Oyo State, Oyindamola Akinso, Atin Adhikari, Jingjing Yin, Joanne Chopak-Foss, Gulzar H. Shah

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Background: Caregivers of asthmatic children have a poor knowledge of proper asthma-management practices in Nigeria. This study examined the knowledge, attitudes, and practice behaviors of caregivers in the management of asthma in children under 5 years of age in Oyo State, Nigeria. Methods: While a mixed method was used in the original research, this brief describes the quantitative method used in this study to evaluate caregivers’ asthma-management practices. A 55-item questionnaire on childhood asthma knowledge, attitude, and practice was administered during child welfare-clinic visits to 118 caregivers. Data were analyzed using the IBM SPSS Version 25.0. Statistical significance was set …