Original Research

Annals of Internal Medicine

Racial Disparities in Colon Cancer Survival A Matched Cohort Study Jeffrey H. Silber, MD, PhD; Paul R. Rosenbaum, PhD; Richard N. Ross, MS; Bijan A. Niknam, BS; Justin M. Ludwig, MA; Wei Wang, PhD; Amy S. Clark, MD; Kevin R. Fox, MD; Min Wang, MHS; Orit Even-Shoshan, MS; and Bruce J. Giantonio, MD

Background: Differences in colon cancer survival by race are a recognized problem among Medicare beneficiaries. Objective: To determine to what extent the racial disparity in survival is due to disparity in presentation characteristics at diagnosis or disparity in subsequent treatment. Design: Black patients with colon cancer were matched with 3 groups of white patients: a “demographic characteristics” match controlling for age, sex, diagnosis year, and Survey, Epidemiology, and End Results (SEER) site; a “presentation” match controlling for demographic characteristics plus comorbid conditions and tumor characteristics, including stage and grade; and a “treatment” match, including presentation variables plus details of surgery, radiation, and chemotherapy. Setting: 16 U.S. SEER sites. Patients: 7677 black patients aged 65 years or older diagnosed between 1991 and 2005 in the SEER–Medicare database and 3 sets of 7677 matched white patients, followed until 31 December 2009.

P ⬍ 0.001) in the demographic characteristics match. This disparity remained unchanged between 1991 and 2005. After matching for presentation characteristics, the difference decreased to 4.9% (CI, 3.6% to 6.1%; P ⬍ 0.001). After additional matching for treatment, this difference decreased to 4.3% (CI, 2.9% to 5.5%; P ⬍ 0.001). The disparity in survival attributed to treatment differences made up only an absolute 0.6% of the overall 9.9% survival disparity. Limitation: An observational study limited to elderly Medicare feefor-service beneficiaries living in selected geographic areas. Conclusion: Racial disparities in colon cancer survival did not decrease among patients diagnosed between 1991 and 2005. This persistent disparity seemed to be more related to presentation characteristics at diagnosis than to subsequent treatment differences. Primary Funding Source: Agency for Healthcare Research and Quality and National Science Foundation.

Measurements: 5-year survival. Results: The absolute difference in 5-year survival between black and white patients was 9.9% (95% CI, 8.3% to 11.4%;

Ann Intern Med. 2014;161:845-854. doi:10.7326/M14-0900 For author affiliations, see end of text.

W

(1991 to 1998) to 1999 and after (1999 to 2005), determined the relative contributions of presentation at diagnosis (and treatment after presentation) to differences in survival experienced by these groups, and explored how socioeconomic variables relate to the overall disparity. Our goal was to assist in determining which paths should be pursued to eliminate the persistent racial disparity in colon cancer survival.

ith nearly 100 000 new cases each year, colon cancer is the fourth-most common cancer in the United States and is also responsible for the second-highest number of deaths with approximately 50 000 per year (1). The incidence of colon cancer is highest among black persons (2), and racial disparities in survival among patients with colon cancer have long existed (3– 6). Numerous reports have not only identified and documented worse outcomes in black patients with colon cancer but have suggested potential reasons for the disparity based on differences in screening (7, 8), comorbid conditions on presentation (9), stage (10 –12), treatment (13–15), and socioeconomic status (16). In the Medicare population as a whole, life tables indicate a disparity between black and white patients in 5-year survival at age 65 years of 3.6% (17), but this widens substantially when a patient develops a serious illness, such as colon cancer (6). Although we examined the extent of the racial disparity in colon cancer survival in the Medicare population, the main purpose is to understand the nature of the disparity. We asked whether white patients who present like black patients are treated as black patients are treated, and if not, to what extent a disparity in treatment explains the disparity in survival. We assessed the magnitude of the disparity; examined whether the disparity has changed from 1998 and before

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METHODS Patient Population

This research protocol was approved by the Institutional Review Board of The Children’s Hospital of Philadelphia (Philadelphia, Pennsylvania). We obtained the Survey, Epidemiology, and End Results (SEER)–Medicare database for the years 1991 to 2005 for 16 SEER sites throughout the United States, including all sites except the Alaska Native Tumor Registry. There were 88 858 patients

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Original Research

Racial Disparities in Colon Cancer Survival

Treatment Variables

Context Black patients have decreased colon cancer survival compared with white patients.

Contribution In a model that sequentially matched patients with colon cancer by demographic characteristics, then presentation, and then treatment, little of the racial difference in colon cancer survival was found to be due to differences in treatment.

Caution Only patients covered by Medicare were studied.

Implication Efforts to decrease racial disparities in colon cancer survival may be best focused on prevention and early detection of disease. —The Editors

aged 65 years or older with newly diagnosed invasive colon cancer. For each patient, the SEER Patient Entitlement and Diagnosis Summary File (18, 19) was merged with Medicare Parts A and B, outpatient claims, and the beneficiary summary file (which was updated to 31 December 2009 for this data set), providing a minimum of 4 years of follow-up for all patients. For all analyses of trends over time, we examined the 12 SEER sites that were collecting data during the entire study. For analyses that did not consider trends over time, we used all 16 sites. Defining Patient Characteristics

We defined race by using the SEER algorithm (20) and compared black with white non-Hispanic and white Hispanic patients for the primary analysis. Patient comorbid conditions, such as congestive heart failure, diabetes, past acute myocardial infarction, stroke, hypertension, and 21 other conditions noted in the Supplement (available at www.annals.org), were defined with International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), codes (21–24) and collected from Medicare claims (inpatient, outpatient, and physician bills) during a 3-month period before diagnosis. Tumor Biology

Characteristics of the patient’s tumor, including stage, grade, number of nodes dissected, and number of positive nodes, were obtained from the SEER Patient Entitlement and Diagnosis Summary File. For patients with stage II colon cancer, we used SEER and Medicare data to define 2 strata (high and low) of risk for recurrence (25–27), on the basis of the presence of 1 of the following prognostic indicators: T4 tumor status, perforation, and fewer than 10 nodes removed (Supplement, available at www.annals .org).

We defined treatment on the basis of information from both SEER and Medicare data. Surgery was defined by billing codes in the Medicare files. Evidence of chemotherapy was also determined by Medicare billing codes. Radiation therapy was determined by Medicare billing codes and information from the SEER Patient Entitlement and Diagnosis Summary File (Supplement). Statistical Analysis

Similar to our previously published work (28), this analysis used tapered multivariate matching (28 –30) to compare the entire population of black patients in SEERMedicare with 3 white populations individually paired to the black population to answer various questions about the origins of the racial disparity. We used all black patients for each match, so the black population was unchanged and fully representative of black patients in the SEER population. The white population changed according to the variables used in the match. We created 3 overlapping (30) matched analyses: a “demographic characteristics” match, which matched white to black patients by SEER site, age, sex, and year of diagnosis; a “presentation” match, which matched black and white patients by demographic characteristics as well as presentation characteristics, comorbid conditions, and tumor biology (stage, including high- and low-risk stage II, grade, and nodes); and a “treatment” match, which included matching variables from demographic characteristics and presentation as well as relevant treatment variables, including surgery, chemotherapy, radiation therapy, and individual types of chemotherapy. The hazards of adjustments made by models rather than matching are discussed by Rubin (31), Hansen (32), Stuart (33), and Lu and colleagues (34). As suggested by Rubin and Rosenbaum (35–37), matching was performed first without viewing outcomes. The PROC ASSIGN (38) function in SAS, version 9.2 (SAS Institute), was used for all matching, providing optimal matches that minimized the total distance within matched pairs (37). We used near-fine balance for the SEER site in the presentation and treatment matches (28, 39, 40). This meant that each site contributed nearly identical numbers of white and black patients to each matched analysis. Matching on patient covariates in the presentation and treatment matches also included a score predicting black race (a propensity score) and a risk score based on a Charlson score (41– 44). The propensity scores for the presentation and treatment matches came from a logistic regression of white-versus-black race using all of the variables to be controlled in the specific match. Matching on the propensity score tends to balance variables making up the propensity score (37, 45– 47). For each matching variable, we checked similarities between black and white patients using the standardized difference in means before and after matching, which is the

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Racial Disparities in Colon Cancer Survival

mean difference between groups in units of the before matching SDs (22, 48, 49). A conventional rule of thumb aims for mean standardized differences below 0.2 of an SD (22, 48, 49), although we aimed for standardized differences below 0.1. We also assessed how closely we achieved balance using 2-sample randomization tests, specifically the Wilcoxon rank-sum test for each continuous covariate, the Fisher exact test for each binary covariate, and a single cross-match test for all covariates in a given match (28, 50 –53). When testing the hypothesis that there were no differences in outcomes between the matched patients, the Wilcoxon sign-rank statistic (54) was calculated for continuous variables and the McNemar statistic (55) was used for binary outcomes. When modeling survival differences over time, we used the paired version of the Cox proportional hazards model (56). When comparing paired survival distributions, we used the Prentice–Wilcoxon test (57). We obtained SEs for the paired differences in survival probabilities using the bootstrap method as described by Efron and Tibshirani (58). Differences among white patients were tested using the exterior match that removed overlap in the white control groups (28, 30), again testing for differences in survival using the Prentice–Wilcoxon test (57). For all tests of outcomes and matching quality, differences were considered statistically significant if the P value was less than 0.05. For analyses that compared survival in the 2 time periods, we used only the 12 SEER sites that collected data for the full duration of these intervals. Role of the Funding Source

The Agency for Healthcare Research and Quality and National Science Foundation had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.

Original Research

presentation match, 24.5% of white patients had diabetes, similar to the rate among black patients). The comparison of the characteristics of white and black patients in the demographic characteristics match provided insight into how different white patients presenting with colon cancer are compared with black patients. The comparison of treatment variables between black and white patients in the presentation match allowed for a reasonable comparison of differences in treatment (without adjustment for presentation, observed differences in treatment may be simply due to differences in burden of disease, which is accounted for by the presentation match). The treatment match also found that white patients had a similar rate of diabetes as black patients but also controlled for cancer treatment. Similar matching results for tumor biology and treatment variables were also achieved (Supplement). Examining Treatment

Table 1 also provides information on differences in treatment by race. Overall, 16.7% of black patients did not have evidence of their colon cancer being treated, compared with 9.3% of white patients matched for demographic characteristics (P ⬍ 0.001). However, even after matching white patients for tumor characteristics and other risk factors, only 12.8% of white patients matched for presentation had no evidence of treatment, a significantly lower proportion than the 16.7% rate of no treatment among black patients (P ⬍ 0.001). Other differences were noted when examining the presentation match: 14.7% of black patients received fluoropyrimidine plus another agent, compared with 21.7% of white patients (P ⬍ 0.001); black patients had surgery with adjuvant chemotherapy less frequently than white patients (19.9% vs. 26.5%; P ⬍ 0.001); and black patients had surgery without any other treatment more often than white patients (61.1% vs. 58.0%; P ⬍ 0.001). Survival Results

RESULTS Quality of the Matches: Matching Results

In Table 1, we report characteristics of the entire black population and 3 white populations matched sequentially to the black population. The 3 matches sequentially removed aspects of the disparity while leaving other aspects in place so we could develop an understanding of how the disparity occurs. In each match, the variables controlled in that match were closely balanced, with no standardized difference exceeding 0.07 SD. Complete matching tables are provided in the Supplement. In a given match, unmatched variables exhibit differences that reveal aspects of the disparity. For example, among all black patients with colon cancer, 25.2% had diabetes, whereas white patients matched for age, sex, year of diagnosis, and SEER site had a much lower rate (17.1%). The presentation match then removed the difference in diabetes and many other characteristics describing patients at cancer diagnosis (for example, in the www.annals.org

Figure 1 displays the survival curves of black patients and the corresponding white matched patients diagnosed with colon cancer between 1991 and 2005 for all 16 SEER sites. The extent of the disparity between black and white patients is the vertical distance between the curves for the black and white patients matched for demographic characteristics. Table 2 describes the 2- and 5-year survival differences and median survival time for the black and matched white populations. The survival difference between black and white patients matched for demographic characteristics at 5 years is 9.9% (P ⬍ 0.001). Figure 1 also displays the white presentation match, representing white patients who had the age, sex, year of diagnosis, and SEER site variables in the match but were also matched for patient characteristics, including comorbid conditions and tumor characteristics (such as stage, including risk-stratified stage II; grade; and nodes). The difference in 5-year survival between the white population matched for presentation and the black population was 16 December 2014 Annals of Internal Medicine Volume 161 • Number 12 847

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Original Research

Racial Disparities in Colon Cancer Survival

Table 1. Quality of Matches* Variable

Mean age at diagnosis (SD), y Mean diagnosis year (SD) Female Congestive heart failure Diabetes Stage I Stage II Stage II, low-risk Stage II, high-risk Stage III Stage IV Stage missing Grade I Grade II Grade III Grade IV Grade missing Mean nodes removed (SD), n Mean nodes that tested positive (SD), n Ratio of nodes (positive:removed) (SD) No treatment Surgery only Surgery ⫹ chemotherapy Surgery ⫹ chemotherapy ⫹ radiation Chemotherapy (fluoropyrimidine only) Chemotherapy (fluoropyrimidine ⫹ other agent) Mean time from diagnosis to treatment, if treated (SD), d

White Patients, n (%)

Black Patients (n ⴝ 7677), n (%)

76.8 (7.4) 1999.2 (4.3) 4712 (61.4) 972 (12.7) 1935 (25.2) 1301 (16.9) 1919 (25.0) 702 (9.1) 1217 (15.9) 1677 (21.8) 1671 (21.8) 1109 (14.4) 644 (8.4) 4654 (60.6) 1023 (13.3) 65 (0.8) 1291 (16.8) 8.8 (8.8) 1.5 (2.8) 0.15 (0.25) 1280 (16.7) 4687 (61.1) 1530 (19.9) 77 (1.0) 1210 (15.8) 1125 (14.7) 13.1 (20.9)

Matched for Treatment ⴙ Presentation ⴙ Demographic Characteristics (n ⴝ 7677)

Matched for Presentation ⴙ Demographic Characteristics (n ⴝ 7677)

Matched for Demographic Characteristics (n ⴝ 7677)

Unmatched (n ⴝ 88 858)

76.8 (7.2) 1999.2 (4.3) 4652 (60.6) 903 (11.8) 1877 (24.4) 1303 (17.0) 1917 (25.0) 696 (9.1) 1221 (15.9) 1677 (21.8) 1671 (21.8) 1109 (14.4) 643 (8.4) 4634 (60.4) 1017 (13.2) 70 (0.9) 1313 (17.1) 8.7 (8.4) 1.5 (3.0) 0.15 (0.26) 1280 (16.7) 4672 (60.9) 1530 (19.9) 84 (1.1) 1202 (15.7) 1140 (14.8) 12.8 (20.1)

76.8 (7.2) 1999.2 (4.3) 4762 (62.0) 902 (11.7) 1882 (24.5) 1314 (17.1) 1906 (24.8) 695 (9.1) 1211 (15.8) 1677 (21.8) 1671 (21.8) 1109 (14.4) 643 (8.4) 4673 (60.9) 1011 (13.2) 51 (0.7) 1299 (16.9) 8.7 (8.5) 1.6 (3.0) 0.15 (0.26) 981 (12.8)† 4451 (58.0)† 2031 (26.5)† 118 (1.5)§ 1670 (21.8)† 1624 (21.2)† 12.0 (17.5)

76.8 (7.4) 1999.2 (4.3) 4713 (61.4) 812 (10.6)† 1315 (17.1)† 1528 (19.9)† 2296 (29.9)† 875 (11.4)† 1421 (18.5)† 1779 (23.2) 1274 (16.6)† 800 (10.4)† 701 (9.1) 4469 (58.2)† 1440 (18.8)† 73 (1.0) 994 (12.9)† 9.8 (8.8)† 1.5 (3.2)† 0.14 (0.25)§ 711 (9.3)† 4706 (61.3) 2089 (27.2)† 148 (1.9)† 1721 (22.4)† 1663 (21.7)† 11.8 (17.0)

78.1 (7.3)† 1999.0 (4.3)† 45 950 (51.9)† 8753 (9.8)† 12 731 (14.3)† 15 314 (17.2)† 24 930 (28.1)† 9052 (10.2)† 15 878 (17.9)† 18 132 (20.4)‡ 13 180 (14.8)† 9625 (10.8)† 7041 (7.9) 47 045 (52.9)§ 15 812 (17.8)† 811 (0.9) 10 472 (11.8)† 9.76 (9.0)† 1.44 (3.0)† 0.14 (0.25)† 8583 (9.7)† 51 240 (57.7)† 19 449 (22.0)† 1268 (1.4)† 16 153 (18.2)† 15 645 (17.6)† 11.5 (16.7)

* Variables without boldface were included in the corresponding match. All P values for these cells are nonpaired as a test for balance, using the Wilcoxon rank-sum test for continuous variables and the Fisher exact test for categorical variables. P values in the boldface cells (excluding those in the unmatched column, which are always nonpaired) are given using paired tests: the Wilcoxon signed-rank test for continuous variables and the McNemar test for categorical variables. Results without P value notations are not significant. † P ⬍ 0.001. ‡ P ⬍ 0.05. § P ⬍ 0.01.

4.9% (P ⬍ 0.001). An additional match described in the Supplement controlled for cancer characteristics at presentation (such as stage) but not for comorbid conditions (such as diabetes). Although comorbid conditions were not explicitly controlled in this match, the white control patients selected for more advanced cancer presentation also had more severe comorbid conditions. This match showed that white patients who presented with tumor characteristics similar to black patients but were treated like white patients had nearly identical survival to white patients who presented like black patients both on comorbid conditions and tumor characteristics (Supplement). In the treatment match, we matched for all of the variables in the presentation and demographic characteristics matches but also for specific treatments, including surgery, type of chemotherapy, and radiation therapy. The difference in 5-year survival between the white treatmentmatched and black patients was 4.3% (P ⬍ 0.001). When comparing 5-year survival of white patients who presented

like black patients (presentation match) with white patients who presented and were treated like black patients (treatment match), the difference was small (0.6%) but statistically significant (P ⫽ 0.005). Changes in Survival Disparity Over Time

Figure 2 shows the survival curves of all black patients and white patients matched for demographic characteristics in pairs diagnosed in 1998 or before (1991 to 1998) and after 1998 (1999 to 2005) for just the 12 SEER sites that collected data in both time periods. These time periods roughly divide our study sample in half, were consistent with our previous work (28), and coincided with a general shift in medical management of colorectal cancer from that of single-agent fluoropyrimidine to the multiagent regimens currently used to treat the disease (Supplement) (59). The change in the point estimate for the difference between black and white patients in 5-year survival showed an increased disparity from the first time period to the

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Racial Disparities in Colon Cancer Survival

second, although this change was not significantly different from 0: 8.5% in 1991 to 1998 and 11.5% in 1999 to 2005 (hazard ratio, 1.10 [95% CI, 0.98 to 1.24]; P ⫽ 0.093). There was also no significant difference in the disparity between black patients and the presentation match or the treatment match when comparing 1998 and before versus after 1998 (Supplement). Exploring the Influence of Treatment Disparities by Stage at Diagnosis

Although we saw little difference in the overall disparity after matching on presentation, we also found that there was a significant difference in survival between white patients matched to black patients for presentation versus white patients matched to black patients for treatment (5-year survival rate, 40.2% vs. 39.6%, respectively; P ⫽ 0.005). Therefore, we examined subgroups of pairs matched for stage at diagnosis, and these results are pro-

Original Research

vided in the Supplement. We did not find that treatment differences influenced survival after matching for presentation for patients with stage I and II colon cancer. In patients with stage IV cancer, survival was dismal for both white and black patients, although white patients matched for presentation fared better than white patients matched for presentation and treatment (P ⬍ 0.001). In patients with stage III cancer, we saw an important treatment effect. We noted that black patients presenting with stage III disease had a greater proportion of patients with no treatment compared with white patients matched for presentation (3.3% vs. 1.6%; P ⫽ 0.002), and fewer black patients had both surgery and chemotherapy (42.1% vs. 55.0%; P ⬍ 0.001). In patients with stage III colon cancer, white patients who were matched to black patients for presentation characteristics displayed a 5-year survival rate of 43.7% versus 41.2% in white patients who were matched

Figure 1. Kaplan–Meier curve for colon cancer survival for black patients and 3 matched white populations diagnosed between 1991 and 2005. 1.0

Survival Probability

0.8

0.6

0.4

White, matched for demographic characteristics

0.2

White, matched for demographic characteristics + presentation White, matched for demographic characteristics + presentation + treatment Black

0 0

12

24

36

48

60

Time After Diagnosis, mo Patients, n White, matched for

7677

5656

4833

4272

3850

3225

7677

5291

4453

3888

3479

2880

7677

5171

4375

3840

3425

2841

7677

5093

4169

3555

3124

2538

demographic characteristics White, matched for demographic characteristics + presentation White, matched for demographic characteristics + presentation + treatment Black

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Original Research

Racial Disparities in Colon Cancer Survival

Table 2. Colon Cancer Outcomes for All Stages Outcome Measure

Black Patients (n ⴝ 7677)

White Patients Matched for Treatment (n ⴝ 7677)

White Patients Matched for Presentation (n ⴝ 7677)

White Patients Matched for Demographic Characteristics (n ⴝ 7677)

Median survival (95% CI), mo 2-y survival (95% CI), % White ⫺ black difference*, % Deaths, n 5-y survival (95% CI), % White ⫺ black difference*, % Deaths, n Paired Cox model hazard ratio (black:white) (95% CI)†

29 (28–31) 53.5 (52.4–54.6) – 3569 35.3 (34.2–36.3) – 4954 –

36 (33–38) (P ⬍ 0.001) 56.3 (55.2–57.4) 2.8 (1.5–4.0) (P ⫽ 0.002) 3356 39.6 (38.5–40.7) 4.3 (2.9–5.5) (P ⬍ 0.001) 4624 1.087 (1.035–1.141) (P ⬍ 0.001)

37 (35–39) (P ⬍ 0.001) 57.2 (56.1–58.3) 3.7 (2.4–4.9) (P ⬍ 0.001) 3288 40.2 (39.1–41.3) 4.9 (3.6–6.1) (P ⬍ 0.001) 4579 1.140 (1.086–1.197) (P ⬍ 0.001)

48 (45–51) (P ⬍ 0.001) 62.1 (61.0–63.2) 8.6 (7.0–10.0) (P ⬍ 0.001) 2908 45.2 (44.1–46.3) 9.9 (8.3–11.4) (P ⬍ 0.001) 4197 1.325 (1.263–1.390) (P ⬍ 0.001)

* P values used the Prentice–Wilcoxon test. All CIs were based on bootstrapped SEs. † P values used all follow-up data after diagnosis.

for both presentation and treatment (P ⫽ 0.013) (Table 3). This suggested that, unlike in stages I and II, some of the survival disparity is associated with a disparity in treatment of patients with stage III cancer and, to a lesser extent, those with stage IV cancer as well.

Explaining Residual Disparity After the Treatment Match

Because some of the survival disparity remained after controlling for factors related to initial diagnosis and treatment, we also explored whether black patients who survived more than 1 year after diagnosis received less salvage

Figure 2. Improvement in colon cancer survival for black and white patients from 1991 to 1998 versus 1999 to 2005. 1.0

Survival Probability

0.8

0.6

0.4

White, matched for demographic characteristics, 1998 and before

0.2

White, matched for demographic characteristics, after 1998 Black, 1998 and before Black, after 1998

0 0

12

24

36

48

60

Time After Diagnosis, mo Patients, n White, matched for

2997

2226

1889

1634

1464

1323

2491

1816

1568

1405

1279

1038

Black, 1998 and before 2997

2026

1648

1396

1211

1066

Black, after 1998

1630

1333

1134

1001

767

demographic characteristics, 1998 and before White, matched for demographic characteristics, after 1998 2491

The overall disparity did not change. 850 16 December 2014 Annals of Internal Medicine Volume 161 • Number 12

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Racial Disparities in Colon Cancer Survival

therapy for years 2 through 5 than paired white patients who also survived more than 1 year. We found no difference in the rate of subsequent chemotherapy after initial treatment ended (Supplement). White patients were more likely to receive subsequent surgery in years 2 through 5 (P ⫽ 0.003); however, adjustment for subsequent surgery as a time-dependent variable in a paired Cox model did not alter the magnitude of the racial disparity (Supplement). Another potential aspect of the racial disparity that was not controlled through matching is the quality of hospitals where black and white patients were treated (60). Because nearly all patients had surgery for colon cancer or had a hospitalization around diagnosis, we analyzed differences in the characteristics of hospitals where black and matched white patients were treated. The results did not indicate that black patients generally went to lower-quality hospitals: 23% of black patients were treated at major teaching hospitals, compared with just 12.6% of white patients matched for treatment. Black patients also more often went to large hospitals and hospitals with better technology; however, white patients more often went to hospitals with slightly higher ratios of nurses to beds and better nurse mixes (Supplement). Although this study focused on sources of survival disparity, most of which were directly relevant to clinical care, other factors (such as socioeconomic status [16]) are known to play a role. Therefore, we asked whether the residual survival disparity in the treatment match was associated with a marker of socioeconomic status as defined by neighborhood income. We fit a paired Cox model using the treatment-matched pairs to evaluate the influence of race before and after adjustment for neighborhood socioeconomic status. Without adjustment, the hazard ratio for death in black versus white patients was 1.09 (CI, 1.04 to 1.14; P ⬍ 0.001). After adjustment for neighborhood median income, the hazard ratio on race became insignificant (1.04 [CI, 0.98 to 1.11]; P ⫽ 0.167). The use of neighborhood variables reflecting poverty displayed similar findings (Supplement). The racial disparity in 5-year survival in the Medicare population at age 65 years was 3.6% (Supplement). More

Original Research

relevant to the current study is the racial disparity in 5-year survival in the overall Medicare population at age 77 years, the mean age in our study, which is 3.5% (17). The residual disparity in 5-year survival after the treatment match was 4.3%, nearly the same as the U.S. disparity at the same age.

DISCUSSION The large racial disparity in colon cancer survival after diagnosis did not change between 1991 to 1998 and 1999 to 2005 and, in fact, was trending in the direction of an increasing disparity, a finding that corroborates recent research (61). Most of the disparity is explained by poorer health of black patients at diagnosis, with more advanced disease and comorbid conditions. The 5-year survival disparity with white patients matched for demographic characteristics (age, year of diagnosis, and SEER site) was 9.9%, or a difference in median survival time of 19 months. For white patients matched for cancer and comorbid conditions (the presentation match), the disparity was 4.9%, or a difference in median survival of 8 months. Although we, like others (13–15), saw a significant racial disparity in receipt of treatment, we found that its overall contribution to the survival disparity was small; compared with white patients who both presented and were treated like black patients (the treatment match), the disparity in 5-year survival barely changed at 4.3%, or a difference in median survival of 7 months. Hence, all recorded treatment differences explained only 0.6% (CI, 4.3% to 4.9%) of the 9.9% 5-year survival disparity. It is possible that the disparity in treatment would matter more if black patients were diagnosed with less advanced cancer, similar to the general white population. However, in the subset of patients with stage III colon cancer, we saw a treatment disparity pointing in the same direction as the survival disparity: White patients with stage III cancer who presented and were treated like black patients did worse than white patients with stage III cancer who presented like black patients and were treated like white patients (5-year survival, 41.2% vs. 43.7%; P ⫽ 0.013), with a reduction in median

Table 3. Outcomes for Patients With Stage III Colon Cancer Outcome Measure

Black Patients (n ⴝ 1677)

White Patients Matched for Treatment (n ⴝ 1677)

White Patients Matched for Presentation* (n ⴝ 1677)

Median survival (95% CI), mo 2-y survival (95% CI), % White ⫺ black difference†, % Deaths, n 5-y survival (95% CI), % White ⫺ black difference†, % Deaths, n Paired Cox model hazard ratio (black:white) (95% CI)‡

38 (34 to 42) 61.8 (59.4 to 64.1) – 641 37.4 (35.1 to 39.8) – 1045 –

44 (39 to 48) (P ⫽ 0.094) 62.9 (60.5 to 65.2) 0.9 (⫺1.9 to 7.2) (P ⫽ 0.48) 622 41.2 (38.8 to 43.6) 3.8 (0.7 to 6.9) (P ⫽ 0.151) 982 1.122 (1.013 to 1.243) (P ⫽ 0.027)

50 (44 to 54) (P ⬍ 0.001) 66.1 (63.8 to 68.3) 4.3 (1.4 to 7.1) (P ⫽ 0.001) 568 43.7 (41.3 to 46.1) 6.3 (3.1 to 9.2) (P ⬍ 0.001) 939 1.211 (1.094 to 1.341) (P ⬍ 0.001)

* The exterior match P value was 0.013 (comparing survival in white patients who were matched for presentation with white patients who were matched for presentation and treatment). † P values used the Prentice–Wilcoxon test. All CIs were based on bootstrapped SEs. ‡ P values used all follow-up data after diagnosis. www.annals.org

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Racial Disparities in Colon Cancer Survival

survival of nearly 6 months (Table 3). The treatment disparity we saw in patients with stage III cancer was consistent with previous findings (13, 14), although those studies did not examine the relationship between the treatment disparity and survival disparity. For all patients, we also saw that a racial disparity in the 5-year survival of 4.3% remained even after matching for presentation and treatment. Although the disparity in survival in our analysis was predominantly cancer-related (Supplement) in the first 5 years, given that racial disparities are seen throughout our health care system (17, 62), it would have been surprising to see a complete elimination of the survival disparity on the basis of only cancer presentation and treatment. The residual disparity in the treatment match is similar to the 5-year survival disparity between black and white patients in the U.S. population as a whole (17). Although similar, we do not suggest that this is acceptable. Much of the residual survival disparity after matching for treatment is absent when comparing black and white patients with similar socioeconomic status. Others have seen similar findings when adjusting for differences in socioeconomic status (9). The shorter residual survival of black patients is also experienced by white patients with similar socioeconomic status. An important strength of our approach to studying the racial disparity using tapered matching is that by removing overlapping controls using the exterior match (28, 30), we could formally test whether white patients who presented like black patients but were treated like white patients had survival similar to white patients who presented like black patients and were treated like black patients. In patients with stage III cancer, a treatment disparity pointed in the same direction as a survival disparity, suggesting that part of the poorer survival of black patients with stage III cancer may be caused by substandard cancer treatment; nothing similar was seen for patients with stage I and II cancer. Another important strength of our study was that 81 181 white patients were used as potential control patients for 7677 black patients, producing a matching ratio of greater than 10:1. This allowed us to achieve very close matches, generally avoiding the need for model-based analyses where model coefficients may reflect the white population (29). There were also limitations to this study. We did not have chart review to verify our definitions of treatments coded from Medicare bills or noted in SEER data. However, for most chemotherapy regimens used in colon cancer, there were bills from Medicare, and for all surgery and radiation therapy, we did have billing documentation. We also did not include covariates describing hospital quality in the treatment match. In conclusion, more of the racial disparity in colon cancer survival is explained by differences in health at diagnosis (both the state of the cancer and comorbid conditions) than by differences in subsequent treatment. Our study suggests that the most effective route to reducing the

racial survival disparity is to find ways to reduce the disparity in presentation, so fewer black patients present with advanced disease. For patients with stage IV cancer (more common in black than white patients), some of the survival disparity could be attributed to treatment differences, but survival was dismal in all comparisons. For stage III, there were significant differences in survival in the treatment match and important treatment differences between black and white patients after matching for presentation, raising concerns about the quality of colon cancer treatment received by black patients with stage III cancer. However, overall, treatment differences accounted for only a very small percentage of the overall racial disparity in 5-year survival. From Center for Outcomes Research, The Children’s Hospital of Philadelphia; Abramson Cancer Center, University of Pennsylvania; Perelman School of Medicine, University of Pennsylvania; The Wharton School, University of Pennsylvania; The Leonard Davis Institute of Health Economics, University of Pennsylvania; and The Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania. Acknowledgment: The authors thank Traci Frank, AA; Hong Zhou,

MS; and Alexander Hill, BS (Center for Outcomes Research, The Children’s Hospital of Philadelphia), for their assistance with this research. Grant Support: By the Agency for Healthcare Research and Quality (grant R01 HS 018355) and the National Science Foundation (grant NSF SBS 1260782). Disclosures: Disclosures can be viewed at www.acponline.org/authors /icmje/ConflictOfInterestForms.do?msNum⫽M14-0900. Reproducible Research Statement: Study protocol: Available from Dr. Silber (e-mail, [email protected]). Statistical code: The code was written in SAS and R. For more information about the statistical code, contact Dr. Silber (e-mail, [email protected]). Data set: SEERMedicare colon cancer data can be acquired from the National Cancer Institute at http://appliedresearch.cancer.gov/seermedicare. Requests for Single Reprints: Jeffrey H. Silber, MD, PhD, Center for Outcomes Research, The Children’s Hospital of Philadelphia, 3535 Market Street, Suite 1029, Philadelphia, PA 19104; e-mail, silber@email .chop.edu.

Current author addresses and author contributions are available at www .annals.org.

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Annals of Internal Medicine Current Author Addresses: Dr. Silber: The Nancy Abramson Wolfson

Author Contributions: Conception and design: J.H. Silber, P.R. Rosen-

Professor of Health Services Research, Center for Outcomes Research, The Children’s Hospital of Philadelphia, 3535 Market Street, Suite 1029, Philadelphia, PA 19104. Dr. Wang, Mr. Ross, Mr. Niknam, Mr. Ludwig, Ms. Wang, and Ms. Even-Shoshan: Center for Outcomes Research, The Children’s Hospital of Philadelphia, 3535 Market Street, Suite 1029, Philadelphia, PA 19104. Dr. Rosenbaum: The Robert G. Putzel Professor, Department of Statistics, The Wharton School, University of Pennsylvania, 473 Jon M. Huntsman Hall, 3730 Walnut Street, Philadelphia, PA 19104-6340. Dr. Clark: Rena Rowan Breast Center, Abramson Cancer Center, Perelman Center for Advanced Medicine, 3 West Pavilion, 3400 Civic Center Boulevard, Philadelphia, PA 19104. Dr. Fox: The Mariann T. and Robert J. MacDonald Professor in Breast Cancer Care Excellence, Perelman Center for Advanced Medicine, 3 West Pavilion, 3400 Civic Center Boulevard, Philadelphia, PA 19104. Dr. Giantonio: Associate Professor of Medicine, Abramson Cancer Center, Perelman Center for Advanced Medicine, University of Pennsylvania, 4 West Pavilion, 3400 Spruce Street, Philadelphia, PA 19104.

baum, K.R. Fox, B.J. Giantonio. Analysis and interpretation of the data: J.H. Silber, P.R. Rosenbaum, R.N. Ross, B.A. Niknam, J.M. Ludwig, W. Wang, A.S. Clark, M. Wang, O. Even-Shoshan, B.J. Giantonio. Drafting of the article: J.H. Silber, P.R. Rosenbaum, B.A. Niknam, A.S. Clark, B.J. Giantonio. Critical revision of the article for important intellectual content: J.H. Silber, P.R. Rosenbaum, B.A. Niknam, J.M. Ludwig, A.S. Clark, K.R. Fox, B.J. Giantonio. Final approval of the article: J.H. Silber, P.R. Rosenbaum, B.A. Niknam, W. Wang, A.S. Clark, K.R. Fox, B.J. Giantonio. Provision of study materials or patients: J.H. Silber, K.R. Fox. Statistical expertise: J.H. Silber, P.R. Rosenbaum, R.N. Ross, W. Wang. Obtaining of funding: J.H. Silber, P.R. Rosenbaum, O. Even-Shoshan. Administrative, technical, or logistic support: J.H. Silber, B.A. Niknam, M. Wang, O. Even-Shoshan. Collection and assembly of data: J.H. Silber.

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