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Cameron Brain Tumor PowerPoint Presentation

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Slide 1 - Cameron Brain Tumor/Brain Cancer InquiryOctober 9, 2008Missouri Department of Health and Senior Services
Slide 2 - Sarah L. Patrick, MPH, PhD State Epidemiologist Administrator, Section of Epidemiology for Public Health Practice 920 Wildwood Ave. Jefferson City, Missouri 65102 Sarah.Patrick@dhss.mo.gov
Slide 3 - Establish a case definition Resident in Caldwell, Clinton, Daviess or DeKalb County Cameron zip code (64429) crosses into all four Diagnosed with malignant brain or central nervous system (CNS) tumor between January 1, 1996 – June 30, 2008, OR Diagnosed with a benign brain or CNS tumor between January 1, 2004 – June 30, 2008 Steps of Cancer Inquiry Data Review
Slide 4 - Find All Cases That Meet the Case Definition Missouri Cancer Registry (MCR) data Malignant brain and CNS tumors, (O3 700-729, O3 malig) Benign brain and CNS tumors, (O3 700-729,751-753, 03 BB) Deaths coded to brain and CNS tumors, ICD-10 codes, 1999 - 2007 Rapid Case Ascertainment (RCA) data (through October 3, 2008) Patient Information Forms Received through September 22, 2008 Follow-up as warranted to confirm information Number of persons meeting the case definition: 70 24 people with benign tumors 46 people with malignant tumors Steps of Cancer Inquiry Data Review
Slide 5 - Percent of Primary Brain and CNS Tumors by Behavior (malignant or benign), 2004-2006, Four-county area (Caldwell, Clinton, Daviess, DeKalb) Compared with Missouri
Slide 6 - Each form reviewed to see if it meets the case definition Received on patients living in multiple states and throughout Missouri Reports covered a 40 year time frame, many different disease sites/types Inmates in Cameron correctional facility included Information on 98 people received; multiple follow-up calls made to confirm/clarify information, when needed. Patient Information Forms
Slide 7 - When Patient Information Forms Did Not Meet the Case Definition
Slide 8 - Orient the Data in Time, Person and Place Useful terms: An incidence rate is a measure of risk and based on new cases of disease in a defined population for a specific time period. It is often shown as ‘per 100,000 people’ for rare diagnoses such as brain tumors. When you compare the incidence rate locally to an ‘expected’ rate (based on state data) you get a Standardized Incidence Ratio (SIR). A 3-year moving average is a smoothing technique used when smaller populations are being reviewed. Steps of Cancer Inquiry Data Review
Slide 9 - Incidence Rates of Brain and CNS Tumors in 4-Counties (Caldwell, Clinton, Daviess and DeKalb) and Missouri Per 100,000
Slide 10 - Incidence Rates of Brain and CNS Tumors in 4-Counties, Missouri, and National Estimates Per 100,000
Slide 11 - The incidence of malignant and benign brain tumors has increased over time in the Cameron area and in Missouri. Same trend as national No difference is detected by specific county of residence so all 4 counties are combined to increase likelihood of detecting differences. Reporting for 2006-2008 is not complete yet so rates are likely to increase. Interpretation of Time Trends
Slide 12 - Age-Specific Incidence of Primary Brain and CNS Tumors
Slide 13 - The incidence of malignant and benign brain tumors varies by age group, but generally increases with age. The 4-county area age-specific rates are similar to Missouri rates, except there is a slight increase in the 0-19 year old age group This increase is in benign brain tumors and based on a very small number of tumors (which may produce an unstable rate). Residents in the area 75 years of age and older had a statistically significant lower brain tumor rate when compared to Missouri. Interpretation of Age-Specific Rates
Slide 14 - No significant differences were found when both types were combined or for benign brain tumors by age. The mortality rate for malignant brain tumors was significantly higher for the 0-19 year old age group in the Cameron zip code when compared to the State rate. This was based on a very small number of cases. Age-Specific Rates Death Rates Due to Malignant or Benign Brain Tumors
Slide 15 - No increases were found in the incidence or mortality rates of ‘all cancers’ in the Cameron zip code, each county, or the 4-county area compared to the State. Lower than expected rates of ‘all cancers’ were found: Daviess County: among 35-74 year olds DeKalb County: among adults > 35 years of age 4-Counties: among 55-74 year olds and all ages combined Cancer from All Causes
Slide 16 - Burden of Cancer and Benign Brain & CNS Tumors, Four-county area Compared with Missouri, 2004-2006 4-County Area Lung & Bronchus (17.1%) Prostate (12.7%) Colon & Rectum (11.9%) Female Breast (11.0%) Urinary Bladder (4.9%) Kidney& Renal Pelvis (4.4%) Leukemia (3.8% Corpus & Uterus (3.4%) Non-Hodgkin Lymphoma (3.4%) Benign and malignant brain (3.1%) Missouri Lung & Bronchus (16.8%) Female Breast (13.5%) Prostate (11.8%) Colon & Rectum (10.8%) Urinary Bladder (4.2%) Benign and malignant brain (3.9%) Non-Hodgkin Lymphoma (3.8%) Melanoma of the Skin (3.5%) Kidney& Renal Pelvis (3.4%) Corpus & Uterus (2.8%)
Slide 17 - Because environmental radon was an expressed concern by some community members, we analyzed lung cancer incidence and mortality comparisons. Findings: Clinton county: higher lung cancer incidence rate than expected for people 20-54 years of age; Daviess county: higher lung cancer incidence rate than expected for people 20-34 years of age. Lung Cancer
Slide 18 - The DHSS Missouri County Level Study was just released and provides information for each county on adults: Preventive health behaviors, Current tobacco use, Tobacco cessation, and Secondhand smoke exposure Some print outs available on back table Searchable database with mapping capability:http://www.dhss.mo.gov/CommunityDataProfiles/ Click on ‘2007 County Level Study’ For Your Information
Slide 19 - Known risk factors for brain tumors include: Ionizing radiation HIV infection Genetics Some chemical exposures (vinyl chloride, acrylonitrile) when measured among workers But most people with brain tumors do not have these risk factors. So, Where Do We Go From Here?
Slide 20 - No one wants to have a tumor, so low numbers in a community are GOOD, Epidemiologically, when we study what causes a disease we most often have to study A LOT of cases in order to find what is causing the disease. Cancer registries often work together through the Central Brain Tumor Registry of the United States (CBTRUS) so they will have sufficient sample sizes to look for cancer causes. The ‘good and bad’ of having too few cases
Slide 21 - Environmental testing has already taken place in areas of concern in the community. No exposures known to cause brain tumors have been found. Because some people are still undergoing diagnostic work-up for potential new tumors, the Missouri Cancer Registry should do a live database search again in 12 months to determine if clustering becomes apparent with additional cases. Observations and Recommendations
Slide 22 - This presentation is dedicated to all the community members who have been affected by cancer and non-malignant brain tumors. We appreciate your desire for healthy lives as individuals, family members, and neighbors within a broader community and your willingness to share your stories and information so our work on the ‘data’ side is as accurate as possible. --Your data team Thank you!
Slide 23 - Contributors Thank You Cherri Baysinger Ellen Ehrhardt Bec Francis Sherri Homan Jeannette Jackson-Thompson Mary Jane King Sarah Patrick Kris Ricketts Chester Schmeltz Margaret Tyler Saba Yemane A special thanks to tumor registrars across the state and partners from other states!
Slide 24 - The Effect of Statistical Power, Exposure Dose, and Resulting Number of Cancers: Example of Nuclear Radiation http://www.unscear.org/unscear/en/publications/2000_2.html
 

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