Geographic Residency Status and Census Tract Socioeconomic Status as Determinants of Colorectal Cancer Outcomes

Hines, Rebecca; Markossian, Talar; Johnson, Asal M.; Dong, Frank; Bayakly, Rana

doi:10.2105/ajph.2013.301572

Cited by 94 publications

(112 citation statements)

References 55 publications

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“…These findings expand on previously reported state disparities in colorectal cancer death rates (3) and are consistent with recent research linking rural residence with increased risk of colorectal cancer death (12,13). The trends in Hotspots 1 and 3 are also compatible with the historical shift in the burden of colorectal cancer from more to less affluent individuals (5).…”

Section: Discussionsupporting

confidence: 89%

Where Can Colorectal Cancer Screening Interventions Have the Most Impact?

Siegel

Sahar

Robbins

et al. 2015

Cancer Epidemiology, Biomarkers &Amp; Prevention

101

112

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Background: Although colorectal cancer death rates in the United States have declined by half since 1970, large geographic disparities persist. Spatial identification of high-risk areas can facilitate targeted screening interventions to close this gap.Methods: We used the Getis-Ord Gi Ã statistic within ArcGIS to identify contemporary colorectal cancer "hotspots" (spatial clusters of counties with high rates) based on county-level mortality data from the national vital statistics system. Hotspots were compared with the remaining aggregated counties (non-hotspot United States) by plotting trends from 1970 to 2011 and calculating rate ratios (RR). Trends were quantified using joinpoint regression.Results: Spatial mapping identified three distinct hotspots in the contemporary United States where colorectal cancer death rates were elevated. The highest rates were in the largest hotspot, which encompassed 94 counties in the Lower Mississippi Delta

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Section: Discussionsupporting

confidence: 89%

Where Can Colorectal Cancer Screening Interventions Have the Most Impact?

Siegel

Sahar

Robbins

et al. 2015

Cancer Epidemiology, Biomarkers &Amp; Prevention

101

112

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“…Variables of interest included race, sex, age at diagnosis, date of diagnosis, tumor-related information (stage and grade), treatment type, last date of follow-up and vital status at last follow-up. Using the corresponding CT, 2000 U.S. Census data and Rural Urban Commuting Area (RUCA) codes from the U.S. Department of Agriculture were merged with GCCR data (24,25). RUCA codes were used to classify each patient as urban, suburban, or rural (26)(27)(28).…”

Section: Study Variablesmentioning

confidence: 99%

The Effects of Residential Segregation and Neighborhood Characteristics on Surgery and Survival in Patients with Early-Stage Non–Small Cell Lung Cancer

Johnson

Hines

et al. 2016

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background: Although the negative effects of lower socioeconomic status on non-small cell lung cancer (NSCLC) treatment and survival have been widely studied, the impact of residential segregation on prognosis and the receipt of treatment has yet to be determined.Methods: This is a retrospective, cohort study of NSCLC patients in Georgia (2000-2009; n ¼ 8,322) using data from the Georgia Comprehensive Cancer Registry. The effects of segregation, economic deprivation, and combined segregation/deprivation on the odds of receiving surgery were examined in separate multilevel models. To determine the association for the exposures of interest on the risk of death for different racial groups, separate multilevel survival models were conducted for black and white patients.Results: Living in areas with the highest [AOR ¼ 0.35, 95% confidence interval (CI), 0.19-0.64] and second highest

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“…While these effects were diminished in sensitivity analyses among women with confirmed HER2 status, regional variations in other unrelated aspects of cancer care and outcomes are well-documented. 40–42 Regional variation in GEP testing could reflect continued clinical uncertainty or professional disagreements among oncologists regarding the utility of GEP testing. Finally, we found that testing rates were higher for patients with greater out of pocket burden for pharmacy costs.…”

Section: Discussionmentioning

confidence: 99%

Adoption of Gene Expression Profiling for Breast Cancer in US Oncology Practice for Women Younger Than 65 Years

O’Neill¹,

Isaacs²,

Chao³

et al. 2015

J Natl Compr Canc Netw

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Background Four practice guidelines incorporate the use of gene expression profiling (GEP) tests for early-stage, hormone-receptor positive, HER2 negative breast tumors. Few studies describe factors associated with GEP testing in US oncology practice. We assessed the relationship between clinical, demographic, and group-level socioeconomic variables and test use in women under age 65. Patients and Methods Data from five state cancer registries were linked with insurance claims data and GEP test results. We assessed rates of testing and variables associated with test use in an incident cohort of 9444 commercially-insured women under age 65, newly-diagnosed with Stage I or II hormone-receptor positive breast cancer from 2006–2012. Results Rates of testing for women with N0 disease increased from 20.4% in 2006 to 35.2% in 2011. Variables associated with higher rates of testing, beyond clinical factors such as nodal status (P < .001), included being diagnosed from 2008–2012 vs. 2006–2007 (adjusted odds ratio, 1.67; 95% CI, 1.47 to 1.90), having preexisting comorbidities (adjusted odds ratio, 1.35; 95% CI, 1.14 to 1.59), and higher out-of-pocket pharmacy costs (adjusted odds ratio, 1.66; 95% CI, 1.40 to 1.97). Women under age 50 were more likely to be tested if they had Stage I vs. Stage II disease (P < .0001). Conclusions In an insured population of women under age 65, GEP testing increased following its inclusion in guidelines and mounting evidence. Additional research is needed to better understand oncologists’ decision not to order GEP testing for their patients who are otherwise eligible.

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Geographic Residency Status and Census Tract Socioeconomic Status as Determinants of Colorectal Cancer Outcomes

Abstract: Future efforts should focus on developing interventions and policies that target rural residents and lower SES areas to eliminate disparities in CRC-related outcomes.

Cited by 94 publications

References 55 publications

Where Can Colorectal Cancer Screening Interventions Have the Most Impact?

Where Can Colorectal Cancer Screening Interventions Have the Most Impact?

The Effects of Residential Segregation and Neighborhood Characteristics on Surgery and Survival in Patients with Early-Stage Non–Small Cell Lung Cancer

Adoption of Gene Expression Profiling for Breast Cancer in US Oncology Practice for Women Younger Than 65 Years

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