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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Cancer. Author manuscript; available in PMC 2011 October 1.
Published in final edited form as:
PMCID: PMC2946464

Racial Disparities in Colorectal Cancer Survival: To What Extent Are Racial Disparities Explained by Differences in Treatment, Tumor or Hospital Characteristics?

Arica L. White, PhD, MPH,1 Sally W. Vernon, PhD,1,2 Luisa Franzini, PhD,3 and Xianglin L. Du, MD, PhD1,3



Racial/ethnic differences in colorectal cancer (CRC) survival have been documented throughout the literature. However, the reasons for these disparities are difficult to decipher. The objective of this analysis was to determine to what extent racial/ethnic disparities in survival are explained by differences in socio-demographics, tumor characteristics, diagnosis, treatment and hospital characteristics.


A cohort of 37,769 Medicare beneficiaries diagnosed with American Joint Committee on Cancer (AJCC) stages I-III CRC from 1992 to 2002 and residing in 16 Surveillance, Epidemiology and End Results (SEER) regions of the United States was identified in the SEER-Medicare linked database. Survival was estimated using the Kaplan-Meier method. Cox proportional hazard modeling was used to estimate hazard ratios (HR) of mortality and 95% confidence intervals (95% CI).


Blacks had worse CRC-specific survival than Whites but this was reduced after adjustment (aHR=1.24; 95%CI:1.14-1.35). Asians had better survival than Whites after adjusting for covariates (aHR=0.80; 95%CI: 0.70-0.92) for stages I-III CRC. Relative to Asians, Blacks and Whites had worse survival after adjustment (aHR=1.55; 95% CI:1.33-1.81; aHR=1.25; 95%CI:1.09-1.43, respectively). Comorbidities and SES were associated with a reduction in the mortality difference between Blacks and Whites and Blacks and Asians.


Comorbidities and SES appear to be more important factors contributing to Blacks’ poorer survival relative to Whites and Asians. However, racial/ethnic differences in CRC survival were not fully explained by differences in a number of factors. Future research should further examine the role of quality of care, the benefit of treatment and post-treatment surveillance in survival disparities.


Colorectal cancer (CRC) is the third most frequently diagnosed non-skin cancer in men and women in the United States.1 In 2009, it was estimated that there would be 146,970 new cases of CRC and 49,920 deaths, accounting for 9% of all cancer deaths in the United States.1 Over the past two decades, there has been a decline in mortality rates, which reflects declining incidence rates and medical advances in early detection and treatment.1 Despite this progress, CRC incidence and mortality varies considerably by race/ethnicity,1 with non-Hispanic Black (hereafter Black) males and females having the highest incidence and mortality, and Hispanics/Latino females and American Indian/Alaskan Native males having the lowest rates.1

Racial/ethnic disparities in CRC survival have been extensively documented in the scientific literature.2-6 These disparities may be attributed to many factors including differences in socioeconomic status (SES),3 tumor biology,7, 8 stage at diagnosis,4, 5 treatment,9-11 post-treatment surveillance,12, 13 physician characteristics,14, 15 and hospital factors.16, 17 Most studies have found that non-Hispanic Blacks have poorer survival relative to non-Hispanic Whites (hereafter White).2-6 The few studies that have included Hispanics and/or Asian/Pacific Islanders (hereafter Asian)2, 4, 6, 18 found that relative to Whites, Hispanics have worse survival 4,18 and Asians have better survival.2, 6 However, no studies have examined survival of other racial/ethnic groups relative to Asians.

The purpose of this study was to determine the degree to which racial disparities in survival were explained by differences in socio-demographic factors, tumor characteristics, diagnosis, treatment, and hospital characteristics. We compared factors contributing to survival disparities between Whites and other racial groups and between Asians and other racial groups in order to reveal the underlying mechanisms of racial/ethnic disparities in survival as they relate to specific racial groups. These findings may inform targeted interventions that may ameliorate or eliminate these disparities.


Data Sources

Incident CRC cases were identified from the Surveillance, Epidemiology and End Results Program-Medicare (SEER-Medicare) linked database. These data files were used to obtain information about tumor characteristics, treatment, vital status, and other factors for persons diagnosed with CRC at age 66 years and older.19

This study included 16 SEER registries in selected geographic areas: San Francisco/Oakland, Detroit, Seattle, Atlanta, Rural Georgia, Los Angeles county, the San Jose-Monterey area, and the rest of California; and the states of Connecticut, Iowa, New Mexico, Utah, Hawaii, Kentucky, Louisiana and New Jersey, which covers approximately 25% of the U.S. population since 2000.19 California registries were combined and so were Rural Georgia and Atlanta registries. Patients who did not have both Medicare Parts A and B, or were members of a Health Maintenance Organization (HMO) within one year prior to and one year after diagnosis were excluded from this study to ensure completeness of Medicare claims. The University of Texas Health Science Center at Houston Committee for Protection of Human Subjects approved the study protocol.

Study Population

The study population consisted of 37,769 men and women, aged ≥66 years, diagnosed with primary CRC (ICD-0-3 codes C180–C189, C199, C209)20 between January 1, 1992 and December 31, 2002. Of these, 87.4% were White, 7.1% were Black, 4.0% were Asian, and 1.6% were Hispanic. Race/ethnicity was based on racial classification in the Medicare Enrollment. A minimum age of 66 years was set to allow at least 1 year of eligibility in Medicare prior to the date of CRC diagnosis to ascertain comorbidity data.

Study Variables

Outcome: Survival

Survival time in months was calculated from the date of diagnosis to the date of death or date of last follow-up (December 31, 2005). The day of diagnosis was defined as the 15th of the month, since SEER only reported the month and year of diagnosis. CRC-specific mortality was defined if CRC was the underlying cause of death. Patients who died of causes other than CRC or were still alive at the last follow-up were censored. The follow-up time ranged from 3 to 13 years.

Socioeconomic status (SES)

Since individual-level SES data is not available in the SEER-Medicare linked data, the percentage of residents living below the federal poverty level, an aggregated measure of SES at the census tract level from the 1990 Census for 1992-99 cases and the 2000 Census for 2000-02 cases, was used in the analysis. This measure is based on a set of money income thresholds that vary by family size and composition.21 These thresholds are used by the Census to determine who is in poverty or below 200% of the federal poverty line.21 Prior studies have demonstrated that poverty level could be the most directly relevant proxy measure of economic status for elderly Medicare beneficiaries.22, 23 This variable was categorized into quartiles: first (<4.04%), second (4.05–7.61%), third (7.62–13.89%), and fourth (>13.90% or poorest SES).



SEER and Medicare codes were used to identify surgery. The detailed methods for the identification of surgical resection through Medicare claims have been described previously.10


Chemotherapy was identified in the Medicare claims. These methods have been described previously.10


Radiation therapy administration within 12 months of diagnosis was ascertained from Medicare claims using ICD-9-CM procedure (92.21-92.29),24 Current Procedural Terminology (77401-77499 or 77750-77799),25 and revenue codes26 (0330 or 0333).

Standard Therapy

Standard therapy was defined based on the Physician Data Query (PDQ) guidelines27, 28 from the National Cancer Institute and is American Joint Committee on Cancer (AJCC) stage-specific. Details regarding the categorization of this variable are described elsewhere.10

Comorbidity score

Comorbidities were ascertained from Medicare claims by identifying eighteen diagnoses or related procedures recorded between one year prior to and one month after the diagnosis of CRC. A weighted comorbidity score was created. Comorbidity score was coded as 0, 1, 2, 3, or 4 or more. Details on creating this variable have been previously reported.29, 30

Other Characteristics

The following patient and tumor characteristics were also assessed in the study: age, sex, marital status, SEER registry, year of diagnosis (1992-2002), AJCC tumor stage, tumor size, tumor grade, number of lymph nodes positive and rural residence. Hospital characteristics included National Cancer Institute designated cancer center as of 2002, teaching hospital and type of hospital.

Statistical Analysis

All data was analyzed using the statistical software package Intercooled Stata version 10.0 (College Station, TX). The distribution of baseline characteristics among the racial/ethnic groups was assessed for differences using the chi-square statistic. Crude survival was estimated using Kaplan-Meier. The log rank test for equality of survivor functions was used to determine whether there were differences in the observed survival by race/ethnicity. Cox proportional hazards regression models were used to estimate the relative risk of dying from CRC. Two series of statistical models (using Whites and then Asians as referent groups) were used to assess the relationship between race/ethnicity and survival after adjusting for a variety of factors. To determine to what extent racial disparities are explained by each of these factors, the reduction or increase in magnitude of the hazard ratios (HR) from one model to the next was calculated.


There were statistically significant differences for all demographic and tumor characteristics for patients diagnosed with CRC from 1992 through 2002 by race/ethnicity (p<0.05) (Table 1). The greatest differences were in SES. Significantly higher percentages of Blacks, Hispanics and Asians resided in the lowest SES areas compared to Whites.

Table 1
Demographic and tumor characteristics of men and women diagnosed with AJCC stages I, II and III colorectal cancer from 1992-2002, by race/ethnicity (percent)

CRC-Specific Mortality

There were significant differences in CRC-specific survival across race/ethnicity (log rank test, p-value <0.0001) (Figure 1A). The survival curve was highest for Asians and lowest for Blacks. The curves for both Whites and Hispanics were between these groups, with the curve for Hispanic higher than the curve for Whites.

Figure 1
Colorectal cancer specific survival for men and women diagnosed with AJCC stages I-III colorectal cancer from 1992 to 2002, by race/ethnicity

Disparities Relative to Whites

Table 2 shows the CRC-specific mortality associated with race/ethnicity in individuals diagnosed with CRC from 1992 to 2002. Blacks had a significantly higher risk of dying (HR=1.33; 95%CI:1.23-1.44) compared to Whites in the unadjusted model. However, this risk was reduced after full adjustment for age, sex, marital status, SEER registry, year of diagnosis, tumor characteristics, treatment, comorbidities, hospital characteristics and SES (1.24;1.14-1.35). For Asians, the risk of death was significantly lower than Whites (0.73;0.64-0.82) in the crude model. However, after full adjustment, their risk increased but remained lower than Whites (0.80;0.70-0.92). Although not statistically significant, Hispanics were at lower risk of dying than Whites (0.86;0.71-1.03) in the unadjusted model. After full adjustment, their risk of death slightly decreased and remained statistically insignificant (0.85;0.70-1.02).

Table 2
Analysis of predictors of colorectal cancer specific mortality for men and women diagnosed with AJCC stages I, II and III colorectal cancer from 1992-2002

The greatest reduction in the CRC-specific mortality difference between Blacks and Whites was associated with SES (5%), followed by tumor characteristics (3%), treatment (2%) and comorbidities (2%). The largest reduction in mortality differences between Asians and Whites was related to tumor characteristics (5%), followed by treatment (2%) and SES (1%). Also, SES (2%) as well as tumor characteristics (1%), treatment (1%) and comorbidities (1%) accounted for a reduction in the mortality differences between Hispanics and Whites. Hospital characteristics did not make a significant impact on mortality differences for any of the groups.

Disparities Relative to Asians

In Table 3, CRC-specific mortality for all racial/ethnic groups relative to Asians is displayed. Blacks had a significantly higher risk of dying (HR=1.84; 95%CI:1.59-2.12) compared to Asians in the unadjusted model. However, this risk was reduced after full adjustment for age, sex, marital status, SEER registry, year of diagnosis, tumor characteristics, treatment, comorbidities, hospital characteristics and SES (1.56; 1.33-1.82). For Whites, the risk of death was significantly higher than Asians (1.38; 1.22-1.56) in the crude model. However, after full adjustment, their risk decreased (1.26; 1.10-1.44). Although not statistically significant, Hispanics were at higher risk of dying than Asians (1.18; 0.95-1.47) in the unadjusted model. After full adjustment, their risk of death slightly decreased but remained statistically insignificant (1.06; 0.84-1.33).

Table 3
Analysis of predictors of colorectal cancer specific mortality relative to Asian/Pacific Islanders for men and women diagnosed with AJCC stages I, II and III colorectal cancer from 1992-2002

The reductions in the CRC-specific mortality difference between Blacks and Asians were associated with socio-demographics characteristics (29%), SES (4%) and comorbidities (3%). The only reduction in mortality differences between Whites and Asians was related to socio-demographic characteristics (24%). Socio-demographic characteristics (17%), comorbidities (1%) and SES (1%) accounted for a reduction in the mortality differences between Hispanics and Whites, although none of these reductions were statistically significant. Similar to the comparison with Whites, hospital characteristics did not reduce the hazard ratios for any group.


This study of a large cohort of men and women diagnosed with colorectal cancer yielded several important findings. There were persistent racial/ethnic survival differences after controlling for numerous variables. Furthermore, some of the factors that appeared to substantially reduce the mortality difference between Whites and Blacks, did not impact the mortality difference between Asians and Blacks. However, adjusting for comorbidities and SES resulted in a reduction in the mortality difference regardless of reference group. Therefore, comorbidities and SES appeared to be more important explanations for the survival differences observed among Blacks relative to Asians and Whites.

Several studies have examined racial/ethnic differences in CRC survival.3, 22 Our finding that racial disparities are largely explained by socioeconomic status is consistent with most of these findings. However, to our knowledge, all prior studies have compared survival among racial/ethnic groups relative to Whites. No studies of CRC survival have used Asians (the group with the best survival in this case) as a referent group, nor examined the underlying mechanisms as they relate to specific racial groups by comparing the variation in factors contributing to survival differences using different referent groups.

In this study, we found that factors contributing to survival disparities varied by racial/ethnic group. There were no statistically significant differences between Hispanics and Whites and Hispanics and Asians; however, the survival differences between Whites and Asians widened after adjusting for a number of factors. On the other hand, SES, which is associated with survival in CRC patients,2, 3 was a key determinant of survival for Blacks. These findings are similar to a meta-analysis that demonstrated that the racial disparity in survival for colon cancer between African Americans and Caucasians was attenuated after adjusting for socioeconomic factors and treatment.3 There were large ethnic differences in SES and rural residence, and SES accounted for large reductions in CRC-specific mortality between Blacks and Whites and Blacks and Asians. Furthermore, comorbidities played a key role in survival disparities for Blacks. As in the case of SES, a larger proportion of Blacks had higher comorbidity scores compared to other racial/ethnic groups and adjusting for comorbidities reduced mortality differences between Blacks and Whites and Blacks and Asians. Although a few studies have shown that comorbidities may independently affect CRC survival,31, 32 no studies prior to this one have found that they impact racial/ethnic survival disparities.

The persistent racial/ethnic survival differences, despite controlling for numerous variables, may be explained by differences in biology,33-37 individual-level SES,3 acculturation,38,39 lifestyle,40 beliefs,41, 42 refusal of43, 44 and compliance with treatment,43, 44 post-treatment surveillance,12, 13 and access to high quality cancer care,14 which were not examined in this study.

Differences in tumor site distribution and genetics may explain the high survival rates observed among Asians. A previous study demonstrated that relative to Whites, Asians have higher rates of distal colon cancer, which is associated with a decreased risk of mortality.33 For Blacks, poor survival may be due to biologic features that may contribute to aggressive tumor behavior,7 or inherited or acquired genetic abnormalities35-37 which may impact response to therapy.37

Patients with low SES are more likely to die from CRC than patients with high SES.3 In this study, a large proportion of Blacks and Hispanics resided in low SES neighborhoods, whereas a larger proportion of Asians and Whites resided in high SES neighborhoods. Percentage of persons within a census tract living under the poverty line was used as a measure of SES; therefore, there might have been residual confounding of SES since we were not able to control for differences in SES at the individual level. In addition, other components of SES such as education were not included in our analysis but may influence diagnosis, treatment, and, ultimately, survival. Despite these limitations, there was no multi-collinearity between SES (percentage of persons in a census tract living below the poverty level) and race/ethnicity present.

Lifestyle differences may explain some of these differences in survival. Obese patients have a 50% increased risk of developing colon cancer and 30% higher risk of dying from colon cancer.45 Moreover, obese patients treated for colon cancer have poorer overall survival than normal weight patients.46 Studies have also found that higher levels of physical activity may reduce the risk of colon cancer by as much as 50%,47 and patients who engage in vigorous physical activity have lower rates of colon cancer recurrence.40 National data has shown that Blacks and Hispanics have higher rates of obesity48 and lower rates of physical activity than Whites.49

Acculturation may also explain some of the survival differences observed among these racial/ethnic groups. Relative to US-born Whites of equivalent socio-demographic backgrounds, foreign born Blacks, Hispanics and Asians, have lower mortality risks.39 However, immigrants’ risk of disability and chronic disease morbidity increases with increasing length of residence.38

Cultural beliefs and norms may be linked to racial/ethnic mortality differences. Cancer fatalism, which is the belief that death is inevitable when cancer is present,41 can be a significant barrier to early detection and treatment all of which are important for achieving optimal survival. Studies have shown that Blacks, Hispanics and Chinese are more likely to possess fatalistic views regarding cancer.41, 42

Adjusting for standard therapy yielded a small reduction (2%) in the survival disparity between Blacks and Whites in this study. However, a more complete depiction of the role of treatment in the racial/ethnic survival disparities may include accounting for differences in treatment compliance and benefit, high-quality surgical care and post-treatment surveillance. Compared to Whites, Blacks are more likely to refuse treatment10, 44 and even when Blacks receive treatment, their survival benefit from adjuvant chemotherapy is not as great.11, 34 Also, there is evidence to suggest that patients treated by a surgical specialist with high caseloads have improved CRC survival.50 Yet, Black patients are less likely to be treated by these surgeons51 or have access to high-quality subspecialists.14 Finally, post-treatment surveillance can detect CRC recurrence and lead to improved survival; however, racial/ethnic minorities are less likely to receive this care.12, 13Additional research is needed to determine the role of each of these factors in racial/ethnic disparities in CRC survival.

In addition to the variables that were not measured in this study, another limitation of this study is that the sequence of the variables in the model may have affected the percentage reduction in hazard ratio attributable to each variable; yet, when changes in the order of the variables were made, there was little difference.

There are a number of strengths that support this study’s validity. The study included nationwide and population-based cases from 16 SEER areas, which accounts for approximately 25% of the U.S. population. The cases were ethnically diverse and included traditionally understudied racial/ethnic groups: Hispanics and Asians. Therefore, these findings may be generalizable to diverse populations 66 years of age or older residing in other areas of the U.S. Furthermore, the linked database allowed us to incorporate a number of treatment, hospital and comorbidity variables across the cancer care continuum and is an accurate and complete source of data.52, 53

In conclusion, although comorbidities and SES appear to be important factors contributing to the poorer CRC-specific survival for Blacks relative to Whites and Asians, substantial racial disparities in survival still persisted and were not fully explained by variations in a number of factors across the cancer continuum. Future research should examine the role of other factors not included in this study such as the quality of care, particularly the benefit of treatment and post-treatment surveillance.


We would like to express our gratitude to NCI, CMS, IMS and SEER tumor registries for the creation of this database. Also, we thank Chih-Chin Liu for extracting this dataset. This study was supported by a grant from the AHRQ (R01-HS016743). Arica White was the recipient of a pre-doctoral fellowship under a NCI training grant (R25-CA057712).


1. American Cancer Society . Cancer Facts and Figures 2009. American Cancer Society; 2009.
2. Le H, Ziogas A, Lipkin SM, et al. Effects of socioeconomic status and treatment disparities in colorectal cancer survival. Cancer Epidemiol Biomarkers Prev. 2008;17(8):1950–62. [PubMed]
3. Du XL, Meyer TE, Franzini L. Meta-analysis of racial disparities in survival in association with socioeconomic status among men and women with colon cancer. Cancer. 2007;109(11):2161–70. [PubMed]
4. Chien C, Morimoto LM, Tom J, et al. Differences in colorectal carcinoma stage and survival by race and ethnicity. Cancer. 2005;104(3):629–39. [PubMed]
5. Marcella S, Miller JE. Racial differences in colorectal cancer mortality. The importance of stage and socioeconomic status. J Clin Epidemiol. 2001;54(4):359–66. [PubMed]
6. Doubeni CA, Field TS, Buist DS, et al. Racial differences in tumor stage and survival for colorectal cancer in an insured population. Cancer. 2007;109(3):612–20. [PubMed]
7. Alexander D, Jhala N, Chatla C, et al. High-grade tumor differentiation is an indicator of poor prognosis in African Americans with colonic adenocarcinomas. Cancer. 2005;103(10):2163–70. [PMC free article] [PubMed]
8. Chen VW, Fenoglio-Preiser CM, Wu XC, et al. National Cancer Institute Black/White Cancer Survival Study Group Aggressiveness of colon carcinoma in blacks and whites. Cancer Epidemiol Biomarkers Prev. 1997;6(12):1087–93. [PubMed]
9. Shavers VL, Brown ML. Racial and ethnic disparities in the receipt of cancer treatment. J Natl Cancer Inst. 2002;94(5):334–57. [PubMed]
10. White A, Liu CC, Xia R, et al. Racial disparities and treatment trends in a large cohort of elderly African Americans and Caucasians with colorectal cancer, 1991 to 2002. Cancer. 2008;113(12):3400–9. [PubMed]
11. Jessup JM, Stewart A, Greene FL, et al. Adjuvant chemotherapy for stage III colon cancer: implications of race/ethnicity, age, and differentiation. JAMA. 2005;294(21):2703–11. [PubMed]
12. Ellison GL, Warren JL, Knopf KB, et al. Racial differences in the receipt of bowel surveillance following potentially curative colorectal cancer surgery. Health Serv Res. 2003;38(6 Pt 2):1885–903. [PMC free article] [PubMed]
13. Rolnick S, Hensley Alford S, Kucera GP, et al. Racial and age differences in colon examination surveillance following a diagnosis of colorectal cancer. J Natl Cancer Inst Monogr. 2005;(35):96–101. [PubMed]
14. Bach PB, Pham HH, Schrag D, et al. Primary care physicians who treat blacks and whites. N Engl J Med. 2004;351(6):575–84. [PubMed]
15. Hodgson DC, Fuchs CS, Ayanian JZ. Impact of patient and provider characteristics on the treatment and outcomes of colorectal cancer. J Natl Cancer Inst. 2001;93(7):501–15. [PubMed]
16. Birkmeyer NJ, Goodney PP, Stukel TA, et al. Do cancer centers designated by the National Cancer Institute have better surgical outcomes? Cancer. 2005;103(3):435–41. [PubMed]
17. Paulson EC, Mitra N, Sonnad S, et al. National Cancer Institute designation predicts improved outcomes in colorectal cancer surgery. Ann Surg. 2008;248(4):675–86. [PubMed]
18. Roetzheim RG, Pal N, Gonzalez EC, et al. Effects of health insurance and race on colorectal cancer treatments and outcomes. Am J Public Health. 2000;90(11):1746–54. [PubMed]
19. Warren JL, Klabunde CN, Schrag D, et al. Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population. Med Care. 2002;40(8 Suppl):IV-3–18. [PubMed]
20. Fritz A, Percy C, Jack A, et al. International Classification of Diseases for Oncology. 3rd Edition World Health Organization; Geneva: 2000.
21. U.S. Census Bureau How the Census Bureau Measures Poverty. [accessed December 1, 2009]. Available from URL:
22. Du XL, Fang S, Vernon SW, et al. Racial disparities and socioeconomic status in association with survival in a large population-based cohort of elderly patients with colon cancer. Cancer. 2007;110(3):660–9. [PubMed]
23. Mandelblatt JS, Kerner JF, Hadley J, et al. Variations in breast carcinoma treatment in older medicare beneficiaries: is it black or white. Cancer. 2002;95(7):1401–14. [PubMed]
24. U.S. Public Health Services . International Classification of Diseases, 9th Revision, Clinical Modification. 5th ed. Practice Management Information Corporation; Los Angeles, CA: 1996.
25. American Medical Association . Physicians’ Current Procedural Terminology-CPT 2000. American Medical Association; Chicago, IL: 2000.
26. Health Care Financing Administration . HCFA Data Dictionary: Revenue Center Codes. Health Care Financing Administration; Baltimore, MD: Jun 17, 1999.
27. National Cancer Institute Colon Cancer Treatment (PDQ®) [accessed October 25, 2007]. Available from URL:
28. National Cancer Institute Rectal Cancer Treatment (PDQ®) [accessed January 20,2008]. Available from URL:
29. National Cancer Institute SEER-Medicare: Calculation of Comorbidity Weights. [accessed March 10, 2009]. Available from URL:
30. Du XL, Chan W, Giordano S, et al. Variation in modes of chemotherapy administration for breast carcinoma and association with hospitalization for chemotherapy-related toxicity. Cancer. 2005;104(5):913–24. [PMC free article] [PubMed]
31. Gross CP, Guo Z, McAvay GJ, et al. Multimorbidity and survival in older persons with colorectal cancer. J Am Geriatr Soc. 2006;54(12):1898–904. [PubMed]
32. Polednak AP. Comorbid diabetes mellitus and risk of death after diagnosis of colorectal cancer: a population-based study. Cancer Detect Prev. 2006;30(5):466–72. [PubMed]
33. Le H, Ziogas A, Taylor TH, et al. Survival of distinct Asian groups among colorectal cancer cases in California. Cancer. 2008;115(2):259–70. [PMC free article] [PubMed]
34. Sanoff HK, Sargent DJ, Green EM, et al. Racial differences in advanced colorectal cancer outcomes and pharmacogenetics: a subgroup analysis of a large randomized clinical trial. J Clin Oncol. 2009;27(25):4109–15. [PMC free article] [PubMed]
35. Ashktorab H, Smoot DT, Farzanmehr H, et al. Clinicopathological features and microsatellite instability (MSI) in colorectal cancers from African Americans. Int J Cancer. 2005;116(6):914–9. [PMC free article] [PubMed]
36. Carethers JM. Racial and ethnic factors in the genetic pathogenesis of colorectal cancer. J Assoc Acad Minor Phys. 1999;10(3):59–67. [PubMed]
37. Carethers JM, Smith EJ, Behling CA, et al. Use of 5-fluorouracil and survival in patients with microsatellite-unstable colorectal cancer. Gastroenterology. 2004;126(2):394–401. [PubMed]
38. Singh GK, Miller BA. Health, life expectancy, and mortality patterns among immigrant populations in the United States. Can J Public Health. 2004;95(3):I14–21. [PubMed]
39. Singh GK, Siahpush M. Ethnic-immigrant differentials in health behaviors, morbidity, and cause-specific mortality in the United States: an analysis of two national data bases. Hum Biol. 2002;74(1):83–109. [PubMed]
40. Meyerhardt JA, Heseltine D, Niedzwiecki D, et al. Impact of physical activity on cancer recurrence and survival in patients with stage III colon cancer: findings from CALGB 89803. J Clin Oncol. 2006;24(22):3535–41. [PubMed]
41. Powe BD. Cancer fatalism among elderly Caucasians and African Americans. Oncol Nurs Forum. 1995;22(9):1355–9. [PubMed]
42. Wang JH, Liang W, Chen MY, et al. The influence of culture and cancer worry on colon cancer screening among older Chinese-American women. Ethn Dis. 2006;16(2):404–11. [PMC free article] [PubMed]
43. Ball JK, Elixhauser A. Treatment differences between blacks and whites with colorectal cancer. Med Care. 1996;34(9):970–84. [PubMed]
44. Demissie K, Oluwole OO, Balasubramanian BA, et al. Racial differences in the treatment of colorectal cancer: a comparison of surgical and radiation therapy between Whites and Blacks. Ann Epidemiol. 2004;14(3):215–21. [PubMed]
45. Calle EE, Rodriguez C, Walker-Thurmond K, et al. Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults. N Engl J Med. 2003;348(17):1625–38. [PubMed]
46. Dignam JJ, Polite BN, Yothers G. Effect of body mass index on outcomes in patients with Dukes B and C colon cancer: An analysis of NSABP randomized trials. J Clin Oncol. 2005;23(254s)
47. Tomeo CA, Colditz GA, Willett WC, et al. Harvard Report on Cancer Prevention. Volume 3: prevention of colon cancer in the United States. Cancer Causes Control. 1999;10(3):167–80. [PubMed]
48. Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of overweight and obesity in the United States, 1999-2004. Jama. 2006;295(13):1549–55. [PubMed]
49. Pratt M, Macera CA, Blanton C. Levels of physical activity and inactivity in children and adults in the United States: current evidence and research issues. Med Sci Sports Exerc. 1999;31(11 Suppl):S526–33. [PubMed]
50. Iversen LH, Harling H, Laurberg S, et al. Influence of caseload and surgical speciality on outcome following surgery for colorectal cancer: a review of evidence. Part 2: long-term outcome. Colorectal Dis. 2007;9(1):38–46. [PubMed]
51. Morris AM, Wei Y, Birkmeyer NJ, et al. Racial disparities in late survival after rectal cancer surgery. J Am Coll Surg. 2006;203(6):787–94. [PubMed]
52. Du X, Freeman JL, Goodwin JS. Information on radiation treatment in patients with breast cancer: the advantages of the linked medicare and SEER data. Surveillance, Epidemiology and End Results. J Clin Epidemiol. 1999;52(5):463–70. [PubMed]
53. Du X, Freeman JL, Warren JL, et al. Accuracy and completeness of Medicare claims data for surgical treatment of breast cancer. Med Care. 2000;38(7):719–27. [PubMed]