Physical Sciences and Mathematics Commons^™

Inter-Rater Reliability Of Statistics Based On Reconstructed Individual Patient Data From Published Kaplan-Meier Curves, Megan E. Smith

Theses & Dissertations

Introduction: Time-to-event outcomes include two elements: an indicator variable for whether the event has taken place, and the length of time from some origin point to the occurrence of the event of interest. Due to the complexity of these data, secondary analysis methods, such as indirect comparisons and meta-analysis, are easier to perform when individual-level patient data (IPD) is available.

Objectives: In 2021, an R package IPDfromKM was published, which contains an algorithm for reconstructing IPD from a Kaplan-Meier graph. The current research aimed to investigate the reproducibility of the IPDfromKM algorithm.

Methods: Three statisticians (MS, LS, …

Prediction Of Rapid Early Progression And Survival Risk With Pre-Radiation Mri In Who Grade 4 Glioma Patients, Walia Farzana, Mustafa M. Basree, Norou Diawara, Zeina Shboul, Sagel Dubey, Marie M. Lockheart, Mohamed Hamza, Joshua D. Palmer, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Rapid early progression (REP) has been defined as increased nodular enhancement at the border of the resection cavity, the appearance of new lesions outside the resection cavity, or increased enhancement of the residual disease after surgery and before radiation. Patients with REP have worse survival compared to patients without REP (non-REP). Therefore, a reliable method for differentiating REP from non-REP is hypothesized to assist in personlized treatment planning. A potential approach is to use the radiomics and fractal texture features extracted from brain tumors to characterize morphological and physiological properties. We propose a random sampling-based ensemble classification model. The proposed …

Angiotensin Blockade Therapy And Survival In Pancreatic Cancer: A Population Study, Scott W Keith, Vittorio Maio, Hwyda A Arafat, Matthew Alcusky, Thomas Karagiannis, Carol Rabinowitz, Harish Lavu, Daniel Z. Louis

College of Population Health Faculty Papers

Background: Pancreatic cancer (PC) is one of the most aggressive and challenging cancer types to effectively treat, ranking as the fourth-leading cause of cancer death in the United States. We investigated if exposures to angiotensin II receptor blockers (ARBs) or angiotensin I converting enzyme (ACE) inhibitors after PC diagnosis are associated with survival.

Methods: PC patients were identified by ICD-9 diagnosis and procedure codes among the 3.7 million adults living in the Emilia-Romagna Region from their administrative health care database containing patient data on demographics, hospital discharges, all-cause mortality, and outpatient pharmacy prescriptions. Cox modeling estimated covariate-adjusted mortality hazard ratios …

(R1239) A New Type Ii Half Logistic-G Family Of Distributions With Properties, Regression Models, System Reliability And Applications, Emrah Altun, Morad Alizadeh, Haitham M. Yousof, Mahdi Rasekhi, G. G. Hamedani

Applications and Applied Mathematics: An International Journal (AAM)

This study proposes a new family of distributions based on the half logistic distribution. With the new family, the baseline distributions gain flexibility through additional shape parameters. The important statistical properties of the proposed family are derived. A new generalization of the Weibull distribution is used to introduce a location-scale regression model for the censored response variable. The utility of the introduced models is demonstrated in survival analysis and estimation of the system reliability. Three data sets are analyzed. According to the empirical results, it is observed that the proposed family gives better results than other existing models.

Infant Mortality In The United States: Socioeconomic Factors Predicting Infant Survival In Late Neo-Natal And Post Neo-Natal Infants From Birth Certificate Data, Mark Brunk-Grady

Theses and Dissertations

According to the Centers for Disease Control and Prevention, the infant mortality rate in the United States in 2018 was 5.6 deaths per 1000 live births. Infant mortality is defined as a child being born alive but dying before their first birthday. This study aimed to determine if adding socioeconomic factors to traditional predictive survival models improved the predictive power in terms of survival for late and post neonatal infants. Secondly, this study looked to develop a risk score to and predict which mothers would be classified as “High” or “Low” risk for infant death.

Data were analyzed from a …

Comparative Survival Of Asian And White Metastatic Castration-Resistant Prostate Cancer Men Treated With Docetaxel, Susan Halabi, Sandipan Dutta, Catherine M. Tangen, Mark Rosenthal, Daniel P. Petrylak, Ian M. Thompson Jr., Kim N. Chi, Johann S. De Bono, John C. Araujo, Christopher Logothetis, Mario A. Eisenberger, David I. Quinn, Karim Fizazi, Michael J. Morris, Celestia S. Higano, Ian F. Tannock, Eric J. Small, William Kevin Kelly

Mathematics & Statistics Faculty Publications

There are few data regarding disparities in overall survival (OS) between Asian and white men with metastatic castration-resistant prostate cancer (mCRPC). We compared OS of Asian and white mCRPC men treated in phase III clinical trials with docetaxel and prednisone (DP) or a DP-containing regimen. Individual participant data from 8820 men with mCRPC randomly assigned on nine phase III trials to receive DP or a DP-containing regimen were combined. Men enrolled in these trials had a diagnosis of prostate adenocarcinoma. The median overall survival was 18.8 months (95% confidence interval [CI] = 17.4 to 22.1 months) and 21.2 months (95% …

Impact Of The Affordable Care Act On Colorectal Cancer Screening, Incidence, And Survival In Kentucky, Tong Gan, Heather F. Sinner, Samuel C. Walling, Quan Chen, Bin Huang, Thomas C. Tucker, Jitesh A. Patel, B. Mark Evers, Avinash S. Bhakta

Surgery Faculty Publications

Background

Kentucky ranks first in the US in cancer incidence and mortality. Compounded by high poverty levels and a high rate of medically uninsured, cancer rates are even worse in Appalachian Kentucky. Being one of the first states to adopt the Affordable Care Act (ACA) Medicaid expansion, insurance coverage markedly increased for Kentucky residents. The purpose of our study was to determine the impact of Medicaid expansion on colorectal cancer (CRC) screening, diagnosis, and survival in Kentucky.

Study Design

The Kentucky Cabinet for Health and Family Services and the Kentucky Cancer Registry were queried for individuals (≥20 years) undergoing CRC …

Adult Atlantic Sturgeon Population Dynamics In The York River, Virginia, Jason E. Kahn

Graduate Theses, Dissertations, and Problem Reports

Sturgeon first appear in the fossil record in the Triassic Period just over 200 million years ago and are among the most primitive of the bony fishes. Despite their large size and historic presence along the East Coast, Atlantic sturgeon were not targeted for their meat and caviar as a commercial fishery until 1880. By 1905 they had declined to less than one percent of their pre-fishing abundance but the fishery continued. Prior to 1980, there had been very little research on Atlantic sturgeon, primarily limited to documenting landing location and poundage, maximum longevity, or weight of eggs per fish. …

Some New Discretization Methods With Application In Reliability, Gholamhossein Yari, Zahra Tondpour

Applications and Applied Mathematics: An International Journal (AAM)

Deriving discrete analogues (Discretization) of continuous distributions has drawn attention of researchers, in recent decades. Discretization has been playing a key role in modeling life time data because in real world, most of original life time data are continuous while they are discrete in observation. In this paper, we introduce three new two-stage composite discretization methods to meet the need of fitting discrete-time reliability and survival data sets. All three proposed methods consist of two stages where using construction a new continuous random variable by underlying continuous random variable in the first stage and so based on maintaining hazard rate …

The Role Of Pre-Existing Type 2 Diabetes Mellitus In Colorectal Cancer Stage And Survival In Elderly Americans: A Seer-Medicare Population-Based Study 2002-~2011, Sanae El Ibrahimi

UNLV Theses, Dissertations, Professional Papers, and Capstones

Diabetes is a common comorbid condition among colorectal cancer (CRC) patients, yet its effects in CRC outcomes, particularly stage at diagnosis, risk of death and variations by diabetes severity (complications vs no complications) and Hispanic ethnicity have not been adequately studied. The purpose of this study was to investigate the association between pre-existing T2DM and advanced stage at diagnosis in elderly patients with CRC; to examine whether diabetes is an independent predictor of poor survival from all-cause and CRC-specific mortality; to assess whether variations exist by diabetes severity and to analyze the outcomes for the Hispanic group.

The Surveillance Epidemiology …

Comparison Of Survival Curves Between Cox Proportional Hazards, Random Forests, And Conditional Inference Forests In Survival Analysis, Brandon Weathers

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Survival analysis methods are a mainstay of the biomedical fields but are finding increasing use in other disciplines including finance and engineering. A widely used tool in survival analysis is the Cox proportional hazards regression model. For this model, all the predicted survivor curves have the same basic shape, which may not be a good approximation to reality. In contrast the Random Survival Forests does not make the proportional hazards assumption and has the flexibility to model survivor curves that are of quite different shapes for different groups of subjects. We applied both techniques to a number of publicly available …

Mediation Analysis For A Survival Outcome With Time-Varying Exposures, Mediators, And Confounders, Sheng-Hsuan Lin, Jessica G. Young, Roger Logan, Tyler J. Vanderweele

Harvard University Biostatistics Working Paper Series

We propose an approach to conduct mediation analysis for survival data with time-varying exposures, mediators, and confounders. We identify certain interventional direct and indirect effects through a survival mediational g-formula and describe the required assumptions. We also provide a feasible parametric approach along with an algorithm and software to estimate these effects. We apply this method to analyze the Framingham Heart Study data to investigate the causal mechanism of smoking on mortality through coronary artery disease. The risk ratio of smoking 30 cigarettes per day for ten years compared with no smoking on mortality is 2.34 (95 % CI = …

Joint Modelling In Liver Transplantation, Elizabeth M. Renouf

Electronic Thesis and Dissertation Repository

In the setting of liver transplantation, clinical trials and transplant registries regularly collect repeated measurements of clinical biomarkers which may be strongly associated with a time-to-event such as graft failure or disease recurrence. Multiple time-to-event outcomes are routinely collected. However, joint models are rarely used. This thesis will describe important considerations for joint modelling in the setting of liver transplantation. We will focus on transplant registry data from the United States. We develop a new tool for joint modelling in the context where a critical health event can be tracked in the longitudinal biomarker and often presents as a non-linear …

Identification Of Biomarkers For The Overall Survival Of Ovarian Cancer Patients, Kristi Mai

Graduate Theses and Dissertations

Rapid advance in sequencing technology has led to genome-wide analysis of genetic and epigenetic features simultaneously, making it possible to understand the biological mechanisms underlying cancer initiation and progression. However, how to identify important prognostic features poses a great challenge for both statistical modeling and computing. In this thesis, a network-based approach is applied to the Cancer Genome Atlas (TCGA) ovarian cancer data to identify important genes related to the overall survival of ovarian cancer patients. In the first step, a stepwise correlation-based selector is used to reduce the dimensionality of TCGA data, by filtering out a large number of …

Some Contributions To Nonparametric And Semiparametric Inference For Clustered And Multistate Data., Sandipan Dutta

Electronic Theses and Dissertations

This dissertation is composed of research projects that involve methods which can be broadly classified as either nonparametric or semiparametric. Chapter 1 provides an introduction of the problems addressed in these projects, a brief review of the related works that have done so far, and an outline of the methods developed in this dissertation. Chapter 2 describes in details the first project which aims at developing a rank-sum test for clustered data where an outcome from group in a cluster is associated with the number of observations belonging to that group in that cluster. Chapter 3 proposes the use of …

The Impact Of Hair Coat Color On Longevity Of Holstein Cows In The Tropics, C. N. Lee, K. S. Baek, A. Parkhurst

Department of Statistics: Faculty Publications

Background: Over two decades of observations in the field in South East Asia and Hawai‘i suggest that majority of the commercial dairy herds are of black hair coat. Hence a simple study to determine the accuracy of the observation was conducted with two large dairy herds in Hawaii in the mid-1990s.

Methods: A retrospective study on longevity of Holstein cattle in the tropics was conducted using DairyComp-305 lactation information coupled with phenotypic evaluation of hair coat color in two large dairy farms. Cows were classified into 3 groups: a) black (B, >90%); b) black/white (BW, 50:50) and c) white (W, …

Double Bootstrap Confidence Interval Estimates With Censored And Truncated Data, Jayanthi Arasan, Mohd B. Adam

Journal of Modern Applied Statistical Methods

Traditional inferential procedures often fail with censored and truncated data, especially when sample sizes are small. In this paper we evaluate the performances of the double and single bootstrap interval estimates by comparing the double percentile (DB-p), double percentile-t (DB-t), single percentile (B-p), and percentile-t (B-t) bootstrap interval estimation methods via a coverage probability study when the data is censored using the log logistic model. We then apply the double bootstrap intervals to real right censored lifetime data on 32 women with breast cancer and failure data on 98 brake pads where all the observations were left truncated.

Causal Mediation In A Survival Setting With Time-Dependent Mediators, Wenjing Zheng, Mark J. Van Der Laan

Wenjing Zheng

The effect of an expsore on an outcome of interest is often mediated by intermediate variables. The goal of causal mediation analysis is to evaluate the role of these intermediate variables (mediators) in the causal effect of the exposure on the outcome. In this paper, we consider causal mediation of a baseline exposure on a survival (or time-to-event) outcome, when the mediator is time-dependent. The challenge in this setting lies in that the event process takes places jointly with the mediator process; in particular, the length of the mediator history depends on the survival time. As a result, we argue …

Optimization In Non-Parametric Survival Analysis And Climate Change Modeling, Iuliana Teodorescu

USF Tampa Graduate Theses and Dissertations

Many of the open problems of current interest in probability and statistics involve complicated data

sets that do not satisfy the strong assumptions of being independent and identically distributed. Often,

the samples are known only empirically, and making assumptions about underlying parametric

distributions is not warranted by the insufficient information available. Under such circumstances,

the usual Fisher or parametric Bayes approaches cannot be used to model the data or make predictions.

However, this situation is quite often encountered in some of the main challenges facing statistical,

data-driven studies of climate change, clinical studies, or financial markets, to name a few. …

Causal Mediation In A Survival Setting With Time-Dependent Mediators, Wenjing Zheng, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

The effect of an expsore on an outcome of interest is often mediated by intermediate variables. The goal of causal mediation analysis is to evaluate the role of these intermediate variables (mediators) in the causal effect of the exposure on the outcome. In this paper, we consider causal mediation of a baseline exposure on a survival (or time-to-event) outcome, when the mediator is time-dependent. The challenge in this setting lies in that the event process takes places jointly with the mediator process; in particular, the length of the mediator history depends on the survival time. As a result, we argue …

An Essay On The Nature And Significance Of Deception And Telling Lies, Sudhanshu K. Mishra

Sudhanshu K Mishra

A lie is an expression at deviance with the truth known or honestly believed by someone with an intention to deceive others for certain purpose, social or personal. An ability to lie might be evolutionary in nature possibly to help in survival, since it is found in the non-human world also. In the biological perspective, each individual is at war against all others. Thus viewed, lies are the cardinal virtues for survival and, by implication, the carriers of evolution. In the human world, lying is morally blameworthy in a relatively un-obscure way. There may be cases of lying to which …

Linear Dependency For The Difference In Exponential Regression, Indika Sathish, Norou Diawara

Mathematics & Statistics Faculty Publications

In the field of reliability, a lot has been written on the analysis of phenomena that are related. Estimation of the difference of two population means have been mostly formulated under the no-correlation assumption. However, in many situations, there is a correlation involved. This paper addresses this issue. A sequential estimation method for linearly related lifetime distributions is presented. Estimations for the scale parameters of the exponential distribution are given under square error loss using a sequential prediction method. Optimal stopping rules are discussed using concepts of mean criteria, and numerical results are presented.

Separate And Joint Analysis Of Longitudinal And Survival Data, Deepthi Rajeev

Theses and Dissertations

Chemotherapy is a method used to treat cancer but it has a number of side-effects. Research conducted by the Department of Chemical Engineering at BYU involves a new method of administering chemotherapy using ultrasound waves and water-soluble capsules. The goal is to reduce the side-effects by localizing the delivery of the medication. As part of this research, a two-factor experiment was conducted on rats to test if the water-soluble capsules and ultrasound waves by themselves have an effect on tumor growth or patient survival. Our project emphasizes the usage of Bayesian Hierarchical Models and Win-BUGS to jointly model the survival …

Modeling The Effect Of Alzheimer's Disease On Mortality, Elizabeth Johnson, Ron Brookmeyer, Kathryn Ziegler-Graham

Ron Brookmeyer

Mortality rate ratios and the associated proportional hazards models have been used to summarize the effect of Alzheimer's disease on longevity. However, the mortality rate ratios vary by age and therefore do not provide a simple parsimonious summary of the effect of the disease on lifespan. Instead, we propose a new parameter that is defined by an additive multistate model. The proposed multistate model accounts for different stages of disease progression. The underlying assumption of the model is that the effect of disease on mortality is to add a constant amount to death rates once the disease progresses from an …

On Corrected Score Approach For Proportional Hazards Model With Covariate Measurement Error, Xiao Song, Yijian Huang

UW Biostatistics Working Paper Series

In the presence of covariate measurement error with the proportional hazards model, several functional modeling methods have been proposed. These include the conditional score estimator (Tsiatis and Davidian, 2001), the parametric correction estimator (Nakamura, 1992) and the nonparametric correction estimator (Huang and Wang, 2000, 2003) in the order of weaker assumptions on the error. Although they are all consistent, each suffers from potential difficulties with small samples and substantial measurement error. In this article, upon noting that the conditional score and parametric correction estimators are asymptotically equivalent in the case of normal error, we investigate their relative finite sample performance …

A Corrected Pseudo-Score Approach For Additive Hazards Model With Longitudinal Covariates Measured With Error, Xiao Song, Yijian Huang

UW Biostatistics Working Paper Series

In medical studies, it is often of interest to characterize the relationship between a time-to-event and covariates, not only time-independent but also time-dependent. Time-dependent covariates are generally measured intermittently and with error. Recent interests focus on the proportional hazards framework, with longitudinal data jointly modeled through a mixed effects model. However, approaches under this framework depend on the normality assumption of the error, and might encounter intractable numerical difficulties in practice. This motivates us to consider an alternative framework, that is, the additive hazards model, under which little has been done when time-dependent covariates are measured with error. We propose …

Accelerated Hazards Model: Method, Theory And Applications, Ying Qing Chen, Nicholas P. Jewell, Jingrong Yang

U.C. Berkeley Division of Biostatistics Working Paper Series

In an accelerated hazards model, the hazard functions of a failure time are related through the time scale-change, which is often a function of covariates and associated parameters. When the hazard functions have special properties, such as monotonicity in time, the parameters may be clinically meaningful in measuring a treatment effect. This paper reviews methodological and theoretical development of this model. Applications of the accelerated hazards model including sample size calculation in clinical trials, are also explored.

Probabilities Of Transition Among Health States For Older Adults, Paula Diehr, Donald L. Patrick

UW Biostatistics Working Paper Series

Goal: To estimate the probabilities of transition among self-rated health states for older adults, and examine how they vary by age and sex. Methods: We used self-rated health (Excellent, Very Good, Good, Fair, Poor, Dead) collected in two longitudinal studies of older adults (Mean age 75) to estimate the probability of transition in two years. We used the estimates to project future health for selected cohorts.

Findings: These older adults were most likely to be in the same health state 2 years later, but a substantial proportion changed in both directions. Transition probabilities varied by initial health state, age and …

Breeding And Genetics 5: Survival Analysis/Threshold Models, Applications In Survival Analysis, Stephen D. Kachman

Department of Statistics: Faculty Publications

Survival or failure time traits such as herd life and days open are both important economically and pose a number of challenges to an analysis based on linear mixed models. The main features of a survival trait are that it is the time until some event occurs, and some of the observations are censored. Survival models and the associated estimation procedures provide a flexible means of modeling survival traits. In this paper I will discuss the application of survival analysis based on the Weibull distribution. The components that make up a survival model will be presented along with their interpretation. …