Workshop Descriptions

Basic SEER*Stat Software Training

Sunday, June 21, 2020

8:30 am – 5:30 pm

$275

Fee includes all course materials, breakfast, and afternoon beverage break

SEER*Stat Basic Training covers case listing, frequency, and rate sessions.  Joinpoint regression software and an introduction to the Health Disparities Calculator.  This course also includes a basic overview of age-adjustment and some key analytic fields.

 

Course Objectives

Introduce basic statistical topics in the analysis of cancer registry data and how data can be analyzed using these techniques within the SEER*Stat software.

 

Requirements

General familiarity with the analysis of registry data.  Each participant must bring a laptop with a Windows operating system or a Windows emulator.  If an emulator is used, then the participant should test compatibility with SEER*Stat prior to the conference.

 

Content

Overview of data, and basic analyses with SEER*Stat and Joinpoint.

 

Course Organizer(s)

  • David Annett, Information Management Services, Inc.

  • Linda Coyle, Information Management Services, Inc.

  • Gonçalo Forjaz, National Cancer Institute

  • Angela Mariotto, National Cancer Institute

  • Steve Scoppa, Information Management Services, Inc.

Match*Pro Linkage Software

Sunday, June 21, 2020

9:00am – 5:00pm

$275

Fee includes all course materials, breakfast, and afternoon beverage break

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

 

Course Objectives

  1. Ensure shared understanding of basic linkage concepts

  2. Provide instructional overview of Match*Pro functionality

  3. Give attendees hands-on experience working with test data  

  4. Increase knowledge of and familiarity with Match*Pro

 

Course Organizers

  • Castine Clekin, North American Association of Central Cancer Registries

  • William R Howe

  • Rich Pinder, Los Angeles Cancer Surveillance Program - USC

Advanced SEER*State Software Training –

Survival Analyses

Monday, June 22, 2020

8:30 am – 12:30 pm

$195

Fee includes all course materials, breakfast, and afternoon beverage break

 

SEER*Stat Advanced Topics covers survival (cause-specific, relative, period, conditional, left-truncated life tables analysis and JPSurv).

 

Course Objectives

Introduce advanced statistical topics in the analysis of cancer registry data and how data can be analyzed using these techniques within the SEER*Stat software.

 

Requirements

Basic SEER*Stat training course or workplace SEER*Stat experience. Each participant must bring a laptop with a Windows operating system or a Windows emulator. If an emulator is used, then the participant should test compatibility with SEER*Stat prior to the conference.

 

Content

Survival analyses, including relative, cause-specific, period, conditional left-truncated life tables, and JPSurv.

Course Organizer(s)

  • David Annett, Information Management Services, Inc.

  • Linda Coyle, Information Management Services, Inc.

  • Gonçalo Forjaz, National Cancer Institute

  • Angela Mariotto, National Cancer Institute

  • Steve Scoppa, Information Management Services, Inc.

Advanced SEER*State Software Training –

Prevalence and Incidence-Based Mortality

Monday, June 22, 2020

1:30pm – 5:30pm

$195

Fee includes all course materials, breakfast, and afternoon beverage break

SEER*Stat Advanced Topics covers prevalence (limited-duration, ProjPrev, and ComPrev) and Incidence-Based Mortality.

 

Course Objectives

Introduce basic statistical topics in the analysis of cancer registry data and how data can be analyzed using these techniques within the SEER*Stat software.

 

Requirements

Basic SEER*Stat training course or workplace SEER*Stat experience. General familiarity with the analysis of registry data. Each participant must bring a laptop with a Windows operating system or a Windows emulator. If an emulator is used, then the participant should test compatibility with SEER*Stat prior to the conference.

 

Content

Limited-duration prevalence; ProjPrev, ComPrev, and Incidence-Based Mortality.

 

Course Organizer(s)

  • David Annett, Information Management Services, Inc.

  • Linda Coyle, Information Management Services, Inc.

  • Gonçalo Forjaz, National Cancer Institute

  • Angela Mariotto, National Cancer Institute

  • Steve Scoppa, Information Management Services, Inc.

Tools and Software to Automate and Normalize

the Cancer Data Abstraction Workflow

Monday, June 22, 2020

9:00 am – 4:00 pm

$275

Fee includes all course materials, breakfast, and afternoon beverage break

Cancer registries routinely collect data on every identified cancer case, including patient demographics, primary tumor site, tumor morphology and stage at diagnosis, first course of treatment, and follow-up for vital status (survival). While these programs are extremely impressive in their breadth of coverage and rivaled by few other national or international entities, they are necessarily hampered by a lack of depth of coverage. The reasons for this are multifactorial but are essentially explained by a mismatch between resources available for capturing detailed data and the sheer complexity of patient cases. Electronic medical records (EMRs) have worsened this mismatch considerably, as they are many orders of magnitude larger and much more complex than the paper-based records that they replaced. Despite this, Certified Tumor Registrar (CTR) workforce expansion has not kept pace. In 2011, the National Cancer Registrars Association published a workload and staffing study that found that more than one-third of hospital-based registries had one or fewer full-time equivalents on their staff. Due to this circumstance, registry programs have been thoughtful in their selection of necessary data elements so as not to overwhelm the existing workforce capacity. Nevertheless, there is a strong desire by both the cancer surveillance community and the many secondary users of this data to enhance the depth of coverage by taking advantage of new and emerging health information technology solutions. This need is becoming especially acute given the rapidity with which new important diagnostic, prognostic, and predictive biomarkers are emerging in this era of personalized oncology. In 2019, we held a half-day tutorial at NAACCR, highlighting and illustrating several tools that can be used right now to enhance the quality of registry data and to automate certain tasks. This tutorial was well-attended and the feedback received was very positive. Due to the time constraints the tutorial was primarily didactic. For 2020, we propose to cover the same topics and expand the tutorial to a full day session. Specifically, we propose to introduce and demonstrate: 1) the National Cancer Institute (NCI)’s Observational Research in Oncology Toolbox; 2) the DeepPhe natural language processing (NLP) and visualization software; 3) the NCI-DOE application programming interface (API); and 4) the HemOnc chemotherapy regimen ontology. These are described below in brief detail.

 

Course Objectives

Upon completion of this tutorial, attendees will be able to:

  1. Understand the tools available in the NCI’s Observational Research in Oncology Toolbox and consider how they might be incorporated into existing workflows. 

  2. Appreciate how natural language processing tools such as DeepPhe can aid in the abstraction process. 

  3. Appreciate the utility of APIs and how they may ease the data collection process. 

  4. Develop an understanding of how formal ontologic modeling of chemotherapy regimen concepts can increase the utility of cancer registry information.

 

Requirements

No particular requirements, but some knowledge of software tools will be helpful.

 

Content

This tutorial will provide several perspectives on the state-of-the-art and challenges of extracting and visualizing cancer patient data. Presentations will cover technical details but are intended to be broadly inclusive and practical. The emphasis will be on the presentation of existing tools and software that could be utilized by central cancer registries and cancer researchers almost immediately. We propose a 6-hour full-day workshop, with a portion devoted to didactics and a portion devoted to hands-on exploration of the tools described.

 

Course Organizers

  • Eric B. Durbin, Kentucky Cancer Registry

  • Harry Hochheiser, Associate Professor

  • Valentina Petkov, National Cancer Institute

  • Donna R Rivera, National Cancer Institute

  • Guergana Savova, Boston Children’s Hospital and Harvard Medical School

  • Jeremy Warner, Associate Professor of Medicine and Biomedical Informatics

Cancer Surveillance Using R: An Introduction

Monday, June 22, 2020

9:00 am – 4:15 pm

$275

Fee includes all course materials, breakfast, and afternoon beverage break

In recent years R has emerged as the statistical analysis platform of choice for scientists in many disciplines. Its main advantages are that it is entirely free, open source, fully customizable, and years ahead of commercial software packages in its features. For current public health students, R is likely the environment in which they are being taught. Nevertheless, there are few R users within the cancer surveillance community. We will use national cancer data as well as the passenger list of the Titanic to illustrate how to manipulate and analyze data using R.

 

Course Objectives

Students will gain a basic understanding of how R can assist their cancer surveillance activities, including data tabulation, analysis, and presentation.

 

Requirements

No prior programming knowledge will be presumed. Students should bring their own laptops - this is a hands-on course. Students should have R and RStudio pre-installed on their laptops before the course begins. All code and data will be provided.

 

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.

 

Course Organizers

  • Francis P Boscoe

Funding for this conference was made possible in part by NCI Grant Number 1RI3CA232427 and Contract Number HHSN261201400004I from the National Cancer Institute.  The views expressed in written conference materials or publications and by speakers or moderators do not necessarily reflect the official policies of the Department of Health and Human Services; nor does mention by trade names, commercial practices, or organizations imply endorsement by the U.S. Government. Additionally, this program is supported in part by CDC Cooperative Agreement Number NU58DP006458 from the Centers for Disease Control and Prevention. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention. Without NCI and CDC support, this scientific conference would not be possible.

Photographers will be taking pictures and video at the conference and workshops, which may be used for promotional and education purposes, and which may be posted on the NAACCR website. Participation in the conference, workshops, and other associated meetings and gatherings constitutes an agreement to allow NAACCR to use and distribute attendee's image and/or voice in photographs and recordings of the meeting.

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