Biostatistics Commons^™

Dietary Inflammatory Index And Risk Of Colorectal Cancer In Japanese Men, Ayaka Kotemori, Kumiko Kito, Motoki Iwasaki, Taiki Yamaji, James Hébert Scd, Junko Ishihara, Manami Inoue, Shoichiro Tsugane, Norie Sawada On The Behalf Of Jphc Study Group

Faculty Publications

Background/Objectives: Unhealthy lifestyles lead to chronic low-grade inflammation, increasing the risk of colorectal cancer. Few studies in East Asia have examined the association between the dietary inflammation potential and colorectal cancer incidence. Therefore, we aimed to investigate this association further in the Japanese population. Methods: This study included 38,807 men aged 45–74 years who participated in the Japan Public Health Center-based prospective study (JPHC Study). The energy-adjusted dietary inflammatory index (E-DII) was derived from a food frequency questionnaire. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression models. Differences in risk due to a …

Protocol For The Development Of The Who Gestational Weight Gain Charts, Thais Rangel Bousquet Carrilho, Olufemi Taiwo Oladapo, Jennifer A. Hutcheon, Giovanna Gatica-Domínquez, Kathleen M. Rasmussen, Monica C. Flores-Urrutia, Richard Kumapley, Ӧzge Tunçalp, Dang Bahya-Batinda, Amel A. Fayed, Annick Bogaerts, Aris T. Papageorghiou, Cinthya Muñoz-Manrique, Dayana Rodrigues Farias, Eric Ohuma, Harshpal Sachdev, Hayfaa A. Wahabi, Helena J. Teede, Molin Wang, Nandita Perumal Phd

Faculty Publications

Introduction Gestational weight gain (GWG) is an important indicator of maternal nutrition to be monitored during pregnancy. However, there is no evidence-based tool that can be used to monitor it across all geographic locations and pre-pregnancy body mass index (BMI) categories. The WHO is undertaking a project to develop GWG charts by pre-pregnancy BMI category, and to identify GWG ranges associated with the lowest risks of adverse maternal and infant outcomes. This protocol describes all the steps that will be used to accomplish the development of these GWG charts.

Methods and analysis This project will involve the analysis of individual …

Sociodemographic And Hiv-Related Characteristics Associated With Mental Health Diagnoses Among People Living With Hiv, Monique J. Brown Ph.D., Mph, Jiayang Xiao, Xueying Yang Ph.D., Bankole Olatosi Ph.D., Sharon Weissman, Xiaoming Li Ph.D., Jiajia Zhang Ph.D.

Faculty Publications

Mental health diagnoses have been linked to poor HIV treatment outcomes and poorer quality of life among people living with HIV (PLWH). Therefore, this study aimed to investigate the association between sociodemographic and HIV-related characteristics, and common and serious mental health disorders among PLWH in South Carolina (SC). Data were obtained from the integrated system of statewide electronic health record (EHR) data in SC (2006–2019; N = 8,124). Multivariable logistic regression models were used to determine the associations between sociodemographic and HIV-related characteristics, and common mental health disorders and serious mental health disorders. Among the study population, 4% were 60 …

Multiple Myeloma Risk Linked To Dna Damage Response Genes, Michael Conry, Irina Ostrovnaya, Yelena Kemel, Saloni Sinha, Linda B. Baughn, Brian Avery, Kylee Maclachlan, Victoria Groner, Lauren Banaszak, Aaron Norman, Nicholas J. Boddicker, Alyssa I. Clay-Gilmour Ph.D., Shaji Kumar, Ellen Kim, Sita Dandiker, Mitul Waghmare, Susan Slager, Douglas Sborov, Judy Garber, Elizabeth E. Brown, Michelle Hildebrandt, Et. Al.

Faculty Publications

Background DNA damage response genes (DDRG), implicated in several cancers as both predisposing risk factors as well as biomarkers for aggressiveness, have not been fully explored in multiple myeloma (MM).

Methods Herein, we analyzed disease associations of pathogenic variations in nine putative candidate genes using 3 446 MM cases and 323 233 cancer-free controls.

Results Increased MM risk was found to be associated with inherited rare pathogenic mutations in TP53, ATM, CHEK2, KDM1A, and ARID1A, with an enrichment of these variants among individuals with early onset or family history of MM. Individuals with TP53 or ATM germline mutations are also …

Cross-Temporal Statistical Approaches For Evaluating Predictor-Outcome Relationships, Jeff Joseph

Dartmouth College Ph.D Dissertations

Central auditory function is linked with cognitive deficits, but few research projects use existing statistical approaches or develop new ones to forecast cognitive deficits using the results of central auditory tests. To address this limitation, we use a series of statistical learning frameworks for predicting a child’s cognitive abilities based on his/her central auditory performances and demographic factors. Two key challenges exist. First, children may start the study at a time when they are unable to perform the central auditory tests or cognitive tests. Second, cognitive performance is age-dependent, particularly in the early formative years of childhood and adolescence. To …

Establishing A Public Health Surveillance System For The Opioid Crisis: The Experience Of The Healing Communities Study, Bridget Freisthler, Daniel J. Feaster, Charles Knott, Marc Larochelle, John Mccarthy, Svetla Slavova, Sharon L. Walsh, Jennifer Villani

Biostatistics Faculty Publications

Introduction: Efforts to reduce opioid overdose deaths in the United States have been stymied by the lack of timely and standardized population-level data for local, state, and national levels. The U.S. has a strong national need for linking opioid and other drug overdose surveillance data to service utilization data for overdose prevention and treatment to inform resource allocation and response planning.

Methods: We provide insight on the challenges of identifying, obtaining, and harmonizing administrative outcome data across four states using the collective experience from the HEALing Communities Study to test a community-engaged, data-driven, population-level intervention to reduce opioid overdose deaths. …

Supplemental Bibliographic Details. From 2001 Mars Odyssey To Earth’S Climate Crisis: Integrating Gamma Spectroscopy, Martian Soil Simulants, And Plant Genomes For Agroecology, Anchored In Sri Lanka’S Mars-Context Serpentinites, Suniti Karunatillake, Maheshi Dassanayake, Carlos Gary Bicas

Planetary Science Lab

Bibliographic details follow to supplement hyperlinked citations in the multinational GANGOTRI-supporting project conceived by Karunatillake, Dassanayake, and Gary-Bicas

Guidelines For Standard Basic Notations In Applied Statistics, Abhaya Indrayan, Shivani Saini Ms

COBRA Preprint Series

Whereas some statistical notations are standard and uniformly used by different workers, many are not. Varying notations lead to confusion among the readers, particularly those engaged with applied statistics material, such as medical professionals. This communication proposes that all basic notations be standardized so that the same notations are consistently used by different authors, in different books, journals, and articles for the benefit of those who are not rigorously trained statisticians. Guidelines for such standard notations are also provided. The lead must be taken by statisticians.

A Comparative Evaluation Of Data Imbalance Handling Techniques In Machine Learning Models For One-Year Mortality Prediction In Liver Cirrhosis, Sumiya Hasan Trisha

UNF Graduate Theses and Dissertations

Liver cirrhosis is associated with substantial morbidity and mortality, making one-year mortality prediction a clinically relevant problem. Using a liver cirrhosis dataset as the motivating application, this thesis evaluates five machine learning classifiers—Logistic Regression, Random Forest, XGBoost, LightGBM, and CatBoost—under five class-imbalance handling strategies: Baseline learning, Random Oversampling, SMOTE-NC, ADASYN, and Cost-Sensitive Learning. Hyperparameter tuning was conducted using randomized search, and predictive performance was assessed over 200 iterations of Monte Carlo Cross-Validation using Accuracy, Precision, Recall, Fl-score, and ROC-AUC.

The results suggest that imbalance-handling strategies can materially affect predictive performance, particularly recall. Because the outcome of interest is death within …

Two-Stage Response-Adaptive Randomization Designs For Multi-Arm Trials With Normal Outcome, Tanjin Tamanna Happy

UNF Graduate Theses and Dissertations

This study focuses on improving how clinical trials compare new treatments with a standard treatment, when the response is quantitative (normally distributed). In a common two-stage design, several new treatments are first evaluated, and the best-performing one is selected if it appears better than the standard. In the second stage, this selected treatment is compared again with the standard using additional data to confirm its effectiveness. This approach is known to be efficient in terms of accuracy and sample size savings. We extend this design by introducing an adaptive method for assigning patients to treatments in the second stage. Instead …

Enhancing Team Science By Training Collaborative Biostatisticians To Have A Strong Statistical Voice, Gina-Maria Pomann, Steven C. Grambow, Marissa C. Ashner, Bibhas Chakraborty, Nan Liu, Megan L. Neely, Sarah Peskoe, Lacey Rende, Emily Slade, Tracy Truong, Lexie Zidanyue Yang, Greg P. Samsa, Jesse D. Troy

Biostatistics Faculty Publications

Strong statistical voice is defined as the ability to advocate and negotiate for good and ethical statistical practices, including integrating and resolving differing scientific approaches. This skill is crucial for biostatisticians who work on biomedical research teams, as it ensures the integrity and accuracy of statistical analyses and fosters productive collaborations with non-statisticians. Despite its importance, new graduates often lack targeted training opportunities. This manuscript presents a scalable training approach through the development of online videos. Preliminary didactic materials focused on two key applications: providing written comments on manuscripts and engaging in study design discussions. To evaluate this training approach, …

Using Camera-Based Unmarked Spatial Capture-Recapture Modeling To Estimate Reintroduced Elk (Cervus Canadensis) Population Parameters And Distribution In Southeastern Kentucky, Claire Marie Muia

Theses and Dissertations--Forestry and Natural Resources

Estimation of population parameters is important for wildlife management decisions. Elk reintroduced to southeastern Kentucky experienced early irruptive population growth and are currently monitored using a statewide harvest-based statistical population reconstruction model (SPR) across the Kentucky Elk Restoration Zone (KERZ). Because the SPR model is spatially coarse and difficult to scale to the smaller management units comprising the KERZ, we conducted a spatially explicit capture-recapture study using a clustered camera-trapping array deployed for 10 weeks from June–August 2024 to estimate elk population parameters within Management Unit 4. Due to a lack of resights of GPS-marked elk, population parameters were estimated …

Body Mass Index Has No Impact On Complications And Mortality For Patients With Stage Iv Pancreatic Ductal Adenocarcinoma, Ren Bryant, Hannah Darnell, Megan Hall, Kelsey N. Karnik, Kristen J. Mcquerry, Ruben R. Plentz

Biostatistics Faculty Publications

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of United States (USA) cancer death. Overweight and obesity developing into a growing global medical and socio-economic problem, affecting approximately 42% of adults in the USA population. The aim of our analysis was to evaluate the influence of overweight and obesity on complications and clinical outcome in patients with stage IV PDAC.

Methods: We retrospectively reviewed electronic health records of patients diagnosed with stage IV PDAC (n=162) who followed with the University of Kentucky from January 2017–October 2024. Comparisons were based on the body mass index (BMI): low BMI …

Beyond The Lace Index: Benchmarking Machine Learning Architectures And Explaining 30-Day Hospital Readmission Risk With Shap Analysis, Carl E. Hughes Iii

Williams Honors College, Honors Research Projects

Unplanned 30-day hospital readmission remains a fundamental challenge in US healthcare, associated with increased risk to patient recovery and representing an estimated $52.4 billion in annual expenses (Beauvais et al., 2022). While the rigorously validated LACE index serves as the clinical standard for readmission modeling, its linear structure and four explanatory variables lack the complexity to capture the high-dimensional and interactive nature of patient risk. This study utilizes an admission granularity level cohort of the MIMIC-IV database to develop and compare machine learning architectures against the baseline LACE index. Due to the imbalanced prevalence of readmission, the penalized logistic regression, …

Feasibility, Acceptability, And Preliminary Efficacy Of A Pilot Study To Integrate Buprenorphine Into A Harm-Reduction Drop-In-Center In Kampala, Uganda, Julia Dickson-Gomez, Sergey Tarima, Wamala Twaibu, Dan Katende, Latifah Kyeswa, Laura Glasman, Arthur Kiconco, Sarah Krechel, Bryan Johnston, Moses Ogwal, Brian Byamah Mutamba, Peter Mudiope, Stella Alamo, Rhoda Wanyenze, Geofrey Musinguzi

Biostatistics Faculty Publications

Illicit drug use has been increasing rapidly in Sub-Saharan Africa in the past decade. However, until recently HIV prevention has largely ignored people who inject drugs and medications to treat opioid use disorder (MOUD) were largely absent. This paper reports results of a pilot intervention that integrated buprenorphine into a harm-reduction drop-in-center for people with opioid use disorder (OUD) in Kampala, Uganda. We collected implementation outcomes and changes in self-reported drug use after buprenorphine initiation. We conducted qualitative interviews with a subset of 14 participants who had initiated buprenorphine. Sixty-two participants were screened for OUD, of whom 57 were eligible …

Artificial Intelligence In Biomedical Team Science: Perceptions, Practices, And Training Needs, Emily Slade, Kelsey N. Karnik, Caitline Phan, Megan E. Hall, Yana Feygin, Kristen J. Mcquerry

Biostatistics Faculty Publications

Introduction: Artificial intelligence (AI) is increasingly used in biomedical research, yet limited empirical work has described how researchers use AI tools on collaborative research teams and how they view their role within team-based research. This study examines researchers’ experience with and attitudes toward AI use in collaborative research environments.

Methods: A cross-sectional survey was administered to 178 investigators engaged in collaborative research at the University of Kentucky. Questions assessed AI use across research and communication tasks, team-related decision-making practices, perceived benefits and concerns, and preferences for training and frameworks.

Results: Thirty-nine participants responded (22%). AI use was heterogeneous: 26% had …

Propensity Score Matching Accounting For Longitudinal Trends Before Baseline With Group-Based Trajectory Modeling, Dustin R. Bastaich

Theses and Dissertations

Propensity score matching is used in observational studies to balance baseline attributes between a treatment of interest and a control group. Propensity score matching typically relies on baseline variables, but longitudinal trends in patient characteristics can also influence treatment decisions and subsequent health outcomes. This dissertation extends standard approaches by explicitly incorporating longitudinal trajectories of key variables into the propensity score estimation process.

Trends in a longitudinal variable prior to baseline were characterized using group-based trajectory modeling. A two-step modeling approach was implemented where trajectory groups of a key variable were first estimated and then included as covariates in the …

Type Ii Diabetes Treatment Comparison Via Compartment Modeling, Abigail M. Collins

Theses and Dissertations

Type II diabetes mellitus affects one in ten adults worldwide, yet the effects of treatment type and adherence level on developing complications and quality of life have not been well characterized at the population level, and mathematical modeling offers a structured way to examine these dynamics. This thesis adapts the Boutayeb et al. (2004) model to incorporate dynamic treatment types and levels of adherence, producing nine scenarios in which complication development rate and complication recovery rate differed, to compare peak complications and quality of life across treatment and adherence conditions. Using a system of ordinary differential equations and compartment modeling, …

A Comparative Study Of Classification Methods For Healthcare Analytics, Xueting Zhao

UNF Graduate Theses and Dissertations

This thesis presents a comparative study of logistic regression, Linear Discriminant Analy- sis (LDA), and Quadratic Discriminant Analysis (QDA) for binary classification in healthcare analytics, integrating theoretical derivation, simulation, and real-data application. A facto- rial simulation study crosses the covariance structure (equal vs. unequal), predictor correla- tion (ρ ∈ {0, 0.5, 0.9}), dimensionality (p ∈ {2, 5, 10}) and sample size (n ∈ {50, 100, 200}) across 54 scenarios with 1,000 Monte Carlo replicates each. Three main findings emerge. Logistic regression and LDA are nearly interchangeable when the assumption of equal-covariance holds. QDA achieves substantially better discrimi- nation when class-specific …

Ridit-Based Adaptive Allocation In Two-Stage Clinical Trials With Binary Outcomes, Dewan Fahim

UNF Graduate Theses and Dissertations

This study explores better ways to assign patients to treatments in clinical trials with binary outcomes, such as success or failure. Adaptive methods are used to learn from early results and adjust treatment assignments during the trial, helping more patients receive better performing treatments while maintaining reliable conclusions. We focus on trials comparing multiple treatments using a two-stage design. In the first stage, several treatments are tested to identify the most promising one; in the second stage, that treatment is compared with a control. Unlike traditional equal assignment, we use adaptive allocation in the second stage to make better use …