Abstract
Purpose
To assess racial differences in the receipt of nephrectomy in patients diagnosed RCC in the US.
Materials and methods
2005 to 2015 data from the SEER database was analyzed and 70,059 patients with RCC were identified. We compared demographic and tumor characteristics between black patients and white patients. We applied logistic regression to assess the association between race and the odds of the receipt of nephrectomy. We also applied Cox proportional hazards model to assess the impact of race on cancer-specific mortality (CSM) and all-cause mortality (ACM) in patients diagnosed with RCC in the US.
Results
Black patients had 18% lower odds of receiving nephrectomy compared to white patients (p < 0.0001). The odds of the receipt of nephrectomy also reduced with age at diagnosis. In addition, patients with T3 stage had the greatest odds of receiving nephrectomy when compared to T1 (p < 0.0001). There was no difference in the risk of cancer-specific mortality between black patients and white patients; black patients had 27% greater odds of all-cause mortality than white patients (p < 0.0001). Patients who did not receive nephrectomy had a 42% and 35% higher risk of CSM and ACM respectively, when compared to patients who received nephrectomy.
Conclusions
Black patients diagnosed with RCC in the US have a greater ACM risk and are less likely than white patients to receive nephrectomy. Systemic changes are needed to eliminate racial disparity in the treatment and outcomes of RCC in the US.
Introduction
The main types of kidney cancer are renal cell cancer (RCC), transitional cell cancer, and Wilms tumor [1], with RCC being the most common type of kidney cancer and constituting approximately 90% of cancers derived from the renal parenchyma [2–5]. Kidney cancer is the 8th most common cancer in the United States (US) [6, 7]. This is a disease of public health importance; in the United States, the prevalence of kidney and renal pelvis cancer was 582,727 as of 2018. In 2021 alone, the estimated number of new kidney cancer cases in the US was 76,080, accounting for about 4.0% of all new cancer cases in the US in 2021 [7]. Kidney cancer is one of the top ten cancers that lead to death, accounting for 2.3% of all estimated cancer deaths in the US in 2021 [7].
Although kidney cancer impacts persons of all races, studies have shown that it does not always affect the races equally [8]. Literature is replete with evidence of racial disparities in health conditions and outcomes between black patients and white patients in the US and how the experiences of different races have shaped health outcomes [9]. Additionally, the incidence rates of kidney cancers have been rising more rapidly among black patients than white patients over the past five decades [10]. An analysis of the incidence and survival among patients with kidney cancer from the national Surveillance, Epidemiology, and End Results (SEER) Registry Database, showed that black patients have a more significant rise in incidence and a poorer outcome than white patients of the same age and disease stage [11].
Nephrectomy is the recommended surgical treatment for non-metastatic kidney cancers [12]. Due to discriminatory policies and practices, black patients are more likely to face barriers in accessing healthcare leading to worse treatment outcomes than their white counterparts. In addition, black patients have more renal-relevant comorbidities (hypertension, diabetes, and chronic renal failure) and poorer overall cancer survival compared to white patients [13, 14].
Studies evaluating disparity in nephrectomy by race have been few and many have yielded equivocal results, necessitating the investigation of the role of race (as a proxy for exposure to structural racism) [15] in the receipt of nephrectomy using a large and nationally representative database. Therefore, this study examines the presentation, early definitive surgical treatment, and mortality among patients with RCC in the US, to investigate racial disparity in the receipt of nephrectomy for renal cell carcinoma patients.
Methods
Data source
We analyzed SEER data of patients diagnosed with renal cell carcinoma between 2005 and 2015 in the United States. The SEER database is a product of a nationally representative surveillance conducted by the National Cancer Institute (NCI), which collects demographic, pathologic, and clinical information on incident cancer across 18 geographic locations in the United States, covering nearly a third of the US population. Our study cohort includes patients diagnosed with renal cell carcinoma between January 1, 2005, and December 31, 2015 [16].
Study population
We identified 75,714 patients diagnosed with histologically confirmed non-metastatic renal cell carcinoma diagnosed between 2005 and 2015. We excluded patients who were diagnosed for the first time in nursing/ convalescent homes (n = 242), patients whose race were neither Black nor White (n = 5,029). Patients diagnosed in Louisiana in 2005 (n = 384) were also excluded. The records from patients diagnosed with RCC in Louisiana were excluded because of the possibility of a differential loss of records due to the impact of Hurricane Katrina in 2005. The final cohort consisted of 70,059 patients with renal cell carcinoma. The outcomes of the study were reviewed until December 31, 2015, or the patient’s demise.
Ethical consideration
This study analyzed publicly available data from the SEER database, hence has been approved based on the broad agreement signed in the SEER data-use agreement. This agreement ensures the study satisfies the Health Insurance Portability and Accountability Act of 1996 (HIPAA), confidentiality, and ethical considerations.
Variables
The baseline demographic data include age (10–year intervals), race was categorized as “Black” vs “White” irrespective of ethnicity, tumor stage (T1, T2, T3, and T4), receipt of nephrectomy (Yes vs No), binary survival status (Dead (Coded as “0”) vs Alive (Coded as “1”)), and SEER registry geographic location according to the Census Bureau of the United States (Northeast, Midwest, South, and West). We defined survival as the number of months following diagnosis of RCC to the earlier of death or the date of the end of the study. The patients in this database who received nephrectomy had their surgery within 4–6 months of diagnosis. The variables were operationalized as categorical variables except for “year of diagnosis” and “survival” variables that were operationalized as continuous variables.
Outcomes
The unit of analysis was the patient. The primary outcome was the receipt of nephrectomy, which was either radical or partial nephrectomy. CSM (cancer-specific mortality) and ACM (all-cause mortality) were the secondary outcome variables operationalized as time-to-event variables.
Analysis
Chi-squared and T-test univariate analyses were used to compare baseline characteristics of black patients vs white patients in the study. The association between race and receipt of nephrectomy was evaluated by fitting a multivariable logistic regression model, with demographic and tumor characteristics as covariates. Cox proportional hazard models were fitted to determine the influence of race on CSM and ACM while controlling for confounders. Additionally, Cox proportional hazard models were fitted to assess the relationship between nephrectomy and survival in the overall study population and within each race category. All analyses were conducted using SAS 9.4 software (Cary, NC). The level of statistical significance was set at p< 0.05.
Results
Black patients and white patients constituted 11.51% (n = 8,066) and 88.49% (n = 61,993) of the study cohort respectively. The post-diagnosis follow-up of the cohort median (interquartile range) was 54 (63) months; the median (interquartile range) post-diagnosis follow-up for black patients and white patients was 51 (60) months and 54 (63) months, respectively. The mean age at diagnosis (SD) was 61.4 (12.4) years; the mean ages (SD) for black patients and white patients were 59.5 (11.7) years and 61.7 (12.5) years, respectively. Fig 1 summarizes the trend of the use of nephrectomy.
Fig 1. Trend of the use of nephrectomy.
Table 1 details the comparison of demographic and tumor characteristics of all study subjects, and black patients versus white patients. Approximately 57.8% (n = 40,484) were ≤ 65 years, 74.4% (n = 52,151) had T1 disease. There were significant differences across tumor stages and geographical location of patients by race (p < 0.0001). A lower proportion of black patients received nephrectomy compared to white patients (82.8% vs 85.4%; p < 0.0001). A greater proportion of white patients vs black patients died of RCC (11.7% vs 9.1%, p < 0.0001) but no difference in all cause death between white patients vs black patients (25.8% vs 26.3%, p = 0.34).
Table 1. Characteristic of study cohort and comparison by patients’ race.
| Covariates | Total (70059: 100%) | Black patients 8066 (11.51%) | White patients 61993 (88.49%) | p value |
|---|---|---|---|---|
| year of diagnosis | ||||
| 2005 | 4809 (6.86) | 466 (5.78) | 4343 (7.01) | <.0001 |
| 2006 | 5667 (8.09) | 543 (6.73) | 5124 (8.27) | |
| 2007 | 6095 (8.70) | 679 (8.42) | 5416 (8.74) | |
| 2008 | 6582 (9.39) | 777 (9.63) | 5805 (9.36) | |
| 2009 | 6903 (9.85) | 803 (9.96) | 6100 (9.84) | |
| 2010 | 6294 (8.98) | 734 (9.10) | 5560 (8.97) | |
| 2011 | 6355 (9.07) | 788 (9.77) | 5567 (8.98) | |
| 2012 | 6499 (9.28) | 777 (9.63) | 5722 (9.23) | |
| 2013 | 6556 (9.36) | 802 (9.94) | 5754 (9.28) | |
| 2014 | 6962 (9.94) | 827 (10.25) | 6135 (9.90) | |
| 2015 | 7337 (10.47) | 870 (10.79) | 6467 (10.43) | |
| Age at diagnosis, years | ||||
| <45 | 6565 (9.37) | 831 (10.30) | 5734 (9.25) | <.0001 |
| 45–54 | 13168 (18.80) | 1760 (21.82) | 11408 (18.40) | |
| 55–64 | 20751 (29.62) | 2656 (32.93) | 18095 (29.19) | |
| 65–74 | 18946 (27.04) | 2033 (25.20) | 16913 (27.28) | |
| 75–84 | 9324 (13.31) | 726 (9.00) | 8598 (13.87) | |
| ≥85 | 1305 (1.86) | 60 (0.74) | 1245 (2.01) | |
| Regions | ||||
| Midwest | 8470 (12.09) | 1219 (15.11) | 7251 (11.70) | <.0001 |
| Northeast | 10009 (14.29) | 1077 (13.35) | 8932 (14.41) | |
| South | 18354 (26.20) | 3519 (43.63) | 14835 (23.93) | |
| West | 33226 (47.43) | 2251 (27.91) | 30975 (49.97) | |
| Tumor stage | ||||
| T1 | 52151 (74.44) | 6598 (81.80) | 45553 (73.48) | <.0001 |
| T2 | 298 (0.43) | 53 (0.66) | 245 (0.40) | |
| T3 | 16451 (23.48) | 1303 (16.15) | 15148 (24.44) | |
| T4 | 1159 (1.65) | 112 (1.39) | 1047 (1.69) | |
| Tumor grade | ||||
| 1 | 8996 (12.84) | 1022 (12.67) | 7974 (12.86) | <.0001 |
| 2 | 36588 (52.22) | 4175 (51.76) | 32413 (52.28) | |
| 3 | 19554 (27.91) | 2406 (29.83) | 17148 (27.66) | |
| 4 | 4921 (7.02) | 463 (5.74) | 4458 (7.19) | |
| Nephrectomy | ||||
| No | 10439 (14.90) | 1384 (17.16) | 9055 (14.61) | <.0001 |
| Yes | 59620 (85.10) | 6682 (82.84) | 52938 (85.39) | |
| Partial Nephrectomy | ||||
| No | 46230 (65.99) | 5272 (65.36) | 40958 (66.07) | 0.2068 |
| Yes | 23829 (34.01) | 2794 (34.64) | 21035 (33.93) | |
| Radical Nephrectomy | ||||
| No | 34268 (48.91) | 4178 (51.80) | 30090 (48.54) | <.0001 |
| Yes | 35791 (51.09) | 3888 (48.20) | 31903 (51.46) | |
| Cancer-specific mortality | ||||
| Alive | 62047 (88.56) | 7331 (90.89) | 54716 (88.26) | <.0001 |
| Dead | 8012 (11.44) | 735 (9.11) | 7277 (11.74) | |
| All-cause mortality | ||||
| Alive | 51946 (74.15) | 5945 (73.70) | 46001 (74.20) | 0.3355 |
| Dead | 18113 (25.85) | 2121 (26.30) | 15992 (25.80) |
Table 2 summarizes the comparison of demographic and tumor characteristics of all study subjects by their nephrectomy status. Approximately 85.1% (n = 59,620) of the patients received nephrectomy. Table 2 presents differences in nephrectomy by age, sex, race, region, and tumor stage. Patients younger than 65 years were more likely to receive nephrectomy than older patients diagnosed with RCC (< 0.0001), and patients with lower-stage disease were more likely to receive nephrectomy (p < 0.0001).
Table 2. Characteristics of the study cohort and comparison by receipt of nephrectomy.
| Covariates | Total (70059; 100%) | Yes (59620; 85.10%) | No (9541; 13.62%) | p value |
|---|---|---|---|---|
| Year of diagnosis | ||||
| 2005 | 4809 (6.86) | 4118 (6.91) | 691 (6.62) | 0.0001 |
| 2006 | 5667 (8.09) | 4772 (8.00) | 895 (8.57) | |
| 2007 | 6095 (8.70) | 5087 (8.53) | 1008 (9.66) | |
| 2008 | 6582 (9.39) | 5519 (9.26) | 1063 (10.18) | |
| 2009 | 6903 (9.85) | 5830 (9.78) | 1073 (10.28) | |
| 2010 | 6294 (8.98) | 5337 (8.95) | 957 (9.17) | |
| 2011 | 6355 (9.07) | 5440 (9.12) | 915 (8.77) | |
| 2012 | 6499 (9.28) | 5571 (9.34) | 928 (8.89) | |
| 2013 | 6556 (9.36) | 5658 (9.49) | (8.60) | |
| 2014 | 6962 (9.94) | 6007 (10.08) | 955 (9.15) | |
| 2015 | 7337 (10.47) | 6281–10.54 | 1056 (10.12) | |
| Age at diagnosis, years | ||||
| <45 | 6565 (9.37) | 5852 (9.82) | 713 (6.83) | 0.0001 |
| 45–54 | 13168 (18.80) | 11525 (19.33) | 1643 (15.74) | |
| 55–64 | 20751 (29.62) | 17941 (30.09) | 2810 (26.92) | |
| 65–74 | 18946 (27.04) | 16016 (26.86) | 2930 (28.07) | |
| 75–84 | 9324 (13.31) | 7375 (12.37) | 1949 (18.67) | |
| ≥85 | 1305 (1.86) | 911 (1.53) | 394 (3.77) | |
| Regions | ||||
| Midwest | 8470 (12.09) | 6505 (10.91) | 1965 (18.82) | 0.0001 |
| Northeast | 10009 (14.29) | 8440 (14.16) | 1569 (15.03) | |
| South | 18354 (26.20) | 15795 (26.49) | 2559 (24.51) | |
| West | 33226 (47.43) | 28880 (48.44) | 4346 (41.63) | |
| Tumor stage | ||||
| T1 | 52151 (74.44) | 44406 (74.48) | 7745 (74.19) | 0.0001 |
| T2 | 298 (0.43) | 138 (0.23) | 160 (1.53) | |
| T3 | 16451 (23.48) | 14396 (24.15) | 2055 (19.69) | |
| T4 | 1159 (1.65) | 680 (1.14) | 479 (4.59) | |
| Tumor grade | ||||
| 1 | 8996 (12.84) | 7249 (12.16) | 1747 (16.74) | 0.0001 |
| 2 | 36588 (52.22) | 31324 (52.54) | 5264 (50.43) | |
| 3 | 19554 (27.91) | 16848 (28.26) | 2706 (25.92) | |
| 4 | 4921 (7.02) | 4199 (7.04) | 722 (6.92) | |
| Cancer-specific mortality | ||||
| Alive | 62047 (88.56) | 53276 (89.36) | 8771 (84.02) | 0.0001 |
| Dead | 8012 (11.44) | 6344 (10.64) | 1668 (15.98) | |
| All-cause mortality | ||||
| Alive | 51946 (74.15) | 45238 (75.88) | 6708 (64.26) | 0.0001 |
| Dead | 18113 (25.85) | 14382 (24.12) | 3731 (35.74) | |
| Race | ||||
| Black patients | 8066 (11.51) | 6682 (11.21) | 1384 (13.26) | 0.0001 |
| White patients | 61993 (88.49) | 52938 (88.79) | 9055 (86.74) |
Table 3 displays the results of the multivariable logistic regression. The odds of receipt of nephrectomy reduced with increasing age. Compared to white patients, black patients had 18% lower adjusted odds of receipt of nephrectomy (Crude = 17% lower odds, p<0.0001). Compared to patients with T1, patients with stages T2, T3, T4 disease were 83% less likely, 17% more likely, and 78% less likely to receive nephrectomy, respectively.
Table 3. Multivariable logistic regression model showing the odds of receipt of nephrectomy.
| Covariates | HR (95% CI) | p value |
|---|---|---|
| Year of diagnosis | 1.01 (1.01–1.02) | 0.0006 |
| Age at diagnosis, years | ||
| <45 | ||
| 45–54 | 0.86 (0.78–0.95) | 0.0017 |
| 55–64 | 0.79 (0.71–0.85) | <.0001 |
| 65–74 | 0.65 (0.60–0.71) | <.0001 |
| 75–84 | 0.46 (0.41–0.50) | <.0001 |
| ≥85 | 0.27 (0.24–0.31) | <.0001 |
| Race | ||
| White patients (reference) | ||
| Black patients | 0.82 (0.76–0.87) | <.0001 |
| Region | ||
| Midwest (reference) | ||
| Northeast | 1.68 (1.56–1.81) | <.0001 |
| South | 1.87 (1.75–2.00) | <.0001 |
| West | 2.03 (1.94–2.16) | <.0001 |
| Tumor stage | ||
| T1 (reference) | ||
| T2 | 0.17 (0.13–0.21) | <.0001 |
| T3 | 1.17 (1.11–1.24) | <.0001 |
| T4 | 0.22 (0.19–0.25) | <.0001 |
| Tumor grade | ||
| 1 (reference) | ||
| 2 | 1.41 (1.33–1.50) | <.0001 |
| 3 | 1.55 (1.44–1.66) | <.0001 |
| 4 | 1.60 (1.43–1.77) | <.0001 |
Table 4 summarizes the mortality risks of the study patients. The risk of CSM is similar between black patients and white patients. However, CSM increased with older age and higher tumor stage. Patients who did not receive nephrectomy had a 42% higher risk of CSM relative to patients who received nephrectomy. The risk of ACM in black patients was 27% higher compared to white patients. ACM increased with older age and higher stage. Patients who did not receive nephrectomy had a 35% higher risk of ACM relative to patients who received nephrectomy.
Table 4. Multivariable Cox proportional hazards models showing the risk of mortality in the study cohort.
| Covariates | Cancer-specific mortality | All-cause mortality | ||
|---|---|---|---|---|
| HR (95% CI) | p value | HR (95% CI) | p value | |
| Nephrectomy | ||||
| Yes | 0.58 (0.55–0.62) | <.0001 | 0.65 (0.63–0.68) | <.0001 |
| Year of diagnosis | 0.96 (0.95–0.97) | <.0001 | 0.97 (0.97–0.98) | <.0001 |
| Age at diagnosis, years | ||||
| <45 (reference) | ||||
| 45–54 | 1.27 (1.14–1.43) | <.0001 | 1.57 (1.43–1.71) | <.0001 |
| 55–64 | 1.37 (1.23–1.52) | <.0001 | 2.05 (1.89–2.23) | <.0001 |
| 65–74 | 1.53 (1.37–1.71) | <.0001 | 2.86 (2.63–3.11) | <.0001 |
| 75–84 | 1.88 (1.68–2.11) | <.0001 | 4.59 (4.22–4.99) | <.0001 |
| ≥85 | 2.33 (1.99–2.74) | <.0001 | 7.13 (6.42–7.92) | <.0001 |
| Race | ||||
| White patients (reference) | ||||
| Black patients | 1.06 (0.98–1.15) | 0.1222 | 1.27 (1.21–1.33) | <.0001 |
| Region | ||||
| Midwest (reference) | ||||
| Northeast | 0.96 (0.88–1.05) | 0.3400 | 0.911 (0.86–0.97) | 0.0014 |
| South | 1.16 (1.07–1.25) | 0.0002 | 1.14 (1.08–1.20) | <.0001 |
| West | 1.11 (1.04–1.19) | 0.0036 | 1.00 (0.95–1.05) | 0.9678 |
| Tumor stage | ||||
| T1 (reference) | ||||
| T2 | 2.73 (1.99–3.75) | <.0001 | 1.43 (1.19–1.73) | 0.0002 |
| T3 | 6.24 (5.90–6.57) | <.0001 | 2.47 (2.40–2.55) | <.0001 |
| T4 | 16.86 (15.44–18.41) | <.0001 | 6.59 (6.13–7.07) | <.0001 |
| Tumor grade | ||||
| 1 (reference) | ||||
| 2 | 1.21 (1.08–1.35) | 0.0011 | 1.01 (0.96–1.07) | 0.6641 |
| 3 | 2.80 (2.50–3.13) | <.0001 | 1.49 (1.41–1.57) | <.0001 |
| 4 | 6.24 (5.55–7.01) | <.0001 | 3.07 (2.89–3.27) | <.0001 |
The risk of CSM and ACM of the study patients, by race, showed a similar trend in patients treated with either radical or partial nephrectomy (Tables 5 & 6).
Table 5. Multivariable Cox proportional hazards models showing the risk of mortality in the radical nephrectomy study cohort.
| Covariates | Cancer-specific mortality | All-cause mortality | ||
|---|---|---|---|---|
| HR (95% CI) | p value | HR (95% CI) | p value | |
| Race | ||||
| White patients (reference) | ||||
| Black patients | 1.08 (1.00–1.17) | 0.0497 | 1.29 (1.23–1.35) | <.0001 |
Table 6. Multivariable Cox proportional hazards models showing the risk of mortality in the partial nephrectomy study cohort.
| Covariates | Cancer-specific mortality | All-cause mortality | ||
|---|---|---|---|---|
| HR (95% CI) | p value | HR (95% CI) | p value | |
| Race | ||||
| White patients (reference) | ||||
| Black patients | 1.09 (1.01–1.18) | 0.0317 | 1.29 (1.23–1.35) | <.0001 |
Discussion
In this study, we investigated the disparity in the receipt of nephrectomy and mortality risk between black patients and white patients, diagnosed with renal cell carcinoma in the US over ten years. Black patients had lower odds of receipt of nephrectomy and a higher risk of all-cause mortality than white patients. In agreement with our findings, a study by Zini et al. suggests that the receipt of nephrectomy, the gold standard treatment for non-metastatic renal cell cancer, differs by race. However, it suggests that this difference did not have any effect on survival outcomes [17]. Another study examining the trends in the use of nephrectomy and cytoreductive surgery in the US reported that black patients were less likely than white patients to receive surgical intervention when diagnosed with RCC [18].
The use of nephrectomy appears to be on the rise, and most patients in this study received some form of nephrectomy. Although younger age at diagnosis was associated with greater odds of receipt of nephrectomy and black patients were more likely to be diagnosed with RCC at a younger age than white patients, black patients still had 18% lesser odds of nephrectomy receipt than white patients in this study. The SEER programs did not collect information on comorbidity or information that may help to calculate comorbidity scores (e.g., Charlson’s Comorbidity Index). Hence the influence of comorbidity on receipt of nephrectomy could not be determined. Previous study examining the influence of age and comorbidity of receipt of radical surgeries for major urological cancers suggest age is more important than comorbidity in the receipt of radical surgeries [19]. While age and comorbidity may not be the only factors limiting RCC health outcomes in black patients, discriminatory policies and practices have created barriers for black patients in accessing and utilizing health care. Also, the inability of the healthcare system to demonstrate trustworthiness is a likely contributor to poorer health outcomes in black patients.
Black patients had higher ACM than white patients when diagnosed with renal cell carcinoma in this study. Increasing age at diagnosis, tumor grade, and stage are associated with greater odds of cancer-specific and all-cause mortality. Because black patients have 18% lesser odds of receipt of nephrectomy than white patients, it is not surprising that black patients have about 27% greater odds of ACM than white patients. Multiple factors such as differential comorbidities and use of other therapies such as adjuvant therapy not captured in this analysis due to the limitation of the data could have affected the ACM outcome. A study that analyzed SEER data concluded that there is reduced receipt of nephrectomy in black patients versus white patients but suggests that the reduction in receipt of nephrectomy does not influence survival outcomes. The study had a smaller population, a shorter follow-up time and due to its timing, was unlikely to have captured the benefits of nephron-sparing surgery [17].
Access to nephrectomy and survival outcomes are lower in black patients than in white patients [17, 20]. Compared to white patients, discriminatory policies have led to lower health insurance coverage, less likelihood of having an established source of healthcare, and greater difficulty in seeking healthcare in black individuals [21–23]. Also, there is a long-standing inability of the healthcare system to show that it is deserving of the trust of black patients [24, 25]. Perhaps, the most discussed example of this is the Tuskegee syphilis experiment, where black patients were intentionally exposed to harm. Similar to this is the experience of African American women unethically subjected to gynecological procedures and such experiences as when slaves were not offered medical care because they were slaves [23]. Similarly, it is reported that providers caring for black patients are less likely to give adequate health information to their patients, thus impairing their ability to participate in shared decision-making about their care [26]. These experiences may have bred a fear of complications, an aversion to surgery [27, 28] and an overall negative attitude towards accepting procedures such as nephrectomy. The discrimination in health care delivery, provider bias plus the negative predisposition towards the health care system contributes to poorer health outcomes in black patients diagnosed with RCC.
Limitations
We applied a retrospective study design. Due to the nature of the SEER data, it was impossible to capture the use of additional therapies such as adjuvant therapies/ chemotherapies which may have effects on survival outcomes. Lastly, information on comorbidities was not available in our data, hence, we were unable to adjust for comorbidities in our analysis.
In this study, the sample size of some racial groups was too small to make meaningful statistical inference. The inability to evaluate the use of nephrectomy in certain racial groups is a limitation.
Lastly, due to the unavailability of social economic data or social determinants of health (SDOH) in the SEER data in this analysis, we were unable to explore the association between socio-economic status or SDOH and receipt of nephrectomy.
Conclusion
Although there has been technological advancement and the use of nephrectomy in treating patients diagnosed with RCC has improved, black patients are still less likely than white patients to receive nephrectomy despite the greater likelihood of RCC incidence and mortality in black patients. Several factors stemming from systemic racism and racial inequalities contribute greatly to a disparity in health care delivery. Improving health outcomes for patients diagnosed with RCC will require a deliberate adoption of system-wide social and medical changes in the approach to health care delivery and treatment decisions that address systemic racism and eliminate disparity in health outcomes in black patients and other minority populations in the US.
Data Availability
SEER data is publicly available on request from the National Cancer Institute (NCI), and can be downloaded through this link - https://seer.cancer.gov/data-software/.
Funding Statement
The authors received no specific funding for this work.
References
- 1.National Cancer of Health (NIH). Kidney (Renal Cell) Cancer—Patient Version. NCI. Accessed July 4, 2022. https://www.cancer.gov/types/kidney
- 2.Mathew A, Devesa SS, Fraumeni JF, Chow WH. Global increases in kidney cancer incidence, 1973–1992. European Journal of Cancer Prevention. 2002;11(2):171–178. http://www.jstor.org/stable/45051248 [DOI] [PubMed] [Google Scholar]
- 3.Jemal A, Siegel R, Xu J, Ward E. Cancer Statistics, 2010. CA: A Cancer Journal for Clinicians. 2010;60(5):277–300. doi: 10.3322/caac.20073 [DOI] [PubMed] [Google Scholar]
- 4.Scelo G, Larose T. Epidemiology and Risk Factors for Kidney Cancer. Journal of Clinical Oncology. 2018;36(36):3574–3581. https://ascopubs.org/doi/10.1200/JCO.2018.79.1905 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Padala SA, Barsouk A, Thandra KC, et al. Epidemiology of Renal Cell Carcinoma. World J Oncol. 2020;11(3):79–87. doi: 10.14740/wjon1279 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.National Cancer of Health (NIH). Cancer Statistics. NCI. Published April 2, 2015. Accessed July 4, 2022. https://www.cancer.gov/about-cancer/understanding/statistics
- 7.National Cancer of Health (NIH). Cancer of the Kidney and Renal Pelvis—Cancer Stat Facts. SEER. Accessed July 4, 2022. https://seer.cancer.gov/statfacts/html/kidrp.html
- 8.Centers for Disease Control and Prevention. USCS Data Visualizations. Accessed July 4, 2022. https://gis.cdc.gov/grasp/USCS/DataViz.html
- 9.Smedley BD. The lived experience of race and its health consequences. Am J Public Health. 2012;102(5):933–935. doi: 10.2105/AJPH.2011.300643 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Lipworth L, Tarone RE, McLaughlin JK. Renal cell cancer among African Americans: an epidemiologic review. BMC Cancer. 2011;11(1):133. doi: 10.1186/1471-2407-11-133 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Vaishampayan UN, Do H, Hussain M, Schwartz K. Racial disparity in incidence patterns and outcome of kidney cancer. Urology. 2003;62(6):1012–1017. doi: 10.1016/j.urology.2003.07.010 [DOI] [PubMed] [Google Scholar]
- 12.Ljungberg B, Bensalah K, Bex A, et al. Disease Management. Guidelines on Renal Cell Carcinoma. European Association of Urology; 2015:24 [Google Scholar]
- 13.Sathianathen NJ, Jarosek SL, Fan Y, Krishna SR, Konety BR. Racial Disparities in Surgical Outcomes Among Males Following Major Urologic Cancer Surgery. American Journal of Preventive Medicine. 2018;55(5, Supplement 1):S14–S21. doi: 10.1016/j.amepre.2018.05.012 [DOI] [PubMed] [Google Scholar]
- 14.Schwartz K, Ruterbusch JJ, Colt JS, Miller DC, Chow WH, Purdue MP. Racial disparities in overall survival among renal cell carcinoma patients with young age and small tumors. Cancer Med. 2016;5(2):200–208. doi: 10.1002/cam4.578 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Boyd RW, Lindo EG, Weeks LD, McLemore MR. On Racism: A New Standard For Publishing On Racial Health Inequities. Health Affairs Forefront. [Google Scholar]
- 16.National Institute of Health (NIH). SEER Registries—About SEER. SEER. Accessed July 4, 2022. https://seer.cancer.gov/registries/index.html
- 17.Zini L, Perrotte P, Capitanio U, et al. Race affects access to nephrectomy but not survival in renal cell carcinoma. BJU international. 2009;103(7):889–893. doi: 10.1111/j.1464-410X.2008.08119.x [DOI] [PubMed] [Google Scholar]
- 18.Tsao CK, Small AC, Moshier EL, et al. Trends in the use of cytoreductive nephrectomy in the United States. Clinical Genitourinary Cancer. 2012;10(3):159–163. doi: 10.1016/j.clgc.2012.03.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Adejoro O, Alishahi A, Konety B. Association of Comorbidity, Age, and Radical Surgical Therapy for Prostate Cancer, Bladder Cancer, and Renal Cell Carcinoma. Urology. 2016;97:130–137.e1. doi: 10.1016/j.urology.2016.06.015 [DOI] [PubMed] [Google Scholar]
- 20.Berndt SI, Carter HB, Schoenberg MP, Newschaffer CJ. Disparities in Treatment and Outcome for Renal Cell Cancer Among Older Black and White Patients. JCO. 2007;25(24):3589–3595. doi: 10.1200/JCO.2006.10.0156 [DOI] [PubMed] [Google Scholar]
- 21.Institute of Medicine (US) Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. (Smedley BD, Stith AY, Nelson AR, eds.). National Academies Press (US); 2003. Accessed July 4, 2022. http://www.ncbi.nlm.nih.gov/books/NBK220358/ [PubMed]
- 22.Copeland VC. African Americans: disparities in health care access and utilization. Health Soc Work. 2005;30(3):265–270. doi: 10.1093/hsw/30.3.265 [DOI] [PubMed] [Google Scholar]
- 23.Jones JH. The Tuskegee Syphilis Experiment. The Oxford Textbook of Clinical Research Ethics. Oxford; New York: Oxford University Press, 2008: 86–96. Accessed July 4, 2022. https://repository.library.georgetown.edu/handle/10822/1039896 [Google Scholar]
- 24.Armstrong K, Putt M, Halbert CH, et al. Prior experiences of racial discrimination and racial differences in health care system distrust. Med Care. 2013;51(2):144–150. doi: 10.1097/MLR.0b013e31827310a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Armstrong K, McMurphy S, Dean LT, et al. Differences in the patterns of health care system distrust between blacks and whites. Journal of general internal medicine. 2008;23(6):827–833. doi: 10.1007/s11606-008-0561-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Peek ME, Odoms-Young A, Quinn MT, Gorawara-Bhat R, Wilson SC, Chin MH. Race and shared decision-making: perspectives of African-Americans with diabetes. Soc Sci Med. 2010;71(1):1–9. doi: 10.1016/j.socscimed.2010.03.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Ibrahim SA, Siminoff LA, Burant CJ, Kwoh CK. Understanding ethnic differences in the utilization of joint replacement for osteoarthritis: the role of patient-level factors. Med Care. 2002;40(1 Suppl):I44–I51. doi: 10.1097/00005650-200201001-00006 [DOI] [PubMed] [Google Scholar]
- 28.Margolis ML, Christie JD, Silvestri GA, Kaiser L, Santiago S, Hansen-Flaschen J. Racial differences pertaining to a belief about lung cancer surgery: results of a multicenter survey. Ann Intern Med. 2003;139(7):558–563. doi: 10.7326/0003-4819-139-7-200310070-00007 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
SEER data is publicly available on request from the National Cancer Institute (NCI), and can be downloaded through this link - https://seer.cancer.gov/data-software/.