Abstract
Background:
Differences in receipt of guideline-concordant treatment might underlie well-established racial disparities in endometrial cancer mortality.
Objective:
Using the National Cancer Database, we assessed the hypothesis that among women with endometrioid endometrial cancer, racial/ethnic minority women would have lower odds of receiving guideline-concordant treatment than White women. In addition, we hypothesized that lack of guideline-concordant treatment was linked with worse survival.
Study design:
We defined receipt of guideline-concordant treatment using the National Comprehensive Cancer Network guidelines. Multivariable logistic regression models were used to compute odds ratios and 95% confidence intervals for associations between race and guideline-concordant treatment. We used multivariable Cox proportional hazards regression models to estimate hazards ratios and 95% confidence intervals for relationships between guideline-concordant treatment and overall survival in the overall study population and stratified by race/ethnicity.
Results:
This analysis was restricted to the 89,319 women diagnosed with an invasive, endometrioid endometrial cancer between 2004 and 2014. Overall, 74.7% of the cohort received guideline-concordant treatment (n=66,699). Analyses stratified by race showed that 75.3% of non-Hispanic White (n=57,442), 70.1% of non-Hispanic Black (n=4,334), 71.0% of Hispanic (n=3,263), and 72.5% of Asian/Pacific Islander patients (n=1,660) received treatment in concordance with guidelines. In multivariable-adjusted models, non-Hispanic Black (odds ratio=0.92, 95% confidence interval=0.86–0.98) and Hispanic women (odds ratio=0.90, 95% confidence interval=0.83–0.97) had lower odds of receiving guideline-concordant treatment compared to non-Hispanic White women, while Asian/Pacific Islander women had a higher odds of receiving guideline-concordant treatment (odds ratio=1.11, 95% confidence interval=1.00–1.23). Lack of guideline-concordant treatment was associated with lower overall survival in the overall study population (hazard ratio=1.12, 95% confidence interval=1.08–1.15), but was not significantly associated with overall survival among non-Hispanic Black (hazard ratio=1.09, 95% confidence interval=0.98–1.21), Hispanic (hazard ratio=0.92, 95% confidence interval=0.78–1.09), or Asian/Pacific Islander (hazard ratio=0.90, 95% confidence interval=0.70–1.16) women.
Conclusions:
Non-Hispanic Black and Hispanic women were less likely than non-Hispanic White women to receive guideline-concordant treatment, while Asian/Pacific Islander women more commonly received treatment in line with guidelines. Further, in the overall study population, overall survival was worse among those not receiving guideline-concordant treatment, although low power may have impacted the race-stratified models. Future studies should evaluate reasons underlying disparate endometrial cancer treatment.
Keywords: chemotherapy, disparities, guideline-concordant treatment, hospital-based cancer registry, race, radiation treatment, uterus neoplasm
Condensation:
Black and Hispanic women with endometrial cancer are less likely than White women to receive guideline-concordant treatment.
Introduction
Uterine cancer is the most common gynecological malignancy in the U.S. with an estimated 61,880 new cases expected in 2019 (1). Recent increases in endometrial cancer (EC) incidence, the most common form of uterine cancer, have been documented (2), with the most dramatic increases occurring among Black and Asian-American women (3). Among women with EC, Blacks have poorer overall and disease-specific survival, which is partly attributable to diagnosis with more aggressive tumor characteristics (4, 5) and a greater prevalence of comorbid conditions (6), all of which adversely affect survival (6–9). However, even among women with indolent forms of EC, such as low-grade endometrioid and/or early-stage disease, Black women experience worse survival compared to White women (3). For example, Cote and colleagues (3) demonstrated significantly lower five-year relative survival for Black women with low-grade endometrioid, localized tumors as compared with White women (94.1% vs. 99.8%).
Differences in the receipt of treatment, specifically guideline-recommended treatment, could underlie survival disparities. The National Comprehensive Cancer Network (NCCN) provides detailed treatment recommendations based on extensive data from clinical trials and observational research. EC treatment usually includes surgery with hysterectomy and bilateral salpingo-oophorectomy with or without nodal assessment. Among women with early stage disease, certain risk factors (e.g. deep myometrial and/or cervical invasion, and poor tumor differentiation) will influence the recommendation for adjuvant treatment to reduce recurrence rates (10). In stage III disease, adjuvant therapy, including chemotherapy or radiation therapy, may be utilized to reduce recurrence and improve survival outcomes. While prior studies have shown that Black women with other gynecological malignancies, such as ovarian cancer, are less likely to receive guideline-concordant treatment (GCT) (11–14), subsequently decreasing overall survival rates (15), few studies have been conducted among women with EC. In the Women’s Health Initiative (WHI) survivor cohort, we observed a non-statistically significant lower odds (odds ratio=0.46) of receipt of guideline-concordant EC treatment among 26 Black women compared to 581 White women (16). However, the analysis was underpowered, requiring additional studies of this relationship.
We initiated the current analysis to examine whether GCT varies according to race, whether predictors of GCT differ by race, and whether GCT is associated with survival among women with EC. We restricted this analysis to women with endometrioid EC, as NCCN guidelines for these tumors are based on several definitive randomized clinical trials, including the Post-operative Radiation Therapy in Endometrial Carcinoma (PORTEC) 1 and 2 studies (17, 18), Gynecologic Oncology Group (GOG)-99 (19), and the UK Medical Research Council A Study in the Treatment of Endometrial Cancer (MRC ASTEC) (20). Based on poorer survival of minority women with EC compared to Whites (3), we hypothesized that minorities would less commonly receive GCT than non-Hispanic White (NHW) women. We further hypothesized that lack of GCT would be associated with worse survival, given these treatment regimens are well-supported by observational and clinical trial data.
Materials and Methods
Data Source
Data were obtained from the National Cancer Database (NCDB), a hospital-based cancer registry containing data from over 1400 facilities accredited by the American College of Surgeons’ Commission on Cancer (CoC). This dataset includes approximately 70% of all malignant cancers diagnosed in the United States, with available information on sociodemographic characteristics, tumor characteristics, attributes of the treatment facilities, and insurance status. All data are de-identified, and the study was considered exempt by the Ohio State University Institutional Review Board (IRB).
Study population
We used the 2015 Participant User Files (PUF), a publicly shared subset of the NCDB. We limited this analysis to the 273,444 women diagnosed with invasive, endometrioid EC [International Classification of Diseases (ICD)-10 morphology codes 8380–8383 8140, 8210, 8211, 8260–8263, 8560, 8570] between 2004 and 2014 who self-identified as NHW, non-Hispanic Black (NHB), Hispanic, or Asian/Pacific Islander (API). We excluded women with missing values for stage (n=58,827), substage (n=14,774), grade (n=22,530), follow-up data (n=19), and follow-up time of 0 months (n=52). We further excluded women with stage 1A, grades 1 or 2 disease (n=69,241) or women with stage IV disease (n=5,324). These subgroups of women were excluded based on our expectations that GCT would not vary among the former group (given that standard observation is routine) but would likely vary substantially in the latter group of high-stage disease.
To classify GCT status, non-missing data on surgical and adjuvant treatment were needed. We therefore excluded women with missing information on surgery (n=6,558), chemotherapy (n=3,603), hormone therapy (n=1,928), or radiation treatment (n=612). We also excluded an additional 411 women who had a discordant treatment sequence (e.g. radiation preceded surgery) as we had no information as to whether these scenarios were clinically indicated. Finally, we excluded 246 women for whom we could not classify GCT status due to missing anatomical radiation location, for a total of 89,319 women in the analytic cohort. Supplemental table 1 shows the distribution of exclusions according to race among women with invasive, endometrioid EC (n=273,444).
Guideline-concordant treatment
Receipt of GCT was defined using the NCCN guidelines for EC (10). The guidelines recommend various combinations of surgery (total hysterectomy with bilateral oophorectomy and salpingectomy), chemotherapy, and radiation (vaginal brachytherapy and pelvic radiation) as appropriate treatments for endometrioid EC dependent on tumor grade and stage. Receipt of GCT was defined by year due to intermittent revisions of the NCCN guidelines. If a patient’s received treatment did not match the recommended treatment options based on tumor characteristics, the patient was coded as non-concordant. For example, a woman diagnosed with EC in 2011, with stage IIIB endometrioid disease was recommended to have surgical intervention plus chemotherapy and/or tumor-directed radiation. Women who underwent surgery, had at least one of these adjuvant modalities, and received no additional treatment not specified in the recommendations were considered in receipt of GCT.
Vital status
The NCDB requires CoC-associated facilities to update patients’ information, including vital status, in 5-year cycles. The NCDB does not collect cause of death data; therefore, we analyzed overall survival, calculated as the time between the date of diagnosis to date of death (among women who died) or date of last contact (among women alive at the end of follow-up).
Covariates
All variables were captured using standardized codes defined by the Facility Oncology Registry Data Standards (FORDS). We included information on race (NHW, NHB, Hispanic, and API), age at EC diagnosis (≤44, 45–54, 55–64, 65–74, and ≥75 years), stage according to the 7th American Joint Commission on Cancer (AJCC) pathologic stage (IA, IB, IC, II, IIA, IIB, IIIA, IIIB, IIIC), grade (1, 2, 3), comorbidity assessed using the Charlson/Deyo comorbidity index (0, 1, 2, and ≥3), educational attainment (quartiles based on proportion of adults in the patient’s zip code who did not graduate from high school: ≥21%, 13%−20.9%, 7%−12.9%, ≤7%), household income (quartiles based on equally proportioned income ranges among all U.S. zip codes: ≤$38,000, $38,000-$47,999, $48,000-$62,999, ≥$63,000), insurance status (private, Medicaid, Medicare, other government insurance, uninsured), facility location ((Northeast, Midwest, Mountain, Pacific, South), rurality as defined by Federal Information Processing System Codes (metro, urban, rural), and facility type (community cancer, comprehensive community cancer, academic/research, integrated network cancer). Integrated network cancer programs offer care coordinated across multiple facilities, including at least one hospital with a CoC-accredited cancer program. Community cancer, comprehensive community cancer, and academic/research programs are centered in a single facility. Unknown or missing values for any covariate were included as a separate missing category.
Statistical analysis
We compared epidemiological, tumor, and facility characteristics of women according to receipt of GCT (no vs. yes) and race (NHW, NHB, Hispanic, API) using chi-square tests. Univariable logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between receipt of GCT and epidemiological, tumor, and facility characteristics. Variables significantly associated with race and treatment in the unadjusted analyses (p<0.05) were included in a multivariable logistic regression model. We also examined predictors of GCT stratified by race. In these models, we included the same adjustment factors included in the model predicting GCT in the overall study population in order to facilitate comparisons across races.
Hazard ratios (HRs) and 95% CIs for the association between GCT and overall survival were estimated using Cox proportional hazards regression. Models were conducted among the overall study population and stratified by race. Confounder selection was based on univariable associations between potential confounders and overall survival with inclusion of variables significantly associated with survival at p<0.05 in a multivariable model. We assessed the proportional hazards assumption by visually examining plots of the Schoenfeld residuals vs. log follow-up time for the main exposure variable (GCT) and noted no significant deviations. All analyses were performed in SAS version 9.4. All p-values were two-sided.
Results
The word women should follow the racial designations. NHW women were older at diagnosis than minority women, while API women less frequently had comorbidities. NHW women were more likely to be treated in a comprehensive community cancer program while women of other race/ethnicity groups more commonly were treated in academic or research programs (includes NCI-designated comprehensive cancer centers). NHB women were more commonly treated in the South compared to API women, who were more commonly treated in the Pacific region. Income and education disparities were observed, with API women more likely to be represented in zip codes with the highest income quartile compared to NHB women who more commonly resided in zip codes with the lowest income quartile. In terms of tumor characteristics, API women had a higher prevalence of advanced stage tumors, while NHB women had a higher prevalence of grade 3 tumors.
Among the 89,319 women included in the analytic cohort, 74.7% (n=66,699) received GCT. Table 1 shows the distribution of epidemiological, tumor, and facility characteristics by receipt of GCT and the univariable and multivariable-adjusted ORs and 95% CIs for the association between receipt of GCT and these characteristics. In the multivariable model, NHB (OR=0.92, 95% CI=0.86–0.98) and Hispanic (OR=0.90, 95% CI=0.83–0.97) women had lower odds of receiving GCT compared to NHW women, while API women (OR=1.11, 95% CI=1.00–1.23) more commonly received GCT. Older age at diagnosis was associated with higher odds of receiving GCT (≥75 vs. <44 OR: 1.39, 95% CI=1.25–1.56) while more advanced stage (ORs for stages IC-IIIC vs. IA range: 0.08–0.66) and poor tumor differentiation (grade 3 vs. 1 OR: 0.53, 95% CI=0.51–0.56) were inversely related to receipt of GCT. Treatment at an integrated network cancer program as compared to a community cancer program was associated with a slightly lower odds of receiving GCT (OR=0.92, 95% CI=0.84–1.00). Although higher zip code level income (≥$63,000 vs. ≤38,000 OR: 1.11, 95% CI=1.06–1.16) and greater education (live in a zip code where <7% vs. ≥21% of residents are without a high school diploma OR: 1.08, 95% CI=1.03–1.13) were significantly associated with higher odds of GCT in the univariable models, neither factor was a significant predictor in the multivariable model. Similarly, private, Medicare, or other government insurance vs. no health insurance were related with greater odds of GCT in the univariable models but not in the multivariable model.
Table 1.
Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between epidemiological and tumor characteristics and guideline-concordant treatment in the overall study population, N=89,319
| Guideline-concordant treatment | ||||||
|---|---|---|---|---|---|---|
| Epidemiological/Tumor Characteristics | No (n=22,620) | Yes (n=66,699) | ||||
| n (%)1 | Univariable OR (95% CI) | p | Multivariable OR (95% CI)2,3 | p | ||
| Race/ethnicity | <0.001 | <0.001 | ||||
| Non-Hispanic White | 18,809 (24.7) | 57,442 (75.3) | 1.00 | 1.00 | ||
| Non-Hispanic Black | 1,852 (29.9) | 4,334 (70.1) | 0.77 (0.72–0.81) | 0.92 (0.86–0.98) | ||
| Hispanic | 1,331 (29.0) | 3,263 (71.0) | 0.80 (0.75–0.86) | 0.90 (0.83–0.97) | ||
| Asian/Pacific Islander | 628 (27.4) | 1,660 (72.5) | 0.87 (0.79–0.95) | 1.11 (1.00–1.23) | ||
| Age at diagnosis | <0.001 | <0.001 | ||||
| ≤44 | 1,438 (34.3) | 2,759 (65.7) | 1.00 | 1.00 | ||
| 45–54 | 3,862 (27.8) | 10,005 (72.1) | 1.35 (1.25–1.45) | 1.20 (1.08–1.32) | ||
| 55–64 | 7,662 (24.3) | 23,923 (75.7) | 1.63 (1.52–1.74) | 1.36 (1.23–1.50) | ||
| 65–74 | 5,683 (23.9) | 18,124 (76.1) | 1.66 (1.55–1.78) | 1.41 (1.27–1.57) | ||
| ≥75 | 3,975 (25.1) | 11,888 (74.9) | 1.56 (1.45–1.68) | 1.39 (1.25–1.56) | ||
| Charlson Comorbidity Score | 0.007 | 0.13 | ||||
| 0 | 17,163 (25.6) | 49,917 (74.4) | 1.00 | 1.00 | ||
| 1 | 4,462 (24.6) | 13,663 (75.4) | 1.05 (1.01–1.09) | 1.03 (0.99–1.08) | ||
| 2 | 810 (24.7) | 2,473 (75.3) | 1.05 (0.97–1.14) | 1.02 (0.94–1.12) | ||
| ≥3 | 185 (22.3) | 646 (77.7) | 1.20 (1.02–1.41) | 1.19 (0.99–1.41) | ||
| Hospital Type | <0.001 | <0.001 | ||||
| Community Cancer Program | 1,220 (26.0) | 3,468 (74.0) | 1.00 | 1.00 | ||
| Comprehensive Community Cancer Program | 9,265 (24.8) | 28,150 (75.2) | 1.07 (0.10–1.15) | 1.01 (0.93–1.09) | ||
| Academic/Research Program | 8,703 (25.0) | 26,153 (75.0) | 1.06 (0.99–1.13) | 1.03 (0.96–1.11) | ||
| Integrated Network Cancer Program | 2,749 (26.2) | 7,755 (73.8) | 0.99 (0.92–1.07) | 0.92 (0.84–1.00) | ||
| Unknown | 683 (36.8) | 1,173 (63.2) | 0.60 (0.54–0.68) | 0.75 (0.64–0.88) | ||
| Hospital Location | <0.001 | |||||
| Northeast | 4,494 (22.9) | 15,137 (77.1) | 1.00 | --- | ||
| Midwest | 5,929 (25.1) | 17,700 (74.9) | 0.89 (0.85–0.93) | --- | ||
| Mountain | 1,187 (31.7) | 2,556 (68.3) | 0.64 (0.59–0.69) | --- | ||
| Pacific | 2,627 (25) | 7,887 (75) | 0.89 (0.84–0.94) | --- | ||
| South | 7,700 (25.7) | 22,246 (74.3) | 0.86 (0.82–0.89) | --- | ||
| Unknown | 683 (36.8) | 1,173 (63.2) | 0.51 (0.46–0.56) | --- | ||
| Urban/Rural | 0.29 | |||||
| Metro | 18,319 (25.5) | 53,636 (74.5) | 1.00 | --- | ||
| Urban | 3,209 (24.9) | 9,697 (75.1) | 1.03 (0.99–1.08) | --- | ||
| Rural | 413 (24.4) | 1,277 (75.6) | 1.05 (0.94–1.18) | --- | ||
| Unknown | 679 (24.5) | 2,089 (75.5) | 1.05 (0.96–1.15) | --- | ||
| Income4 | <0.001 | 0.18 | ||||
| ≤$38,000 | 3,783 (26.8) | 10,353 (73.2) | 1.00 | 1.00 | ||
| $38,000 – $47,999 | 5,298 (25.5) | 15,454 (74.5) | 1.07 (1.01–1.12) | 1.03 (0.97–1.09) | ||
| $48,000 – $62,999 | 6,016 (24.9) | 18,113 (75.1) | 1.10 (1.05–1.15) | 1.07 (1.01–1.14) | ||
| ≥$63,000 | 7,268 (24.7) | 22,128 (75.3) | 1.11 (1.06–1.16) | 1.06 (0.99–1.13) | ||
| Unknown | 255 (28.1) | 651 (71.8) | 0.93 (0.80–1.08) | 1.02 (0.49–2.12) | ||
| Education (% without high school diploma)5 | <0.001 | 0.17 | ||||
| ≥21% | 3,668 (26.1) | 10,377 (73.9) | 1.00 | 1.00 | ||
| 13%–20.9% | 5,785 (26.0) | 16,493 (74.0) | 1.01 (0.96–1.06) | 0.94 (0.89–0.99) | ||
| 7%–12.9% | 7,501 (24.9) | 22,631 (75.1) | 1.07 (1.02–1.12) | 0.94 (0.89–1.00) | ||
| <7% | 5,423 (24.6) | 16,575 (75.3) | 1.08 (1.03–1.13) | 0.92 (0.86–0.99) | ||
| Unknown | 243 (28.1) | 623 (71.9) | 0.91 (0.78–1.06) | 0.98 (0.46–2.07) | ||
| Insurance | <0.001 | <0.001 | ||||
| None | 960 (29.9) | 2,246 (70.1) | 1.00 | 1.00 | ||
| Private | 10,752 (25.0) | 32,202 (75.0) | 1.28 (1.18–1.38) | 1.07 (0.98–1.17) | ||
| Medicaid | 1,211 (31.0) | 2,692 (69.0) | 0.95 (0.86–1.05) | 0.98 (0.87–1.09) | ||
| Medicare | 9,130 (24.5) | 28,149 (75.5) | 1.32 (1.22–1.43) | 1.05 (0.95–1.15) | ||
| Other Government | 201 (25.7) | 581 (74.3) | 1.24 (1.03–1.47) | 1.06 (0.88–1.28) | ||
| Unknown | 366 (30.6) | 829 (69.4) | 0.97 (0.84–1.12) | 0.82 (0.70–0.96) | ||
| Stage | <0.001 | <0.001 | ||||
| IA | 1,214 (22.1) | 4,280 (77.9) | 1.00 | 1.00 | ||
| IB | 6,452 (14.1) | 39,296 (85.9) | 1.73 (1.61–1.85) | 1.08 (1.00–1.17) | ||
| IC | 2,395 (21.7) | 8,633 (78.3) | 1.02 (0.95–1.11) | 0.66 (0.61–0.72) | ||
| II | 1,391 (35.8) | 2,492 (64.2) | 0.51 (0.46–0.56) | 0.34 (0.31–0.38) | ||
| IIA | 829 (31.9) | 1,770 (68.1) | 0.61 (0.55–0.67) | 0.39 (0.35–0.44) | ||
| IIB | 1,299 (36.8) | 2,230 (63.2) | 0.49 (0.44–0.53) | 0.33 (0.30–0.36) | ||
| IIIA | 2,396 (39.4) | 3,684 (60.6) | 0.44 (0.40–0.47) | 0.31 (0.28–0.34) | ||
| IIIB | 691 (71.5) | 275 (28.5) | 0.11 (0.10–0.13) | 0.08 (0.07–0.10) | ||
| IIIC | 5,953 (59.6) | 4,039 (40.4) | 0.19 (0.18–0.21) | 0.14 (0.13–0.15) | ||
| Grade | <0.001 | <0.001 | ||||
| 1 | 6,085 (18.5) | 26,747 (81.5) | 1.00 | 1.00 | ||
| 2 | 8,342 (24.9) | 25,210 (75.1) | 0.69 (0.66–0.71) | 0.87 (0.84 –0.91) | ||
| 3 | 8,193 (35.7) | 14,742 (64.3) | 0.41 (0.39–0.43) | 0.53 (0.51–0.56) | ||
row percentage
Multivariable OR adjusted for race (NHW, NHB, Hispanic, API), age (≤44, 45–54, 55–64, 65–74, ≥75), Charlson comorbidity score (0, 1, 2, ≥3), hospital type (Community Cancer Program, Comprehensive Community Cancer Program, Academic/Research Program, Integrated Network Cancer Program, unknown), income (≤$38,000, $38,000 – $47,999, $48,000 – $62,999, ≥$63,000, unknown), education (≥21%, 13%–20.9%, 7%–12.9%, <7%, unknown), insurance (None, Private, Medicaid, Medicare, Other Government, unknown), stage (IA, IB, IC, II, IIA, IIB, IIIA, IIIB, IIIC), grade (1, 2, 3)
Hospital location was not included in the multivariable model due to collinearity with hospital type
Income: quartiles based on equally proportioned income ranges among all U.S. zip codes
Education: quartiles based on proportion of adults in the patient’s zip code who did not graduate from high school
OR: odds ratio, CI: confidence interval
We evaluated predictors of GCT stratified by race in order to discern whether certain characteristics were more strongly associated with receipt of GCT for specific groups of women (Table 2). Older age was associated with higher odds of GCT among NHW, NHB, and Hispanic women while more advanced stage and higher grade were inversely associated with receipt of GCT across all race/ethnicity groups. We noted that a higher number of comorbidities (≥3 vs. 0 OR: 2.06, 95% CI=1.14–3.73 and 1 vs. 0 OR: 1.19, 95% CI=1.03–1.37) and private insurance (vs. none OR: 1.30, 95% CI 1.00–1.67) were associated with higher odds of guideline-based care among NHB women. Among NHW women, although zip code level income was not significantly associated with treatment overall (p=0.09) we observed that certain categories of higher income were related to higher odds of receiving GCT.
Table 2.
Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between epidemiological and tumor characteristics and guideline-concordant treatment stratified by race/ethnicity, N=89,319
| Non-Hispanic White (n=76,251) | Non-Hispanic Black (n=6,186) | Hispanic (n=4,594) | Asian/Pacific Islander (n=2,288) | |||||
|---|---|---|---|---|---|---|---|---|
| OR (95% CI)1 | p | OR (95% CI)1 | p | OR (95% CI)1 | p | OR (95% CI)1 | p | |
| Age | <0.001 | <0.001 | <0.001 | 0.74 | ||||
| 18–44 | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| 45–54 | 1.12 (0.99–1.26) | 1.43 (1.02–2.01) | 1.50 (1.11–2.02) | 1.18 (0.74–1.86) | ||||
| 55–64 | 1.26 (1.13–1.42) | 1.90 (1.37–2.62) | 1.73 (1.30–2.31) | 1.12 (0.72–1.76) | ||||
| 65–74 | 1.30 (1.14–1.47) | 1.93 (1.37–2.73) | 2.00 (1.43–2.79) | 1.39 (0.82–2.37) | ||||
| 75+ | 1.29 (1.14–1.47) | 1.75 (1.21–2.51) | 1.85 (1.27–2.69) | 1.20 (0.66–2.19) | ||||
| Charlson Comorbidity Score | 0.46 | 0.008 | 0.44 | 0.23 | ||||
| 0 | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| 1 | 1.02 (0.98–1.07) | 1.19 (1.03–1.37) | 0.95 (0.81–1.12) | 0.97 (0.75–1.26) | ||||
| 2 | 1.05 (0.95–1.16) | 0.91 (0.69–1.20) | 0.98 (0.68–1.40) | 0.51 (0.26–1.01) | ||||
| 3+ | 1.10 (0.90–1.33) | 2.06 (1.14–3.73) | 1.90 (0.82–4.41) | 0.60 (0.16–2.29) | ||||
| Hospital Type | <0.001 | 0.17 | 0.69 | 0.23 | ||||
| Community Cancer Program | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| Comprehensive Community Cancer Program | 1.01 (0.93–1.10) | 1.22 (0.89–1.67) | 0.99 (0.71–1.40) | 0.69 (0.46–1.02) | ||||
| Academic/Research Program | 1.05 (0.97–1.14) | 1.04 (0.76–1.41) | 0.99 (0.71–1.39) | 0.74 (0.50–1.09) | ||||
| Integrated Network Cancer Program | 0.92 (0.84–1.02) | 1.20 (0.85–1.68) | 0.84 (0.58–1.23) | 0.62 (0.36–1.06) | ||||
| Unknown | 0.70 (0.58–0.84) | 1.10 (0.65–1.85) | 0.95 (0.59–1.52) | 0.51 (0.26–0.99) | ||||
| Income2 | 0.09 | 0.28 | 0.73 | 0.74 | ||||
| > $38,000 | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| $38,000 – $47,999 | 1.05 (0.98–1.12) | 0.91 (0.77–1.07) | 1.04 (0.86–1.26) | 1.11 (0.70–1.76) | ||||
| $48,000 – $62,999 | 1.10 (1.02–1.17) | 0.85 (0.70–1.03) | 1.15 (0.94–1.42) | 1.32 (0.85–1.03) | ||||
| $63,000 + | 1.08 (1.01–1.16) | 0.80 (0.63–1.02) | 1.10 (0.84–1.44) | 1.24 (0.79–1.96) | ||||
| Unknown | 1.15 (0.54–2.46) | 0.18 (0.01–3.08) | 1.19 (0.53–2.66) | 1.21 (0.44–3.35) | ||||
| Education (% without high school diploma)3 | 0.41 | 0.89 | 0.42 | |||||
| 21% + | 1.00 | 1.00 | 1.00 | 0.23 | 1.00 | |||
| 13% – 20.9% | 0.95 (0.89–1.01) | 1.01 (0.86–1.17) | 0.84 (0.70–1.00) | 0.77 (0.56–1.06) | ||||
| 7% – 12.9% | 0.95 (0.88–1.01) | 1.06 (0.86–1.31) | 0.85 (0.67–1.07) | 0.83 (0.60–1.15) | ||||
| < 7% | 0.93 (0.86–1.00) | 1.10 (0.81–1.49) | 0.92 (0.67–1.28) | 0.78 (0.54–1.13) | ||||
| Unknown | 0.93 (0.42–2.02) | 3.41 (0.19–62.45) | NE | NE | ||||
| Insurance | 0.34 | 0.006 | 0.13 | |||||
| None | 1.00 | 1.00 | 1.00 | 0.09 | 1.00 | |||
| Private | 1.02 (0.92–1.14) | 1.30 (1.00 –1.67) | 1.08 (0.86–1.36) | 1.24 (0.83–1.87) | ||||
| Medicaid | 0.97 (0.84–1.11) | 0.97 (0.71–1.31) | 0.96 (0.73–1.26) | 1.10 (0.68–1.80) | ||||
| Medicare | 1.02 (0.90–1.14) | 1.14 (0.86– 1.52) | 0.95 (0.72–1.26) | 1.42 (0.87–2.34) | ||||
| Other Government | 0.97 (0.79–1.21) | 2.00 (0.97–4.12) | 1.52 (0.65–3.56) | 0.84 (0.34–2.11) | ||||
| Unknown | 0.86 (0.72–1.04) | 0.70 (0.41–1.18) | 0.59 (0.37–0.93) | 0.52 (0.23–1.19) | ||||
| Stage | <0.001 | <0.001 | <0.001 | <0.001 | ||||
| IA | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| IB | 1.06 (0.97–1.15) | 1.26 (1.00–1.58) | 1.17 (0.83–1.65) | 0.96 (0.61–1.50) | ||||
| IC | 0.66 (0.60–0.73) | 0.57 (0.44–0.76) | 0.67 (0.46–0.98) | 0.78 (0.46–1.33) | ||||
| II | 0.33 (0.29–0.37) | 0.42 (0.31–0.56) | 0.42 (0.28–0.63) | 0.32 (0.18–0.57) | ||||
| IIA | 0.39 (0.34–0.44) | 0.43 (0.30–0.60) | 0.45 (0.28–0.71) | 0.32 (0.16–0.65) | ||||
| IIB | 0.33 (0.29–0.36) | 0.41 (0.30–0.56) | 0.38 (0.25–0.58) | 0.15 (0.08–0.27) | ||||
| IIIA | 0.30 (0.27–0.33) | 0.41 (0.31–0.54) | 0.36 (0.25–0.53) | 0.25 (0.15–0.42) | ||||
| IIIB | 0.08 (0.07–0.09) | 0.08 (0.05–0.14) | 0.14 (0.07–0.29) | 0.10 (0.05–0.20) | ||||
| IIIC | 0.13 (0.12–0.15) | 0.14 (0.11–0.18) | 0.19 (0.13–0.26) | 0.15 (0.09–0.24) | ||||
| Grade | <0.001 | <0.001 | <0.001 | <0.001 | ||||
| 1 | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| 2 | 0.88 (0.84–0.91) | 0.83 (0.70–0.68) | 0.86 (0.73–1.02) | 0.76 (0.59–0.99) | ||||
| 3 | 0.52 (0.50–0.55) | 0.56 (0.47–0.66) | 0.65 (0.54–0.79) | 0.45 (0.34–0.60) |
ORs adjusted for age (≤44, 45–54, 55–64, 65–74, ≥75), Charlson comorbidity score (0, 1, 2, ≥3), hospital type (Community Cancer Program, Comprehensive Community Cancer Program, Academic/Research Program, Integrated Network Cancer Program, unknown), income (≤$38,000, $38,000 – $47,999, $48,000 – $62,999, ≥$63,000, unknown), education (≥21%, 13%–20.9%, 7%–12.9%, <7%, unknown), insurance (None, Private, Medicaid, Medicare, Other Government, unknown), stage (IA, IB, IC, II, IIA, IIB, IIIA, IIIB, IIIC), grade (1, 2, 3)
Income: quartiles based on equally proportioned income ranges among all U.S. zip codes
Education: quartiles based on proportion of adults in the patient’s zip code who did not graduate from high school
OR: odds ratio, CI: confidence interval
In the univariable Cox regression models, lack of GCT was associated with worse overall survival in the overall study population (HR=1.63, 95% CI=1.59–1.68) and among women of all race/ethnicity groups: NHW (HR=1.65, 95% CI=1.60–1.70), NHB (HR=1.67, 95% CI=1.52–1.84), Hispanic (HR=1.24, 95% CI=1.06–1.44), and API (HR=1.50, 95% CI=1.19–1.88). In multivariable-adjusted Cox regression models, GCT was related to worse survival in the overall study population (HR=1.12, 95% CI=1.08–1.15) and among NHW women (HR=1.14, 95% CI=1.10–1.18, Table 3), but not among NHB (HR=1.09, 95% CI=0.98–1.21), Hispanic (HR=0.92, 95% CI=0.78–1.09), or API (HR=0.90, 95% CI=0.70–1.16) women.
Table 3.
Hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between guideline-concordant treatment and overall survival in the overall population and stratified by race/ethnicity
| Deaths, n (%)1 | HR (95% CI)2 | HR (95% CI)3 | |
|---|---|---|---|
| Overall, n=89,319 | |||
| Guideline-concordant treatment | |||
| Yes | 13,181/66,699 (19.8) | 1.00 | 1.00 |
| No | 6,363/22,620 (28.1) | 1.63 (1.59–1.68) | 1.12 (1.08–1.15) |
| Non-Hispanic White, n=76,251 | |||
| Guideline-concordant treatment | |||
| Yes | 11,369/57,442 (19.8) | 1.00 | 1.00 |
| No | 5,351/18,809 (28.4) | 1.65 (1.60–1.70) | 1.14 (1.10–1.18) |
| Non-Hispanic Black, n=6,186 | |||
| Guideline-concordant treatment | |||
| Yes | 1,101/4,334 (25.4) | 1.00 | 1.00 |
| No | 668/1,852 (36.1) | 1.67 (1.52–1.84) | 1.09 (0.98–1.21) |
| Hispanic, n=4,594 | |||
| Guideline-concordant treatment | |||
| Yes | 495/3,263 (15.2) | 1.00 | 1.00 |
| No | 234/1,331 (17.6) | 1.24 (1.06–1.44) | 0.92 (0.78–1.09) |
| Asian/Pacific Islander, n=2,288 | |||
| Guideline-concordant treatment | |||
| Yes | 216/1,660 (13) | 1.00 | 1.00 |
| No | 110/628 (17.5) | 1.50 (1.19–1.88) | 0.90 (0.70–1.16) |
Row percentage
Unadjusted HR
HRs adjusted for age (≤44, 45–54, 55–64, 65–74, ≥75), Charlson comorbidity score (0, 1, 2, ≥3), hospital type (Community Cancer Program, Comprehensive Community Cancer Program, Academic/Research Program, Integrated Network Cancer Program, unknown), rurality (Metro, Rural, Urban, unknown), income (quartiles based on equally proportioned income ranges among all U.S. zip codes: ≤$38,000, $38,000 – $47,999, $48,000 – $62,999, ≥$63,000, unknown), education (quartiles based on proportion of adults in the patient’s zip code who did not graduate from high school ≥21%, 13%–20.9%, 7%–12.9%, <7%, unknown), insurance (None, Private, Medicaid, Medicare, Other Government, unknown), stage (IA, IB, IC, II, IIA, IIB, IIIA, IIIB, IIIC), grade (1, 2, 3)
HR: hazard ratio, CI: confidence interval
Comment
Principal findings of the study
In this large retrospective cohort of women with EC, we observed small, but significant differences in receipt of NCCN recommended treatment according to race. While NHB and Hispanic women were less likely than NHWs to receive GCT, receipt was more common among API women. Although many predictors of GCT were consistent across race/ethnicity groups, we identified a few key differences. Counterintuitively, older age was associated with higher odds of receiving GCT among NHW, NHB, and Hispanic women, while aggressive disease characteristics were uniformly associated with lower odds of receiving GCT. Unique to NHB women, we observed that a higher number of comorbidities and private insurance were related to higher odds of GCT receipt. While lack of GCT was associated with worse survival in the overall study population, stratification by race revealed a significant multivariable association for NHW women only.
Racial disparities in treatment receipt
The 2003 Institute of Medicine (IOM) Report, Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care, defined racial and ethnic health care disparities as “differences in health care services received by the two groups that are not due to differences in the underlying health care needs or preferences of members of the groups (21).” Therefore, the IOM definition explicitly parses out treatment differences due to differences in underlying health status or preference from those differences that are the result of the “operation of health care systems, the legal and regulatory climate, discrimination, or other factors.” (21) Based on this definition one would expect some differences in EC treatment between women of different race/ethnicity groups because the underlying distribution of tumor features, which drives clinical treatment strategies, varies by race. For example, among women diagnosed with endometrioid EC, NHB women are more likely to present with poor tumor differentiation (5), which should prompt adjuvant treatment. Further, treatment preferences may vary by race, which could impact treatment receipt. For instance, Black women with cervical cancer more commonly refused intracavitary radiotherapy than White women (22). Moreover, health status indicators (e.g. presence of comorbid conditions) also varies by race, potentially impacting differential treatment receipt by race. We also acknowledge that other important factors, including perceived discrimination (23, 24), oncologist implicit racial bias (25), poor patient-provider communication (26, 27), patient non-adherence (28), and access (29) likely contribute to the observed disparate treatment patterns. These factors have not been well-characterized among EC patients, nor are variables characterizing these factors available in this hospital-based cancer registry. Although we were unable to implement the IOM definition of disparities in this analysis, and are therefore unable to account for all etiologic factors that may contribute to GCT disparities, defining treatment as concordant vs. non-concordant on the basis of tumor characteristics (i.e. histology, grade, and stage) allows us to quantify racial differences in treatment quality.
Minority women with endometrial cancer are less likely than Whites to receive GCT
Results from the current analysis are in line with the few published studies that have specifically defined EC treatment on the basis of concordance with national guidelines. In an analysis of 629 EC survivors enrolled in the Women’s Health Initiative (WHI) Survivorship cohort, we observed that 69% of Black as compared to 84% of White women received GCT; however, this comparison was underpowered and did not reach statistical significance (16). A Surveillance, Epidemiology, End Results (SEER) analysis of 711 EC patients, including women of all stages and histology types, revealed that NHB women were less likely to receive guideline-directed treatment than NHW (OR=0.50, 95% CI=0.20–0.97) (30). Although the inclusive study populations in the WHI and SEER analyses differed from our population restricted to women with endometrioid tumors, a pattern of non-GCT among minority women is evident.
In contrast to the scant literature on guideline-concordant EC, numerous studies have examined racial differences in the receipt of hysterectomy and/or adjuvant treatment, but with conflicting results. For example, Black (31–35) and Hispanic (32, 35) women are reportedly less likely than Whites to receive hysterectomy. Differences in receipt of adjuvant therapy, with a higher prevalence of adjuvant chemotherapy and/or radiation among Black as compared with White EC patients, have been reported by some (32, 36, 37) but not others (33, 38–40). In a SEER-Medicare study of approximately 9,000 women with high-grade endometrioid and non-endometrioid EC, Rauh-Hain and colleagues (31) reported significantly lower odds of surgery and chemotherapy, but not radiotherapy, among Black as compared to White women. These analyses varied in their analytic approach, with some reporting racial differences in treatment prevalence (36, 38, 39) while others conducted multivariable-adjusted analyses with adjustment and/or stratification by tumor characteristics (32, 33, 37, 40). For example, in the large Gynecologic Oncology Group (GOG)-210 Study, we reported that Black women with EC had higher multivariable-adjusted odds of receiving chemotherapy plus radiation compared to Whites in subgroups of women with low-grade endometrioid or serous tumors (37). These findings were unexpected given the stratification by histology and adjustment for stage. We hypothesized that clinician awareness of worse mortality among Black as compared with White women with EC may have impacted treatment decisions in this study. Furthermore, the Black women enrolled in this observational cohort study were recruited at large academic medical centers and are likely not representative of Black women included in national database studies. We hypothesize there may have been fewer barriers among Black women enrolled in GOG-210 as compared with women in the community. Other factors, apart from differences in analytic approach, likely influence the discrepant literature and include differences in the underlying study population, sample sizes, and ascertainment of treatment. Nonetheless, this body of work describing treatment differences according to race is important; however, the comparison of actual treatment received with guideline-recommended treatment provides an assessment of treatment quality.
While many studies have compared treatment differences between White and Black women with EC and to a lesser extent, Hispanic women, analyses of API women with EC are largely missing from the literature. We observed that API women were more likely than NHW to receive GCT. The API women in this study population were younger at EC diagnosis, less likely to have comorbidities, more commonly living in the Pacific region at the time of EC diagnosis, and residing in more affluent areas than the other racial/ethnic groups; however, adjustment for most characteristics (except region) likely precludes these specific factors from explaining the higher odds of receipt of GCT in this population. The cancer health disparities literature focused on API populations has largely reported better survival in this heterogeneous and fast-growing population compared with NHWs (41). However, the underlying mechanisms that provide protection are not well understood. In fact, evidence suggests that APIs are less likely to report having a primary care doctor, potentially due to barriers such as language and immigration status (42). Like other studies, we aggregated across many diverse ethnicities (e.g. Chinese, Korean, Filipina), which might obscure important culture-specific differences underlying higher GCT receipt (41). There are likely unique cultural factors that explain the higher odds of GCT receipt among API women with EC, which should be explored in future studies.
Other factors associated with receipt of GCT overall and by race
In the current study, older age was related to higher odds of GCT, which is in contrast to our previous WHI findings (16) and another single-institution study (43), where inverse relationships between age at diagnosis and receipt of guideline-concordant EC treatment were observed. Differences in the underlying study populations may account for the unexpected age findings in our cohort, as the NCDB is a hospital-based registry. We also observed that a higher number of comorbidities and private insurance were associated with higher odds of GCT receipt among NHBs. It is possible that NHBs who are in more frequent contact with their provider, either because of increased interactions to control comorbid conditions or due to a more generous insurance plan that allows frequent contacts, are more likely to advocate for better treatment in line with guidelines. Further research should be performed to assess why these associations may exist. In line with prior studies, we noted that advanced stage and poor tumor differentiation were associated with lower odds of receiving GCT among women of all race/ethnicity groups, which may be due to lack of evidence from clinical trials focused on these populations, as well as the need for more individualized treatments for aggressive disease characteristics (16). Recently published results from GOG 258 (44) and PORTEC-3 (45) will inform future NCCN recommendations for women with high-risk EC.
Lack of GCT is related to worse survival
As expected, lack of GCT was associated with poorer survival in this population of women with endometrioid EC. Prior observational studies have also demonstrated a higher risk of death associated with non-concordant EC treatment (46, 47), while two observed no association (48, 49). Although the association between lack of GCT and worse survival among minority groups of women did not hold in the multivariable analyses, this null association is more likely due to underpowered analyses as opposed to a true lack of importance of guideline-based treatment on survival. In particular, the association among NHB women is borderline non-significant, suggesting low power as a likely explanation for the lack of association. Alternatively, our results may in fact reflect that recommended treatment paradigms do not play a role in the overall survival of minority women with EC, arguing for future trials to include larger numbers of minority women. This would allow well-powered sub-group analyses to determine treatment effectiveness across a range of race/ethnic groups.
Strengths and limitations
Several limitations of our descriptive analysis warrant mention. As mentioned, we lacked information on contextual social factors (e.g. perceived discrimination, oncologist implicit racial bias, etc.), which may account for the remaining racial differences in receipt of GCT. In addition, we lacked information on epidemiological factors of interest (smoking status, body mass index, etc.) and cause of death, preventing cause-specific mortality analyses. Some misclassification of treatment concordance is expected given the lack of central pathology review and we excluded a large proportion of women due to missing data. Finally, relative to White women, we had low numbers of minority women, potentially affecting power in the analyses of GCT receipt and racial minority characteristics and survival among minority women. Our analysis also has several strengths including information on substage, which allowed us to classify treatment concordance, and information on a large number of potential clinical confounders.
Conclusion
In conclusion, we observed clinically relevant racial differences in receipt of GCT in this large, hospital-based registry of women with EC. As expected, receipt of treatment recommended by the NCCN was associated with better survival; yet this observation was only identified among White women. We suspect low power may underlie the null associations observed in the minority groups. Although our analysis lacked information on important contextual factors, our results indicate that racial differences in the quality of EC treatment exist and should prompt future etiologic research to provide explanations for racial disparities in GCT receipt.
Supplementary Material
AJOG at a Glance.
A. Why was this study conducted?
Poorer survival among African American women is often attributed to more aggressive tumor characteristics. However, even among women with more indolent forms of the disease, this survival disparity persists. Therefore, we assessed the hypothesis that disparate receipt of guideline-concordant treatment contributes to the survival disparity among women diagnosed with endometrioid endometrial cancer.
B. What are the key findings?
Both Black and Hispanic women were less likely to receive guideline-concordant treatment compared to White women, while Asian/Pacific Islanders showed to be more likely. Additionally, we found that receipt of guideline-concordant treatment is associated with improved overall survival.
C. What does this study add to what is already known?
Our results suggest that differential receipt of guideline-concordant treatment contributes to observed survival disparities among women with endometrioid endometrial cancer.
Financial Support:
This work was supported by the National Cancer Institute (K01CA21845701A1 to ASF).
Footnotes
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Conflict of interest: The authors report no conflict of interest.
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