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  • PREPARING YOUR INCIDENCE DATA TO BE USED IN SEER*STAT

    Contains 2 Component(s) Recorded On: 01/23/2019

    SEER*Stat is a powerful statistical application that is available free of charge from the US National Cancer Institute and provides a mechanism for the analysis of population-based cancer registry data. It has modules for the analysis and reporting of the four most common cancer-related metrics: incidence, survival, prevalence, and mortality.

    SEER*Stat for Global Cancer Registry Data

    SEER*Stat is a powerful statistical application that is available free of charge from the US National Cancer Institute and provides a mechanism for the analysis of population-based cancer registry data. It has modules for the analysis and reporting of the four most common cancer-related metrics: incidence, survival, prevalence, and mortality.

    SEER*Prep is a software that converts text data files to the format required by SEER*Stat. The objective of these series of webinars is to facilitate the use of SEER*Stat software for data that are not in accordance with the NAACCR format. Specifically, we will make use of a more generic, simplified format that complies with data usually available from cancer registries across the world, thus facilitating the use of SEER*prep and SEER*Stat. New variables in this global format include CI5 groupings and Essential TNM. These features will facilitate analysis and reporting of population-based cancer data in a standard format.

    In these series of webinars, participants will be guided on a step-by-step fashion in the process of how to use SEER*Prep to generate a SEER*Stat database for analysis of incidence (webinar 1) and mortality (webinar 2) data, using the new global format. The demonstration will be done using real data. Future webinars will focus on how to use SEER*Stat more in-depth (dates TBD).

    By the end of each of the first 2 webinars participants should be able to:

    • -Define a Directory to save user-defined data, reports and database description files
    • -Understand each variable in SEER*Prep’s database description file
    • -Make use of user-defined variables
    • -Convert text data into fixed length format using FixLen
    • -Generate a SEER*Stat database using SEER*Prep
    • -Check and, if necessary, correct any variable in the original file using the report generated by SEER*Prep
    • -Configure file locations in SEER*Stat
    • -Generate frequencies and rates (age-specific, crude, age-standardized) in SEER*Stat
    • -Generate standard reports (e.g., CI5 format)
    • -Create and edit variables using the dictionary in SEER*Stat
  • Producing Cancer Statistics at the Census Tract Level: A Louisiana Story

    Contains 1 Component(s) Recorded On: 11/14/2018

    During the 2017 Louisiana Legislative Session, a new law was signed requiring that the Louisiana Tumor Registry (LTR) produce and release cancer incidence counts and rates at the census tract level. Previously, cancer statistics could be released to the public at the parish (county) level. To comply with this law, the LTR convened a team, including experts from NCI-SEER and IMS, to develop the appropriate methodology to produce incidence rates at the census tract level while ensuring rate stability and patient confidentiality. The objective of this presentation is to describe the LTR's experience with identifying the appropriate population source, selecting the time period for the analysis, and producing reliable cancer statistics at the census tract level, as well as to share a summary of the results.

    During the 2017 Louisiana Legislative Session, a new law was signed requiring that the Louisiana Tumor Registry (LTR) produce and release cancer incidence counts and rates at the census tract level. Previously, cancer statistics could be released to the public at the parish (county) level. To comply with this law, the LTR convened a team, including experts from NCI-SEER and IMS, to develop the appropriate methodology to produce incidence rates at the census tract level while ensuring rate stability and patient confidentiality. The objective of this presentation is to describe the LTR's experience with identifying the appropriate population source, selecting the time period for the analysis, and producing reliable cancer statistics at the census tract level, as well as to share a summary of the results.

  • Setting up NCD Surveillance in an island context: Lessons from the Pacific

    Contains 1 Component(s)

    Setting up NCD Surveillance in an island context: Lessons from the Pacific

    Setting up NCD Surveillance in an island context: Lessons from the Pacific

    Please click "Handouts" tab above to access material.

  • International Registry Review Questionnaire

    Contains 1 Component(s)

    International Registry Review Questionnaire

    International Registry Review Questionnaire

  • Regional Workshop On Using Cancer Registry Data to Inform Cancer Prevention and Control Policy/Research

    Contains 1 Component(s)

    Regional Workshop On Using Cancer Registry Data to Inform Cancer Prevention and Control Policy/Research

    This session will focus on Regional Workshop On Using Cancer Registry Data to Inform Cancer Prevention and Control Policy/Research.

    Brenda Edwards

    Senior Advisor for Cancer Surveillance

    Brenda K. Edwards, PhD, has been with the Surveillance Research Program (SRP) and its predecessor organizations at the National Cancer Institute (NCI) since 1989, serving as SRP's Associate Director from 1990-2011. She has been involved in cancer prevention and control since its formative days early in the 1980s. Dr. Edwards' research has focused on the full spectrum of cancer surveillance research, including risk factors, patterns of care, behavioral studies and survivorship, statistical methodology, and analytic studies.

    Under her leadership, NCI's Surveillance, Epidemiology, and End Results (SEER) Program has become an important resource for monitoring the nation's cancer burden and for measuring progress in cancer control. Dr. Edwards has played a major role in preparing and disseminating the “Annual Report to the Nation on the Status of Cancer."

    Dr. Edwards has received numerous awards, including the North American Association of Central Cancer Registries Calum S. Muir Memorial Award, in recognition for her work in cancer surveillance and registration. She has co-authored more than 100 peer-reviewed publications.

  • Survey Course: Understanding Population-Based Cancer Registries Course

    Contains 15 Component(s)

    Survey Course: Understanding Population-Based Cancer Registries Course

    Introduction to Cancer Registries and Cancer Surveillance

    1. Public Health Surveillance Introduction & Fundamentals
    2. Establishing an Effective Population-based Cancer Registry System

    Registry Operations

    1. Casefinding
    2. Follow-up
    3. Data Editing
    4. Record consolidation
    5. Death clearance

    Registry Management

    1. Registry Development
    2. Data Quality and Completeness
    3. Ethics & confidentiality
    4. Data Management – IT resources

    Uses of Population-Based Registry Data

    1. Calculation and Assessment of Survival Rates
    2. Calculation and Assessment of Cancer Incidence
    3. Using Central Cancer Registry Data for Cancer Control and Cancer Research
  • RDU Webinar Series: Online Interactive Tool to Improve the Understanding of Survival Statistics

    Contains 1 Component(s) Recorded On: 09/14/2017

    Background There are a variety of ways to quantify cancer survival with each measure having advantages and disadvantages. For example, relative/net survival is useful for making fair comparisons between population groups and over time, but is of less relevance to clinicians or patients. The differences between the various measures and how they should be interpreted has led to confusion among scientists, the media, health care professionals and patients. Purpose and methods. We have developed an online interactive tool to help improve the understanding of a variety of cancer survival measures and how these vary between patients. Its primary purpose is to function as an aid in the interpretation of a variety of commonly reported, important and more complex cancer survival measures that are available from fitting statistical models. The interpretation is facilitated through the use of dynamic interactive graphics available using an online interactive tool. The interactivity improves understanding of these measures and how survival or mortality may vary by age and sex. Routine measures of cancer survival are reported, such as net and all-cause survival. In addition, individualised estimates using crude probabilities are often more appropriate for patients or health care professionals. The results are presented in a variety of ways, including graphs, “people charts”, tables and descriptive text using natural frequencies. All results are updated immediately when using drag bars, drop-down menus or radio buttons. This immediate feedback together with the simple text descriptions leads to both better understanding of individual risk and the differences between the various measures. Results and conclusion The online tool is in final testing using English data for a range of cancer sites. The tool is available at www.interpret.le.ac.uk. We have plans to further develop the interactive tool by incorporating data from different countries and from statistical models that incorporate more disease characteristics (e.g. stage, grade and tumour size).

    Background

    There are a variety of ways to quantify cancer survival with each measure having advantages and disadvantages. For example, relative/net survival is useful for making fair comparisons between population groups and over time, but is of less relevance to clinicians or patients. The differences between the various measures and how they should be interpreted has led to confusion among scientists, the media, health care professionals and patients.

    Purpose and methods.

    We have developed an online interactive tool to help improve the understanding of a variety of cancer survival measures and how these vary between patients. Its primary purpose is to function as an aid in the interpretation of a variety of commonly reported, important and more complex cancer survival measures that are available from fitting statistical models. The interpretation is facilitated through the use of dynamic interactive graphics available using an online interactive tool. The interactivity improves understanding of these measures and how survival or mortality may vary by age and sex. Routine measures of cancer survival are reported, such as net and all-cause survival. In addition, individualised estimates using crude probabilities are often more appropriate for patients or health care professionals. The results are presented in a variety of ways, including graphs, “people charts”, tables and descriptive text using natural frequencies. All results are updated immediately when using drag bars, drop-down menus or radio buttons. This immediate feedback together with the simple text descriptions leads to both better understanding of individual risk and the differences between the various measures.

    Results and conclusion

    The online tool is in final testing using English data for a range of cancer sites. The tool is available at www.interpret.le.ac.uk.  We have plans to further develop the interactive tool by incorporating data from different countries and from statistical models that incorporate more disease characteristics (e.g. stage, grade and tumour size).  

    Paul C Lambert

    Paul C Lambert is a professor of Biostatistics working in the Biostatistics Research Group in the Department of Health Sciences at the University of Leicester, UK. He also part-time in the Biostatistics Group in the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

  • RDU Webinar Series: Identifying Target Areas for Colorectal Cancer Screening in Louisiana through Geospatial Analysis

    Contains 1 Component(s) Recorded On: 08/10/2017

    The Louisiana Tumor Registry (LTR), along with the Louisiana Colorectal Cancer Roundtable and geospatial experts from NCI, Westat, and Temple University, collaborated to map colorectal cancer in Louisiana to support the National Colorectal Cancer Roundtable’s “80% by 2018” initiative. The overall goal of the project was to use multiple data sources and geospatial analyses in order to identify the places and high-risk populations who may benefit the most from screening interventions. Through this webinar, the LTR will share its experiences with address cleaning and geospatial analyses, as well as present the resulting maps and implications for screening in Louisiana.

    The Louisiana Tumor Registry (LTR), along with the Louisiana Colorectal Cancer Roundtable and geospatial experts from NCI, Westat, and Temple University, collaborated to map colorectal cancer in Louisiana to support the National Colorectal Cancer Roundtable’s “80% by 2018” initiative.  The overall goal of the project was to use multiple data sources and geospatial analyses in order to identify the places and high-risk populations who may benefit the most from screening interventions.  Through this webinar, the LTR will share its experiences with address cleaning and geospatial analyses, as well as present the resulting maps and implications for screening in Louisiana.

  • RDU Webinar Series: Precision Cancer Medicine: Focus on Children

    Contains 1 Component(s) Recorded On: 02/15/2017

    This webinar is part of a series sponsored by the Research & Data Use Steering Committee. The idea is to bring high quality presentations that were presented during the annual conference to a wider audience via webinar. If you have seen a presentation at the annual conference, or elsewhere, that you feel would benefit the larger NAACCR community, please suggest it be presented in this forum.

    Oncologists heave been personalizing patient care for many years. When oncologists review slides with a pathologist to arrive at an accurate diagnosis or review radiology scans to determine stage in order to determine the most appropriate treatment regimen, they are personalizing patient care. The significant advances that have occurred in gene sequencing technologies and the development of new more targeted drugs has allowed oncologists to personalize care even more by matching gene alterations (mutations, copy number alterations and translocations) found in an individuals own tumor to targeted therapies. The term precision cancer medicine is now used most often used to refer to this type of care. Dr. Katherine Janeway is pediatric hematologist-oncologist and researcher with joint appointments at Harvard Medical School, Dana-Farber Cancer Institute, and Children’s Hospital, Boston.  She is the Director of the Pediatric Solid Tumor Program, a member of the Dana-Farber/Harvard Cancer Center Genetics Program and leader of the Pediatric Oncology Precision Cancer Medicine Initiative. This presentation will provide an overview of the advances in genomics and targeted therapy that make precision cancer medicine possible and will review the research being conducted in Precision Cancer Medicine with a focus on clinical sequencing studies, basket trials and pediatric oncology.

  • RDU Webinar Series: Estimating Neighbourhood-level Behavioural Risk Factor Prevalence from Large Population-Based Surveys: a Bayesian Approach

    Contains 1 Component(s) Recorded On: 11/02/2016

    This webinar is part of a series sponsored by the Research & Data Use Steering Committee. The idea is to bring high quality presentations that were presented during the annual conference to a wider audience via webinar. If you have seen a presentation at the annual conference, or elsewhere, that you feel would benefit the larger NAACCR community, please suggest it be presented in this forum.

    Complex survey-based behavioural risk factor estimates are available at the regional level, but public health insights are limited due to unobserved heterogeneity that may exist in these regions. Advanced spatial analysis techniques can produce sensible small-area estimates of risk factors and identify areas of high prevalence. This presentation describes a spatial Bayesian hierarchical model which estimates small-area prevalence of current smoking and excess bodyweight (body mass index ≥ 25 kg/m2) by pooling 5 cycles of the Canadian Community Health Survey for a region in southwestern Ontario. This study demonstrates the feasibility of a full Bayesian model for complex survey data to identify areas with elevated risk factor prevalence. These spatial analysis techniques provide small-area estimates to inform surveillance activities and may be used to explain cancer incidence at small-area levels of geography.