Temporal trends in geographic disparities in small-area breast cancer incidence and mortality, 1988 to 2005

Exploring age-standardized cancer incidence rates and regional disparities: A retrospective cohort study of 8 major cancers in South Korea

BACKGROUND

We analyzed trends in cancer incidence and regional disparities of eight major types of cancer in Korea.

METHODS

This retrospective cohort study used the data of 17 cities/provinces from the Korea Central Cancer Registry (1999-2020) in South Korea. Age-standardized incidence rates (per 100,000 person-years), between-group variance (per 100,000 person-years)2, and annual percentage changes ( %) were calculated for the eight most common malignancies. Joinpoint regression was utilized to identify the points at which significant changes occur in cancer incidence or regional disparity trends over time to characterize these trends.

RESULTS

The incidence of stomach cancer decreased as regional disparity decreased and that of colorectal cancer initially increased but recently declined, showing fluctuations in regional disparity. The incidence and regional disparity in liver cancer decreased. The incidence of lung cancer remained stable, with reduced regional disparities. The incidence of breast cancer rose with increasing regional disparity, whereas the incidence of cervical cancer decreased, accompanied by decreased regional disparity. A significant increase in prostate cancer was found, with initially reduced regional disparities but later showed a resurgence. The incidence of thyroid cancer fluctuated alongside variations in regional disparities.

CONCLUSION

This study revealed cancer incidence and regional variations in each cancer type in Korea. More studies are needed to understand the underlying factors and potential interventions for reducing cancer incidence and addressing regional disparity.

Evaluation of ionizing radiation as a risk factor for the incidence of breast cancer: long-term analysis after the cesium-137 accident in Goiânia, Brazil. An ecological study

BACKGROUND

The largest radiological accident to occur in any urban area happened in Goiânia, Brazil, in 1987.

OBJECTIVE

To evaluate the association between breast cancer incidence and ionizing radiation levels.

DESIGN AND SETTING

Ecological study among residents of the city of Goiânia, Brazil.

METHODS

The central region of Goiânia, with seven major sources of contamination from cesium-137, was defined as the study area. The addresses of women diagnosed with breast cancer were identified between 2001 and 2010. The data were geographically referenced and, using census data, the annual averages of crude incidence rates were estimated. The existence of clusters of new cases was ascertained by means of the Moran index. Correlations of radiometric measurements with the incidence were assessed using unconditional linear regression.

RESULTS

A total of 4,105 new cases were identified, of which 2,233 were in the study area, and of these, 1,286 (57.59%) were georeferenced. The gross rates of total and referenced cases were 102.91 and 71.86/100,000 women, respectively. These were close to the average for Brazilian state capitals, which is 79.37/100,000 women. The cluster analysis showed slight correlations in three small sets of census tracts, but these were far from the sources of contamination. The scatter plot of points and the R2 value close to zero indicated that there was no association between the variables.

CONCLUSION

This study reinforces the hypothesis that the ionizing radiation levels to which women living in Goiânia are now exposed to are not associated with the onset of new cases of breast cancer.

Regional diagnostic rates, treatments, and outcomes among patients with invasive ductal carcinoma

BACKGROUND

The association between regional breast cancer diagnostic rates, treatments, and outcomes is unclear. We sought to investigate the management and survival of women with invasive ductal carcinoma (IDC) from geographic regions with variable rates of diagnosis.

METHODS

Data on women diagnosed with IDC years 2009-2010 were obtained from the Surveillance, Epidemiology, and End Results database. Patients were divided into quartiles based on the IDC diagnostic rate within their county of residence. Chi-square and one-way analysis of variance (ANOVA) analyses tested the association between patient and clinical characteristics and the diagnostic rate quartiles. Cox regression analyses compared survival between the quartiles.

RESULTS

Among the 83,375 patients included, the mean age was 60.8 y and 70.9% were white. Patients residing in counties with the highest diagnostic rates were more frequently white, employed, educated, and wealthier and more often received adjuvant radiation following both partial mastectomy for localized disease and complete mastectomy for advanced disease compared to patients in counties with the lowest diagnostic rates. The highest diagnostic rate quartile had 10% decreased odds of death compared to the lower quartile (hazard ratio: 0.897; 95% confidence interval: 0.832-0.966). However, after adjustment for socioeconomic variables, survival was comparable (hazard ratio: 0.916; 95% confidence interval: 0.835-1.003).

CONCLUSIONS

Regional variation in IDC diagnostic rates is associated with differences in socioeconomic status, grade, stage, and treatment. Patients from regions with the highest rates of diagnosis may have improved access to evidence-based care and resultant superior survival. Enhancing access to care may improve outcomes of patients residing in regions where breast cancer is diagnosed less frequently.

Mapping hot spots of breast cancer mortality in the United States: place matters for Blacks and Hispanics

PURPOSE

The goals of this study were to identify geographic and racial/ethnic variation in breast cancer mortality, and evaluate whether observed geographic differences are explained by county-level characteristics.

METHODS

We analyzed data on breast cancer deaths among women in 3,108 contiguous United States (US) counties from years 2000 through 2015. We applied novel geospatial methods and identified hot spot counties based on breast cancer mortality rates. We assessed differences in county-level characteristics between hot spot and other counties using Wilcoxon rank-sum test and Spearman correlation, and stratified all analysis by race/ethnicity.

RESULTS

Among all women, 80 of 3,108 (2.57%) contiguous US counties were deemed hot spots for breast cancer mortality with the majority located in the southern region of the US (72.50%, p value < 0.001). In race/ethnicity-specific analyses, 119 (3.83%) hot spot counties were identified for NH-Black women, with the majority being located in southern states (98.32%, p value < 0.001). Among Hispanic women, there were 83 (2.67%) hot spot counties and the majority was located in the southwest region of the US (southern = 61.45%, western = 33.73%, p value < 0.001). We did not observe definitive geographic patterns in breast cancer mortality for NH-White women. Hot spot counties were more likely to have residents with lower education, lower household income, higher unemployment rates, higher uninsured population, and higher proportion indicating cost as a barrier to medical care.

CONCLUSIONS

We observed geographic and racial/ethnic disparities in breast cancer mortality: NH-Black and Hispanic breast cancer deaths were more concentrated in southern, lower SES counties.

Tumoral expression of drug and xenobiotic metabolizing enzymes in breast cancer patients of different ethnicities with implications to personalized medicine

Drug and xenobiotic metabolizing enzymes (DXME) play important roles in drug responses and carcinogenesis. Recent studies have found that expression of DXME in cancer cells significantly affects drug clearance and the onset of drug resistance. In this study we compared the expression of DXME in breast tumor tissue samples from patients representing three ethnic groups: Caucasian Americans (CA), African Americans (AA), and Asian Americans (AS). We further combined DXME gene expression data with eQTL data from the GTEx project and with allele frequency data from the 1000 Genomes project to identify SNPs that may be associated with differential expression of DXME genes. We identified substantial differences among CA, AA, and AS populations in the expression of DXME genes and in activation of pathways involved in drug metabolism, including those involved in metabolizing chemotherapy drugs that are commonly used in the treatment of breast cancer. These data suggest that differential expression of DXME may associate with health disparities in breast cancer outcomes observed among these three ethnic groups. Our study suggests that development of personalized treatment strategies for breast cancer patients could be improved by considering both germline genotypes and tumor specific mutations and expression profiles related to DXME genes.

New algorithm for constructing area-based index with geographical heterogeneities and variable selection: An application to gastric cancer screening

To optimally allocate health resources, policy planners require an indicator reflecting the inequality. Currently, health inequalities are frequently measured by area-based indices. However, methodologies for constructing the indices have been hampered by two difficulties: 1) incorporating the geographical relationship into the model and 2) selecting appropriate variables from the high-dimensional census data. Here, we constructed a new area-based health coverage index using the geographical information and a variable selection procedure with the example of gastric cancer. We also characterized the geographical distribution of health inequality in Japan. To construct the index, we proposed a methodology of a geographically weighted logistic lasso model. We adopted a geographical kernel and selected the optimal bandwidth and the regularization parameters by a two-stage algorithm. Sensitivity was checked by correlation to several cancer mortalities/screening rates. Lastly, we mapped the current distribution of health inequality in Japan and detected unique predictors at sampled locations. The interquartile range of the index was 0.0001 to 0.354 (mean: 0.178, SD: 0.109). The selections from 91 candidate variables in Japanese census data showed regional heterogeneities (median number of selected variables: 29). Our index was more correlated to cancer mortalities/screening rates than previous index and revealed several geographical clusters with unique predictors.

Comparing methods of measuring geographic patterns in temporal trends: an application to county-level heart disease mortality in the United States, 1973 to 2010

PURPOSE

To demonstrate the implications of choosing analytical methods for quantifying spatiotemporal trends, we compare the assumptions, implementation, and outcomes of popular methods using county-level heart disease mortality in the United States between 1973 and 2010.

METHODS

We applied four regression-based approaches (joinpoint regression, both aspatial and spatial generalized linear mixed models, and Bayesian space-time model) and compared resulting inferences for geographic patterns of local estimates of annual percent change and associated uncertainty.

RESULTS

The average local percent change in heart disease mortality from each method was -4.5%, with the Bayesian model having the smallest range of values. The associated uncertainty in percent change differed markedly across the methods, with the Bayesian space-time model producing the narrowest range of variance (0.0-0.8). The geographic pattern of percent change was consistent across methods with smaller declines in the South Central United States and larger declines in the Northeast and Midwest. However, the geographic patterns of uncertainty differed markedly between methods.

CONCLUSIONS

The similarity of results, including geographic patterns, for magnitude of percent change across these methods validates the underlying spatial pattern of declines in heart disease mortality. However, marked differences in degree of uncertainty indicate that Bayesian modeling offers substantially more precise estimates.

The increasing incidence of thyroid cancer: the influence of access to care

BACKGROUND

The rapidly rising incidence of papillary thyroid cancer may be due to overdiagnosis of a reservoir of subclinical disease. To conclude that overdiagnosis is occurring, evidence for an association between access to health care and the incidence of cancer is necessary.

METHODS

We used Surveillance, Epidemiology, and End Results (SEER) data to examine U.S. papillary thyroid cancer incidence trends in Medicare-age and non-Medicare-age cohorts over three decades. We performed an ecologic analysis across 497 U.S. counties, examining the association of nine county-level socioeconomic markers of health care access and the incidence of papillary thyroid cancer.

RESULTS

Papillary thyroid cancer incidence is rising most rapidly in Americans over age 65 years (annual percentage change, 8.8%), who have broad health insurance coverage through Medicare. Among those under 65, in whom health insurance coverage is not universal, the rate of increase has been slower (annual percentage change, 6.4%). Over three decades, the mortality rate from thyroid cancer has not changed. Across U.S. counties, incidence ranged widely, from 0 to 29.7 per 100,000. County papillary thyroid cancer incidence was significantly correlated with all nine sociodemographic markers of health care access: it was positively correlated with rates of college education, white-collar employment, and family income; and negatively correlated with the percentage of residents who were uninsured, in poverty, unemployed, of nonwhite ethnicity, non-English speaking, and lacking high school education.

CONCLUSION

Markers for higher levels of health care access, both sociodemographic and age-based, are associated with higher papillary thyroid cancer incidence rates. More papillary thyroid cancers are diagnosed among populations with wider access to healthcare. Despite the threefold increase in incidence over three decades, the mortality rate remains unchanged. Together with the large subclinical reservoir of occult papillary thyroid cancers, these data provide supportive evidence for the widespread overdiagnosis of this entity.

Efficient mapping and geographic disparities in breast cancer mortality at the county-level by race and age in the U.S

This study identified geographic disparities in breast cancer mortality across the U.S. using kriging to overcome unavailability of data because of confidentiality and reliability concerns. A structured additive regression model was used to detect where breast cancer mortality rates were elevated across nine divisions with 3109 U.S. counties during 1982-2004. Our analysis identified at least 25.8% of counties where breast cancer mortality rates were elevated. High-risk counties compared to lower-risk counties had higher relative risks for African American women than for White women. Greater geographic disparities more likely present in African American women and younger women. To sum up, our statistical approach reduced the impact of unavailable data, and identified the number and location of counties with high breast cancer mortality risk by race and age across the U.S.

Analysis of geographical disparities in temporal trends of health outcomes using space-time joinpoint regression

Analyzing temporal trends in health outcomes can provide a more comprehensive picture of the burden of a disease like cancer and generate new insights about the impact of various interventions. In the United States such an analysis is increasingly conducted using joinpoint regression outside a spatial framework, which overlooks the existence of significant variation among U.S. counties and states with regard to the incidence of cancer. This paper presents several innovative ways to account for space in joinpoint regression: (1) prior filtering of noise in the data by binomial kriging and use of the kriging variance as measure of reliability in weighted least-square regression, (2) detection of significant boundaries between adjacent counties based on tests of parallelism of time trends and confidence intervals of annual percent change of rates, and (3) creation of spatially compact groups of counties with similar temporal trends through the application of hierarchical cluster analysis to the results of boundary analysis. The approach is illustrated using time series of proportions of prostate cancer late-stage cases diagnosed yearly in every county of Florida since 1980s. The annual percent change (APC) in late-stage diagnosis and the onset years for significant declines vary greatly across Florida. Most counties with non-significant average APC are located in the north-western part of Florida, known as the Panhandle, which is more rural than other parts of Florida. The number of significant boundaries peaked in the early 1990s when prostate-specific antigen (PSA) test became widely available, a temporal trend that suggests the existence of geographical disparities in the implementation and/or impact of the new screening procedure, in particular as it began available.

Trends in breast cancer stage and mortality in Michigan (1992-2009) by race, socioeconomic status, and area healthcare resources

The long-term effect of socioeconomic status (SES) and healthcare resources availability (HCA) on breast cancer stage of presentation and mortality rates among patients in Michigan is unclear. Using data from the Michigan Department of Community Health (MDCH) between 1992 and 2009, we calculated annual proportions of late-stage diagnosis and age-adjusted breast cancer mortality rates by race and zip code in Michigan. SES and HCA were defined at the zip-code level. Joinpoint regression was used to compare the Average Annual Percent Change (AAPC) in the median zip-code level percent late stage diagnosis and mortality rate for blacks and whites and for each level of SES and HCA. Between 1992 and 2009, the proportion of late stage diagnosis increased among white women [AAPC = 1.0 (0.4, 1.6)], but was statistically unchanged among black women [AAPC = −0.5 (−1.9, 0.8)]. The breast cancer mortality rate declined among whites [AAPC = −1.3% (−1.8,−0.8)], but remained statistically unchanged among blacks [AAPC = −0.3% (−0.3, 1.0)]. In all SES and HCA area types, disparities in percent late stage between blacks and whites appeared to narrow over time, while the differences in breast cancer mortality rates between blacks and whites appeared to increase over time.

State-of-the-art and future directions in multilevel interventions across the cancer control continuum

We conducted literature searches and analyses to describe the current state of multilevel intervention (MLI) research and to identify opportunities to advance cancer control and prevention. We found single-level studies that considered other contextually important levels, and multilevel health-care systems research and community-wide studies. This literature is characterized by limited reporting of theoretical, contextual, temporal, and implementation factors. Most MLIs focus on prevention and screening, rather than diagnosis, treatment, or survivorship. Opportunities relate to 1) dynamic, adaptive emergent interventions and research designs that evolve over time by attending to contextual factors and interactions across levels; 2) analyses that include simulation modeling, or multimethod approaches that integrate quantitative and qualitative methods; and 3) translation and intervention approaches that locally reinvent MLIs in different contexts. MLIs have great potential to reduce cancer burden by using theory and integrating quantitative, qualitative, participatory, and transdisciplinary methods that continually seek alignment across intervention levels, pay attention to context, and adapt over time.

Geographical, temporal and racial disparities in late-stage prostate cancer incidence across Florida: a multiscale joinpoint regression analysis

BACKGROUND

Although prostate cancer-related incidence and mortality have declined recently, striking racial/ethnic differences persist in the United States. Visualizing and modelling temporal trends of prostate cancer late-stage incidence, and how they vary according to geographic locations and race, should help explaining such disparities. Joinpoint regression is increasingly used to identify the timing and extent of changes in time series of health outcomes. Yet, most analyses of temporal trends are aspatial and conducted at the national level or for a single cancer registry.

METHODS

Time series (1981-2007) of annual proportions of prostate cancer late-stage cases were analyzed for non-Hispanic Whites and non-Hispanic Blacks in each county of Florida. Noise in the data was first filtered by binomial kriging and results were modelled using joinpoint regression. A similar analysis was also conducted at the state level and for groups of metropolitan and non-metropolitan counties. Significant racial differences were detected using tests of parallelism and coincidence of time trends. A new disparity statistic was introduced to measure spatial and temporal changes in the frequency of racial disparities.

RESULTS

State-level percentage of late-stage diagnosis decreased 50% since 1981; a decline that accelerated in the 90's when Prostate Specific Antigen (PSA) screening was introduced. Analysis at the metropolitan and non-metropolitan levels revealed that the frequency of late-stage diagnosis increased recently in urban areas, and this trend was significant for white males. The annual rate of decrease in late-stage diagnosis and the onset years for significant declines varied greatly among counties and racial groups. Most counties with non-significant average annual percent change (AAPC) were located in the Florida Panhandle for white males, whereas they clustered in South-eastern Florida for black males. The new disparity statistic indicated that the spatial extent of racial disparities reached a peak in 1990 because of an early decline in frequency of late-stage diagnosis observed for black males.

CONCLUSIONS

Analyzing temporal trends in cancer incidence and mortality rates outside a spatial framework is unsatisfactory, since it leads one to overlook significant geographical variation which can potentially generate new insights about the impact of various interventions. Differences observed among nested geographies in Florida show how the modifiable areal unit problem (MAUP) also impacts the analysis of temporal changes.

Temporal trends in geographic disparities in small-area-level colorectal cancer incidence and mortality in the United States

OBJECTIVE

We examined the extent of changes in absolute and relative geographic disparities in six colorectal cancer (CRC) indicators using data about persons aged 50 and older from 195 counties in the 1988-2006 Surveillance, Epidemiology, and End Results Program database.

METHODS

County-level trends in six colorectal cancer indicators (overall CRC incidence, descending colon cancer incidence, proximal colon cancer incidence, late-stage CRC incidence, CRC mortality, and 5-year probability of CRC death) were summarized using the estimated annual percentage change. Observed county rates were smoothed using Bayesian hierarchical spatiotemporal methods to calculate measures of absolute and relative geographic disparity and their changes over time.

RESULTS

During the study period, absolute disparity for all six indicators decreased (CRC incidence: 43.2%; proximal colon cancer: 31.9%; descending colon cancer: 52.8%; late-stage CRC: 50.0%; CRC mortality: 57.8%; 5-year CRC-specific probability of death: 12.2%). Relative disparity remained stable for all six indicators over the entire study period.

CONCLUSION

Important progress has been made toward achieving the Healthy People 2010 and NCI strategic objectives for reducing geographic disparities, although absolute and relative disparities remain in CRC.

Association of the joint effect of menopause and hormone replacement therapy and cancer in African American women: the Jackson Heart Study

Cancer is the second leading cause of death in the US and in Mississippi. Breast cancer (BC) is the most common cancer among women, and the underlying pathophysiology remains unknown, especially among African American (AA) women. The study purpose was to examine the joint effect of menopause status (MS) and hormone replacement therapy (HRT) on the association with cancers, particularly BC using data from the Jackson Heart Study. The analytic sample consisted of 3202 women between 35 and 84 years of which 73.7% and 22.6% were postmenopausal and on HRT, respectively. There were a total of 190 prevalent cancer cases (5.9%) in the sample with 22.6% breast cancer cases. Menopause (p<0.0001), but not HRT (p=0.6402), was independently associated with cancer. Similar results were obtained for BC. BC, cancer, hypertension, type 2 diabetes, prevalent cardiovascular disease, physical activity and certain dietary practices were all significantly associated with the joint effect of menopause and HRT in the unadjusted analyses. The family history of cancer was the only covariate that was significantly associated with cancer in the age-adjusted models. In examining the association of cancer and the joint effect of menopause and HRT, AA women who were menopausal and were not on HRT had a 1.97 (95% CI: 1.15, 3.38) times odds of having cancer compared to pre-menopausal women after adjusting for age; which was attenuated after further adjusting for family history of cancer. Given that the cancer and BC cases were small and key significant associations were attenuated after adjusting for the above mentioned covariates, these findings warrant further investigation in studies with larger sample sizes of cancer (and BC) cases.