Meningioma Characteristics Influencing Overall Survival by Race and Ethnicity

Meningioma Characteristics Influencing Overall Survival by Race and Ethnicity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Meningioma Characteristics Influencing Overall Survival by Race and Ethnicity Alper Dincer, Joanna Tabor, Alexandros Pappajohn, Haoyi Lei, Miri Kim, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3834926/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background There are known racial and ethnic disparities affecting overall survival (OS) in meningiomas. This has largely been presumed to be due to differences in socioeconomic status (SES). However, there are conflicting studies that demonstrate better survival for Hispanic compared to Black populations, two groups with similar SES. Thus, we hypothesize additional underlying factors, including tumor biology, may differ amongst race and influence OS of patients with meningioma. Methods We queried the NCDB for patients with pathology-confirmed meningiomas from 2012-2020. Race and ethnicity were self-reported and grouped into White, Hispanic White, Black, Hispanic Black, and Asian categories. Logistic regression analyses were performed to determine tumor and patient characteristics associated with race and Cox hazards model was performed on these characteristics to determine influence on OS. Results We included 85,244 patients in this study. Black patients have worse OS compared to White patients. Black patients were also more likely to harbor higher grade tumors and undergo subtotal resection compared to White patients. Hispanic White patients had improved overall survival (P<0.0001) with less higher-grade tumors (P=0.0051) compared to White patients. There was no difference in overall survival for Hispanic Black patients (P=0.49) despite being more likely to have higher grade tumors (P=0.0164). Conclusions Differences in meningioma biology may contribute to the differences in OS seen in racial groups beyond SES. Black patients are a particularly vulnerable group as they tend to harbor higher-grade tumors and undergo less aggressive surgical resections. Further studies are necessary to determine possible differences in underlying biology. meningioma race overall survival socioeconomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Racial and ethnic disparities affecting outcomes amongst patients with various types of neoplasms is a widely described phenomenon and has been studied in meningiomas. Indeed, studies have shown Black patients undergoing resection of a meningioma have worse overall survival (OS) compared to White patients. 1–4 The causality of these disparities is not well described and has been presumed to be related to socioeconomic status (SES). 2,5,6 However, Hispanic patients have similar or improved OS compared to White patients. 7 Given that the Hispanic population has been noted to have similar SES compared to Blacks, it suggests other factors, perhaps related to differences in tumor biology amongst races and ethnicities, may contribute to the disparities observed in OS after meningioma resection. In several types of neoplasms, including gliomas, race has been found to be associated with differences in tumor grade, severity, and genetic mutations. 8–14 In meningiomas, it has been shown that Black patients are more likely to have higher grade and larger tumors on presentation , 2 suggesting there may be racial differences in tumor behavior. However, large-scale studies investigating post-surgical OS have primarily focused on race associations with SES, creating a paucity of data reporting associations between race, ethnicity, and tumor characteristics. Additionally, the Hispanic population, which is made up of a complex and heterogenous group of White, Black, and other races, are typically grouped together, further limiting our understanding of racial disparities and how tumor behavior may differ between racial and ethnic groups. This is further complicated by the subjective nature and fluidity in the definitions of self-reported race and ethnicity, which can often have significant cultural and geographic influences. To better understand the potential differences in tumor characteristics between racial groups and possible influence on OS, we utilized a large national database to compare tumor biology and OS by racial and ethnic group. Importantly, we separated Hispanic population into Hispanic White and Hispanic Black to better understand the influence of underlying race in this population, which has not been previously analyzed in the literature. We hypothesized that Black and Hispanic Black patients more commonly harbor more aggressive meningiomas compared to White and Hispanic White patients. In each racial category, we predicted an interplay between tumor characteristics and SES will likely dictate OS. METHODS Data Source The National Cancer Database (NCDB) is a national tumor registry founded as a joint project by the American Cancer Society and the American College of Surgeons’ Commission on Cancer. The database includes more than 1,500 approved cancer facilities and represents 70% of all newly diagnosed cancers in the United States. The database provides information for the analysis on patterns of care and patient outcomes. The de-identified data includes patient demographics, tumor staging, treatment types, postoperative mortality and complications. Patient zip code data includes percent without a high school degree and median income. Patient Selection The NCDB was queried for patients diagnosed with central nervous system tumors between 2012 and 2020. Those with a histologic code corresponding to meningiomas (histology codes 9530, 9539, 9531, 9537, 9532, 9533, 9534, 9538, 9150, 9535) were included (Fig. 1 ). Patients were excluded for: age < 18 years old, missing variables (surgical procedure, extent of resection, WHO grade), extracranial location, and unconfirmed pathologic diagnosis. This study was exempt from the Institutional Review Board (IRB) approval as only de-identified data were received and analyzed. Patient Population Race was self-reported and grouped into “White,” “Black,” and “Asian”. Ethnicity was self-reported and defined as Hispanic or non-Hispanic. We created a combined Ethnicity/Race classification to account for the heterogenous population of patients reporting Hispanic ethnicity as such: non-Hispanic White (White), non-Hispanic Black (Black), non-Hispanic/Asian (Asian), Hispanic White, and Hispanic Black. In addition to self-reported race and ethnicity, we collected data for: age at surgery, gender, facility type (academic versus non-academic), World Health Organization (WHO) tumor grade (WHO grade 1 meningioma [low-grade], WHO grade 2 and 3 meningiomas [high-grade]), extent of resection (coded subtotal resection [STR], or gross total resection [GTR] based on the codes provided for the “Surgery at Primary Site” variable. STR included codes 20 [local excision or excisional biopsy], 21 [subtotal resection], and 40 [partial resection of the lobe of the brain when surgery cannot be coded as 20–30]. GTR included codes 30 [radical, total, gross resection of the tumor], and 55 [GTR of a lobe of the brain], consistent with prior studies 8 ), tumor diameter (small [1-3.5cm], moderate [3.5-6.3cm], and large [ ≥ 6.4cm] as determined by partition analysis optimized for effect on mortality), and length of hospital stay. In an effort to obtain insight into SES and SDOH, we also collected data for: percent of population without high school diploma quartile by zip code (1st quartile < 14.0%; 2nd quartile 14.0-19.9%; 3rd quartile 20.0-28.9%; 4th quartile ≥ 29.0%), median income quartile by zip code 1st quartile ≥ $ 74,063; 2nd quartile $ 57,857 − 74,062; 3rd quartile $ 46,277 − 57,856; 4th quartile ≤ $ 46,277), insurance status (no insurance, government, private, and other), facility location (metro, urban, rural), and patient distance from facility. Statistical Analysis The primary outcome of interest was all-cause OS. Statistical analyses were performed using JMP Pro (Version 17.0.0, 2021 SAS Institute Inc.). Continuous and categorical variables were summarized by means and standard deviations and frequencies and percentages, respectively. Differences between normally and non-normally distributed continuous variables were compared using Welch’s t-tests and Wilcoxon rank sum tests, respectively. χ 2 test or Fishers exact test, when necessary due to limited sample sizes, were used to evaluate categorical variables. All analysis involving associations of race used White patients as the reference variable. The Cox proportional hazards model was used to determine contributors to OS based on age, gender, race, facility type, WHO grade, tumor diameter, extent of resection, high school diploma quartile, median quartile, and length of hospital stay. A univariate analysis was performed and factors that had a p-value < 0.15 were included in the multivariate hazards model. A binary logistical regression was used to determine the association between race and several other factors including gender, facility type, high grade tumor, extent of resection, tumor diameter, high school diploma quartile, and median income quartile. A univariate logistic regression was performed first, and a factor was then included in the multivariate model if the p-value was ≤ 0.15. Statistical significance was defined as p < 0.05; all statistical tests were two-sided. RESULTS Patient Characteristics We found 366,987 patients with a presumed meningioma in the NCDB from 2012–2020 (Fig. 1 ). We excluded a total of 281,743 patients due to unconfirmed histologic diagnosis, age < 18 years old, extracranial tumor location, incomplete racial information or other missing relevant variables. Our final cohort included 85,244 patients. Table 1 demonstrates the distribution of patient and tumor characteristics by patient race. The average age for the cohort was 58 years (SD 13) and the majority of patients were White (74%), followed by Black (13.5%), Hispanic White (6.9%), Hispanic Black (0.16%), and Asian (4.2%) (Fig. 2 ). Table 1 Patient and tumor characteristics comparisons based on race. *symbol denotes statistical significance between racial groups with a P-value < 0.0001. Patient & Tumor Characteristics All White Black Hispanic White Hispanic Black Asian p-value N 100% 74.2% 13.5% 6.9% 0.16% 4.2% Age 58 (13) 59 (13) 56 (13) 54 (14) 55 (14) 57 (13) * Sex * Male 31.3% 32.1% 29.6% 29.3% 26.1% 28.2% Female 68.7% 67.9% 70.4% 70.7% 73.9% 71.8% Facility Type Academic 50.2% 48.6% 55.8% 51.1% 61.3% 52.5% Non-Academic 49.8% 51.4% 44.3% 48.9% 38.7% 47.5% No High School Diploma * 1st Quartile 21.6% 26.4% 8.3% 7.7% 5.0% 23.9% 2nd Quartile 27.5% 31.8% 20.1% 14.9% 10.9% 25.6% 3rd Quartile 28.6% 27.1% 35.2% 21.9% 27.7% 23.0% 4th Quartile 22.3% 14.7% 36.4% 55.6% 56.3% 27.6% Median Income * 1st Quartile 16.3% 41.8% 21.0% 28.3% 25.2% 60.0% 2nd Quartile 20.9% 24.9% 19.2% 26.2% 14.3% 19.9% 3rd Quartile 23.9% 21.2% 22.9% 21.2% 31.1% 12.2% 4th Quartile 38.9% 12.2% 36.9% 24.3% 29.4% 7.9% Insurance Status * No Insurance 3.9% 2.5% 6.7% 12.5% 5.2% 4.2% Private 48.9% 50.8% 42.6% 41.1% 35.1% 51.6% Government 45.8% 45.5% 49.3% 45.0% 58.2% 43.0% Other 1.3% 1.2% 1.5% 1.4% 1.5% 1.2% Location * Metro 85.3% 82.5% 90.9% 93.6% 97.8% 96.9% Urban 13.1% 15.6% 8.1% 6.0% 2.2% 2.5% Rural 1.61% 1.9% 1.0% 0.4% 0.0% 0.6% Distance from Hospital (miles) 45.9 50 (147) 28 (86) 30 (78) 13 (29) 39 (217) * Length of Stay (days) 5.2 4 (6) 6 (9) 5 (7) 6 (7) 5 (6) * WHO Grade * 1 78.6% 79.2% 75.3% 81.1% 68.0% 76.5% 2 19.3% 18.8% 22.8% 17.0% 28.2% 21.8% 3 2.0% 2.1% 1.9% 1.9% 3.9% 1.7% Extent of Resection * STR 40.9% 39.9% 44.2% 44.3% 52.2% 41.2% GTR 59.1% 55.8% 55.7% 47.8% 56.3% 55.8% Tumor Size (mm) 1–34 40.7% 41.3% 38.5% 40.4% 41.9% 34.7% 35–63 48.7% 48.3% 49.7% 50.2% 53.5% 52.6% >64 10.7% 10.4% 11.8% 9.4% 4.7% 12.7% * Hispanic Black, Hispanic White, and Black patients were more likely to have no health insurance, live in the lowest median income zip codes, and live in zip codes with the highest proportion of people without a high school diploma (Table 1 ). Hispanic Black patients had the highest proportion of WHO grade 2 (28.2%) and 3 meningiomas (3.9%), followed by Black patients with slightly less WHO grade 2 (22.8%) and grade 3 meningiomas (1.9%) (Fig. 3 ). Hispanic Black patients also had the highest rate of STR (52.2%). Moderate-sized tumors (3.5-6.4cm) were more likely to occur in Hispanic Black patients (53.5%) and large tumors (greater than 6.4cm) were more often encountered in Black patients (11.8%). Factors Influencing Overall Survival Among the racial groups, only Black patients had a worse OS compared to White patients (HR 1.3; P < 0.0001) (Fig. 4 , Fig. 5 ). Hispanic White (HR 0.82; P = 0.012) and Asian (HR 0.71; P 70 years) (HR 1.07, P < 0.0001) and male sex (HR 1.5, p = < 0.0001) (Fig. 4 ). Several tumor characteristics were similarly associated with worse OS including WHO grade 2 (HR 1.5; P < 0.001) and grade 3 meningiomas (HR 3.7; P < 0.0001), moderate-sized tumors (HR 1.15; P = < 0.0001), and large tumors (HR 1.33; P < 0.0001), and subtotal resection (HR 1.13; P < 0.0001). Socioeconomic factors influencing worse OS included nonacademic facility type (HR 1.29; P < 0.0001), lack of health insurance (HR 1.5; P < 0.0001), government health insurance (HR 1.5; P < 0.0001), lower median income quartile (HR 1.3; P < 0.015), and lowest quartile for no high school diploma (HR 1.1; P = 0.016) (Fig. 4 ). Association of Race and Factors influencing Overall Survival Given the patient distribution, we used White patients as the reference group for all subsequent analyses we performed to understand the possible relationship between race and factors influencing OS. Moreover, we included only those variables that were significantly correlated to OS in these analyses. We found Black patients were more likely to have higher-grade tumors (WHO grade 2 and 3 meningiomas) (OR 1.24; P < 0.0001) (Fig. 4 ) large tumors (OR 1.14; P < 0.0048) and more likely to undergo STR (OR 1.18; P < 0.0001). Black patients also had several associated low SES factors, including lack of health insurance (OR 3.18; P < 0.0001) and living in disparate areas with low education (OR 3.3; P < 0.0001) and lower median income (OR 4.2; P < 0.0001). While Black patients were less likely to be male (OR 0.88, P 70 years old (OR 0.66; P < 0.0001), and present to non-academic facilities (OR 0.75; P < 0.0001). Hispanic White patients were more likely to have lower grade meningiomas (OR 0.87; P = 0.005) compared to White patients (Fig. 3 ). However, these patients had a higher likelihood of STR (OR 1.19; P < 0.0001). Hispanic White patients were more likely to lack health insurance (OR 6.2; P < 0.0001) and live in regions with the low education (OR 7.3; P < 0.0001) and low median income (OR 2.32 P < 0.0001). There was no difference in OS for Hispanic Black patients (HR 0.70; P = 0.49) compared to White patients, despite the increased likelihood of higher-grade tumors (OR 1.79; P = 0.0164) and subtotal resection (OR 1.64; P = 0.004) in Hispanic Black patients. There were no differences in frequency of large tumors (OR 0.42; P = 0.23). Hispanic Black patients were also more likely to lack health insurance (OR 3.0; P = 0.007) and live in regions with low education (OR 7.5; P < 0.0001) and low median income (OR 3.0; P < 0.0001). Asian patients with a meningioma had better OS compared to White patients (HR 0.71; P = 0.0001) despite being more likely to have higher grade tumors (OR 1.22; P = 0.0023) and large tumor size (OR 1.25; P = 0.0051). Asian patients were the only race to not have an increased likelihood of STR (P = 0.14). Additionally, they uniquely were more likely to have health insurance (OR 0.60; P < 0.0001) and not live areas with the lowest median income (OR 0.62; P < 0.0001). DISCUSSION There are known racial disparities affecting OS in patients with meningiomas and it has been presumed these are likely due to differences in SES. However, differences remain in outcome in racial and ethnic groups of similar SES, suggesting that other underlying factors may also contribute. To our knowledge, this is the first study to demonstrate differences in tumor and patient characteristics associated with OS within each racial and ethnic group beyond SES. Overall, we found that combinations of tumor characteristics and SES influence OS in a race-specific manner (Fig. 6 ). White, Hispanic Black, and Black patients were likely to have both aggressive tumor features and low SES that influence OS. Hispanic White patients were mostly influenced by low SES and were less likely to have aggressive tumor features, whereas Asian patients had aggressive tumor features and higher SES (Fig. 6 ). We found Black patients are seemingly the most vulnerable population of patients, with a more aggressive tumors and lower SES. Black patients are more likely to have higher grade meningiomas and to undergo STR, both of which are known contributors to worse OS, which is also reflected in our results. 9,10 Additionally, they are more likely to lack health insurance and live in areas with a lower median income and education level. Although limited access to hospital facilities has been previously reported for Black patients, 4,11,12 our study demonstrates that the Black population can access academic facilities similar to other groups. While SES-related factors can undeniably contribute to poor outcomes, the finding of a higher prevalence of high-grade tumors and higher occurrence of STR among Black patients with meningioma is alarming This finding can potentially help raise awareness for opportunities to improve care for this patient population. The Hispanic population is unique in that it represents a heterogenous group of individuals with admixture of genetic ancestry. 13 Hispanic ethnicity is independent of race and encompasses a population who may also identify and self-report with different races, such as White, Black, or Asian. The heterogeneity of this population can likely account for some of the conflicting results thus far in the literature demonstrating either no difference or improved OS for Hispanic patients with meningiomas. 7,14–16 We subclassified Hispanic ethnicity into Hispanic White and Hispanic Black to account for this admixture and its potential influence on outcome. Hispanic White populations have significantly improved OS compared to White populations. Interestingly, the improved OS in the Hispanic White population was seemingly independent of socioeconomic factors that could contribute to worsened OS. Indeed, they tended to have a younger age of presentation, lower grade tumors, and be of female sex. This is consistent with the “Hispanic Paradox” that has been well established in the medical literature, even beyond that of brain tumors (citations). Unfortunately, Black and Hispanic patients have also been reported to receive substandard care with less extensive resections, 17–20 which is reflected in our results as well. Similar to Black patients, we found an increased likelihood of higher-grade tumors among the Hispanic Black population that may contribute to worse OS. These findings underscore the need for more specific distinctions in future studies investigating race, ethnicity and outcome, as Hispanic patients in particular cannot simply be grouped together in the same category without significant limitations. Interestingly, our findings centered around the Asian population may perhaps exemplify the potential positive influence of SES on outcome for patients with meningioma. Indeed we found improved OS for Asians with meningiomas, consistent with prior studies that have shown either no difference or improved OS compared to White patients. 7,11,21,22 While we found Asian patients were more likely to have higher grade and larger meningiomas, Asian patients was more likely to have private health insurance and less likely to live in impoverished areas. Asian patients were also the least likely to undergo STR, and thus perhaps the SES and SDOH factors may have helped contribute to an improved OS. Our findings demonstrate a clear racial disparity in meningioma aggressiveness amongst certain racial/ethnic populations and potential OS implications to form the basis for further investigations with genetic ancestry. To date, there have been no studies focused on elucidating the association between potential underlying genetic and epigenetic factors and tumor biology and behavior. However, these relationships have been well-studied in other tumors. Race-specific driver mutations have been identified in lung, breast, prostate, and colorectal cancer (PMID 34994651). 23 Glial tumors in the Hispanic White and non-Hispanic White patients were more likely to have EGFR expression, whereas Asian-American patients were more likely to have a p53-pathway mutations and these differences can have significant implications in outcome and patient-centered interventions. 24 Further studies are necessary to determine the underlying genomic influences that may be associated in the differences we observed in this study. LIMITATIONS Our results warrant careful interpretation in the context of the study limitations. The NCDB is a national database, and with potential for selection bias related to non-randomized participation of certain institutions over others. Additionally, there is a certain crudeness in the reported variables in NCDB. Most relevant, our primary outcome, OS, is an “all-cause mortality” and does not distinguish non-meningioma related death to meningioma-related death. This is further compromised by the fact that NCDB does not offer recurrence data which could have been useful in interpreting outcome. The known differences in the average life-expectancy between racial and ethnic groups, such that Asians have the highest life expectancy, followed by Hispanic, White, and Black populations, 25 could not be accounted for in our study. Additionally, several SES factors, such as median income and high school diploma percentages, were inferred from zip code. CONCLUSION There are racial differences in tumor and patient factors that influence overall survival for patients with meningiomas. Black patients appear particularly vulnerable, as they are more likely to harbor large, higher-grade meningiomas, undergo less aggressive surgical resections, and low socioeconomic status. Hispanic patients have distinct findings depending on whether they identify as White or Black race and this should be accounted for in any race and ethnicity meningioma study. Asian patients, despite being more likely to have higher grade meningiomas and larger meningiomas, have improved SES which may confer a survival benefit. Further studies are necessary to understand the possible difference in genetic ancestry that may influence tumor biology and overall survival of patients with meningioma. Declarations Conflict of Interest: JM: Consultant, BK Medical; Consultant, Stryker Funding: none Previous presentations: none Author Contribution Conceptualization: A.D. and J.M.; Data curation: A.D.; Formal analysis: A.D.; Investigation: A.D.; Methodology: A.D. and J.M.; Project administration: J.M.; Resources: J.M.; Supervision: J.M.; Validation: A.D. and J.M.; Writing – original draft: J.T., A.P., H.L., M.K. and J.M.; Writing - review & editing: J.T., A.P., H.L., M.K. and J.M.; References Lei H, Tabor JK, O’Brien J, et al. Associations of race and socioeconomic status with outcomes after intracranial meningioma resection: a systematic review and meta-analysis. J Neurooncol . 2023;163(3):529-539. doi:10.1007/s11060-023-04393-5 Jackson HN, Hadley CC, Khan AB, et al. Racial and Socioeconomic Disparities in Patients With Meningioma: A Retrospective Cohort Study. Neurosurgery . 2022;90(1):114-123. doi:10.1227/NEU.0000000000001751 Curry WT, Carter BS, Barker FG. 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Racial and socioeconomic correlates of treatment and survival among patients with meningioma: a population-based study. J Neurooncol . 2020;147(2):495-501. doi:10.1007/s11060-020-03455-2 Garzon-Muvdi T, Yang W, Lim M, Brem H, Huang J. Atypical and anaplastic meningioma: outcomes in a population based study. J Neurooncol . 2017;133(2):321-330. doi:10.1007/s11060-017-2436-6 Kamran SC, Xie J, Cheung ATM, et al. Tumor Mutations Across Racial Groups in a Real-World Data Registry. JCO Precis Oncol . 2021;5:1654-1658. doi:10.1200/PO.21.00340 Wiencke JK, Aldape K, McMillan A, et al. Molecular features of adult glioma associated with patient race/ethnicity, age, and a polymorphism in O6-methylguanine-DNA-methyltransferase. Cancer Epidemiol Biomarkers Prev . 2005;14(7):1774-1783. doi:10.1158/1055-9965.EPI-05-0089 GBD US Health Disparities Collaborators. Life expectancy by county, race, and ethnicity in the USA, 2000-19: a systematic analysis of health disparities. Lancet . 2022;400(10345):25-38. doi:10.1016/S0140-6736(22)00876-5 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3834926","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":265391020,"identity":"8d3536b9-2aeb-4006-b447-d3c93c5a44ca","order_by":0,"name":"Alper Dincer","email":"","orcid":"","institution":"Tufts Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Alper","middleName":"","lastName":"Dincer","suffix":""},{"id":265391021,"identity":"bb7b1402-454f-4a4c-a8b8-3dd66279deda","order_by":1,"name":"Joanna Tabor","email":"","orcid":"","institution":"Yale New Haven Hospital","correspondingAuthor":false,"prefix":"","firstName":"Joanna","middleName":"","lastName":"Tabor","suffix":""},{"id":265391022,"identity":"19c00b91-ad58-4430-a1c9-f1fe507700cb","order_by":2,"name":"Alexandros Pappajohn","email":"","orcid":"","institution":"Yale New Haven Hospital","correspondingAuthor":false,"prefix":"","firstName":"Alexandros","middleName":"","lastName":"Pappajohn","suffix":""},{"id":265391023,"identity":"73fcc6b7-2ec3-4ebf-aef0-96c05e60a381","order_by":3,"name":"Haoyi Lei","email":"","orcid":"","institution":"Yale New Haven Hospital","correspondingAuthor":false,"prefix":"","firstName":"Haoyi","middleName":"","lastName":"Lei","suffix":""},{"id":265391024,"identity":"c57d3e63-8cd2-419b-b109-04f8965a7ee7","order_by":4,"name":"Miri Kim","email":"","orcid":"","institution":"Yale New Haven Hospital","correspondingAuthor":false,"prefix":"","firstName":"Miri","middleName":"","lastName":"Kim","suffix":""},{"id":265391025,"identity":"296c6c98-cb1b-4c11-9b17-3b7d5a94e27f","order_by":5,"name":"Jennifer Moliterno","email":"data:image/png;base64,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","orcid":"","institution":"Yale New Haven Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jennifer","middleName":"","lastName":"Moliterno","suffix":""}],"badges":[],"createdAt":"2024-01-04 15:59:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3834926/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3834926/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49326218,"identity":"12c5a1f5-0255-450d-aa50-9dc7d9c00017","added_by":"auto","created_at":"2024-01-08 17:30:51","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":93175,"visible":true,"origin":"","legend":"\u003cp\u003eInclusion and exclusion criteria for current study using the National Cancer Database.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3834926/v1/2687c419ed92a5ff4b16da2f.jpg"},{"id":49327374,"identity":"c2e9b93f-aeed-40eb-822f-dac181bcf2ad","added_by":"auto","created_at":"2024-01-08 17:38:51","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":43395,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of patients by race and ethnicity. Total count is provided within the chart.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3834926/v1/060d1ae754fcbc1789adf579.jpg"},{"id":49326223,"identity":"b41d806e-6c11-4037-b8f1-43d390d9a591","added_by":"auto","created_at":"2024-01-08 17:30:51","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":47318,"visible":true,"origin":"","legend":"\u003cp\u003eBar graph of percent WHO grade meningiomas by race and ethnicity. Race/ethnicity ordered by increasing percent high grade meningioma.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3834926/v1/6b49f7e94b02c8f287ce9879.jpg"},{"id":49326220,"identity":"58e8ce4a-6c23-4c05-bd96-56c14da45917","added_by":"auto","created_at":"2024-01-08 17:30:51","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":140052,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of hazard ratios for patient, socioeconomic, and tumor factors associated with overall survival.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3834926/v1/abd245cda265c4c6fa1a2b23.jpg"},{"id":49327375,"identity":"1c1861a4-2b41-49db-9d93-d20ce901ac6d","added_by":"auto","created_at":"2024-01-08 17:38:51","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":41172,"visible":true,"origin":"","legend":"\u003cp\u003eOverall survival by race/ethnicity.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3834926/v1/69566842a834aaf8121fa6f8.jpg"},{"id":49326222,"identity":"56efef69-cec4-4070-9f2c-3ece6f0d3fe6","added_by":"auto","created_at":"2024-01-08 17:30:51","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":55897,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTumor and socioeconomic factors influencing survival outcome.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3834926/v1/59e5139682375b28cc2b52ac.jpg"},{"id":49942597,"identity":"217cce2b-b241-445a-8b3c-e44f14ade856","added_by":"auto","created_at":"2024-01-22 03:07:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":664712,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3834926/v1/7db95e79-97db-4a12-9608-e34789309713.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Meningioma Characteristics Influencing Overall Survival by Race and Ethnicity","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eRacial and ethnic disparities affecting outcomes amongst patients with various types of neoplasms is a widely described phenomenon and has been studied in meningiomas. Indeed, studies have shown Black patients undergoing resection of a meningioma have worse overall survival (OS) compared to White patients.\u003csup\u003e1\u0026ndash;4\u003c/sup\u003e The causality of these disparities is not well described and has been presumed to be related to socioeconomic status (SES).\u003csup\u003e2,5,6\u003c/sup\u003e However, Hispanic patients have similar or improved OS compared to White patients.\u003csup\u003e7\u003c/sup\u003e Given that the Hispanic population has been noted to have similar SES compared to Blacks, it suggests other factors, perhaps related to differences in tumor biology amongst races and ethnicities, may contribute to the disparities observed in OS after meningioma resection.\u003c/p\u003e \u003cp\u003eIn several types of neoplasms, including gliomas, race has been found to be associated with differences in tumor grade, severity, and genetic mutations.\u003csup\u003e8\u0026ndash;14\u003c/sup\u003e In meningiomas, it has been shown that Black patients are more likely to have higher grade and larger tumors on presentation ,\u003csup\u003e2\u003c/sup\u003e suggesting there may be racial differences in tumor behavior. However, large-scale studies investigating post-surgical OS have primarily focused on race associations with SES, creating a paucity of data reporting associations between race, ethnicity, and tumor characteristics. Additionally, the Hispanic population, which is made up of a complex and heterogenous group of White, Black, and other races, are typically grouped together, further limiting our understanding of racial disparities and how tumor behavior may differ between racial and ethnic groups. This is further complicated by the subjective nature and fluidity in the definitions of self-reported race and ethnicity, which can often have significant cultural and geographic influences.\u003c/p\u003e \u003cp\u003eTo better understand the potential differences in tumor characteristics between racial groups and possible influence on OS, we utilized a large national database to compare tumor biology and OS by racial and ethnic group. Importantly, we separated Hispanic population into Hispanic White and Hispanic Black to better understand the influence of underlying race in this population, which has not been previously analyzed in the literature. We hypothesized that Black and Hispanic Black patients more commonly harbor more aggressive meningiomas compared to White and Hispanic White patients. In each racial category, we predicted an interplay between tumor characteristics and SES will likely dictate OS.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source\u003c/h2\u003e \u003cp\u003eThe National Cancer Database (NCDB) is a national tumor registry founded as a joint project by the American Cancer Society and the American College of Surgeons\u0026rsquo; Commission on Cancer. The database includes more than 1,500 approved cancer facilities and represents 70% of all newly diagnosed cancers in the United States. The database provides information for the analysis on patterns of care and patient outcomes. The de-identified data includes patient demographics, tumor staging, treatment types, postoperative mortality and complications. Patient zip code data includes percent without a high school degree and median income.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePatient Selection\u003c/h2\u003e \u003cp\u003eThe NCDB was queried for patients diagnosed with central nervous system tumors between 2012 and 2020. Those with a histologic code corresponding to meningiomas (histology codes 9530, 9539, 9531, 9537, 9532, 9533, 9534, 9538, 9150, 9535) were included (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Patients were excluded for: age\u0026thinsp;\u0026lt;\u0026thinsp;18 years old, missing variables (surgical procedure, extent of resection, WHO grade), extracranial location, and unconfirmed pathologic diagnosis. This study was exempt from the Institutional Review Board (IRB) approval as only de-identified data were received and analyzed.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003ePatient Population\u003c/h2\u003e \u003cp\u003eRace was self-reported and grouped into \u0026ldquo;White,\u0026rdquo; \u0026ldquo;Black,\u0026rdquo; and \u0026ldquo;Asian\u0026rdquo;. Ethnicity was self-reported and defined as Hispanic or non-Hispanic. We created a combined Ethnicity/Race classification to account for the heterogenous population of patients reporting Hispanic ethnicity as such: non-Hispanic White (White), non-Hispanic Black (Black), non-Hispanic/Asian (Asian), Hispanic White, and Hispanic Black.\u003c/p\u003e \u003cp\u003e In addition to self-reported race and ethnicity, we collected data for: age at surgery, gender, facility type (academic versus non-academic), World Health Organization (WHO) tumor grade (WHO grade 1 meningioma [low-grade], WHO grade 2 and 3 meningiomas [high-grade]), extent of resection (coded subtotal resection [STR], or gross total resection [GTR] based on the codes provided for the \u0026ldquo;Surgery at Primary Site\u0026rdquo; variable. STR included codes 20 [local excision or excisional biopsy], 21 [subtotal resection], and 40 [partial resection of the lobe of the brain when surgery cannot be coded as 20\u0026ndash;30]. GTR included codes 30 [radical, total, gross resection of the tumor], and 55 [GTR of a lobe of the brain], consistent with prior studies\u003csup\u003e8\u003c/sup\u003e), tumor diameter (small [1-3.5cm], moderate [3.5-6.3cm], and large [\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;6.4cm] as determined by partition analysis optimized for effect on mortality), and length of hospital stay.\u003c/p\u003e \u003cp\u003eIn an effort to obtain insight into SES and SDOH, we also collected data for: percent of population without high school diploma quartile by zip code (1st quartile\u0026thinsp;\u0026lt;\u0026thinsp;14.0%; 2nd quartile 14.0-19.9%; 3rd quartile 20.0-28.9%; 4th quartile\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;29.0%), median income quartile by zip code 1st quartile \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u003cspan\u003e$\u003c/span\u003e74,063; 2nd quartile \u003cspan\u003e$\u003c/span\u003e57,857\u0026thinsp;\u0026minus;\u0026thinsp;74,062; 3rd quartile \u003cspan\u003e$\u003c/span\u003e46,277\u0026thinsp;\u0026minus;\u0026thinsp;57,856; 4th quartile \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u003cspan\u003e$\u003c/span\u003e46,277), insurance status (no insurance, government, private, and other), facility location (metro, urban, rural), and patient distance from facility.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThe primary outcome of interest was all-cause OS. Statistical analyses were performed using JMP Pro (Version 17.0.0, 2021 SAS Institute Inc.). Continuous and categorical variables were summarized by means and standard deviations and frequencies and percentages, respectively. Differences between normally and non-normally distributed continuous variables were compared using Welch\u0026rsquo;s t-tests and Wilcoxon rank sum tests, respectively. χ\u003csup\u003e2\u003c/sup\u003e test or Fishers exact test, when necessary due to limited sample sizes, were used to evaluate categorical variables.\u003c/p\u003e \u003cp\u003eAll analysis involving associations of race used White patients as the reference variable. The Cox proportional hazards model was used to determine contributors to OS based on age, gender, race, facility type, WHO grade, tumor diameter, extent of resection, high school diploma quartile, median quartile, and length of hospital stay. A univariate analysis was performed and factors that had a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.15 were included in the multivariate hazards model. A binary logistical regression was used to determine the association between race and several other factors including gender, facility type, high grade tumor, extent of resection, tumor diameter, high school diploma quartile, and median income quartile. A univariate logistic regression was performed first, and a factor was then included in the multivariate model if the p-value was \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;0.15. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; all statistical tests were two-sided.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatient Characteristics\u003c/h2\u003e \u003cp\u003eWe found 366,987 patients with a presumed meningioma in the NCDB from 2012\u0026ndash;2020 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We excluded a total of 281,743 patients due to unconfirmed histologic diagnosis, age\u0026thinsp;\u0026lt;\u0026thinsp;18 years old, extracranial tumor location, incomplete racial information or other missing relevant variables. Our final cohort included 85,244 patients. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e demonstrates the distribution of patient and tumor characteristics by patient race. The average age for the cohort was 58 years (SD 13) and the majority of patients were White (74%), followed by Black (13.5%), Hispanic White (6.9%), Hispanic Black (0.16%), and Asian (4.2%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient and tumor characteristics comparisons based on race. *symbol denotes statistical significance between racial groups with a P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.0001.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient \u0026amp; Tumor Characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHispanic White\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHispanic Black\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54 (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55 (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFemale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e71.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility Type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAcademic\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNon-Academic\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo High School Diploma\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e1st Quartile\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e2nd Quartile\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e3rd Quartile\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e4th Quartile\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e1st Quartile\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e2nd Quartile\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e3rd Quartile\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e4th Quartile\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInsurance Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo Insurance\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePrivate\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGovernment\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLocation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMetro\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUrban\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRural\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.61%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDistance from Hospital (miles)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (147)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 (78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39 (217)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of Stay (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWHO Grade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e76.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExtent of Resection\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSTR\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGTR\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor Size (mm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e1\u0026ndash;34\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e35\u0026ndash;63\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e\u0026gt;64\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHispanic Black, Hispanic White, and Black patients were more likely to have no health insurance, live in the lowest median income zip codes, and live in zip codes with the highest proportion of people without a high school diploma (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Hispanic Black patients had the highest proportion of WHO grade 2 (28.2%) and 3 meningiomas (3.9%), followed by Black patients with slightly less WHO grade 2 (22.8%) and grade 3 meningiomas (1.9%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Hispanic Black patients also had the highest rate of STR (52.2%). Moderate-sized tumors (3.5-6.4cm) were more likely to occur in Hispanic Black patients (53.5%) and large tumors (greater than 6.4cm) were more often encountered in Black patients (11.8%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eFactors Influencing Overall Survival\u003c/h2\u003e \u003cp\u003eAmong the racial groups, only Black patients had a worse OS compared to White patients (HR 1.3; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Hispanic White (HR 0.82; P\u0026thinsp;=\u0026thinsp;0.012) and Asian (HR 0.71; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) patients and improved OS. There was no difference among Hispanic Black patients. Additional patient factors associated with worse OS included older age (i.e. \u0026gt;70 years) (HR 1.07, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and male sex (HR 1.5, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSeveral tumor characteristics were similarly associated with worse OS including WHO grade 2 (HR 1.5; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and grade 3 meningiomas (HR 3.7; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), moderate-sized tumors (HR 1.15; P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and large tumors (HR 1.33; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and subtotal resection (HR 1.13; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Socioeconomic factors influencing worse OS included nonacademic facility type (HR 1.29; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), lack of health insurance (HR 1.5; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), government health insurance (HR 1.5; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), lower median income quartile (HR 1.3; P\u0026thinsp;\u0026lt;\u0026thinsp;0.015), and lowest quartile for no high school diploma (HR 1.1; P\u0026thinsp;=\u0026thinsp;0.016) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eAssociation of Race and Factors influencing Overall Survival\u003c/h2\u003e \u003cp\u003eGiven the patient distribution, we used White patients as the reference group for all subsequent analyses we performed to understand the possible relationship between race and factors influencing OS. Moreover, we included only those variables that were significantly correlated to OS in these analyses. We found Black patients were more likely to have higher-grade tumors (WHO grade 2 and 3 meningiomas) (OR 1.24; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) large tumors (OR 1.14; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0048) and more likely to undergo STR (OR 1.18; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Black patients also had several associated low SES factors, including lack of health insurance (OR 3.18; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and living in disparate areas with low education (OR 3.3; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and lower median income (OR 4.2; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). While Black patients were less likely to be male (OR 0.88, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) or at an age\u0026thinsp;\u0026gt;\u0026thinsp;70 years old (OR 0.66; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and present to non-academic facilities (OR 0.75; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eHispanic White patients were more likely to have lower grade meningiomas (OR 0.87; P\u0026thinsp;=\u0026thinsp;0.005) compared to White patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, these patients had a higher likelihood of STR (OR 1.19; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Hispanic White patients were more likely to lack health insurance (OR 6.2; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and live in regions with the low education (OR 7.3; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and low median income (OR 2.32 P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eThere was no difference in OS for Hispanic Black patients (HR 0.70; P\u0026thinsp;=\u0026thinsp;0.49) compared to White patients, despite the increased likelihood of higher-grade tumors (OR 1.79; P\u0026thinsp;=\u0026thinsp;0.0164) and subtotal resection (OR 1.64; P\u0026thinsp;=\u0026thinsp;0.004) in Hispanic Black patients. There were no differences in frequency of large tumors (OR 0.42; P\u0026thinsp;=\u0026thinsp;0.23). Hispanic Black patients were also more likely to lack health insurance (OR 3.0; P\u0026thinsp;=\u0026thinsp;0.007) and live in regions with low education (OR 7.5; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and low median income (OR 3.0; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eAsian patients with a meningioma had better OS compared to White patients (HR 0.71; P\u0026thinsp;=\u0026thinsp;0.0001) despite being more likely to have higher grade tumors (OR 1.22; P\u0026thinsp;=\u0026thinsp;0.0023) and large tumor size (OR 1.25; P\u0026thinsp;=\u0026thinsp;0.0051). Asian patients were the only race to not have an increased likelihood of STR (P\u0026thinsp;=\u0026thinsp;0.14). Additionally, they uniquely were more likely to have health insurance (OR 0.60; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and not live areas with the lowest median income (OR 0.62; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThere are known racial disparities affecting OS in patients with meningiomas and it has been presumed these are likely due to differences in SES. However, differences remain in outcome in racial and ethnic groups of similar SES, suggesting that other underlying factors may also contribute. To our knowledge, this is the first study to demonstrate differences in tumor and patient characteristics associated with OS within each racial and ethnic group beyond SES. Overall, we found that combinations of tumor characteristics and SES influence OS in a race-specific manner (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). White, Hispanic Black, and Black patients were likely to have both aggressive tumor features and low SES that influence OS. Hispanic White patients were mostly influenced by low SES and were less likely to have aggressive tumor features, whereas Asian patients had aggressive tumor features and higher SES (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe found Black patients are seemingly the most vulnerable population of patients, with a more aggressive tumors and lower SES. Black patients are more likely to have higher grade meningiomas and to undergo STR, both of which are known contributors to worse OS, which is also reflected in our results. \u003csup\u003e9,10\u003c/sup\u003eAdditionally, they are more likely to lack health insurance and live in areas with a lower median income and education level. Although limited access to hospital facilities has been previously reported for Black patients,\u003csup\u003e4,11,12\u003c/sup\u003e our study demonstrates that the Black population can access academic facilities similar to other groups. While SES-related factors can undeniably contribute to poor outcomes, the finding of a higher prevalence of high-grade tumors and higher occurrence of STR among Black patients with meningioma is alarming This finding can potentially help raise awareness for opportunities to improve care for this patient population.\u003c/p\u003e \u003cp\u003eThe Hispanic population is unique in that it represents a heterogenous group of individuals with admixture of genetic ancestry.\u003csup\u003e13\u003c/sup\u003e Hispanic ethnicity is independent of race and encompasses a population who may also identify and self-report with different races, such as White, Black, or Asian. The heterogeneity of this population can likely account for some of the conflicting results thus far in the literature demonstrating either no difference or improved OS for Hispanic patients with meningiomas.\u003csup\u003e7,14\u0026ndash;16\u003c/sup\u003e We subclassified Hispanic ethnicity into Hispanic White and Hispanic Black to account for this admixture and its potential influence on outcome. Hispanic White populations have significantly improved OS compared to White populations. Interestingly, the improved OS in the Hispanic White population was seemingly independent of socioeconomic factors that could contribute to worsened OS. Indeed, they tended to have a younger age of presentation, lower grade tumors, and be of female sex. This is consistent with the \u0026ldquo;Hispanic Paradox\u0026rdquo; that has been well established in the medical literature, even beyond that of brain tumors (citations). Unfortunately, Black and Hispanic patients have also been reported to receive substandard care with less extensive resections,\u003csup\u003e17\u0026ndash;20\u003c/sup\u003e which is reflected in our results as well. Similar to Black patients, we found an increased likelihood of higher-grade tumors among the Hispanic Black population that may contribute to worse OS. These findings underscore the need for more specific distinctions in future studies investigating race, ethnicity and outcome, as Hispanic patients in particular cannot simply be grouped together in the same category without significant limitations.\u003c/p\u003e \u003cp\u003eInterestingly, our findings centered around the Asian population may perhaps exemplify the potential positive influence of SES on outcome for patients with meningioma. Indeed we found improved OS for Asians with meningiomas, consistent with prior studies that have shown either no difference or improved OS compared to White patients.\u003csup\u003e7,11,21,22\u003c/sup\u003e While we found Asian patients were more likely to have higher grade and larger meningiomas, Asian patients was more likely to have private health insurance and less likely to live in impoverished areas. Asian patients were also the least likely to undergo STR, and thus perhaps the SES and SDOH factors may have helped contribute to an improved OS.\u003c/p\u003e \u003cp\u003eOur findings demonstrate a clear racial disparity in meningioma aggressiveness amongst certain racial/ethnic populations and potential OS implications to form the basis for further investigations with genetic ancestry. To date, there have been no studies focused on elucidating the association between potential underlying genetic and epigenetic factors and tumor biology and behavior. However, these relationships have been well-studied in other tumors. Race-specific driver mutations have been identified in lung, breast, prostate, and colorectal cancer (PMID 34994651). \u003csup\u003e23\u003c/sup\u003e Glial tumors in the Hispanic White and non-Hispanic White patients were more likely to have EGFR expression, whereas Asian-American patients were more likely to have a p53-pathway mutations and these differences can have significant implications in outcome and patient-centered interventions.\u003csup\u003e24\u003c/sup\u003e Further studies are necessary to determine the underlying genomic influences that may be associated in the differences we observed in this study.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLIMITATIONS\u003c/h2\u003e \u003cp\u003eOur results warrant careful interpretation in the context of the study limitations. The NCDB is a national database, and with potential for selection bias related to non-randomized participation of certain institutions over others. Additionally, there is a certain crudeness in the reported variables in NCDB. Most relevant, our primary outcome, OS, is an \u0026ldquo;all-cause mortality\u0026rdquo; and does not distinguish non-meningioma related death to meningioma-related death. This is further compromised by the fact that NCDB does not offer recurrence data which could have been useful in interpreting outcome. The known differences in the average life-expectancy between racial and ethnic groups, such that Asians have the highest life expectancy, followed by Hispanic, White, and Black populations,\u003csup\u003e25\u003c/sup\u003e could not be accounted for in our study. Additionally, several SES factors, such as median income and high school diploma percentages, were inferred from zip code.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThere are racial differences in tumor and patient factors that influence overall survival for patients with meningiomas. Black patients appear particularly vulnerable, as they are more likely to harbor large, higher-grade meningiomas, undergo less aggressive surgical resections, and low socioeconomic status. Hispanic patients have distinct findings depending on whether they identify as White or Black race and this should be accounted for in any race and ethnicity meningioma study. Asian patients, despite being more likely to have higher grade meningiomas and larger meningiomas, have improved SES which may confer a survival benefit. Further studies are necessary to understand the possible difference in genetic ancestry that may influence tumor biology and overall survival of patients with meningioma.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u0026nbsp;\u003c/strong\u003eJM: Consultant, BK Medical; Consultant, Stryker\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003enone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevious presentations:\u0026nbsp;\u003c/strong\u003enone\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: A.D. and J.M.; Data curation: A.D.; Formal analysis: A.D.; Investigation: A.D.; Methodology: A.D. and J.M.; Project administration: J.M.; Resources: J.M.; Supervision: J.M.; Validation: A.D. and J.M.; Writing \u0026ndash; original draft: J.T., A.P., H.L., M.K. and J.M.; Writing - review \u0026amp; editing: J.T., A.P., H.L., M.K. and J.M.;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLei H, Tabor JK, O\u0026rsquo;Brien J, et al. Associations of race and socioeconomic status with outcomes after intracranial meningioma resection: a systematic review and meta-analysis. \u003cem\u003eJ Neurooncol\u003c/em\u003e. 2023;163(3):529-539. doi:10.1007/s11060-023-04393-5\u003c/li\u003e\n\u003cli\u003eJackson HN, Hadley CC, Khan AB, et al. Racial and Socioeconomic Disparities in Patients With Meningioma: A Retrospective Cohort Study. \u003cem\u003eNeurosurgery\u003c/em\u003e. 2022;90(1):114-123. doi:10.1227/NEU.0000000000001751\u003c/li\u003e\n\u003cli\u003eCurry WT, Carter BS, Barker FG. Racial, ethnic, and socioeconomic disparities in patient outcomes after craniotomy for tumor in adult patients in the United States, 1988-2004. \u003cem\u003eNeurosurgery\u003c/em\u003e. 2010;66(3):427-437; discussion 437-438. doi:10.1227/01.NEU.0000365265.10141.8E\u003c/li\u003e\n\u003cli\u003eAnzalone CL, Glasgow AE, Van Gompel JJ, Carlson ML. 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Life expectancy by county, race, and ethnicity in the USA, 2000-19: a systematic analysis of health disparities. \u003cem\u003eLancet\u003c/em\u003e. 2022;400(10345):25-38. doi:10.1016/S0140-6736(22)00876-5\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"meningioma, race, overall survival, socioeconomics","lastPublishedDoi":"10.21203/rs.3.rs-3834926/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3834926/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground \u003c/strong\u003eThere are known\u003cstrong\u003e \u003c/strong\u003eracial and ethnic disparities affecting overall survival (OS) in meningiomas. This has largely been presumed to be due to differences in socioeconomic status (SES). However, there are conflicting studies that demonstrate better survival for Hispanic compared to Black populations, two groups with similar SES. Thus, we hypothesize additional underlying factors, including tumor biology, may differ amongst race and influence OS of patients with meningioma.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eWe queried the NCDB for patients with pathology-confirmed meningiomas from 2012-2020. Race and ethnicity were self-reported and grouped into White, Hispanic White, Black, Hispanic Black, and Asian categories. Logistic regression analyses were performed to determine tumor and patient characteristics associated with race and Cox hazards model was performed on these characteristics to determine influence on OS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eWe included 85,244 patients in this study. Black patients have worse OS compared to White patients. Black patients were also more likely to harbor higher grade tumors and undergo subtotal resection compared to White patients. Hispanic White patients had improved overall survival (P\u0026lt;0.0001) with less higher-grade tumors (P=0.0051) compared to White patients. There was no difference in overall survival for Hispanic Black patients (P=0.49) despite being more likely to have higher grade tumors (P=0.0164).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions \u003c/strong\u003eDifferences in meningioma biology may contribute to the differences in OS seen in racial groups beyond SES. Black patients are a particularly vulnerable group as they tend to harbor higher-grade tumors and undergo less aggressive surgical resections. Further studies are necessary to determine possible \u0026nbsp;differences in underlying biology.\u003c/p\u003e","manuscriptTitle":"Meningioma Characteristics Influencing Overall Survival by Race and Ethnicity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-08 17:30:46","doi":"10.21203/rs.3.rs-3834926/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"acf319f3-04e8-4f95-9418-e67cca86543c","owner":[],"postedDate":"January 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-22T02:59:17+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-08 17:30:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3834926","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3834926","identity":"rs-3834926","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}