Awatef Ahmed Ben Ramadan1,2,3, Jeannette Jackson-Thompson1,2,3, Chester Lee Schmaltz1,2. 1. Missouri Cancer Registry and Research Center, University of Missouri-Columbia. 2. School of Medicine Department of Health Management and Informatics, University of Missouri-Columbia. 3. MU Informatics Institute, University of Missouri-Columbia.
Abstract
OBJECTIVES: To measure and interactively visualize female breast cancer (FBC) incidence rates in Missouri by age, race, stage and grade, and senate district of residence at diagnosis from 2008 to 2012. METHODS: An observational epidemiological study. The FBC cases in counties split by senate districts were geocoded. Population database was created. A database was created within SEER*Stat. The incidence rates and the 95% Confidence Interval (CI) were age standardized using US 2000 Standard Population. The Census Bureau's Cartographic Boundary Files were used to create maps showing Missouri senate districts. Incidence results were loaded along with the maps into InstantAtlas™ software to produce interactive reports. RESULTS: Cancer profiles were created for all 34 Missouri senate districts. An area profile and a double map that included interactive maps, graphs, and tables for the 34 Missouri senate districts were built. CONCLUSION: The results may provide an estimation of social inequality within the state and could provide clues about the impact of level of coverage and accessibility to screening and health care services on disease prevention and early diagnosis.
OBJECTIVES: To measure and interactively visualize female breast cancer (FBC) incidence rates in Missouri by age, race, stage and grade, and senate district of residence at diagnosis from 2008 to 2012. METHODS: An observational epidemiological study. The FBC cases in counties split by senate districts were geocoded. Population database was created. A database was created within SEER*Stat. The incidence rates and the 95% Confidence Interval (CI) were age standardized using US 2000 Standard Population. The Census Bureau's Cartographic Boundary Files were used to create maps showing Missouri senate districts. Incidence results were loaded along with the maps into InstantAtlas™ software to produce interactive reports. RESULTS: Cancer profiles were created for all 34 Missouri senate districts. An area profile and a double map that included interactive maps, graphs, and tables for the 34 Missouri senate districts were built. CONCLUSION: The results may provide an estimation of social inequality within the state and could provide clues about the impact of level of coverage and accessibility to screening and health care services on disease prevention and early diagnosis.
Breast cancer incidence rates could be increased by increasing the intensity of
breast cancer screening measures and interventions. These rates might be decreased
by increasing prevention measures for cancer risk factors [1].The central cancer registry database is considered to be a high-quality source to
estimate the epidemiological rates because it follows very strict regularly updated
measures and standards [2]. Many studies have
shown that there are inequalities between cancer cases according to age, race, and
stage and grade at diagnosis [3-9].Numerous evidence-based studies have concluded that the use of interactive geographic
mapping software could allow users to interact easily with the datasets and help in
publishing high-quality interactive reports. Distribution of geospatial health data
could help public health leaders and decision makers in designing, developing, and
adopting effective and efficient strategies and programs to improve public health
outcomes targeting the heavily affected geographical areas with the visualized
health event [10-12].The aims of the current study were to: 1) measure female breast cancer (FBC)
incidence rates in Missouri from 2008 to 2012 according to the FBC cases’ age
at diagnosis, race, and the Senate District of residence at diagnosis; 2) visualize
the measured incidence rates in InstantAtlas™ interactive mapping reports;
and 3) compare spatial variances and potential disparities in incidence data between
some senate districts and the state of Missouri.
Methods
The study’s design was an observational epidemiological study. The
investigators did secondary analysis of all FBC cases in the Missouri Cancer
Registry (MCR) database from January 1, 2008 through December 31, 2012.The calculated incidence rates were age standardized using US 2000 Standard
Population for comparability across regions with differing age structures. We
calculated the 95% confidence interval (CI) for these rates using SEER*Stat
statistical package [13]. The investigators
compared the calculated Missouri demographic and geographical incidence rates using
the same statistical package. The FBC cases in counties split by senate districts
were geocoded to determine their district of residence; obtaining the denominator
for districts with split counties presented a challenge. The investigators used
TIGER/Line® Shapefiles and ESRI ArcMap™ to assign these FBC cases to
senate districts [14].Population data at the district, age, race, and year level for these cases was
created by combining Census American Community Survey (ACS) and Population
Estimation Program (PEP) data. A database was created in (SEER*Stat), a statistical
software package for analyzing cancer data; variables were created and imported to
aid analyzing MCR’s FBC in SEER*Stat. The Census Bureau’s Cartographic
Boundary Files were used to create maps showing Missouri counties and state senate
districts [15]. Incidence results were loaded
along with the Cartographic Boundary Files into the InstantAtlas™ software to
produce interactive mapping reports that display our study’s results. We will
attach our interactive mapping reports to the MCR-ARC website. The interactive
reports include maps, graphs, and tables for Missouri’s 34 senate
districts.The senate district assignment process included all of MCR’s FBC cases
diagnosed from 1996 through 2012 who were residents of Missouri at diagnosis; the
final analysis and maps only include those diagnosed from 2008 through 2012 with a
known county of residence. To keep the registered FBC cases’ confidentiality,
we suppressed cells with small counts, using a commonly-used threshold of five or
fewer FBC cases [16].Race was assessed due to persistent disparities between African-American and white
FBC patients, these data are collected by reporting facilities and may be a mixture
of self-reported and assigned values. For the years included in this study, fairly
detailed racial categories could be specified (e.g., Vietnamese)
and up to five races could be recorded.
Results
The senate districts’ incidence rates of FBC were classified, as shown in
tables 1-3,
along with the following variables: All malignant FBC cases, age at diagnosis
(<50, 50-64, and 65+), race (African-American or white), late stage (regional +
distant), and high grade (III + IV). The tables contain the incidence rates for all
34 senate districts and Missouri and the 95% confidence intervals of the measured
incidence data for all the above-mentioned variables.
Figure 1
Area Profile Interactive InstantAtlas™ Report Displaying Female Breast Cancer
(FBC) Incidence Data by Senate District (Age 65+ Years Old) 2008-2012 [17].
Figure 2
Double Map Interactive InstantAtlas™ Report Displaying Female Breast Cancer
(FBC) Incidence Rates and Percent Late Stage and High Grade by Senate
District (Age <50 Years Old) Compared to the Female Breast 5-Year
Cause-Specific Survival by Senate District (Age <50 Years Old) 2008-2012
[18].
Area Profile Interactive InstantAtlas™ Report Displaying Female Breast Cancer
(FBC) Incidence Data by Senate District (Age 65+ Years Old) 2008-2012 [17].Double Map Interactive InstantAtlas™ Report Displaying Female Breast Cancer
(FBC) Incidence Rates and Percent Late Stage and High Grade by Senate
District (Age <50 Years Old) Compared to the Female Breast 5-Year
Cause-Specific Survival by Senate District (Age <50 Years Old) 2008-2012
[18].Table 1. Female breast cancer (FBC) incidence rates across different age
groups of females in Missouri (2008-2012).Table 2. Female breast cancer (FBC) incidence
rates by race (African-American and white) in
Missouri (2008-2012).^: Incidence statistics based on small number of new cases are suppressed to
help protect confidentiality. As commonly used by MCR-ARC and other central
cancer registries, the threshold of five (5) was utilized.Table 3. Incidence rates of all malignant, high grade, and late
stage of female breast cancer (FBC) cases in
Missouri (2008-2012).From the current study’s results, as shown in tables # 1, 2, & 3, we can
build FBC incidence profiles for the 34 Missouri senate districts. These profiles
enable us to compare individual district’s results to the state of Missouri
and to other districts’ incidence data.The current study investigators produced senate districts interactive reporting maps
using the Census Bureau’s Cartographic Boundary Shapefiles. Our senior
statistician uploaded these mapping data along with our FBC incidence results
obtained by analyzing MCR data using SEER*Stat to InstantAtlas™ data
visualization software to generate interactive maps [17,18]. These interactive maps,
in addition to the FBC incidence rates, also display mortality for FBC and other
cancers and survival data on county, senate district, and senate district grouped to
county boundaries (SDGC). The maps visualize FBC incidence data and the mapping
reports are in two layouts: Area profile and double map formats. These maps consist
of joint spatial and statistical data. The following figures show the final layouts
of the InstantAtlas™ mapping reports we constructed at the Missouri Cancer
Registry and Research Center (MCR-ARC) to present Missouri FBC incidence data.Both mapping reports displayed our results in different formats (example: charts,
tables, maps) [17,18]. The area profile report shows a single map and focuses on
displaying many indicators for every senate district and compares the
districts’ findings to each other and to Missouri. The double map focuses on
exploring the inferential statistical relationships between the selected indicators
[17,18].
Discussion
The central cancer registry database is created from different data sources,
including hospitals (inpatient and outpatient settings), pathology labs, ambulatory
surgical centers, long-term care facilities, physician offices and free-standing
cancer clinics and treatment centers (192.650-192.657 RSMo) and data exchange with
other states’ central registry. The MCR data undergo strict quality control
measures and the data have been assessed continually according to nationwide
standards [1,2]. For all these reasons, central cancer registry databases are
considered the best population-based sources to estimate the distribution of cancer
incidence within the studied states.Calculation and visualization of the FBC age-standardized incidence rates could help
public health officials and policy makers to be informed about FBC distribution by age,
race, grade and stage at diagnosis, and senate district. This might effectively
impact FBC policy and research, determine female at-risk groups, support targeting
FBC geographical foci, and evaluate and compare diagnostic and treatment strategies
all over Missouri.
Potential Problems
In high population density areas — Kansas City metropolitan area, Saint
Louis metropolitan area and the City of Springfield — district limits do
not follow county boundaries [19]. In
these areas, the Census Bureau’s TIGER/Line shapefiles software was used
to determine the district containing the latitude and longitude of the address
at diagnosis [14].A problem encountered is that we did not have successfully geocoded street
addresses of all FBC cases due to missing or inaccurate addresses. In these
situations, we categorized them as residents of the most likely senate district
by matching to cases that were successfully assigned into their senate district
with the same county (if known), race (if known and categorized as white,
African-American, and other), year of diagnosis (categorized into two time
periods), and the nine-digit Postal ZIP Code. When multiple senate districts
matched, then the most common one was selected; when none matched, then the
process was iteratively repeated by removing the least significant digit of the
Postal ZIP Code until a senate district was imputed for every case.Unlike with county-level data, a detailed population file by age (in 19 groups of
mostly 5-years except with <1 year-olds and 85+), race (bridged single-race),
year, and sex was not found at the senate district level and had to be
constructed. The limitations of this population file are that for senate
districts that do not follow county boundaries, there is a mismatch between the
Office of Management and Budget (OMB) 1977 and 1997 race classifications;
granular age-groupings were approximated; and there is an increasing inaccuracy
as one moves away from 2009-2013.
Conclusion
Measurement of incidence rates by race, age, stage and grade at diagnosis and
district of residence may provide an estimation of social inequality within the
state and could provide clues about the impact of level of coverage and
accessibility to screening and health care services on disease prevention and early
diagnosis [1]. The detailed and visually
presented FBC age-adjusted incidence profiles by senate district might lead
researchers and policy makers to understand effectiveness of current breast cancer
initiatives and interventions and give clues about possible environmental and
socioeconomic risk factors on breast cancer.According to the study results and by future research based on these results, policy
makers might embrace new effective breast cancer screening and prevention
initiatives and interventions in Missouri, nationally, and internationally.
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