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  • A Condensed Training for the Rate Stabilizing Tool

    Contains 4 Component(s) Recorded On: 04/21/2021

    The Rate Stabilizing Tool (RST) is an ArcGIS-based tool that allows users to input their own record-level data to generate reliable, local-level age-standardized measures of chronic disease (e.g., prevalence, incidence, and mortality), or other population health outcomes. Bayesian modelling techniques are used to generate population health estimates and enable users to evaluate statistical uncertainty in the estimates. The RST is especially useful for estimating population health measures when the population, or number of events is small. More information on the RST can be found here: https://www.cdc.gov/dhdsp/maps/gisx/rst.html

    The Rate Stabilizing Tool (RST) is an ArcGIS-based tool that allows users to input their own record-level data to generate reliable, local-level age-standardized measures of chronic disease (e.g., prevalence, incidence, and mortality), or other population health outcomes. 

    Bayesian modelling techniques are used to generate population health estimates and enable users to evaluate statistical uncertainty in the estimates. The RST is especially useful for estimating population health measures when the population, or number of events is small. 
    More information on the RST can be found here: https://www.cdc.gov/dhdsp/maps/gisx/rst.html  

    We plan to provide a two part RST training for the April 21st and April 28th NAACCR Talks. During the training we will discuss the objectives and rationale of the RST, review data parameters that are important for use with the RST, and provide opportunities for participants to engage directly with RST.

     

    Session 1: During this first session we will delve into the RST with a focus on inputting local level data into the RST.

    Learning Objectives:

    Introduce the Rate Stabilizing Tool (RST)

    Understand the inputs and outputs of the RST

    Gain experience downloading and installing and running the RST in ArcGIS Pro and or ArcMap

     

    Session 2: In this second session we will review the RST’s output, including how to map and interpret the results. We will also explore strategies for fine tuning. 

    Learning Objectives:

    Develop an understanding of the RST outputs

    Discuss and interpret the RST output, including the evaluation of rate differences and reliability

    Gain experience mapping the RST and symbolizing output

    Joshua Tootoo

    Director

    Geospatial Sciences for the Children's Environmental Health Initiative (CEHI)

    Joshua Tootoo serves as the Director of Training and Geospatial Sciences for the Children’s Environmental Health Initiative (CEHI). HIs research interests include: the application of administrative datasets into analyses examining environmentally driven health disparities; informal project based approaches to education and training for public health/environmental professionals; and the communication of complex data analyses and explanatory narratives to the public, and policy makers through visualization.

    Adam Vaughan

    Epidemiologist

    CDC Division for Heart Disease and Stroke Prevention

    Adam Vaughan is an epidemiologist in CDC’s Division for Heart Disease and Stroke Prevention. His work focuses on generating and analyzing cardiovascular disease death rates and trends at the local level. He is also interested in ensuring that health departments and communities have access to the data they need to address the rising burden of cardiovascular disease.

     

  • Cancer Surveillance Using R: An Introduction

    Contains 1 Component(s)

    R is a free and open source statistical programming language that has now surpassed in popularity all commercial equivalents. However, its use in cancer surveillance has still been limited. This course will provide a gentle introduction to R and its application to cancer surveillance, including reading in data, data cleaning, rate calculation, and producing graphics. The second part of the course will use passenger and crew data from the Titanic disaster to illustrate the concept of predictive modeling.

    Date: Friday June 11, 2021

    Time: 9:00am-4:15pm ET

    Price: Members $145 Non-Members $200

    To purchase and register: https://netforumpro.com/IntrotoR

    R is a free and open source statistical programming language that has now surpassed in popularity all commercial equivalents. However, its use in cancer surveillance has still been limited. This course will provide a gentle introduction to R and its application to cancer surveillance, including reading in data, data cleaning, rate calculation, and producing graphics. The second part of the course will use passenger and crew data from the Titanic disaster to illustrate the concept of predictive modeling.   

    Course Objectives
    • Gain a basic understanding of the free and open source R programming language
    • Gain a basic understanding of RStudio, a widely-used graphical user interface for R
    • Learn how to read in external data, such as output from SEER*Stat, and perform what is known as data wrangling: filter by specific rows and columns, manage missing data, group data into categories, handle outliers, and so on.
    • Perform typical
    • Produce simple graphics
    • Use R to build a predictive model, using the engaging example of the Titanic passengers and crew.

    Requirements
    Participants should have both R and Rstudio pre-installed on a desktop or laptop computer. Instructions for installing this software will be provided a few weeks before the course date.  Participants should have a basic familiarity with Windows or Mac OS, including how to install new software and the file and folder structure each uses. No prior programming experience or statistical expertise is presumed.

    Content
    The essential minimum skills needed to begin using R back at the home office. These skills will be integrated into the two worked examples - first, reading in, wrangling, and displaying some cancer surveillance data, then using Titanic passenger data to build a simple predictive model.

  • Tools and Software to Automate and Normalize the Cancer Data Abstraction Workflow

    Contains 1 Component(s)

    This course will provide an introduction and demonstration of modern tools for extracting and harmonizing cancer patient data, including: 1) the National Cancer Institute (NCI)’s Observational Research in Oncology Toolbox; 2) the DeepPhe natural language processing (NLP) and visualization software and the related DeepPhe-CR cancer registry tools; 3) the NCI-DOE application programming interface (API); and 4) the HemOnc chemotherapy regimen ontology. Due to the virtual nature of the meeting, this course will be primarily didactic, with a demonstration and interactive session at the end.

    Date: June 18, 2021

    Time: 1:00pm-4:00pm ET

    Price: Members $95 Non-Members $130

    To Purchase and Register:https://netforumpro.com/Tools

    This course will provide an introduction and demonstration of modern tools for extracting and harmonizing cancer patient data, including: 1) the National Cancer Institute (NCI)’s Observational Research in Oncology Toolbox; 2) the DeepPhe natural language processing (NLP) and visualization software and the related DeepPhe-CR cancer registry tools; 3) the NCI-DOE application programming interface (API); and 4) the HemOnc chemotherapy regimen ontology. Due to the virtual nature of the meeting, this course will be primarily didactic, with a demonstration and interactive session at the end.

    Course Objectives
    Upon completion of this tutorial, attendees will be able to:  
    • Understand the tools available in the NCI’s Observational Research in Oncology Toolbox and consider how they might be incorporated into existing workflows.  
    • Appreciate how natural language processing tools such as DeepPhe can aid in the abstraction process.  
    • Appreciate the utility of APIs and how they may ease the data collection process.  
    • Develop an understanding of how formal ontologic modeling of chemotherapy regimen concepts can increase the utility of cancer registry information.
    • Understand how the DeepPhe-CR tools might be used to facilitate cancer registry abstraction efforts.

    Requirements
    There are no requirements for this workshop

    Content
    • The Cancer Medications Enquiry Database (CanMED)
    • The DeepPhe and DeepPhe-CR NLP tools
    • The NCI/DOE cancer NLP API
    • The HemOnc chemotherapy regimen vocabulary

  • Match*Pro Record Linkage Software

    Contains 1 Component(s)

    This course will provide instruction on the use of Match*Pro linkage software developed by IMS, Inc. Attendees will learn about probabilistic record linkage concepts, receive instruction on Match*Pro software functionality, perform test linkages and explore the system capabilities.

    Date: June 8 and 9, 2021

    Time: 1:00pm-5:00pm ET

    Price: Members $145 Non-Members $200

    To Purchase and Register: https://netforumpro.com/Match*Pro

    Course Objectives

    Ensure shared understanding of basic linkage concepts

    Provide instructional overview of Match*Pro functionality

    Give attendees hands-on experience working with test data 

    Increase knowledge of and familiarity with Match*Pro

    Requirements

    Participants should come to the workshop with the Match*Pro software pre-installed on their PC or laptop. It is highly recommended that participants have access to 2 monitors: 1 for displaying the instructor’s screen and another for the usage of Match*Pro. Course materials (slides, test data files, configuration files, etc.) will be provided to attendees prior to the workshop.

     Content

    We will provide some background information on probabilistic record linkage theory, conduct a hands-on exercise to teach users how they can utilize Match*Pro’s validation engine to improve the quality of their linkage data and explore the basic functionality and options that are available to users on the linkage configuration and linkage results screens with guided tours and hands-on exercises.  We will close out the session with a review of Match*Pro’s more advanced/niche features.  

  • Test - free webinars

    Contains 2 Component(s)

    test

    TEST

  • Sassafras! Reading and Writing NAACCR V21 XML using SAS

    Contains 2 Component(s) Recorded On: 03/24/2021

    NAACCR has for many years provided SAS tools to the cancer surveillance community for reading and writing NAACCR-standard flat files. With the switch in V21 to only XML format, the toolset needed an upgrade. This webinar will demonstrate how to read and write NAACCR V21 XML files using SAS. It is highly recommended for registry staff and others in the cancer surveillance community who want to interface with NAACCR V21 XML files using SAS.

    NAACCR has for many years provided SAS tools to the cancer surveillance community for reading and writing NAACCR-standard flat files. With the switch in V21 to only XML format, the toolset needed an upgrade. This webinar will demonstrate how to read and write NAACCR V21 XML files using SAS. It is highly recommended for registry staff and others in the cancer surveillance community who want to interface with NAACCR V21 XML files using SAS.

    Christopher Johnson, MPH

    Epidemiologist, Idaho SEER Principal Investigator

    Cancer Data Registry of Idaho

    Chris Johnson is an epidemiologist for the Cancer Data Registry of Idaho and the Principal Investigator for the Idaho SEER registry. He received a Masters of Public Health degree in biostatistics from the University of North Carolina. Mr. Johnson is a past NAACCR Board member and continues to be involved with several NAACCR work groups. A long-term SAS user, Chris has assisted NAACCR with creating SAS tools for reading and writing NAACCR files since way back in the flat file epoch.

  • Advanced Data Collection

    Contains 2 Component(s) Recorded On: 12/02/2020

    This NAACCR Talk is based on a concurrent session that had been planned for the in person 2020 NAACCR Annual Conference.

    This NAACCR Talk is based on a concurrent session that had been planned for the in person 2020 NAACCR Annual Conference.

    Valerie Yoder, BS

    Database Analyst

    Utah Cancer Registry

    Valerie Yoder has a Bachelor’s of Science in Computer Science with a focus on algorithms and data processing. She has worked in the Utah Cancer Registry Informatics department for five years processing, extracting, and analyzing data. She continuously explores process improvements and automation for registry operations and research and has successfully integrated several new and changing data sources. Previously, she worked for many years developing procedures to process and analyze pre-clinical medical imaging data with programming and scientific software.

    Carol Sweeney, PhD

    Director

    Utah Cancer Registry

    Carol Sweeney PhD is a cancer epidemiologist and Professor in the department of Internal Medicine at the University of Utah.  She has over 10 years experience teaching epidemiology and conducting cancer research as a university faculty member.  She has been a director at Utah Cancer Registry from 2014 to the present.

    Joseph Rogers, MS

    Team Lead for Informatics, Data

    Center for Disease Control and Prevention

    Joseph D. Rogers received his B.S. and M.S. in Biology/Chemistry and Information Management respectively from Arizona State University (ASU).  He worked in Arizona for the Maricopa County Health Department as a project manager and data analyst before joining CDC in 1991 (first as a contractor and then as a federal employee in 1997).  During Mr. Rogers’ contracting years at CDC, he worked as a systems analyst on information technology projects, as a project manager, and as a data manager within the National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP).  When Mr. Rogers joined the Centers for Disease Control and Prevention (CDC) as a federal employee, he initially worked for the Agency for Toxic Substances and Disease Registry (ATSDR) as data manager and later joined the Division of Cancer Prevention and Control (DCPC)/Cancer Surveillance Branch (CSB) in 1998 as the Team Lead for the Informatics, Data 

    Bozena Morawski, PhD, MPH

    Epidemiologist

    Cancer Data Registry of Idaho

    Bozena Morawski received a PhD in epidemiology from the University of Minnesota and an MPH from the University of California, Los Angeles. Dr. Morawski is an epidemiologist at the Cancer Data Registry of Idaho. Her research interests include vulnerable and minority populations, infectious disease-associated cancers, and analysis of cancer data by geography. She is a member of the CiNA Editorial Work Group and coauthor of the CiNA Prevalence Volume. 

  • Focus on Brain Tumors

    Contains 2 Component(s) Recorded On: 11/04/2020

    This NAACCR Talk is based on a concurrent session that had been planned for the in person 2020 NAACCR Annual Conference.

    Trends in Non-Malignant Brain Tumor Rates in the USA during 2004-2017:real or artifact?* 

    Diana Withrow, PhD

    Epidemiologist, National Cancer Institute

    Missing Meningiomas: Are Non-Pathologically Diagnosed Cancers Underreported?

    Dennis Deapen DrPH, MPH

    Epidemiologist, Los Angeles Cancer Surveillance Program

    Ependymoma, NOS and Anaplastic Ependymoma Incidence and Survival in the United States Varies Widely by Patient and Clinical Charateristics, 2000-2016

    Gino Cioffi, MPH

    Biostatistician, Case Western Reserve University School of Medicine & CBTRUS

    Epidemiology of Brainstem High-Grade Gliomas in Children and Adolescents in the United States, 2000-2017

    Nirav Patil, MBBS, MPH

    Senior Biostatistician, University Hospitals Cleveland Medical Center & CBTRUS

    *At the request of the present, we did not post the slides for this presentation.  

    Diana Withrow, PhD

    Epidemiologist, National Cancer Institue

    Diana Withrow, Ph.D., joined the Radiation Epidemiology Branch (REB) as a postdoctoral fellow in May 2016 and promoted to Research Fellow in June 2018. Dr. Withrow earned her Ph.D. in epidemiology from the University of Toronto Dalla Lana School of Public Health in 2016. Working with Dr. Loraine Marrett, her doctoral research comprised the first national-level analysis of cancer survival among First Nations and Métis adults in Canada. In 2010, Dr. Withrow earned an M.Sc. in epidemiology from the London School of Hygiene and Tropical Medicine. Since 2016, Dr. Withrow has worked as a post-doctoral and research fellow in the Division of Cancer Epidemiology and Genetics at teh National Cancer Institute. There, Dr. Withrow’s research interests include socio-demographic and economic disparities in survival and survivorship, the role of therapy on second cancer risk, and the optimal application of survival analysis techniques to these research areas. 

    Dennis Deapen, DrPH, MPH

    Epidemiologist, Los Angeles Cancer Surveillance Program - USCer

    Dennis Deapen is Professor of Preventive Medicine at the USC School of Medicine. He has been Director of the Los Angeles Cancer Surveillance Program (CSP) since 1988. The CSP functions in the USC Norris Comprehensive Cancer Center and is also a member of the California Cancer Registry and the SEER Program. He received a MPH from Loma Linda University and Doctor of Public Health from UCLA. He has been an epidemiologist since 1977 conducting research in etiology, prevention and survivorship of cancer. He has created or led large, long-term cohort studies of cancer risk.  Most recently he initiated the Virtual Pooled Registry which creates the capacity for linking cancer epidemiology cohort studies with all US cancer registries simultaneously. He has been author or co-author of over 180 peer-reviewed publications. He served as President of NAACCR and a member of the Executive Committee of the International Association of Cancer Registries.

    Gino Cioffi, MPH

    Biostatistician, Case Western Reserve University School of Medicine & CBTRUS

    Gino  Cioffi is a biostatistician at Case Western University School of Medicine. He graduated from Kent State University with a Bachelor of Science in Biotechnology in 2016 and a Master of Public Health in Biostatistics in 2018. He has been involved in CBTRUS since 2018, where he contributes to the preparation of the CBTRUS analytic data files, data analysis, interpretation, manuscripts, reports and data requests.

    Nirav Patil, MBBS, MPH

    Senior Biostatistician; University Hospitals: Cleveland Medical Center & CBTRUS

    Nirav Patil received Bachelor of Medicine, Bachelor of Surgery from Dr. D. Y. Patil Vidyapeeth, Pune, India in 2010, and a Master of Public Health in Biostatistics from University of North Texas Health Science Center, Fort Worth, Texas in 2013. Currently, I am working a biostatistician at University Hospitals, Cleveland. Beginning 2019, I am contributing to the preparation of the Central Brain Tumor Registry of the United States (CBTRUS) analytic data files, data analysis, interpretation, reports and data requests in addition to preparation of presentations and publications for CBTRUS projects.

  • Social Determinants of Health Part 2

    Contains 2 Component(s) Recorded On: 10/28/2020

    This NAACCR Talk is based on a concurrent session that had been planned for the in person 2020 NAACCR Annual Conference.

    The importance of examining the intersection of rural-urban status and race/ethnicity in cancer surveillance research: an early-onset colorectal cancer example
    Whitney Zahnd, PhD; University of South Carolina

    Implementation of a Health-Related Social Needs Screening Tool to Inform Cancer Care Improvement Strategies among Diverse Patients in Primary Care Settings
    Jennifer Tsui, PhD, MPH; Assistant Professor, University of Southern California

    Application of Machine Learning and computer vision models to identify green and blue space in remote sensing images
    Pushkar Inamdar, PhD; Greater Bay Area Cancer Registry

    Spatial Econometrics: A framework to understand geographic disparities in cancer outcomes
    Sandi Pruitt, PhD; University of Texas Southwestern Medical Center

    Whitney Zahnd, PhD

    Research Assistant Professor, University of South Carolina

    Dr. Whitney Zahnd is a research assistant professor with the Rural & Minority Health Research Center in the Arnold School of Public Health at the University of South Carolina.

    Jennifer Tsui, PhD

    Associate Professor, University of Southern California

    Jennifer Tsui is an Associate Professor at the University of Southern California, Keck School of Medicine and a member of the USC Norris Comprehensive Cancer Center. She is a health services researcher with a focus on disparities in cancer care delivery and cancer outcomes, particularly among racial/ethnic minority and low-income populations.  Dr. (SWAY) Tsui’s research utilizes cancer registry information, health care claims, population-based surveys, and geographic/spatial data to understand multilevel influences on patterns of care and cancer care quality for diverse populations. Her other area of research focuses on HPV vaccination and the implementation of evidence-based strategies to increase uptake in safety-net health care settings. 

    Pushkar Inamdar, PhD

    Data Scientist, University of California, San Francisco

    Dr. Pushkar Inamdar is a Data Scientist in the Department of Epidemiology and Biostatistics and also a part of the Greater Bay Area Cancer Registry at the University of California, San Francisco (UCSF). His Ph.D. is in the field of Earth and Atmospheric Sciences. His previous research experience is in the Geospatial Sciences, including an application of geostatistics in understanding temporal-spatial patterns. Since, joining UCSF, he has gained experience in characterizing neighborhood attributes for epidemiologic studies, including cohort and electronic health records studies as well as conducting geospatial analyses (e.g., spatial autocorrelation, proximity analysis, data wrangling, kriging, geocoding, remote sensing image analysis). He is applying more advanced concepts like deep learning to perform remote sensing data analysis for the neighborhood characterization, and application of machine learning on geospatial datasets to understand underlying patterns of health risk factors and outcomes.

    Sandi Pruitt, PhD, MPH

    Associate Professor, University of Texas Southwestern Medical Center

    Sandi L. Pruitt, PhD MPH, is an Associate Professor in the Department of Population and Data Sciences at the University of Texas Southwestern Medical Center in Dallas, Texas. Dr. Pruitt uses cancer registry data, electronic health record data, and neighborhood data to better understand geographic, socioeconomic, and racial/ethnic disparities in cancer behaviors and outcomes.

  • Social Determinants of Health Part 1

    Contains 2 Component(s) Recorded On: 10/21/2020

    This NAACCR Talk is based on a concurrent session that had been planned for the in person 2020 NAACCR Annual Conference.

    Multilevel social stressors and prostate cancer disparities in African American men 

    Scarlett Gomez, PhD, MPH; Greater Bay Area Cancer Registry

    Socioeconomic Disparities in Colon Cancer Survival: Revisiting Neighborhood Poverty using Residential Histories

    Daniel Wiese, Doctoral Student, Temple University 

    Using cancer registries to understand sexual minorities’ cancer survivorship 

    Ulrike Boehmer, PhD; Boston University School of Public Health

    Ethnic Enclaves in Cancer Surveillance and Registry-Based Research among Asian American and Hispanic populations

    Salma Shariff-Marco, PhD, MPH; University of California, San Francisco

    Scarlett Lin Gomez, PhD

    Research Scientist & Director, Greater Bay Area Cancer Registry

    Scarlett Lin Gomez, M.P.H. and Ph.D. in Epidemiology, is Professor in the Department of Epidemiology and Biostatistics and a member of the Helen Diller Family Comprehensive Cancer Center, at the University of California, San Francisco. She is Director of the Greater Bay Area Cancer Registry, a participant in the NCI SEER (Surveillance, Epidemiology, End Results) program and the California Cancer Registry.  Her research focuses primarily on cancer health disparities and aims to understand the multilevel drivers of those disparities. 

    Daniel Wiese

    Doctoral Student, Temple University

    DanielWiese is a doctoral student in the department of geography and urban studies atTemple University. Currently he is working on his dissertation undersupervision of Dr. Kevin Henry, and is expected to graduate in May 2021. Hisbackground is in remote sensing and GIS-based spatial modeling. The mainresearch interests include the understanding of geographic disparities incancer incidence and mortality in relation to socio-spatial mobility andneighborhood effects.

    Ulrike Boehmer, PhD

    Associate Professor, Boston University School of Public Health

    Ulrike Boehmer, PhD is an Associate Professor of Community Health Sciences at Boston University School of Public Health. Dr. Boehmer received her Ph.D. and M.A. in Sociology from Boston College. Dr. Boehmer’s research interests are in the areas of health disparities, LGBT health, and cancer prevention and control. She is particularly known for her work on LGBT cancer survivorship. Dr. Boehmer is recognized as a leader in LGBT health, especially in the context of cancer. She edited together with Dr. Elk the first book on Cancer and the LGBT population entitled, Cancer and the LGBT Community: Unique perspectives from Risk to Survivorship. She served on the Federal Advisory Committee on Breast Cancer in Young Women, serves on Scientific Advisory Committees for various NIH grants that focus on LGBT health, and is the Associate Editor of the Journal LGBT Health.

    Salma Shariff-Maro, PhD, MPH

    Social and Behavioral Scientist, University of California, San Francisco

    Salma Shariff-Marco, PhD, MPH is a social and behavioral scientist with a research portfolio focused on understanding the role of social determinants of health in shaping and perpetuating health disparities. One main area of her research is on place and health, with studies evaluating how neighborhood characteristics (e.g., social, built, and physical environment attributes) and geographic variation may shape cancer-related health behaviors and outcomes across the cancer continuum. In addition, her research includes efforts to better characterize neighborhoods for population health studies (neighborhood archetypes, virtual audits with Google Street View).