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ENAR 2018 Spring Meeting ABSTRACTS & POSTER ENAR 2018 Spring Meeting ABSTRACTS & POSTER PRESENTATIONS 1b. EVALUATING ALTERNATIVE APPROACHES 1. POSTERS: BIOMARKERS TO BOOTSTRAP ESTIMATION PROCEDURES IN TWO-STAGE GROUP 1a. P-VALUE EVALUATION, VARIABILITY INDEX SEQUENTIAL DESIGNS AND BIOMARKER CATEGORIZATION FOR ADAPTIVELY WEIGHTED FISHER’S Sara Biesiadny*, Rice University META-ANALYSIS METHOD IN OMICS Nabihah Tayob, University of Texas MD Anderson APPLICATIONS Cancer Center Zhiguang Huo Huo*, University of Florida Two-stage group sequential designs with early termination Shaowu Tang, Roche Molecular Systems, Inc. for futility are important and widely used in EDRN Phase 2 and 3 biomarker studies since they allow us to conserve Yongseok Park, University of Florida valuable sample specimens in the case of inadequate bio- marker performance. Obtaining unbiased estimates using George Tseng, University of Pittsburgh all the available data in completed studies is not trivial. We K independent studies and to provide better biological have previously developed a nonparametric conditional interpretation by characterizing which studies contribute resampling algorithm to unbiasedly estimate both the to meta-analysis. Currently, AW-Fisher suffers from lack of combination rule and performance of a biomarker panel in a fast, accurate p-value computation and variability estimate two-stage group sequential design. Here we explore alterna- of AW weights. When the number of studies K is large, tive approaches to the computationally intensive bootstrap the 3K - 1 possible differential expression pattern cate- procedure to obtain estimates of the distributions of our gories can become intractable. In this paper, we apply an proposed estimators. This will allow us to utilize simulation importance sampling technique with spline interpolation to studies to explore the operating characteristics and identify increase accuracy and speed of p-value calculation. Using optimal designs for evaluating a biomarker panel in a study resampling techniques, we propose a variability index for that includes an interim analysis with termination for futility. the AW weight estimator and a co-membership matrix [email protected] to characterize pattern similarities between genes. The co-membership matrix is further used to categorize differ- entially expressed genes based on their meta-patterns for 1c. NOVEL QUANTILE APPROACH FOR THE further biological investigation. The superior performance IDENTIFICATION OF BIOMARKERS of the proposed methods is shown in simulations. These ASSOCIATED WITH TYPE II DIABETES methods are also applied to two real applications to demon- USING NHANES DATABASE strate intriguing biological findings. Hanying Yan*, Columbia University [email protected] Ying Li, IBM T. J. Watson Research Center Xiaoyu Song, Icahn School of Medicine at Mount Sanai Discovering new uses for approved drugs to provide pos- sible transition from bench to bedside is a crucial strategy to reduce time and cost and improve success rate for drug development. The investigation of hidden connections HYATT REGENCY ATLANTA ON PEACHTREE ST | ATLANTA, GA 115 ENAR 2018 Spring Meeting ABSTRACT & POSTER PRESENTATIONS between diseases and biomarkers is a critical step to as a set of structural causal equations with mixed effects. facilitate such drug repurposing research. Existing studies The directed edges between nodes depend on observed have leveraged the valuable resource of National Health covariates on each of the individual and unobserved latent and Nutrition Examination Survey (NHANES) but only variables. The strength of the connection is decomposed considered traditional statistical approaches such as linear into a fixed-effect term representing the average causal models and correlation analyses. In this study, we propose effect given the covariates and a random effect term repre- a robust quantile rank-score based approach (QRank) to senting the latent causal effect due to unobserved pathways. incorporate the features of complex survey data (multistage We propose a penalized likelihood-based approach to han- stratified, cluster-sampled and unequally weighted sampling dle high dimensionality of the DAG model. We theoretically scheme). The novel QRank approach is able to identify prove the identifiability of mSEM. Extensive simulations biomarkers with entire distribution differentially affected and an application to protein signaling data show that the by diabetes status. We applied this approach to NHANES true causal relationships can be recovered from interven- 2013-2014 dataset and identified more potential biomarkers tional data. We also identify gray matter atrophy networks in which were more likely to be validated in two independent regions of brain from patients with Huntington’s disease. NHANES datasets (2009-2010 and 2011-2012). It suggests that our QRank approach is promising for survey study and [email protected] the analysis of drug repurposing. 1e. A REGRESSION-BASED APPROACH [email protected] INCORPORATING PATIENTS’ CHARACTERISTICS TO OPTIMIZE 1d. LEARNING SUBJECT-SPECIFIC DIRECTED CONTINUOUS DIAGNOSTIC ACYCLIC GRAPHS (DAGS) FROM HIGH- MARKER CUTOFF DIMENSIONAL BIOMARKER DATA Yan Li*, University of Minnesota Shanghong Xie*, Columbia University Chap T. Le, University of Minnesota Xiang Li, Janssen Research & Development, LLC Many diagnostic markers are either continuous/on an Peter McColgan, UCL Institute of Neurology, London ordinal scale. It is important to dichotomize such markers at an optimum cut-point in order to accurately categorize Sarah J. Tabrizi, UCL Institute of Neurology, London subjects as diseased or healthy. Le (2006) proposed such a and National Hospital for Neurology and Neurosurgery, method by maximizing the Youden’s Index, which integrates London both sensitivity and specificity. However, that approach only Rachael I. Scahill, UCL Institute of Neurology, London consider the relationship between the continuous marker and the disease status, leaving out the subjects’ char- Donglin Zeng, University of North Carolina, Chapel Hill acteristics, which could greatly affect diagnostic-marker Yuanjia Wang, Columbia University cutoff optimization. Here we propose a regression-based model that takes account of patients’ characteristics in the The identification of causal relationships between random dichotomization of the continuous diagnostic biomarker. variables from large-scale observational data using directed By analyzing a prostate cancer dataset, we found that the acyclic graphs (DAG) is highly challenging. We propose optimal cut-point for acid phosphatase level changes along a new mixed-effects structural equation model (mSEM) with subjects’ characteristics, including age, cancer stage, framework to estimate subject-specific DAGs, where we represent joint distribution of random variables in the DAG 116 ENAR 2018 PRELIMINARY PROGRAM | MARCH 25-28, 2018 | *Presenter | • Student Award Winner ENAR 2018 Spring Meeting ABSTRACT & POSTER PRESENTATIONS disease grade, and X ray status in the diagnosis of nodal cutoff exploration (for continuous biomarker), subgroup involvement. A comprehensive evaluation using all patients’ analysis, ROC analysis, and longitudinal analysis. characteristics in the dichotomizing efforts will be very informative and efficient for clinical research at the era of [email protected] individualized medicine. [email protected] 2. POSTERS: LONGITUDINAL DATA ANALYSIS 1f. gClinBiomarker: AN R PACKAGE FOR CLINICAL BIOMARKER ANALYSES, 2a. PENALIZED SMOOTHING SPLINES IN ALONG WITH “ONE-CLICK” REPORT ADOLESCENT GROWTH STUDIES GENERATING TEMPLATES Justin M. Leach*, University of Alabama at Birmingham Ning Leng*, Genentech Inmaculada Aban, University of Alabama at Birmingham Alexey Pronin, Genentech Adolescent patients with Sickle Cell Anemia (SCA) may Christina Rabe, Genentech demonstrate impaired growth. To better understand the Doug Kelkhoff, Genentech impact of transfusion, hydroxyurea, or no modifying therapy on growth, we retrospectively analyzed the growth patterns Kwame Okrah, Genentech over 18 years for a large cohort of patients from one insti- tution with HbSS or SB0 thalassemia. Employing mixed Jane Fridlyand, Genentech models can account for within subject correlation in longi- Zhuoye Xu, Genentech tudinal data analyses, but cases with nonlinear relationships require the assumption of a functional form to have valid Imola Fodor, Genentech inferences. In modeling the relationship between age and Recent development of high throughput technology provides growth, a quadratic fit outperforms a linear fit, but is both unprecedented power in discovering clinical biomarkers biologically implausible and a poor fit to the data. Fitting from retrospective analyses. However, these data-driven penalized splines to within subject data with the R package analyses can also introduce statistical caveats, which may fda allows for flexible and more reasonable estimates of diminish a biomarker’s reproducibility in future trials. A growth trajectories. We then chose discrete points from number of statistical analyses had been used to sophis- the fitted curves and used the mixed model with age as a tically evaluate those potential caveats. We developed an categorical variable to avoid further functional assumptions R package gClinBiomarker, which allows users to easily and simplify computation. Alternatively, one may incorpo- perform such analyses and generate high-quality figures rate a functional form into the within-subject portion of the and tables. The gClinBiomarker
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