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Racial/ethnic differences in survival for patients with gliosarcoma: an analysis of the National cancer database

  • James M. Wright
  • Tiffany R. Hodges
  • Christina Huang Wright
  • Haley Gittleman
  • Xiaofei Zhou
  • Kelsey Duncan
  • Carol Kruchko
  • Andrew SloanEmail author
  • Jill S. Barnholtz-SloanEmail author
Clinical Study

Abstract

Purpose

Gliosarcoma is characterized by the World Health Organization as a Grade IV malignant neoplasm and a variant of glioblastoma. The association of race and ethnicity with survival has been established for numerous CNS malignancies, however, no epidemiological studies have reported these findings for patients with gliosarcoma. The aim of this study was to examine differences by race and ethnicity in overall survival, 30-day mortality, 90-day mortality, and 30-day readmission.

Methods

Data were obtained by query of the National Cancer Database (NCDB) for years 2004–2014. Patients with gliosarcoma were identified by International Classification of Diseases for Oncology, Third Edition (ICD-O-3)—Oncology morphologic code 9442/3 and topographical codes C71.0–C71.9. Differences in survival by race/ethnicity were examined using univariable and multivariable Cox proportional hazards models. Readmission and mortality outcomes were examined with univariable and multivariable logistic regression.

Results

A total of 1988 patients diagnosed with gliosarcoma were identified (White Non-Hispanic n = 1,682, Black Non-Hispanic n = 165, Asian n = 40, Hispanic n = 101). There were no differences in overall survival, 30- and 90-day mortality, or 30-day readmission between the races and ethnicities examined. Median survival was 10.4 months for White Non-Hispanics (95% CI 9.8, 11.2), 10.2 months for Black Non-Hispanics (95% CI 8.6, 13.1), 9.0 months for Asian Non-Hispanics (95% CI 5.1, 18.2), and 10.6 months for Hispanics (95% CI 8.3,16.2). 7.3% of all patients examined had an unplanned readmission within 30 days.

Conclusion

Race/ethnicity are not associated with differences in overall survival, 30-day mortality, 90-day mortality, or 30-day readmission following surgical intervention for gliosarcoma.

Keywords

Gliosarcoma Survival Mortality Race Socioeconomics NCDB 

Notes

Acknowledgements

This project is sponsored by the Junior Faculty Mentorship Program in the Department of Neurosurgery, UH-Cleveland Medical Center (AES). AES is also supported by NIH CA217956; as well as the Peter D Cristal Chair, the Center of Excellence for Translational Neuro-Oncology, the Gerald Kaufman Fund for Glioma Research, the Kimble Family Foundation, and the Ferry Family Foundation at University Hospitals of Cleveland. JBS is supported by the Research Division, University Hospitals of Cleveland.

Author contributions

JSB—IRB writing, study design, data collection, data analysis/interpretation, figure preparation, reviewing/editing, and final approval of manuscript. KD—data collection, reviewing/editing manuscript. HG—study design, data collection, data analysis/interpretation, figure preparation, manuscript drafting, reviewing/editing manuscript. TRH, study design, data collection, data analysis/interpretation, figure preparation, reviewing/editing manuscript. CK—study design, data analysis/interpretation, reviewing/editing manuscript. AES—Project Conception, IRB Sponsorship and writing, acquisition of NCDB data, study design, data collection, reviewing/editing and final approval of manuscript. CHW—IRB writing, study design, data collection, data analysis/interpretation, figure preparation, manuscript drafting, reviewing/editing manuscript. JMW—IRB writing, study design, data collection, data analysis/interpretation, figure preparation, manuscript drafting, reviewing/editing manuscript. XZ—data collection, reviewing/editing manuscript.

Compliance with ethical standards

Conflict of interest

There are no conflicts of interest to report.

Supplementary material

11060_2019_3170_MOESM1_ESM.tiff (12.4 mb)
Supplementary material 1 Supplementary Figure 1. Insurance over Time, Gliosarcoma, National Cancer Database (NCDB) 2004-2014 (TIFF 12659 kb)

References

  1. 1.
    Ostrom QT, Gittleman H, Truitt G, Boscia A, Kruchko C, Barnholtz-Sloan JS (2018) CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2011-2015. Neuro Oncol 20(suppl_4):iv1–iv86Google Scholar
  2. 2.
    Kruchko C, Ostrom QT, Gittleman H, Barnholtz-Sloan JS (2018) The CBTRUS story: providing accurate population-based statistics on brain and other central nervous system tumors for everyone. Neuro Oncol 20(3):295–298Google Scholar
  3. 3.
    Kozak KR, Mahadevan A, Moody JS (2009) Adult gliosarcoma: epidemiology, natural history, and factors associated with outcome. Neuro Oncol 11(2):183–191Google Scholar
  4. 4.
    Galanis E, Buckner JC, Dinapoli RP et al (1998) Clinical outcome of gliosarcoma compared with glioblastoma multiforme: north central cancer treatment group results. J Neurosurg 89(3):425–430Google Scholar
  5. 5.
    Han SJ, Yang I, Ahn BJ et al (2010) Clinical characteristics and outcomes for a modern series of primary gliosarcoma patients. Cancer 116(5):1358–1366Google Scholar
  6. 6.
    Rath GK, Sharma DN, Mallick S et al (2015) Clinical outcome of patients with primary gliosarcoma treated with concomitant and adjuvant temozolomide: a single institutional analysis of 27 cases. Indian J Cancer 52(4):599–603Google Scholar
  7. 7.
    Singh G, Das KK, Sharma P et al (2015) Cerebral gliosarcoma: analysis of 16 patients and review of literature. Asian J Neurosurg 10(3):195–202Google Scholar
  8. 8.
    Zhang G, Huang S, Zhang J, Wu Z, Lin S, Wang Y (2016) Clinical outcome of gliosarcoma compared with glioblastoma multiforme: a clinical study in Chinese patients. J Neurooncol 127(2):355–362Google Scholar
  9. 9.
    Ma R, Alexe DM, Boeris D, Pereira E (2017) Primary gliosarcoma: epidemiology, clinical presentation, management and survival. J Neurosurg Sci.  https://doi.org/10.23736/S0390-5616.17.04077-2 Google Scholar
  10. 10.
    Frandsen J, Orton A, Jensen R et al (2018) Patterns of care and outcomes in gliosarcoma: an analysis of the National Cancer Database. J Neurosurg 128(4):1133–1138Google Scholar
  11. 11.
    Barnholtz-Sloan JS, Sloan AE, Schwartz AG (2003) Racial differences in survival after diagnosis with primary malignant brain tumor. Cancer 98(3):603–609Google Scholar
  12. 12.
    Barnholtz-Sloan JS, Williams VL, Maldonado JL et al (2008) Patterns of care and outcomes among elderly individuals with primary malignant astrocytoma. J Neurosurg 108(4):642–648Google Scholar
  13. 13.
    Chakrabarti I, Cockburn M, Cozen W, Wang YP, Preston-Martin S (2005) A population-based description of glioblastoma multiforme in Los Angeles County, 1974-1999. Cancer 104(12):2798–2806Google Scholar
  14. 14.
    Darefsky AS, King JT Jr, Dubrow R (2012) Adult glioblastoma multiforme survival in the temozolomide era: a population-based analysis of surveillance, epidemiology, and end results registries. Cancer 118(8):2163–2172Google Scholar
  15. 15.
    Ostrom QT, Gittleman H, Fulop J et al (2015) CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2008-2012. Neuro Oncol. 17(Suppl 4):iv1–iv62Google Scholar
  16. 16.
    Thakkar JP, Dolecek TA, Horbinski C et al (2014) Epidemiologic and molecular prognostic review of glioblastoma. Cancer Epidemiol Biomark Prev 23(10):1985–1996Google Scholar
  17. 17.
    Xu H, Chen J, Xu H, Qin Z (2017) Geographic variations in the incidence of glioblastoma and prognostic factors predictive of overall survival in US Adults from 2004-2013. Front Aging Neurosci 9:352Google Scholar
  18. 18.
    Smith DR, Wu CC, Saadatmand HJ et al (2018) Clinical and molecular characteristics of gliosarcoma and modern prognostic significance relative to conventional glioblastoma. J Neurooncol 137(2):303–311Google Scholar
  19. 19.
    Lerro CC, Robbins AS, Phillips JL, Stewart AK (2013) Comparison of cases captured in the national cancer data base with those in population-based central cancer registries. Ann Surg Oncol 20(6):1759–1765Google Scholar
  20. 20.
    Bohn A, Braley A, Rodriguez de la Vega P, Zevallos JC, Barengo NC (2018) The association between race and survival in glioblastoma patients in the US: a retrospective cohort study. PLoS ONE 13(6):e0198581Google Scholar
  21. 21.
    Srivastava H, Dewan A, Sharma SK et al (2018) Adjuvant radiation therapy and temozolomide in gliosarcoma: is it enough? Case series of seven patients. Asian J Neurosurg 13(2):297–301Google Scholar
  22. 22.
    Ostrom QT, Cote DJ, Ascha M, Kruchko C, Barnholtz-Sloan JS (2018) Adult glioma incidence and survival by race or ethnicity in the United States From 2000 to 2014. JAMA Oncol 4(9):1254–1262Google Scholar
  23. 23.
    Brown DA, Himes BT, Kerezoudis P et al (2018) Insurance correlates with improved access to care and outcome among glioblastoma patients. Neuro Oncol 20(10):1374–1382Google Scholar
  24. 24.
    Bojko MM, Kucejko RJ, Poggio JL (2018) Racial disparities and the effect of county level income on the incidence and survival of young men with anal cancer. Health Equity 2(1):193–198Google Scholar
  25. 25.
    Altman AD, Lambert P, Love AJ et al (2017) Examining the effects of time to diagnosis, income, symptoms, and incidental detection on overall survival in epithelial ovarian cancer: manitoba ovarian cancer outcomes (MOCO) study group. Int J Gynecol Cancer. 27(8):1637–1644Google Scholar
  26. 26.
    Steenland K, Rodriguez C, Mondul A, Calle EE, Thun M (2004) Prostate cancer incidence and survival in relation to education (United States). Cancer Causes Control 15(9):939–945Google Scholar
  27. 27.
    Smailyte G, Jasilionis D, Vincerzevskiene I, Shkolnikov VM (2016) Education, survival, and avoidable deaths in Lithuanian cancer patients, 2001-2009. Acta Oncol 55(7):859–864Google Scholar
  28. 28.
    de Vries E, Uribe C, Pardo C, Lemmens V, Van de Poel E, Forman D (2015) Gastric cancer survival and affiliation to health insurance in a middle-income setting. Cancer Epidemiol 39(1):91–96Google Scholar
  29. 29.
    Hussain SK, Altieri A, Sundquist J, Hemminki K (2008) Influence of education level on breast cancer risk and survival in Sweden between 1990 and 2004. Int J Cancer 122(1):165–169Google Scholar
  30. 30.
    Hussain SK, Lenner P, Sundquist J, Hemminki K (2008) Influence of education level on cancer survival in Sweden. Ann Oncol 19(1):156–162Google Scholar
  31. 31.
    Brusselaers N, Ljung R, Mattsson F et al (2013) Education level and survival after oesophageal cancer surgery: a prospective population-based cohort study. BMJ Open 3(12):e003754Google Scholar
  32. 32.
    Ansell D, Whitman S, Lipton R, Cooper R (1993) Race, income, and survival from breast cancer at two public hospitals. Cancer 72(10):2974–2978Google Scholar
  33. 33.
    Vincerzevskiene I, Jasilionis D, Austys D, Stukas R, Kaceniene A, Smailyte G (2017) Education predicts cervical cancer survival: a Lithuanian cohort study. Eur J Public Health 27(3):421–424Google Scholar
  34. 34.
    Herndon JE 2nd, Kornblith AB, Holland JC, Paskett ED (2008) Patient education level as a predictor of survival in lung cancer clinical trials. J Clin Oncol 26(25):4116–4123Google Scholar
  35. 35.
    Herndon JE 2nd, Kornblith AB, Holland JC, Paskett ED (2013) Effect of socioeconomic status as measured by education level on survival in breast cancer clinical trials. Psychooncology 22(2):315–323Google Scholar
  36. 36.
    Boyd C, Zhang-Salomons JY, Groome PA, Mackillop WJ (1999) Associations between community income and cancer survival in Ontario, Canada, and the United States. J Clin Oncol 17(7):2244–2255Google Scholar
  37. 37.
    Dalton SO, Steding-Jessen M, Gislum M, Frederiksen K, Engholm G, Schuz J (2008) Social inequality and incidence of and survival from cancer in a population-based study in Denmark, 1994-2003: background, aims, materials and methods. Eur J Cancer 44(14):1938–1949Google Scholar
  38. 38.
    Gorey KM (2009) Breast cancer survival in Canada and the USA: meta-analytic evidence of a Canadian advantage in low-income areas. Int J Epidemiol 38(6):1543–1551Google Scholar
  39. 39.
    Gorey KM, Fung KY, Luginaah IN, Holowaty EJ, Hamm C (2010) Income and long-term breast cancer survival: comparisons of vulnerable urban places in Ontario and California. Breast J 16(4):416–419Google Scholar
  40. 40.
    Gorey KM, Kanjeekal SM, Wright FC et al (2015) Colon cancer care and survival: income and insurance are more predictive in the USA, community primary care physician supply more so in Canada. Int J Equity Health 14:109Google Scholar
  41. 41.
    Bajaj A, Martin B, Bhasin R et al (2018) The impact of academic facility type and case volume on survival in patients undergoing curative radiation therapy for muscle-invasive bladder cancer. Int J Radiat Oncol Biol Phys 100(4):851–857Google Scholar
  42. 42.
    Cheraghlou S, Kuo P, Judson BL (2017) Treatment delay and facility case volume are associated with survival in early-stage glottic cancer. Laryngoscope 127(3):616–622Google Scholar
  43. 43.
    Baade PD, Dasgupta P, Aitken JF, Turrell G (2011) Distance to the closest radiotherapy facility and survival after a diagnosis of rectal cancer in Queensland. Med J Aust 195(6):350–354Google Scholar
  44. 44.
    Chen YW, Mahal BA, Muralidhar V et al (2016) Association between treatment at a high-volume facility and improved survival for radiation-treated men with high-risk prostate cancer. Int J Radiat Oncol Biol Phys 94(4):683–690Google Scholar
  45. 45.
    Koshy M, Malik R, Mahmood U, Husain Z, Sher DJ (2015) Stereotactic body radiotherapy and treatment at a high volume facility is associated with improved survival in patients with inoperable stage I non-small cell lung cancer. Radiother Oncol 114(2):148–154Google Scholar
  46. 46.
    Boffa DJ, Rosen JE, Mallin K et al (2017) Using the national cancer database for outcomes research: a review. JAMA Oncol 3(12):1722–1728Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Neurosurgery, University Hospitals Cleveland Medical CenterCase Western Reserve UniversityClevelandUSA
  2. 2.Seidman Cancer Center & Case Comprehensive Cancer CenterClevelandUSA
  3. 3.Case Comprehensive Cancer Center and Department of Population and Quantitative Health SciencesCase Western Reserve University School of MedicineClevelandUSA
  4. 4.Central Brain Tumor Registry of the United StatesHinsdaleUSA
  5. 5.Department of NeurologyUniversity Hospitals Cleveland Medical CenterClevelandUSA
  6. 6.Case Western Reserve University School of MedicineCase Comprehensive Cancer CenterClevelandUSA

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