The relationship between racial and socioeconomic status (SES) disparities and the quality of epithelial ovarian cancer care and survival outcome are unclear.
MethodsA population-based analysis of National Cancer Data Base (NCDB) records for invasive primary epithelial ovarian cancer diagnosed in the period from 1998 to 2002 was done using data from patients classified as white or black. Adherence to National Comprehensive Cancer Network (NCCN) guideline care was defined by stage-appropriate surgical procedures and recommended chemotherapy. The main outcome measures were differences in adherence to NCCN guidelines and overall survival according to race and SES and were analyzed using binomial logistic regression and multilevel survival analysis.
ResultsA total of 47 160 patients (white = 43 995; black = 3165) were identified. Non-NCCN-guideline-adherent care was an independent predictor of inferior overall survival (hazard ratio [HR] = 1.43, 95% confidence interval [CI] = 1.38 to 1.47). Demographic characteristics independently associated with a higher likelihood of not receiving NCCN guideline-adherent care were black race (odds ratio [OR] = 1.36, 95% CI = 1.25 to 1.48), Medicare payer status (OR = 1.20, 95% CI = 1.12 to 1.28), and not insured payer status (OR = 1.33, 95% CI = 1.19 to 1.49). After controlling for disease and treatment-related variables, independent racial and SES predictors of survival were black race (HR = 1.29, 95% CI = 1.22 to 1.36), Medicaid payer status (HR = 1.29, 95% CI = 1.20 to 1.38), not insured payer status (HR = 1.32, 95% CI = 1.20 to 1.44), and median household income less than $35 000 (HR = 1.06, 95% CI = 1.02 to 1.11).
ConclusionsThese data highlight statistically and clinically significant disparities in the quality of ovarian cancer care and overall survival, independent of NCCN guidelines, along racial and SES parameters. Increased efforts are needed to more precisely define the patient, provider, health-care system, and societal factors leading to these observed disparities and guide targeted interventions.
Despite improvements in cancer care during the past two decades, persistent disparities exist in the United States with regard to receipt of recommended guideline therapy and survival. Disparities in cancer care and outcomes have been linked to race and ethnic classification, socioeconomic status (SES), educational level, geographic locale, culture, and health system factors (1–3). For many types of cancer, blacks have lower stage-specific survival than whites (4).
In the United States, there are 22 000 new cases of ovarian cancer diagnosed and more than 15 000 disease-related deaths annually (5). Racial disparities in ovarian cancer have been documented with respect to stage of diagnosis, extent of treatment, and survival (6–9). There is more limited data on ovarian cancer disparities associated with SES characteristics (10–13). Previous studies have been limited by analyses of race without the context of SES indicators, correlation of race with either treatment or survival but not both outcomes in the same population, an absence of validated standards of quality care, or small study groups that may not be representative of the broader population. As a result, accurately quantifying the magnitude of ovarian cancer disparities and characterizing those sociodemographic characteristics associated with limited access to care, substandard care, and worse clinical outcomes remain important prerequisites to developing corrective measures.
The National Cancer Data Base (NCDB) is an oncology outcomes database of approximately 70% of all newly diagnosed patients with cancer in the United States. Previous studies of ovarian cancer using the NCDB have found correlations between both race and payer status and receipt of surgery as initial therapy but have not benchmarked treatment to validated quality outcome measures (12–14). The objective of this study was to examine disparities according to race and SES indicators in the quality of epithelial ovarian cancer care and survival outcome. For the purposes of this study, adherence to National Comprehensive Cancer Network (NCCN) guideline therapy was selected as the measure of quality of cancer care and considered the therapeutic standard that the majority of ovarian cancer patients should be provided.
Methods Case Ascertainment and Definition of VariablesThis study received exempt status from the Institutional Review Board of Washington University. All NCDB cases of invasive malignant epithelial ovarian cancer classified as white or black diagnosed between January 1, 1998, and December 31, 2002, were selected from the NCDB using topography code C56.9; individual subjects and facilities were de-identified before delivery of the public use file. Records were included if the tumor corresponded to one malignant or the first of two or more independent malignant primary tumors and if either the pathological or clinical staging was known. Histology codes were sorted into serous, mucinous, endometrioid, clear-cell, mixed, and undifferentiated tumors. Nonepithelial ovarian cancer, borderline cancers, and tumors of nonovarian origin were excluded. Tumor grade was consolidated into two categories: well/moderately differentiated and poorly differentiated/undifferentiated/anaplastic. A new overall staging variable was constructed based on 1) complete pathologic staging or 2) clinical staging if pathologic staging was missing or improperly reported.
The average annual hospital ovarian cancer volume was ranked into quartiles (1–6 cases, 7–14 cases, 15–25 cases, and ≥26 cases). Zipcode of residence was matched against year 2000 US Census data and US Department of Agriculture data to estimate median household income, the percentage of residents with a college degree, and the continuum of rural/urban residence. Payer status was consolidated into six categories. Private insurance included fee-for-service, health maintenance organization, or independent physician association. Patients with managed care insurance, TRICARE, or other military coverage were grouped under a single category (managed care). Patients were classified as having Medicare if they had Medicare with or without supplemental coverage. Patients with Medicaid, public health service insurance, and other federal insurance programs were consolidated into a single category (Medicaid). Patients without insurance coverage were classified as “not insured/self pay,” and the remaining patients were classified as “insurance status unknown.”
Statistical AnalysisThe first outcome variable was adherence to NCCN guidelines for treatment for ovarian cancer and was based on recommendations for surgical and chemotherapy treatment according to the time period of diagnosis (1998–2000, 2001–2002) (15–17). Surgical treatment was considered adherent to NCCN guidelines if any of the following procedures were recorded: 1) partial or total unilateral or bilateral salpingo-oophorectomy with omentectomy, with or without hysterectomy; 2) debulking or cytoreductive surgery with colon (including appendix) and/or small intestine resection and/or partial resection of urinary tract (not incidental); or 3) anterior, posterior, total, or extended pelvic exenteration. For tumors that were International Federation of Gynecology and Obstetrics stage I to IIIB, examination of pelvic and/or para-aortic lymph nodes was required for adherent care. NCCN-specified administration of multiagent chemotherapy was considered adherent care. The second outcome variable was 5-year overall survival. In all analyses, age at diagnosis was modeled as a continuous variable.
Differences between white and black patients according to demographic and clinical variables and deviations from NCCN guideline care, stratified by race and insurance payer, were examined using the χ2 test. The independent effects of race, SES indicators, tumor characteristics, and healthcare system factors on adherence to NCCN guidelines for overall treatment were examined using binomial logistic regression. Survival analysis was performed using the Kaplan–Meier method and log rank test. The Cox proportional hazards model, taking into consideration clustering within treating facilities, was used to evaluate the independent effect of all variables on 5-year survival. The appropriateness of the proportional hazards assumptions were validated by examining plots of the deviance residuals from the fit model. Statistical significance was set to P less than .05, and all analyses were performed using SAS version 9.2 (SAS Institute, Inc, Cary, NC). All statistical tests were two-sided.
Results Cohort CharacteristicsThe final study population consisted of 47 160 patients: 43 995 patients were white, and 3165 patients were black (Table 1). Statistically significant differences between white and black patients were noted for age, median household income, education, urban/rural residence, and payer status.
Table 1.Cohort characteristics of 47160 cases of epithelial ovarian cancer in the period from 1998 to 2002*
Characteristic White (n = 43 995) Black (n = 3165) P† Age, mean (SD), y 62.4 (13.8) 61.3 (14.1) Adherence to NCCN guidelines for treatment, No. (%) <.001 Adherent 19 304 (43.9) 1128 (35.6) Nonadherent 24 691 (56.1) 2037 (64.4) Percentage with college degree, No. (%) <.001 <9% 19 321 (43.9) 792 (25.0) 9%–12.9% 11 767 (26.8) 847 (26.8) 13%–20.9% 6401 (14.6) 699 (22.1) ≥21% 4130 (9.4) 682 (21.6) Not available 2376 (5.4) 145 (4.6) Median household income 2000, No. (%) <.001 ≥$46 000 17 319 (39.4) 519 (16.4) $35 000–$45 999 12 130 (27.6) 690 (21.8) <$35 000 12 172 (27.7) 1811 (57.2) Missing 2374 (5.4) 145 (4.6) Primary payer at diagnosis, No. (%) <.001 Private insurance 8825 (20.1) 480 (15.2) Medicare/Medicare with supplements 17 622 (40.1) 1275 (40.3) Managed care/ TRICARE/military 12 764 (29.0) 725 (22.9) Medicaid/federal insurance programs/public health service 1504 (3.4) 287 (9.1) Not insured/self pay 1392 (3.2) 249 (7.9) Insurance status unknown 1888 (4.3) 149 (4.7) Tumor stage, No. (%) <.001 Stage I 7814 (17.8) 359 (11.3) Stage II 3641 (8.3) 214 (6.8) Stage III 19 753 (44.9) 1294 (40.9) Stage IV 12 787 (29.1) 1298 (41.0) Tumor grade, No. (%) <.001 Well/moderately differentiated (referent) 11 949 (27.2) 767 (24.2) Poorly/undifferentiated/anaplastic 22 969 (52.2) 1489 (47.1) Missing 9077 (20.6) 909 (28.7) Tumor histology, No. (%) <.001 Serous 21 335 (48.49) 1418 (44.80) Mucinous 3093 (7.03) 257 (8.12) Endometrioid 5744 (13.06) 300 (9.48) Clear-cell 2437 (5.54) 89 (2.81) Mixed 345 (0.78) 21 (0.66) NOS/undifferentiated 11 041 (25.10) 1080 (34.12) Facility type, No. (%) <.001 Community cancer program 5579 (12.68) 323 (10.21) Comprehensive community cancer program 20 284 (46.11) 1097 (34.66) Academic/research program (includes NCI-designated comprehensive cancer centers) 18 132 (41.21) 1745 (55.13) Urban rural continuum 2003, No. (%) <.001 Counties in metro areas of ≥1 million population 20 641 (46.92) 1912 (60.41) Counties in metro areas of 250 000–1 million population 9020 (20.50) 535 (16.90) Counties in metro areas of <250 000 population 4623 (10.51) 241 (7.61) Urban population of ≥20 000, adjacent to a metro area 2182 (4.96) 100 (3.16) Urban population of ≥20 000, not adjacent to a metro area 809 (1.84) 30 (0.95) Urban population of 2500–19 999, adjacent to a metro area 2130 (4.84) 133 (4.20) Urban population of 2500–19 999, not adjacent to a metro area 1114 (2.53) 33 (1.04) Completely rural or <2500 urban population, adjacent to a metro area 432 (0.98) 29 (0.92) Completely rural or <2500 urban population, not adjacent to a metro area 3044 (6.92) 152 (4.80) Number of reasons for nonadherence to NCCN guidelines for treatment, No. (%)‡ <.001 0 19 304 (43.88) 1128 (35.64) 1 15 745 (35.79) 1140 (36.02) 2 7754 (17.62) 780 (24.64) 3 1192 (2.71) 117 (3.70) Hospital ovarian cancer volume, No. of cases per year <.001 1–6 10 970 (24.93) 772 (24.39) 7–14 10 986 (24.97) 882 (27.87) 15–25 10 985 (24.97) 835 (26.38) ≥26 11 054 (25.13) 676 (21.36) Total 43 995 (100.00) 3165 (100.00) Adherence to NCCN Guideline CareThe distributions of subjects by elements of nonadherent care stratified by race and payer are shown in Table 2. NCCN guideline adherent care was administered in 43.9% of white patients and 35.6% of black patients (P < .0001). Black patients were statistically significantly less likely to receive proper chemotherapy and proper surgery. Managed care and private insurance had the highest rates of adherent care, whereas not insured/self pay (42.3%) and Medicare (35.3%) had the lowest rates of adherence. Across all payer categories, black patients with ovarian cancer were less likely than white patients to receive NCCN guideline-adherent overall care, surgical treatment, and proper chemotherapy.
Table 2.Distribution of patients according to treatment elements of National Comprehensive Cancer Network guideline nonadherent care stratified by race, payer, and a bivariable combination of race/payer
Characteristic Chemotherapy Surgery and lymph node examination Overall treatment Proper Improper P* Proper Improper P* Proper Improper P* No. % No. % No. % No. % No. % No. % Race <.001 <.001 <.001 White 28847 65.6 15148 34.4 27062 61.5 16933 38.5 19304 43.9 24691 56.1 Black 1879 59.4 1286 40.6 1623 51.3 1542 48.7 1128 35.6 2037 64.4 Insurance payer <.001 <.001 <.001 Private insurance 6673 71.7 2632 28.3 6175 66.4 3130 33.6 4639 49.9 4666 50.2 Medicare/ Medicare with supplements 11042 58.4 7855 41.6 10119 53.6 8778 46.5 6678 35.3 12219 64.7 Managed care/ TRICARE/military 9490 70.4 3999 29.7 9202 68.2 4287 31.8 6788 50.3 6701 49.7 Medicaid/federal insurance programs/public health service 1287 71.9 504 28.1 1083 60.5 708 39.5 847 47.3 944 52.7 Not insured/self pay 1083 66.0 558 34.0 946 57.7 695 42.4 694 42.3 947 57.7 Insurance status Unknown 1151 56.5 886 43.5 1160 57.0 877 43.1 786 38.6 1251 61.4 Race and insurance payer Whites with private insurance 6356 72.0 2469 28.0 0.005 5899 66.8 2926 33.2 <.001 4438 50.3 4387 49.7 <.001 Blacks with private insurance 317 66.0 163 34.0 276 57.5 204 42.5 201 41.9 279 58.1 Whites with Medicare/Medicare with supplements 10372 58.9 7250 41.1 <.001 9578 54.4 8044 45.7 <.001 6320 35.9 11302 64.1 <.001 Blacks with Medicare/Medicare with supplements 670 52.6 605 47.5 541 42.4 734 57.6 358 28.1 917 71.9 Whites with managed care/ TRICARE/military 9019 70.7 3745 29.3 0.001 8750 68.6 4014 31.5 <.001 6476 50.7 6288 49.3 <.001 Blacks with managed care/ TRICARE/military 471 65.0 254 35.0 452 62.3 273 37.7 312 43.0 413 57.0 Whites with Medicaid/federal insurance programs/public health service 1100 73.1 404 26.9 0.006 929 61.8 575 38.2 0.010 731 48.6 773 51.4 .01 Blacks with Medicaid/federal insurance programs/public health service 187 65.2 100 34.8 154 53.7 133 46.3 116 40.4 171 59.6 Whites with not insured/self pay 929 66.7 463 33.3 0.134 815 58.6 577 41.5 0.081 598 43.0 794 57.0 .20 Blacks with not insured/self pay 154 61.9 95 38.2 131 52.6 118 47.4 96 38.6 153 61.5 Whites with insurance status unknown 1071 56.7 817 43.3 0.472 1091 57.8 797 42.2 0.007 741 39.3 1147 60.8 .03 Blacks with insurance status unknown 80 53.7 69 46.3 69 46.3 80 53.7 45 30.2 104 69.8Logistic regression analysis revealed that age, stage of disease, histologic subtype, and annual hospital case volume were statistically significantly associated with receipt of NCCN guideline-adherent care (Table 3). Median household income was positively associated with receipt of adherent care, whereas education level was not a statistically significant predictor. Black race (odds ratio [OR] = 1.36, 95% confidence interval [CI] = 1.25 to 1.48), Medicare payer status (OR = 1.20, 95% CI = 1.12 to 1.28), and not insured payer status (OR = 1.33, 95% CI = 1.19 to 1.49) were independently associated with a higher likelihood of not receiving NCCN guideline-adherent care.
Table 3.Logistic regression model (binomial logistic regression) of demographic, clinical, pathological, and treatment variables associated with National Comprehensive Cancer Network guideline nonadherent care*
Risk factor No. % Unadjusted OR (95% CI) Adjusted OR (95% CI) Patient Characteristics Age, mean, SD, y 62.31 13.8 1.03 (1.02 to 1.03) 1.02 (1.02 to 1.03) Race White 43 995 93.3 1.00 (referent) 1.00 (referent) Black 3165 6.7 1.41 (1.31 to 1.52) 1.36 (1.25 to 1.48) Proportion with college degree-2000 <9% 20 113 42.7 1.00 (referent) 1.00 (referent) 9%–12.9% 12 614 26.8 1.10 (1.05 to 1.15) 0.96 (0.90 to 1.01) 13%–20.9% 7100 15.1 1.18 (1.12 to 1.25) 1.03 (0.96 to 1.10) ≥21% 4812 10.2 1.22 (1.15 to 1.30) 1.00 (0.92 to 1.09) Missing 2521 5.4 1.05 (0.97 to 1.15) 0.24 (0.01 to 4.74) Median household income - 2000 ≥$46 000 17 838 37.8 1.00 (referent) 1.00 (referent) $35 000–$45 999 12 820 27.2 1.12 (1.07 to 1.18) 1.05 (0.99 to 1.11) <$35 000 13 983 29.7 1.26 (1.21 to 1.32) 1.09 (1.02 to 1.16) Missing 2519 5.3 1.09 (1.00 to 1.18) 4.63 (0.23 to 91.68) Primary payer at diagnosis Private insurance 9305 19.7 1.00 (referent) 1.00 (referent) Medicare/Medicare with supplements 18 897 40.1 1.82 (1.73 to 1.91) 1.20 (1.12 to 1.28) Managed care/TRICARE/military 13 489 28.6 0.98 (.093 to 1.04) 1.03 (0.97 to 1.09) Medicaid/federal insurance programs/public health service 1791 3.8 1.11 (1.00 to 1.23) 1.08 (0.96 to 1.20) Not insured/self pay 1641 3.5 1.36 (1.22 to 1.51) 1.33 (1.19 to 1.49) Missing: insurance status unknown 2037 4.3 1.58 (1.44 to 1.75) 1.80 (1.61 to 2.00) Tumor Characteristics Tumor stage Stage IA 4464 9.5 1.00 (referent) 1.00 (referent) Stage IB 511 1.1 1.10 (0.90 to 1.35) 1.13 (0.91 to 1.39) Stage IC 3198 6.8 0.80 (0.73 to 0.88) 0.78 (0.70 to 0.86) Stage IIA 833 1.8 1.20 (1.02 to 1.42) 1.06 (0.89 to 1.27) Stage IIB 1198 2.5 0.87 (0.76 to 1.00) 0.73 (0.64 to 0.85) Stage IIC 1824 3.9 0.91 (0.81 to 1.02) 0.74 (0.66 to 0.84) Stage IIIA 1529 3.2 1.22 (1.07 to 1.39) 0.92 (0.80 to 1.05) Stage IIIB 1999 4.2 1.24 (1.10 to 1.39) 0.98 (0.86 to 1.11) Stage IIIC 17 519 37.2 0.28 (0.26 to 0.30) 0.21 (0.19 to 0.23) Stage IV 14 085 29.9 0.76 (0.71 to 0.82) 0.40 (0.37 to 0.43) Tumor grade Well/moderately differentiated 12 716 27.0 1.00 (referent) 1.00 (referent) Poorly/undifferentiated/anaplastic 24 458 51.9 0.77 (0.74 to 0.80) 0.91 (0.87 to 0.96) Missing 9986 21.2 2.07 (1.96 to 2.19) 1.95 (1.83 to 2.09) Tumor histology Serous 22 753 48.3 1.00 (referent) 1.00 (referent) Mucinous 3350 7.1 2.09 (1.94 to 2.26) 1.39 (1.27 to 1.51) Endometroid 6044 12.8 1.49 (1.40 to 1.57) 1.10 (1.03 to 1.18) Clear-cell 2526 5.4 1.65 (1.51 to 1.79) 1.36 (1.23 to 1.49) Mixed 366 0.8 1.46 (1.19 to 1.80) 1.56 (1.25 to 1.95) NOS/undifferentiated 12 121 25.7 2.97 (2.83 to 3.11) 2.11 (2.00 to 2.22) Hospital ovarian cancer volume, no. of cases per year 1–6 11 742 24.9 1.00 (referent) 1.00 (referent) 7–14 11 868 25.2 0.65 (0.62 to 0.69) 0.78 (0.73 to 0.82) 15–25 11 820 25.1 0.45 (0.43 to 0.48) 0.59 (0.55 to 0.62) ≥26 11 730 24.9 0.36 (0.34 to 0.38) 0.47 (0.45 to 0.50) Total 47 160 100.0 Survival AnalysisThe 5-year overall survival for all patients was 38.4% (95% CI = 38.0% to 38.9%). Statistically significant differences in overall 5-year survival rates were observed according to both race and payer stratified by adherence to NCCN guidelines. The 5-year overall survival rates for white patients receiving NCCN guideline-adherent care (41.4%) and nonadherent care (37.8%) were statistically significantly better compared with black patients receiving NCCN guideline-adherent care (33.3%) and nonadherent care (22.5%; P < .0001) (Figure 1A). The directionality and statistical significance of these trends in 5-year overall survival stratified by race and NCCN guideline adherence were the same regardless of facility type or annual hospital ovarian cancer volume (Supplementary Figures 1 and 2, available online). Statistically significant differences in 5-year overall survival were also observed according to payer status. Those with private insurance and managed care payer status had statistically significantly improved 5-year overall survival outcomes compared with patients with Medicaid, those who were not insured/self pay, and patients with Medicare for both NCCN guideline-adherent (Figure 1B) (P < .0001) and nonadherent (data not shown) care.
Figure 1.Overall survival (OS) probability for patients with invasive primary epithelial ovarian cancer from the National Cancer Data Base stratified by adherence to National Comprehensive Cancer Network (NCCN) guideline therapy and race and payer category. Survival analyses were performed using the Kaplan–Meier method and two-sided log rank test. A) Data from all patients (n = 47 160) were analyzed according to race and adherence and nonadherence to NCCN guideline care. The 5-year overall survival was 41.4% (95% confidence interval [CI] = 40.6% to 42.1%) for adherent whites, 33.3% (95% CI = 30.4% to 36.2%) for adherent blacks, 37.8% (95% CI = 37.1% to 38.4%) for nonadherent whites, and 22.5% (95% CI = 20.6% to 24.4%) for nonadherent blacks (two-sided P < .001). B) Data from all patients receiving NCCN guideline-adherent therapy (n = 20 432) were analyzed according to payer category. The 5-year overall survival was 46.3% (95% CI = 44.8% to 47.8%) for patients with private payer category, 47.3% (95% CI = 46.0% to 48.5%) for patients with managed care payer category, 31.6% (95% CI = 30.4% to 32.7%) for patients with Medicare payer category, 35.8% (95% CI = 32.4% to 39.3%) for patients with Medicaid payer category, and 42.4% (95% CI = 38.4% to 46.4%) for patients with not insured/self pay payer category (two-sided P < .001). The number of patients at risk in each group at various time points are listed below the graphs.
Multilevel survival analysis revealed that tumor stage, grade, histological subtype, and annual hospital ovarian cancer case volume were all statistically significantly predictive of overall survival (Table 4). Non-NCCN-guideline-adherent care was an independent predictor of inferior overall survival (hazard ratio [HR] = 1.43, 95% CI = 1.38 to 1.47). The negative effect of Medicare payer status on overall survival was attenuated although still statistically significant. A median household income less than $35 000 was also independently negatively associated with survival (HR = 1.06, 95% CI = 1.02 to 1.11). However, of the sociodemographic factors evaluable in this study, the three strongest predictors of a worse overall survival outcome, after controlling for other factors, including NCCN guideline-adherent care, were black race (HR = 1.29, 95% CI = 1.22 to 1.36), Medicaid payer status (HR = 1.29, 95% CI = 1.20 to 1.38), and not insured payer status (HR = 1.32, 95% CI = 1.20 to 1.44). Each of these characteristics was associated with an approximately 30% increase in the risk of death.
Table 4.Multilevel survival analysis*
Risk factor No. % Unadjusted HR (95% CI) Adjusted HR (95% CI) Treatment Characteristics Adherence to NCCN guidelines for treatment Yes 20 432 43.3 1.00 (referent) 1.00 (referent) No 26 728 56.7 1.33 (1.29 to 1.37) 1.43 (1.38 to 1.47) Patient Characteristics Age, mean, SD, y 62.31 13.8 1.04 (1.04 to 1.04) 1.03 (1.03 to 1.03) Race White 43 995 93.3 1.00 (referent) 1.00 (referent) Black 3165 6.7 1.50 (1.43 to 1.59) 1.29 (1.22 to 1.36) Proportion with college degree-2000 <9% 20 113 42.7 1.00 (referent) 1.00 (referent) 9%–12.9% 12 614 26.8 1.16 (1.12 to 1.20) 1.08 (1.04 to 1.12) 13%–20.9% 7100 15.1 1.19 (1.15 to 1.24) 1.08 (1.04 to 1.13) ≥21% 4812 10.2 1.21 (1.16 to 1.27) 1.05 (0.99 to 1.11) Missing 2521 5.4 0.99 (0.94 to 1.05) 0.66 (0.56 to 0.77) Median household income - 2000 ≥$46,000 17 838 37.8 1.00 (referent) 1.00 (referent) $35 000–$45 999 12 820 27.2 1.12 (1.09 to 1.16) 1.00 (0.97 to 1.04) <$35 000 13 983 29.7 1.28 (1.24 to 1.33) 1.06 (1.02 to 1.11) Missing 2519 5.3 1.02 (0.96 to 1.07) 1.48 (1.25 to 1.75) Primary payer at diagnosis Private insurance 9305 19.7 1.00 (referent) 1.00 (referent) Medicare/Medicare with supplements 18 897 40.1 2.14 (2.07 to 2.22) 1.07 (1.02 to 1.11) Managed care/TRICARE/military 13 489 28.6 1.03 (0.99 to 1.07) 1.02 (0.98 to 1.06) Medicaid/federal insurance programs/public health service 1791 3.8 1.49 (1.39 to 1.60) 1.29 (1.20 to 1.38) Not insured/self pay 1641 3.5 1.39 (1.28 to 1.50) 1.32 (1.20 to 1.44) Missing: insurance status unknown 2037 4.3 1.45 (1.34 to 1.58) 1.05 (0.93 to 1.17) Tumor Characteristics Tumor stage Stage IA 4464 9.5 1.00 (referent) 1.00 (referent) Stage IB 511 1.1 1.44 (1.15 to 1.81) 1.61 (1.29 to 2.02) Stage IC 3198 6.8 1.50 (1.33 to 1.69) 1.59 (1.41 to 1.78) Stage IIA 833 1.8 2.20 (1.87 to 2.60) 2.23 (1.89 to 2.63) Stage IIB 1198 2.5 2.52 (2.18 to 2.91) 2.46 (2.13 to 2.85) Stage IIC 1824 3.9 3.61 (3.19 to 4.08) 3.58 (3.17 to 4.04) Stage IIIA 1529 3.2 5.72 (5.10 to 6.42) 5.34 (4.76 to 6.00) Stage IIIB 1999 4.2 6.02 (5.43 to 6.69) 5.65 (5.06 to 6.30) Stage IIIC 17 519 37.2 8.15 (7.45 to 8.90) 8.79 (8.00 to 9.66) Stage IV 14 085 29.9 14.26 (13.03 to 15.60) 12.45 (11.34 to 13.68) Tumor grade Well/moderately differentiated 12 716 27.0 1.00 (referent) 1.00 (referent) Poorly/undifferentiated/anaplastic 24 458 51.9 1.78 (1.72 to 1.84) 1.11 (1.07 to 1.15) Missing 9986 21.2 3.09 (2.97 to 3.22) 1.32 (1.27 to 1.37) Tumor histology Serous 22 753 48.3 1.00 (referent) 1.00 (referent) Mucinous 3350 7.1 0.77 (0.72 to 0.82) 1.78 (1.67 to 1.90) Endometroid 6044 12.8 0.41 (0.39 to 0.44) 0.85 (0.81 to 0.90) Clear-cell 2526 5.4 0.53 (0.49 to 0.57) 1.47 (1.35 to 1.59) Mixed 366 0.8 0.73 (0.62 to 0.85) 1.00 (0.85 to 1.17) NOS/undifferentiated 12 121 25.7 1.72 (1.67 to 1.78) 1.31 (1.26 to 1.35) Hospital ovarian cancer volume, no. of cases per year 1–6 11 742 24.9 1.00 (referent) 1.00 (referent) 7–14 11 868 25.2 0.85 (0.82 to 0.89) 0.96 (0.92 to 1.00) 15–25 11 820 25.1 0.79 (0.75 to 0.82) 0.93 (0.89 to 0.97) ≥26 11 730 24.9 0.74 (0.70 to 0.78) 0.92 (0.88 to 0.97) Total 47 160 100.0 DiscussionOvarian cancer is the fifth leading cause of cancer-related death among US women and accounts for more deaths than all other gynecologic cancers combined. Although treatment advances have improved the expected survival outcome of the general population of women with ovarian cancer over the past 30 years, this improvement in survival has not been universal across racial, ethnic, and socioeconomic groups (7). Women with ovarian cancer from racial or ethnic minorities and socioeconomically disadvantaged populations suffer a disproportionately greater mortality burden (6–8,12,14,18–22). The literature is divided, however, on whether race and SES indicators are independent negative prognostic factors for ovarian cancer survival. Many of these studies have had limited numbers of black patients and inconsistently controlled for the effects of tumor characteristics, treatment, and SES variables that might also influence survival. The objective of this study was to examine disparities in the quality of epithelial ovarian cancer care and survival outcome according to race and socioeconomic indicators using the resources of the NCDB.
Ultimately, disparities in healthcare based on race and SES can be reframed as fundamental issues of healthcare quality under the assumption that high-quality care should be universally accessible and administered irrespective of one’s phenotypic features or socioeconomic station. The literature examining disparities in the quality of ovarian cancer care, benchmarked to a validated national standard, is limited. In 2005, Harlan et al. studied 7134 patients with 11 different cancer types from the Surveillance Epidemiology and End Results (SEER) Patterns of Care database and found that whites received NCCN guideline cancer therapy more often than blacks and Hispanics (3). This study did not link receipt of guideline therapy to survival and included only 504 patients with ovarian cancer. The only other study linking ovarian cancer care to specific treatment guidelines was reported by Harlan et al. and described 1167 ovarian cancer patients from the SEER database in 1991 and 1996 (10). These investigators examined trends in surgery and chemotherapy according to recommendations from the 1994 National Institutes of Health Consensus Development Conference on ovarian cancer and found that 55.2% of whites received recommended therapy compared with just 43.6% of blacks. This study, however, included only 118 black patients and did not link treatment to survival outcome.
The current dataset draws from approximately 70% of the ovarian cancer cases diagnosed in the United States during a time interval of standardized contemporary treatment. The resulting perspective is unique and offers the first large-scale, population-based analysis benchmarking racial and SES disparities in ovarian cancer care to a quality process measure—NCCN guideline therapy—that has been simultaneously validated and linked with survival outcome. In this dataset, black race was independently associated with 36% increased likelihood of not receiving NCCN guideline-adherent care. Furthermore, after adjusting for the effects of other variables, including receipt of NCCN guideline therapy, black patients experienced a 29% increase in the risk of death compared with whites. The contribution of reduced access to expert care to the race-based survival gap is difficult to ascertain. Although previous investigators have reported that blacks have reduced access to high-volume ovarian cancer surgeons, the observed survival disparity is adjusted for the effect of hospital case volume (23,24).
Disentangling the observed race-based ovarian cancer survival gap from differences in the quality of care administered is a complex problem. For example, in an early study using the NCDB, Parham et al. found that blacks with ovarian cancer were more than twice as likely as whites to not receive recommended treatment and had a 30% increased risk of death (14). This analysis was only adjusted for age, stage, and residential income and did not correct for the type or quality of treatment or other demographic variables. More recently, Chase et al. found that black race was independently predictive of receiving initial chemotherapy for ovarian cancer rather than primary surgery; however, the associated effect on survival was not examined (13). In an analysis of 4262 ovarian cancer patients from the SEER database, Du and colleagues found that although only 50.2% of blacks received recommended chemotherapy treatment, compared with 64.7% of whites, there was no difference in survival after adjusting for tumor characteristics, treatment, and sociodemographic factors (25). Data supporting the hypothesis that differences in ovarian cancer treatment could account for all or most of the race-based survival differences come from single institution studies, population-based studies, and cooperative group trial data showing that when equal treatment is administered, race-based survival disparities are largely mitigated or even eliminated (25–31). In contrast, the current analysis revealed a persistent and statistically significant negative survival impact associated with black race after controlling for NCCN guideline-adherent care and suggests that there may be subtle but important survival determinants (eg, amount of residual disease, chemotherapy dose intensity, access to high-volume surgeons) within the initial treatment program that are not captured by the algorithm for adherence to NCCN guidelines (23,30). Alternatively, unmeasured factors along the clinical care continuum impacting survival (eg, second-line therapy) may be unequally distributed according to race (32). It is unlikely that the presence of potential underlying biological differences between races, including variation in BRCA mutation status, would be of a magnitude that would account for the observed differences in quality of care and survival (33).
The influence of SES indicators, such as education level, employment status, and household income, as independent predictors of ovarian cancer treatment and survival has been inconsistent. In several studies, an increasing level of Census-area poverty has been associated with both a lower likelihood of receiving recommended treatment and worse ovarian cancer survival (18,22,34). In contrast, others have failed to identify poverty level, household income, or education as predictive of either treatment or outcome (14,26,35). In the current study, a median annual household income less than $35 000 was statistically significantly associated with a lower likelihood of receiving proper treatment and worse overall survival independent of race, although the effects were modest.
The type of health insurance is both a health system factor and an individual-level measure of SES and has been linked to expenditure on cancer treatment, suggesting that payer status may influence receipt of appropriate care (3,36). In this analysis, patients with Medicare and not insured/self pay payer status were statistically significantly less likely to receive NCCN guideline-adherent care and experienced an approximately 30% increased risk of death. These data confirm findings of previous studies of ovarian cancer in which nonprivate or uninsured payer status was highly predictive of receiving nonstandard treatment and death (12,13,33,37). Interestingly, in the 2003 study by Harlan et al., the lack of private insurance was an impediment to receiving appropriate ovarian cancer therapy for both black and Hispanic patients but not whites (10). Two population-based studies and one single institution study, however, have found that payer status was not predictive of ovarian cancer treatment (3,28,38).
There are several limitations of this study that must be considered in interpreting the data. First, the dataset contained incomplete information for some characteristics, which may have introduced selection bias in determining the final study population. Second, the NCDB is subject to potential errors in reporting, although rigorous validation of data accuracy is performed through internal monitoring, site surveys, and review of data quality (39,40). Third, the NCDB does not contain information on surgeon specialty, the extent of residual disease, specific chemotherapy agents, platinum dose intensity/cumulative dose, or treatment of recurrent disease. It is possible that differences in these parameters could account for a proportion of the observed survival disparities. A fourth potential limitation is that the NCCN guideline adherence decision algorithm incorporated both initial surgery and initial chemotherapy (neoadjuvant chemotherapy). To the extent that neoadjuvant chemotherapy has been associated with a worse survival outcome, associations between race and payer status and the frequency of neoadjuvant chemotherapy could be reflected as disparities in survival (12,13). A fifth limitation of this study is that information on medical comorbidity and performance status was not available for the 1998 to 2002 study cohort. As a result, neither NCCN guideline adherence nor survival could be adjusted for the presence of medical comorbidity. Although unmeasured differences in medical comorbidity likely accounts for a portion of the observed disparities according to race and payer status, it is improbable that this would explain the full extent of differences in treatment quality and survival (13,25).
This is the largest, most comprehensive dataset reported to date that analyzes ovarian cancer disparities using a validated quality process measure linked to a meaningful clinical outcome. These data highlight and quantify clinically significant disparities in the quality of ovarian cancer care and overall survival, independent of NCCN guidelines, along racial and SES parameters in the United States and indicate that not all segments of the population have benefitted equally from improvements in ovarian cancer care. It is also apparent that factors other than adherence to NCCN guideline care influence ovarian cancer survival for racial minorities and the socioeconomically disadvantaged. Increased efforts are needed to more precisely define the patient, provider, healthcare system, and societal factors leading to these observed disparities and develop an informed platform from which targeted interventions can be designed to reduce and ultimately eliminate ovarian cancer disparities among persons from all racial groups and socioeconomic strata.
FundingREB was supported in part by the Queen of Hearts Foundation .
Supplementary MaterialSupplementary Data
The sponsor had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript; and the decision to submit the manuscript for publication.
This paper received the Hugh Barber Best Scientific Abstract Plenary Presentation at the Society of Gynecologic Oncology Annual Meeting on Women’s Cancer, Austin, Texas, March 27, 2012.
ReferencesThis section collects any data citations, data availability statements, or supplementary materials included in this article.
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