Biostatistics Commons^™

Meta-Analysis Of Genome-Wide Association Studies With Correlated Individuals: Application To The Hispanic Community Health Study/Study Of Latinos (Hchs/Sol), Tamar Sofer, John R. Shaffer, Misa Graff, Qibin Qi, Adrienne M. Stilp, Stephanie M. Gogarten, Kari E. North, Carmen R. Isasi, Cathy C. Laurie, Adam A. Szpiro

UW Biostatistics Working Paper Series

Investigators often meta-analyze multiple genome-wide association studies (GWASs) to increase the power to detect associations of single nucleotide polymorphisms (SNPs) with a trait. Meta-analysis is also performed within a single cohort that is stratified by, e.g., sex or ancestry group. Having correlated individuals among the strata may complicate meta-analyses, limit power, and inflate Type 1 error. For example, in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), sources of correlation include genetic relatedness, shared household, and shared community. We propose a novel mixed-effect model for meta-analysis, “MetaCor", which accounts for correlation between stratum-specific effect estimates. Simulations show that MetaCor controls …

Nested Partially-Latent, Class Models For Dependent Binary Data, Estimating Disease Etiology, Zhenke Wu, Maria Deloria-Knoll, Scott L. Zeger

Johns Hopkins University, Dept. of Biostatistics Working Papers

The Pneumonia Etiology Research for Child Health (PERCH) study seeks to use modern measurement technology to infer the causes of pneumonia for which gold-standard evidence is unavailable. The paper describes a latent variable model designed to infer from case-control data the etiology distribution for the population of cases, and for an individual case given his or her measurements. We assume each observation is drawn from a mixture model for which each component represents one cause or disease class. The model addresses a major limitation of the traditional latent class approach by taking account of residual dependence among multivariate binary outcome …

Identification And Survival Outcomes Of A Cohort Of Patients With Cancer Of Unknown Primary In Ontario, Canada., Chong S Kim, Malek B Hannouf, Sisira Sarma, George B Rodrigues, Peter K Rogan, Salaheddin M Mahmud, Eric Winquist, Muriel Brackstone, Gregory S Zaric

Epidemiology and Biostatistics Publications

BACKGROUND: Cancer of unknown primary origin (CUP) is defined by the presence of pathologically identified metastatic disease without clinical or radiological evidence of a primary tumour. Our objective was to identify incident cases of CUP in Ontario, Canada, and determine the influence of histology and sites of metastases on overall survival (OS).

MATERIAL AND METHODS: We used the Ontario Cancer Registry (OCR) and the Same-Day Surgery and Discharge Abstract Database (SDS/DAD) to identify patients diagnosed with CUP in Ontario between 1 January 2000, and 31 December 2005. Patient diagnostic information, including histology and survival data, was obtained from the OCR. …

Abcc9/Sur2 In The Brain: Implications For Hippocampal Sclerosis Of Aging And A Potential Therapeutic Target, Peter T. Nelson, Gregory A. Jicha, Wang-Xia Wang, Eseosa T. Ighodaro, Sergey C. Artiushin, Colin G. Nichols, David W. Fardo

Sanders-Brown Center on Aging Faculty Publications

The ABCC9 gene and its polypeptide product, SUR2, are increasingly implicated in human neurologic disease, including prevalent diseases of the aged brain. SUR2 proteins are a component of the ATP-sensitive potassium (“K _ATP ”) channel, a metabolic sensor for stress and/or hypoxia that has been shown to change in aging. The K _ATP channel also helps regulate the neurovascular unit. Most brain cell types express SUR2, including neurons, astrocytes, oligodendrocytes, microglia, vascular smooth muscle, pericytes, and endothelial cells. Thus it is not surprising that ABCC9 gene variants are associated with risk for human brain diseases. For example, Cantu syndrome is …

Removing Inter-Subject Technical Variability In Magnetic Resonance Imaging Studies, Jean-Philippe Fortin, Elizabeth M. Sweeney, John Muschelli, Ciprian M. Crainiceanu, Russell T. Shinohara, Alzheimer’S Disease Neuroimaging Initiative

UPenn Biostatistics Working Papers

Magnetic resonance imaging (MRI) intensities are acquired in arbitrary units, making scans non-comparable across sites and between subjects. Intensity normalization is a first step for the improvement of comparability of the images across subjects. However, we show that unwanted inter-scan variability associated with imaging site, scanner effect and other technical artifacts is still present after standard intensity normalization in large multi-site neuroimaging studies. We propose RAVEL (Removal of Artificial Voxel Effect by Linear regression), a tool to remove residual technical variability after intensity normalization. As proposed by SVA and RUV [Leek and Storey, 2007, …

Functional Linear Models Extensions Uncover Pleiotropic Effects Of Chronic Pain Phenotypes, Dmitri V. Zaykin, L. Qing, G. D. Slade, R. Dubner, R. B. Fillingim, J. D. Greenspan, R. Ohrbach, W. Maixner, L. B. Diatchenko, Olga A. Vsevolozhskaya

Biostatistics Presentations

Growing scientific evidence suggests that intricate interactions of genetic risk factors with environmental exposures play a major role in the development of chronic pain conditions. In studies of relative contribution of an individual’s genetic composition to the perception of pain, the general characteristics of pain sensitivity are typically measured by a wide range of different, yet possibly etiologically related pain phenotypes. Testing each of these pain-perception traits individually is subject to problems of multiple testing and low statistical power. Furthermore, pain-related traits may share common etiology and comprise binary, categorical, and quantitative measurements. In the current study, we propose a …

Validation Of A New Predictive Risk Model: Measuring The Impact Of The Major Modifiable Risks Of Death For Patients And Populations, Stephen S. Lim, Emily Carnahan, Eugene C. Nelson, Catherine W. Gillespie, Ali H. Mokdad, Christopher J. L. Murray, Elliott S. Fisher

Dartmouth Scholarship

Background: Modifiable risks account for a large fraction of disease and death, but clinicians and patients lack tools to identify high risk populations or compare the possible benefit of different interventions.

Methods: We used data on the distribution of exposure to 12 major behavioral and biometric risk factors inthe US population, mortality rates by cause, and estimates of the proportional hazards of risk factor exposure from published systematic reviews to develop a risk prediction model that estimates an adult's 10 year mortality risk compared to a population with optimum risk factors. We compared predicted risk to observed mortality in 8,241 …

Patient-Specific Variations In Biomarkers Across Gingivitis And Periodontitis, Radhakrishnan Nagarajan, Craig S. Miller, Dolph Dawson, Mohanad Al-Sabbagh, J. L. Ebersole

Biostatistics Faculty Publications

This study investigates the use of saliva, as an emerging diagnostic fluid in conjunction with classification techniques to discern biological heterogeneity in clinically labelled gingivitis and periodontitis subjects (80 subjects; 40/group) A battery of classification techniques were investigated as traditional single classifier systems as well as within a novel selective voting ensemble classification approach (SVA) framework. Unlike traditional single classifiers, SVA is shown to reveal patient-specific variations within disease groups, which may be important for identifying proclivity to disease progression or disease stability. Salivary expression profiles of IL-1ß, IL-6, MMP-8, and MIP-1α from 80 patients were analyzed using four classification …

Addressing Confounding In Predictive Models With An Application To Neuroimaging, Kristin A. Linn, Bilwaj Gaonkar, Jimit Doshi, Christos Davatzikos, Russell T. Shinohara

UPenn Biostatistics Working Papers

Understanding structural changes in the brain that are caused by a particular disease is a major goal of neuroimaging research. Multivariate pattern analysis (MVPA) comprises a collection of tools that can be used to understand complex disease effects across the brain. We discuss several important issues that must be considered when analyzing data from neuroimaging studies using MVPA. In particular, we focus on the consequences of confounding by non-imaging variables such as age and sex on the results of MVPA. After reviewing current practice to address confounding in neuroimaging studies, we propose an alternative approach based on inverse probability weighting. …

Control-Group Feature Normalization For Multivariate Pattern Analysis Using The Support Vector Machine, Kristin A. Linn, Bilwaj Gaonkar, Jimit Doshi, Christos Davatzikos, Russell T. Shinohara

UPenn Biostatistics Working Papers

Normalization of feature vector values is a common practice in machine learning. Generally, each feature value is standardized to the unit hypercube or by normalizing to zero mean and unit variance. Classification decisions based on support vector machines (SVMs) or by other methods are sensitive to the specific normalization used on the features. In the context of multivariate pattern analysis using neuroimaging data, standardization effectively up- and down-weights features based on their individual variability. Since the standard approach uses the entire data set to guide the normalization it utilizes the total variability of these features. This total variation is inevitably …

A Simple Method To Estimate The Time-Dependent Roc Curve Under Right Censoring, Liang Li, Bo Hu, Tom Greene

COBRA Preprint Series

The time-dependent Receiver Operating Characteristic (ROC) curve is often used to study the diagnostic accuracy of a single continuous biomarker, measured at baseline, on the onset of a disease condition when the disease onset may occur at different times during the follow-up and hence may be right censored. Due to censoring, the true disease onset status prior to the pre-specified time horizon may be unknown on some patients, which causes difficulty in calculating the time-dependent sensitivity and specificity. We study a simple method that adjusts for censoring by weighting the censored data by the conditional probability of disease onset prior …

Bayesian Inference On Longitudinal Semi-Continuous Substance Abuse/Dependence Symptoms Data, Dongyuan Xing

USF Tampa Graduate Theses and Dissertations

Substance use data such as alcohol drinking often contain a high proportion of zeros. In studies examining the alcohol consumption in college students, for instance, many students may not drink in the studied period, resulting in a number of zeros. Zero-inflated continuous data, also called semi continuous data, typically consist of a mixture of a degenerate distribution at the origin (zero) and a right-skewed, continuous distribution for the positive values. Ignoring the extreme non-normality in semi-continuous data may lead to substantially biased estimates and inference. Longitudinal or repeated measures of semi-continuous data present special challenges in statistical inference because of …

On Varieties Of Doubly Robust Estimators Under Missing Not At Random With An Ancillary Variable, Wang Miao, Eric Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Pairwise Likelihood Augmented Estimator For The Cox Model Under Left-Truncation, Fan Wu, Sehee Kim, Jing Qin, Rajiv Saran, Yi Li

The University of Michigan Department of Biostatistics Working Paper Series

Survival data collected from prevalent cohorts are subject to left-truncation and the analysis is challenging. Conditional approaches for left-truncated data under the Cox model are inefficient as they typically ignore the information in the marginal likelihood of the truncation times. Length-biased sampling methods can improve the estimation efficiency but only when the stationarity assumption of the disease incidence holds, i.e., the truncation distribution is uniform; otherwise they may generate biased estimates. In this paper, we propose a semi-parametric method for the Cox model under general left-truncation, where the truncation distribution is unspecified. Our approach is to make inference based on …

On Partial Identification Of The Pure Direct Effect, Caleb Miles, Phyllis Kanki, Seema Meloni, Eric Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.

Preparedness Of Hospitals In The Republic Of Ireland For An Influenza Pandemic, An Infection Control Perspective, Mary Reidy, Fiona Ryan, Dervla Hogan, Seán Lacey, Claire Buckley

Department of Mathematics Publications

When an influenza pandemic occurs most of the population is susceptible and attack rates can range as high as 40–50 %. The most important failure in pandemic planning is the lack of standards or guidelines regarding what it means to be ‘prepared’. The aim of this study was to assess the preparedness of acute hospitals in the Republic of Ireland for an influenza pandemic from an infection control perspective.

Novel Human Abcc9/Sur2 Brain-Expressed Transcripts And An Eqtl Relevant To Hippocampal Sclerosis Of Aging, Peter T. Nelson, Wang-Xia Wang, Bernard R. Wilfred, Angela Wei, James Dimayuga, Qingwei Huang, Eseosa T. Ighodaro, Sergey C. Artiushin, David W. Fardo

Sanders-Brown Center on Aging Faculty Publications

ABCC9 genetic polymorphisms are associated with increased risk for various human diseases including hippocampal sclerosis of aging. The main goals of this study were 1 > to detect the ABCC9 variants and define the specific 3′ untranslated region (3′UTR) for each variant in human brain, and 2 > to determine whether a polymorphism (rs704180) associated with risk for hippocampal sclerosis of aging pathology is also associated with variation in ABCC9 transcript expression and/or splicing. Rapid amplification of ABCC9 cDNA ends (3′RACE) provided evidence of novel 3′ UTR portions of ABCC9 in human brain. In silico and experimental studies were performed focusing on …

Assessment Of Nutrition Information System Using Health Metrics Network Framework, Mochamad Iqbal Nurmansyah, Catur Rosidati, Riastuti Kusuma Wardani, Badra Al-Aufa

Kesmas

Sistem informasi gizi (Sigizi) dikembangkan oleh Direktorat Bina Gizi Kementerian Kesehatan sejak 2011. Data Sigizi mencakup data penimbangan balita di posyandu, kasus gizi buruk, cakupan pemberian tablet Fe pada ibu hamil, konsumsi garam beryodium, pemberian vitamin A, dan ASI eksklusif. Penelitian ini bertujuan untuk mengukur kinerja pengelolaan Sigizi di Dinas Kesehatan Kota Tangerang Selatan menggunakan kerangka Health Metrics Network yang dikeluarkan oleh WHO tahun 2008. Sigizi merupakan sistem informasi yang diaplikasikan pada tingkat nasional dengan mekanisme pelaporan berjenjang, dari 508 kabupaten/kota menuju 34 provinsi dan bermuara di tingkat nasional. Di Provinsi Banten, terdapat delapan kabupaten/kota yang menjalankan Sigizi. Informan penelitian …

Sociodemographic Factors To Dengue Hemmorrhagic Fever Case In Indonesia, Desy Nuryunarsih

Kesmas

Demam berdarah dengue (DBD) adalah penyebab utama rawat inap dan kematian pada anak-anak. Indonesia adalah salah satu negara yang oleh WHO dikategorikan hyperendemicity dengan empat serotipe virus tersebar di daerah perkotaan. Faktor sosiodemografi dianggap sebagai faktor pendukung terjadinya DBD di Indonesia. Studi ini menggunakan data sekunder yang diunduh dari Basis Data Kesehatan Provinsi tahun 2010 Kementerian Kesehatan Republik Indonesia untuk menentukan korelasi antara ketiga faktor sosiodemografi dengan insiden DBD. Penelitian ini menggunakan metode kuantitatif deskripsi korelasi. Hasil penelitian menunjukkan bahwa dua faktor sosiodemografi terpilih memiliki korelasi linier dengan insiden DBD. Analisa regresi multivariat menunjukkan kecilnya korelasi antara insiden DBD dengan …

Penerapan Sistem Remunerasi Dan Kinerja Pelayanan, Tri Wisesa Soetisna, Dumilah Ayuningtyas, Misnaniarti Misnaniarti

Kesmas

Remuneration can influence worker`s motivation, and improve their performance. Likewise in hospital as capital-intensive, human resources-intensive as well as knowledge and technology-intensive health care institution. This study aimed to analyze employee’s perception of remuneration system implementation and adult cardiac surgery services unit’s performance at hospital. This study used a mixed method approach (quantitative and qualitative). Quantitative study design was cross-sectional using questionnaire for self-assesment. Meanwhile, qualitative study design was descriptive conducted through focus group discussion and document review on data in forms of schedule book, registration book, nursing notes and medical records. Data collection was conducted in 2013 at one …