BACKGROUND:
Meningiomas are the most common intracranial neoplasms. Although genomic analysis has helped elucidate differences in survival, there is evidence that racial disparities may influence outcomes. African Americans have a higher incidence of meningiomas and poorer survival outcomes. The etiology of these disparities remains unclear, but may include a combination of pathophysiology and other factors.
OBJECTIVE:
To determine factors that contribute to different clinical outcomes in racial populations.
METHODS:
We retrospectively reviewed 305 patients who underwent resection for meningiomas at a single tertiary care facility. We used descriptive statistics and univariate, multivariable, and Kaplan-Meier analyses to study clinical, radiographical, and histopathological differences.
RESULTS:
Minority patients were more likely to present through the emergency department than an outpatient clinic (P < .0001). They were more likely to present with more advanced clinical symptoms with lower Karnofsky Performance scores, more frequently had peritumoral edema (P = .0031), and experienced longer postoperative stays in the hospital (P = .0053), and African-American patients had higher hospitalization costs (P = .046) and were more likely to be publicly insured. Extent of resection was an independent predictor of recurrence freedom (P = .039). Presentation in clinic setting trended toward an association with recurrence-free survival (P = .055). We observed no significant difference in gross total resection rates, postoperative recurrence, or recurrence-free survival.
CONCLUSION:
Minority patients are more likely to present with severe symptoms, require longer perioperative hospitalization, and generate higher hospitalization costs. This may be due to socioeconomic factors that affect access to health care. Targeting barriers to access, especially to subspecialty care, may facilitate more appropriate and timely diagnosis, thereby improving patient care and outcomes.
KEY WORDS: Meningioma, Meningioma surgery, Racial disparities, Social determinants of health
ABBREVIATIONS:
- CBTRUS
Central Brain Tumor Registry of the United States
- GTR
gross total resection
- KPS
Karnofsky Performance Score
- WHO
World Health Organization
Healthcare disparities between different racial groups are well-documented and known to affect overall outcomes in many disease processes.1-3 African Americans have the highest mortality rates for heart disease, cerebrovascular disease, and HIV/AIDS.1-3 Minority patients are also less likely to be insured, receive more of their medical care in an emergency department vs clinical setting, and are less likely to have a primary care provider.3-5 Beyond differences in healthcare access, minority patients are less likely to undergo certain medical procedures or receive treatment for acute pain and chronic medical conditions3,6 Racial disparities are also notable in patients with cancer, with higher cancer-specific mortality among African Americans for numerous solid tumors.6
As with other tumor types, racial disparities exist in primary brain tumor management.1 Meningiomas are one of the most common brain tumors, accounting for almost 40% of primary brain tumors.7,8 The majority are benign, WHO grade I tumors.9,10 However, approximately 20% are WHO grade II or III and exhibit insidious growth, frequent recurrence, and poor progression-free survival.11-14 Genomic analysis has improved our understanding of meningiomas' underlying biology.12-17 Several genes drive meningioma formation, with NF2 being the most common.12,15,16,18,19 In addition to genomic aberrations, epidemiological studies have identified important differences between patients with meningioma. Data from the Central Brain Tumor Registry of the United States (CBTRUS) indicate that meningiomas of all grades occur in African Americans approximately twice as frequently as Whites.20 There are limited data to explain these tumors' higher incidence in African-American patients. Studies have identified larger tumor size at presentation and decreased overall survival in the African-American population.21,22 The progression-free survival benefit of gross total resection (GTR) is well-documented in meningiomas; however, African-American patients are less likely to undergo GTR and have significantly higher postoperative mortality.14,22-24 The etiology of these differences is likely multifactorial and requires further investigation. In this study, we characterized the effect of race, socioeconomic, and other demographic factors on the outcomes of patients with meningioma.
METHODS
Patient Population
We retrospectively reviewed 305 patients who underwent pathology-proven meningioma resection between 2009 and 2020 at a single tertiary care hospital. We collected clinical, histopathological, and radiographical data by reviewing electronic medical records and compared patients in 4 different self-reported racial and ethnic groups: White, African American, Asian, and non-White Hispanic. We drew comparisons between these groups for multiple variables, including patient demographics, admission source, surgical and radiation history, preoperative symptomatology, postoperative complications, insurance type, and hospitalization costs. Histopathological data included the following: WHO grade, MIB-1 proliferation index, and histological subtype. MIB-1 proliferation index was calculated by determining the percentage of meningioma cell nuclei positive for Ki-67 staining. We analyzed pre- and postoperative MR and computed tomography imaging to evaluate initial tumor size, extent of resection, and evidence of recurrence. We determined progression-free survival from resection date to the first documented recurrence. Our Institutional Review Board approved this study and did not require patient consent.
Statistical Analyses
We comparatively analyzed variables across the 4 racial groups and between White and African-American groups alone. Statistical analysis was performed using the Fisher exact test, chi square tests, one-way analysis of variance, and unpaired t-test for categorical and numerical variables. Multivariable analysis was performed for recurrence freedom with prognostic and socioeconomic factors. Cox proportional hazards multivariable regression was used to assess statistical significance. The Kaplan-Meier method was performed for progression-free survival analysis. We used GraphPad Prism version 8 (GraphPad Software Inc), R Statistical Computing Software (R Core Team), and SPSS software (IBM) for statistical analysis and considered P-values ≤.05 significant.
RESULTS
Patient Population
We identified 305 patients who met study criteria. Of these, 97 were male and 208 were female; this gender distribution reflects the reported increased incidence in women compared with men.19 General demographic variables, such as sex, preoperative seizures, surgical history, tumor size, and hospital complications, were similar across racial groups, although Asian patients underwent resection at a younger age than White patients (mean of 50 yr vs 60 yr, respectively, P = .0068; Table 1).
TABLE 1.
Patient Characteristics
| Clinical variables | White n = 166 |
African American n = 65 |
Hispanic n = 54 |
Asian n = 20 |
P value |
|---|---|---|---|---|---|
| Sex | .16 | ||||
| Male | 61 (37%) | 16 (24%) | 13 (24%) | 7 (35%) | |
| Female | 105 (63%) | 50 (76%) | 41 (76%) | 13 (65%) | |
| Age at surgery (yr) | .0068 | ||||
| Mean | 60.05 | 58.44 | 56.23 | 50.15 | |
| SD | 12.93 | 12.91 | 12.46 | 14.53 | |
| Preoperative seizures | .24 | ||||
| Yes | 30 (17%) | 18 (27%) | 9 (17%) | 6 (30%) | |
| No | 136 (83%) | 47 (73%) | 45 (83%) | 14 (70%) | |
| Previous surgery | .41 | ||||
| Yes | 23 (13%) | 4 (8%) | 6 (11%) | 3 (15%) | |
| No | 143 (87%) | 61 (92%) | 48 (89%) | 17 (85%) | |
| Tumor size (cm) | .44 | ||||
| Mean | 3.54 | 3.92 | 3.78 | 3.82 | |
| SD | 1.62 | 1.63 | 1.55 | 1.99 | |
| Hospital complications | .11 | ||||
| Yes | 27 (16%) | 11 (17%) | 16 (30%) | 2 (10%) | |
| No | 139 (84%) | 54 (83%) | 38 (70%) | 18 (90%) |
SD, standard deviation.
Minority patients were more likely to first encounter a neurosurgeon through the emergency department, whereas White patients more frequently presented in clinic. Thirty-nine percent of African-American patients, 40% of Hispanic patients, and 20% of Asian patients were admitted through the emergency department compared with 13% of White patients (P < .0001; Table 2). Presenting clinical symptoms for those admitted through the emergency department included moderate to severe weakness, speech deficits, and altered mental status. Comparatively, presenting symptoms for clinic patients included headache and mild weakness. The average Karnofsky Performance Score (KPS) at initial presentation was lower among minority patients (P = .014). Compared with the average KPS of White patients (80.6), African-American patients had an average KPS of 76.8 (P = .023), Asian patients had an average KPS of 77 (P = .13), and Hispanic patients had the lowest score of 75.6 (P = .0028) (Tables 2 and 3). White and Asian patients were more likely to have multiple lesions (P = .04; Table 2). Preoperative seizures, previous surgical resection, and previous radiation treatment did not vary significantly across racial groups (Table 2).
TABLE 2.
Univariate Analysis of Demographic and Clinical Parameters Between All 4 Racial Populations
| Clinical variables | White n = 166 |
African American n = 65 |
Hispanic n = 54 |
Asian n = 20 |
P value |
|---|---|---|---|---|---|
| Age at surgery (yr) | .0068 | ||||
| Mean | 60.1 | 58.4 | 56.2 | 50.2 | |
| SD | 12.9 | 12.9 | 12.5 | 14.5 | |
| Source of admission | <.0001 | ||||
| Clinic/referral | 144 (87%) | 39 (61%) | 32 (60%) | 16 (80%) | |
| Emergency department | 22 (13%) | 26 (39%) | 22 (40%) | 4 (20%) | |
| History of previous resection | .41 | ||||
| Yes | 23 (13%) | 4 (8%) | 6 (11%) | 3 (15%) | |
| No | 143 (87%) | 61 (92%) | 48 (89%) | 17 (85%) | |
| History of seizures | .24 | ||||
| Yes | 30 (17%) | 18 (27%) | 9 (17%) | 6 (30%) | |
| No | 136 (83%) | 47 (73%) | 45 (83%) | 14 (70%) | |
| History of previous radiation | .27 | ||||
| Yes | 11 (6%) | 1 (3%) | 1 (2%) | 1 (5%) | |
| No | 155 (94%) | 64 (97%) | 53 (98%) | 19 (95%) | |
| Length of stay (d) | .0053 | ||||
| Mean | 4.06 | 6.28 | 5.68 | 5.7 | |
| SD | 3.91 | 4.33 | 6.22 | 5.86 | |
| KPS | .014 | ||||
| Mean | 80.6 | 76.8 | 75.6 | 77 | |
| SD | 9.89 | 13.89 | 11.69 | 11.29 | |
| Tumor size (cm) | .44 | ||||
| Mean | 3.54 | 3.92 | 3.78 | 3.82 | |
| SD | 1.62 | 1.63 | 1.55 | 1.99 | |
| Hospital complications | .11 | ||||
| Yes | 27 (16%) | 11 (17%) | 16 (30%) | 2 (10%) | |
| No | 139 (84%) | 54 (83%) | 38 (70%) | 18 (90%) | |
| Simpson grade | .57 | ||||
| 1 | 62 (41%) | 20 (36%) | 16 (34%) | 5 (29%) | |
| 2 | 41 (27%) | 13 (24%) | 12 (26%) | 7 (41%) | |
| 3 | 12 (8%) | 2 (4%) | 3 (6%) | 0 (0%) | |
| 4 | 36 (23%) | 20 (36%) | 16 (34%) | 5 (29%) | |
| No MRIa | 15 (9%) | 10 (15%) | 7 (13%) | 3 (15%) | |
| Readmission within 30 d | .78 | ||||
| Yes | 14 (8%) | 8 (12%) | 4 (7%) | 2 (10%) | |
| No | 152 (92%) | 57 (88%) | 50 (93%) | 18 (90%) | |
| WHO grade | .71 | ||||
| I | 145 (88%) | 55 (85%) | 45 (83%) | 19 (95%) | |
| II | 19 (11%) | 10 (15%) | 8 (15%) | 1 (5%) | |
| III | 1 (1%) | 0 (0%) | 1 (2%) | 0 (0%) | |
| Histologic type | .08 | ||||
| Anaplastic | 1 (1%) | 0 (0%) | 1 (2%) | 0 (0%) | |
| Angiomatous | 3 (2%) | 3 (4%) | 5 (9%) | 1 (5%) | |
| Atypical | 16 (10%) | 11 (16%) | 7 (13%) | 0 (0%) | |
| Chordoid | 1 (1%) | 1 (1%) | 1 (2%) | 0 (0%) | |
| Clear cell | 1 (1%) | 0 (0%) | 0 (0%) | 0 (0%) | |
| Fibroblastic | 15 (9%) | 6 (9%) | 7 (13%) | 3 (16%) | |
| Meningothelial | 84 (51%) | 31 (4%) | 21 (39%) | 9 (47%) | |
| Metaplastic | 3 (2%) | 3 (4%) | 1 (2%) | 0 (0%) | |
| Microcystic | 1 (1%) | 3 (4%) | 2 (4%) | 1 (5%) | |
| Psammomatous | 5 (3%) | 2 (3%) | 0 (0%) | 1 (5%) | |
| Secretory | 4 (2%) | 2 (3%) | 4 (7%) | 1 (5%) | |
| Transitional | 32 (19%) | 6 (7%) | 5 (9%) | 2 (11%) | |
| Lymphocyte-rich | 0 (0%) | 0 (0%) | 0 (0%) | 1 (5%) | |
| MIB-1 reactivity | .55 | ||||
| Mean | 5.52 | 7.08 | 6.33 | 5.01 | |
| SD | 6.85 | 9.12 | 9.98 | 4.45 | |
| Adjuvant radiation | .92 | ||||
| Yes | 14 (8%) | 4 (6%) | 4 (7%) | 2 (10%) | |
| No | 152 (92%) | 61 (94%) | 50 (93%) | 18 (90%) | |
| Additional surgical resection | .78 | ||||
| Yes | 18 (11%) | 5 (8%) | 5 (9%) | 1 (5%) | |
| No | 148 (89%) | 60 (92%) | 49 (91%) | 19 (95%) | |
| Multiple lesions | .04 | ||||
| Yes | 24 (14%) | 2 (3%) | 11 (20%) | 3 (15%) | |
| No | 142 (86%) | 63 (97%) | 44 (80%) | 17 (85%) | |
| Postoperative recurrence | |||||
| Yes | 26 (20%) | 7 (14%) | 10 (22%) | 3 (17%) | .78 |
| No | 107 (80%) | 42 (86%) | 35 (78%) | 15 (83%) | |
| No surveillance imaginga | 33 (20%) | 16 (25%) | 9 (17%) | 2 (10%) | |
| Duration of postoperative follow-up (mo) | .32 | ||||
| Median | 13 | 5 | 12 | 10 | |
| Range | 0.20-106 | 0.30-78 | 0.30-101 | 0.43-103 | |
| SEM | 58.3 | 77.6 | 108 | 191 | |
| Hospitalization cost | .17 | ||||
| Mean | 26 547 | 31 204 | 32 344 | 31 081 | |
| SD | 14 588 | 15 909 | 27 697 | 24 821 | |
| Insurance type | .14 | ||||
| Private | 88 (61%) | 25 (44%) | 27 (59%) | 12 (71%) | |
| Public | 55 (38%) | 31 (54%) | 17 (37%) | 5 (29%) | |
| Self-pay | 1 (1%) | 1 (2%) | 2 (4%) | 0 (0%) | |
| Data unavailablea | 22 (13%) | 8 (12%) | 8 (15%) | 3 (15%) | |
| Peritumoral edema | .0031 | ||||
| Yes | 56 (34%) | 37 (57%) | 29 (54%) | 10 (50%) | |
| No | 110 (66%) | 28 (43%) | 25 (46%) | 10 (50%) | |
| Area of edema (cm2) | .48 | ||||
| Median | 56.1 | 60.3 | 109 | 60.9 | |
| Range | 4.23-406 | 2.8-271 | 4.54-289 | 2.11-409 | |
| SEM | 14.3 | 13.1 | 15.4 | 37.7 |
KPS, Karnofsky Performance Score; SD, standard deviation; SEM, standard error of the mean; WHO, World Health Organization.
A total of 35 patients did not undergo postoperative MRI imaging for Simpson grade to be assessed.
TABLE 3.
Pairwise Analysis of Demographic and Clinical Parameters Between African-American and White Patients
| Clinical variables | White n = 166 |
African American n = 65 |
P value |
|---|---|---|---|
| Age at surgery (yr) | .39 | ||
| Mean | 60.1 | 58.4 | |
| SD | 12.9 | 12.9 | |
| Source of admission | <.0001 | ||
| Clinic/referral | 144 (87%) | 39 (61%) | |
| Emergency department | 22 (13%) | 26 (39%) | |
| Previous resection | .12 | ||
| Yes | 23 (13%) | 4 (8%) | |
| No | 143 (87%) | 61 (92%) | |
| Previous seizures | .11 | ||
| Yes | 30 (17%) | 18 (27%) | |
| No | 136 (83%) | 47 (73%) | |
| Previous radiation | .19 | ||
| Yes | 11 (6%) | 1 (3%) | |
| No | 155 (94%) | 64 (97%) | |
| Length of stay (d) | .0003 | ||
| Mean | 4.06 | 6.28 | |
| SD | 3.91 | 4.33 | |
| KPS | .023 | ||
| Mean | 80.6 | 76.83 | |
| SD | 9.89 | 13.89 | |
| Tumor size (cm) | .13 | ||
| Mean | 3.54 | 3.92 | |
| SD | 1.62 | 1.63 | |
| Hospital complications | >.99 | ||
| Yes | 27 (16%) | 11 (17%) | |
| No | 139 (84%) | 54 (83%) | |
| Simpson grade | .28 | ||
| 1 | 62 (41%) | 20 (36%) | |
| 2 | 41 (27%) | 13 (24%) | |
| 3 | 12 (8%) | 2 (4%) | |
| 4 | 36 (23%) | 20 (36%) | |
| No MRIa | 15 (9%) | 10 (15%) | |
| Readmission within 30 d | .45 | ||
| Yes | 14 (8%) | 8 (12%) | |
| No | 152 (92%) | 57 (88%) | |
| WHO grade | .61 | ||
| I | 145 (88%) | 55 (85%) | |
| II | 19 (11%) | 10 (15%) | |
| III | 1 (1%) | 0 (0%) | |
| Histologic type | .28 | ||
| Anaplastic | 1 (1%) | 0 (0%) | |
| Angiomatous | 3 (2%) | 3 (4%) | |
| Atypical | 16 (10%) | 11 (16%) | |
| Chordoid | 1 (1%) | 1 (1%) | |
| Clear cell | 1 (1%) | 0 (0%) | |
| Fibroblastic | 15 (9%) | 6 (9%) | |
| Meningothelial | 84 (51%) | 31 (4^%) | |
| Metaplastic | 3 (2%) | 3 (4%) | |
| Microcystic | 1 (1%) | 3 (4%) | |
| Psammomatous | 5 (3%) | 2 (3%) | |
| Secretory | 4 (2%) | 2 (3%) | |
| Transitional | 32 (19%) | 6 (7%) | |
| Lymphocyte-rich | 0 (0%) | 0 (0%) | |
| MIB-1 reactivity | .37 | ||
| Mean | 5.52 | 7.08 | |
| SD | 6.85 | 9.12 | |
| Adjuvant radiation | .79 | ||
| Yes | 14 (8%) | 4 (6%) | |
| No | 152 (92%) | 61 (94%) | |
| Additional surgical resection | .63 | ||
| Yes | 18 (11%) | 5 (8%) | |
| No | 148 (89%) | 60 (92%) | |
| Multiple lesions | .01 | ||
| Yes | 24 (14%) | 2 (3%) | |
| No | 142 (86%) | 63 (97%) | |
| Postoperative recurrence | .52 | ||
| Yes | 26 (20%) | 7 (14%) | |
| No | 107 (80%) | 42 (86%) | |
| No surveillance imaginga | 33 (20%) | 16 (25%) | |
| Duration of postoperative follow-up (mo) | .059 | ||
| Median | 13 | 5 | |
| Range | 0.20-106 | 0.30-78 | |
| SEM | 58.3 | 77.6 | |
| Hospitalization cost | |||
| Mean | 26 547 | 31 204 | .046 |
| SD | 14 588 | 15 909 | |
| Insurance type | .077 | ||
| Private | 88 (61%) | 25 (44%) | |
| Public | 55 (38%) | 31 (54%) | |
| Self-pay | 1 (1%) | 1 (2%) | |
| Unknownb | 22 (13%) | 8 (12%) | |
| Peritumoral edema | .0017 | ||
| Yes | 56 (34%) | 37 (57%) | |
| No | 110 (66%) | 28 (43%) | |
| Area of edema (cm2) | .29 | ||
| Median | 56.1 | 60.3 | |
| Range | 4.23-406 | 2.8-271 | |
| SEM | 14.3 | 13.1 |
KPS, Karnofsky Performance Score; SD, standard deviation; SEM, standard error of the mean; WHO, World Health Organization.
A total of 60 patients did not undergo interval surveillance imaging beyond the immediate postoperative period to assess recurrence.
A total of 41 patients did not have a reported insurance type available within the hospital system.
Histopathology, Surgical Resection, and Postoperative Course
Tumor size, extent of resection, postoperative radiation, histological subtype, WHO grade, and MIB-1 index did not differ significantly by group. GTR was defined as Simpson Grade I-III resection. Although tumor size was comparable between groups, minority patients were more likely to have associated peritumoral edema. Fifty-seven percent of African-American patients, 54% of Hispanic patients, and 50% of Asian patients had peritumoral edema, compared with 33% of White patients (P = .0031; Table 2). The area of edema was not significantly different between racial groups: 56.1 cm2 (range 4.23-406 cm2) for White patients, 60.3 cm2 (range 2.80-271 cm2) for African-American patients, 109 cm2 (range 4.54-289 cm2) for Hispanic patients, and 60.9 cm2 (range 2.11-409 cm2) for Asian patients. Postoperative recurrence was similar, ranging from 6% to 10% of patients within each group (Table 2). There was no difference in overall recurrence-free survival by race or insurance type with last noted recurrence occurring at 6 yr (Figures 1 and 2). Maximal extent of resection was the sole independent predictor of recurrence freedom in multivariable analysis (Table 4) (odds ratio [OR], 2.57; 95% CI [1.09, 6.05]; P = .039). Presentation in clinical setting trended toward an association with recurrence-free survival; however, it did not reach significance (Table 4) (OR, 1.93; 95% CI, [0.94-5.51]; P = .055). Neither race nor insurance status predicted recurrence freedom at lengthiest follow-up.
FIGURE 1.
Progression-free survival between racial groups, P = .45.
FIGURE 2.
Progression-free survival between insurance groups, P = .93.
TABLE 4.
Cox Proportional Hazards Multivariable Regression of Recurrence Freedom by Prognostic Factors
| Prognostic factor | OR | 95% CI | P value |
|---|---|---|---|
| Race—White | 1.51 | 0.60-3.77 | .4 |
| Age >60 yr | 1.29 | 0.52-3.20 | .6 |
| Sex—Male | 0.46 | 0.19-1.11 | .084 |
| Insurance—Private | 1.87 | 0.70-4.94 | .2 |
| KPS <80 | 0.89 | 0.35-2.27 | .8 |
| Peritumoral edema | 0.70 | 0.33-2.21 | .42 |
| WHO grade I | 2.54 | 0.76-8.52 | .12 |
| MIB-1 >5% | 0.57 | 0.18-1.79 | .3 |
| Simpson grade I-III | 2.49 | 1.05-5.90 | .039 |
| Length of stay >5 d | 0.96 | 0.36-2.56 | .9 |
| Admission—Clinic | 1.93 | 0.94-5.81 | .055 |
| Any complication | 0.22 | 0.03-1.12 | .3 |
95% CI, 95% confidence interval (P < .05); KPS, Karnofsky Performance Scale; OR, odds ratio; WHO, World Health Organization.
The median duration of postoperative follow-up was 5 mo (range 8 d to 6.5 yr) for African-American patients compared with 13 mo (range 6 d to 8.8 yr) for White patients, which approached significance (P = .059; Table 3). Among other racial minorities, the duration of follow-up was comparable with that of White patients: 12 mo (range 8 d to 8.4 yr) for Hispanic patients and 10 mo (range 13 d to 8.6 yr) for Asian patients (Table 2). A total of 55 patients had no postoperative follow-up: 15% of White patients, 22% of African-American patients, 22% Hispanic patients, and 20% of Asian patients. Twenty-nine of 305 patients underwent additional resection, ranging from 5% to 11% of patients between groups (Table 2), which was not statistically significant.
Hospital Course and Resources
The length of stay was increased in minority patients, compared with White patients (average = 4.1 d), with the longest observed duration of 6.3 d in African-American patients, 5.7 d in Hispanic patients, and 5.7 d in Asian patients (P = .0053, Table 2). Hospitalization costs were almost 1.2-fold higher for minority patients ($31 081-$32 344) than White patients ($26 547), although this did not reach significance in grouped analysis (Table 2). Pairwise comparison between African-American and White patients did demonstrate that the average hospitalization cost was significantly higher in African-American patients, who bore an average cost of $31 204 (P = .046; Table 3).
For insurance type, no significant difference was observed in the grouped analysis by race. However, in pairwise comparison between African Americans and Whites, 54% of African-American patients had public insurance, which included Medicare or Medicaid, compared with only 38% of White patients, which trended toward significance (P = .08, Table 3). In comparison of insurance types alone, patients who had public insurance underwent surgery at an older age, 63.5 yr, compared with 54.7 yr and 49.8 yr in those who were privately insured and self-pay, respectively (P < .0001; Table 5). The length of stay was longer in patients who were publicly insured, with an average duration of 6.0 d compared with 4.2 d for privately insured patients and 5.25 d in those who were self-pay (P = .01; Table 5). Hospital complications and 30-d readmission rates did not significantly differ between groups (Table 2).
TABLE 5.
Univariate Analysis of Clinical and Demographic Parameters Between Insurance Groups
| Clinical variables | Private n = 152 |
Public n = 108 |
Self-pay n = 4 |
P value |
|---|---|---|---|---|
| Age at surgery (yr) | <.0001 | |||
| Mean | 54.7 | 63.5 | 49.8 | |
| SD | 12.1 | 13.2 | 21.6 | |
| Source of admission | .1 | |||
| Clinic | 127 (84%) | 82 (76%) | 2 (50%) | |
| ER | 25 (16%) | 26 (24%) | 2 (50%) | |
| History of previous radiation | .063 | |||
| Yes | 5 (3%) | 11 (10%) | 0 (0%) | |
| No | 147 (97%) | 97 (90%) | 4 (100%) | |
| Length of stay | .011 | |||
| Mean | 4.166 | 6.009 | 5.25 | |
| SD | 4.438 | 5.328 | 4.193 | |
| KPS | .0006 | |||
| Mean | 80.6 | 76.3 | 65 | |
| SD | 9.254 | 12.94 | 23.8 | |
| Tumor size | .079 | |||
| Mean | 3.544 | 3.799 | 5.225 | |
| SD | 1.542 | 1.731 | 1.864 | |
| Hospital complications | .55 | |||
| Yes | 27 (18%) | 25 (23%) | 1 (25%) | |
| No | 125 (82%) | 83 (77%) | 3 (75%) | |
| Readmission within 30 d | .072 | |||
| Yes | 10 (6%) | 16 (15%) | 0 (0%) | |
| No | 142 (93%) | 92 (85%) | 4 (100%) | |
| WHO grade | .6 | |||
| 1 | 136 (89%) | 92 (85%) | 3 (75%) | |
| 2 | 15 (10%) | 16 (15%) | 1 (25%) | |
| 3 | 1 (1%) | 0 (0%) | 0 (0%) | |
| Adjuvant radiation | .91 | |||
| Yes | 12 (8%) | 8 (7%) | 0 (0%) | |
| No | 140 (92%) | 100 (93%) | 4 (100%) | |
| Additional surgical resection | .80 | |||
| Yes | 15 (10%) | 10 (9%) | 0 (0%) | |
| No | 137 (90%) | 98 (91%) | 4 (100%) | |
| Hospitalization cost | .31 | |||
| Mean | 27 524 | 30 647 | 23 107 | |
| SD | 15 851 | 21 400 | 5 422 | |
| Postoperative follow-up (mo) | .48 | |||
| Median | 8 | 10 | 3 | |
| Range | 0.20-78 | 0.30-88 | 0.87-12 | |
| SEM | 49.9 | 60.5 | 109 |
KPS, Karnofsky Performance Score; SD, standard deviation; SEM, standard error of the mean; WHO, World Health Organization.
DISCUSSION
Current literature indicates that healthcare disparities exist that affect the management and outcomes of numerous medical conditions. Minority patients have disproportionately higher mortality rates in cancer and cardiac, cerebrovascular, and renal disease and less frequently receive standard-of-care treatment for these conditions.3,19 There are limited data available characterizing the effect of race on clinical outcomes and treatment paradigms in patients with meningioma. Although studies using consensus data from CBTRUS and Surveillance, Epidemiology, and End Results have identified higher meningioma incidence rates within African-American patients,6,18,20 the etiology of this difference remains unclear and these multi-institutional census data introduce biases based on socioeconomical factors rather than the disease itself. Our study provides a large, single tertiary care hospital analysis of sociodemographic, clinical, and histopathological variables between racial populations in a patient cohort with primarily benign, WHO grade I meningiomas.
We identified significant differences between clinical presentation and hospital course between White and minority patients. Minority patients had a lower KPS and were more likely to present through the emergency department. Patients who presented electively through the clinic were more frequently asymptomatic or mildly symptomatic. Comparatively, those presenting through the emergency department were more symptomatic. The more severe clinical presentations correlated with longer hospital stays and higher hospitalization costs for African-American patients. Despite comparable tumor burden, minority patients were more symptomatic on presentation, which may be related to differences in peritumoral edema, because peritumoral edema was observed more frequently in minority patients. However, the area of edema did not significantly differ between groups. This may be due to the smaller subset of patients for analysis; of the full 305 patient cohort, only a total of 132 patients had surrounding edema. A larger number of patients with edema may be necessary for significant differences to be detected. Similar to our findings, previous studies have identified that Hispanic and African-American patients more frequently receive care in hospital emergency departments.3,4,25
Minority patients' increased tendency to present in the emergency setting is likely due in part to healthcare access. Minority patients are more likely to be uninsured, have poorer social determinants of health, are disproportionately enrolled in publicly funded insurance programs, and less frequently have regular primary care providers.3,4,10,25-27 The cost barriers associated with lack of insurance and less ambulatory care likely contribute to the higher emergency department utilization. Sufficient access to health care—particularly advanced neurodiagnostic imaging—is integral to early identification and diagnosis of primary brain tumors.21,22 Impaired healthcare access results in diagnostic delays, which contributes to more advanced disease at time of presentation.
Patients' cultural perspectives may also influence racial disparities. A mistrust of the healthcare system because of historical discriminatory healthcare practices, like the Tuskegee syphilis experiments, may discourage racial minorities from seeking medical care.1,3,6,19 Provider-related factors include implicit biases that influence physician behaviors.1,3,6,19 Poor communication skills, the quantity and quality of information provided to the patient, and subtle racial biases likely contribute to perceived discrimination in racially discordant patient-physician interactions.
Although limited, there is growing evidence that African-American patients have decreased overall survival.11,14,24 We did not identify a difference in progression-free survival in different races, as has been previously reported.14,24 The reported difference in survival outcomes may be due to meningioma subtype. Others have identified decreased survival outcomes in African-American patients with atypical and/or malignant meningiomas,14,24 whereas most meningiomas (87%) within our cohort were WHO grade I.
We also observed a trend toward shorter duration of postoperative follow-up for African-American patients. Poor postoperative follow-up further highlights disparities in subspecialty care documented in the literature.3,4,25 GTR is a well-documented prognostic indicator of improved survival and decreased recurrence rates.8,28-30 Similar to current literature, extent of resection was a predictor of recurrence freedom within our cohort. Aizer et al23 identified that African-American patients were less likely to undergo GTR; this difference in treatment strategy was not reflected in our patient cohort. In our cohort, treatment strategies and recurrence rates did not differ significantly by racial population. This difference compared with the current literature is likely because the institution serves as a tertiary referral center with a well-developed multidisciplinary system for neuro-oncological care.
Previous studies suggested a relationship between race and hospital costs. Mukherjee et al1 identified ∼$20 000 higher total hospitalization charges in African-American patients with meningioma, compared with White patients. This trend was observed in our patient population as well. The higher hospitalization costs are likely in part due to more advanced clinical disease as evidenced by lower overall KPS. We also found that African-American patients were more likely to be publicly insured compared with White patients, which is consistent with current literature.16,24 Patients who were publicly insured underwent surgery at an older age and had longer length of stay, highlighting the impact of socioeconomic status on clinical outcomes. The threshold for advanced diagnostic imaging may be lower for patients with superior insurance coverage, compared with those subjected to higher out-of-pocket costs, potentially contributing to diagnostic delays.22
Limitations
Further research efforts are warranted to evaluate tumor characteristics within different racial populations that may contribute to differences in clinical presentation. Although histopathological characteristics were similar, more detailed genomic analysis may elucidate genetic and/or molecular markers associated with different racial groups. Limitations in our study include inferior level of evidence compared with prospective studies and potential misclassification because of interobserver differences. Although a number of patients were followed up to 6 to 8 yr postoperatively, the median duration across racial groups was shorter, ranging from 5 to 13 mo. A median follow-up of this duration may be too short to detect differences in slow-growing tumor, such as meningiomas. Longer follow-up may be necessary to observe survival differences. Understanding the genomic profiles of meningiomas in different racial groups may identify potential etiologies underlying the higher incidence in African Americans. An examination of income and other socioeconomic data may further identify financial barriers affecting access to care.
CONCLUSION
This study demonstrates that race/ethnicity influences severity of clinical presentation, length of hospital stay, and hospitalization costs for patients with meningioma undergoing surgical resection. These findings highlight important racial disparities in the overall clinical course of patients with meningioma. Sociodemographic factors, including insurance coverage, may affect healthcare accessibility, diagnostic imaging workup, and stage at diagnosis. Identification of the factors contributing to observed racial/ethnic disparities is critical to adequately deploy resources addressing barriers to care. Additional work is necessary to better identify and target barriers to access to subspecialty care and to ensure that patients receive the diagnoses and treatments they need to achieve optimal care and outcomes.
Minority patients report higher overall satisfaction when receiving care from minority physicians.3
Acknowledgments
We thank Emily Schaffer for her insightful comments on the manuscript.
Funding
Portions of this study were funded by the Roderick D. MacDonald Fund and the Jan and Dan Duncan Neurologic Research Institute at Texas Children's Hospital.
Disclosures
The authors have no personal, financial, or institutional interest in any of the drugs, materials, or devices described in this article. Dr Patel is supported by a K08 award from the National Institute of Neurological Disorders and Stroke (K08NS102474).
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