Advertisement

Primary brain and other central nervous system tumors in Appalachia: regional differences in incidence, mortality, and survival

  • Quinn T. Ostrom
  • Haley Gittleman
  • Carol Kruchko
  • Jill S. Barnholtz-SloanEmail author
Laboratory Investigation

Abstract

Background

The Appalachian region is a large geographic and economic area, representing 7.69% of the United States (US). This region is more rural, whiter, older, and has a higher level of poverty as compared to the rest of the US. Limited research has been done on primary brain and other central nervous system tumors (PBT) epidemiology in this region. In this analysis we characterize incidence, mortality, and survival patterns.

Methods

Data from 2006 to 2015 were obtained from the central brain tumor registry of the US (provided by CDC and NCI). Appalachian counties were categorized using the Appalachia Regional Council scheme. Overall and histology-specific age-adjusted incidence and mortality rates per 100,000 population were generated. 1-, 5-, and 10-year relative survival (RS) was estimated using CDC national program of cancer registry data from 2001 to 2014.

Results

Overall PBT incidence within Appalachia was 22.62 per 100,000, which is not significantly different from the non-Appalachian US (22.77/100,000, p = 0.1189). Malignant incidence was 5% higher in Appalachia (7.55/100,000 vs. 7.23/100,000, p < 0.0001), while non-malignant incidence was 3% lower (15.07/100,000 vs. 15.54/100,000, p < 0.0001). 5-year RS for malignant PBT was lower (31.4% vs. 36.0%), and mortality due to malignant PBT was higher in Appalachia (4.86/100,000 vs. 4.34/100,000, p < 0.0001).

Conclusion

Appalachia has increased malignant and decreased non-malignant PBT incidence, and poorer survival outcomes for malignant PBT compared to the non-Appalachian US.

Keywords

Brain and CNS tumors Incidence Relative survival Mortality Appalachia 

Notes

Acknowledgements

This work was previously presented at the 2018 annual meeting of the Society for Neuro-Oncology.

Author Contributions

Conceptualization: QTO. Formal analysis: QTO. Data curation: QTO, HG. Writing—original draft: QTO. Writing - review and editing: QTO, HG, CK, JSB. Funding acquisition: CK, JSB.

Funding

QTO is supported by a Research Training Grant from the Cancer Prevention and Research Institute of Texas (CPRIT; RP160097T). Funding for CBTRUS was provided by the Centers for Disease Control and Prevention (CDC) under Contract No. 2016-M-9030, the American Brain Tumor Association, The Sontag Foundation, Novocure, Abbvie, the Musella Foundation, and the National Cancer Institute (NCI) under contract No. HHSN261201800176P, as well as private and in kind donations. Contents are solely the responsibility of the authors and do not necessarily reflect the official views of the CDC or the NCI.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This study was approved by the Institutional Review Board at University Hospitals Cleveland Medical Center.

Informed consent

This was a retrospective study using de-identified national cancer registries. Thus, formal consent was not required.

Supplementary material

11060_2018_3073_MOESM1_ESM.docx (1.1 mb)
Supplementary material 1 (DOCX 1124 KB)

References

  1. 1.
    Ostrom QT, Gittleman H, Liao P, Vecchione-Koval T, Wolinsky Y, Kruchko C, Barnholtz-Sloan JS (2017) CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2010–2014. Neuro Oncol 19:v1–v88CrossRefGoogle Scholar
  2. 2.
    Leece R, Xu J, Ostrom QT, Chen Y, Kruchko C, Barnholtz-Sloan JS (2017) Global incidence of malignant brain and other central nervous system tumors by histology, 2003–2007. Neuro Oncol 19:1553–1564.  https://doi.org/10.1093/neuonc/nox091 CrossRefGoogle Scholar
  3. 3.
    Ostrom QT, Bauchet L, Davis FG, Deltour I, Fisher JL, Langer CE, Pekmezci M, Schwartzbaum JA, Turner MC, Walsh KM, Wrensch MR, Barnholtz-Sloan JS (2014) The epidemiology of glioma in adults: a “state of the science” review. Neuro Oncol 16:896–913.  https://doi.org/10.1093/neuonc/nou087 CrossRefGoogle Scholar
  4. 4.
    Amirian ES, Ostrom QT, Liu Y, Barnholtz-Sloan J, Bondy ML (2017) Nervous System. In: Thun M, Linet MS, Cerhan JR, Haiman CA, Schottenfeld D (eds) Cancer epidemiology and prevention, 4 edn. Oxford University Press, New YorkGoogle Scholar
  5. 5.
    Appalachian Regional Commission Counties in Appalachia. https://www.arc.gov/appalachian_region/CountiesinAppalachia.asp
  6. 6.
    Marshall JL, Thomas L, Lane NM, Arcury TA, Randolph R, Silberman P, Holding W, Villamil L, Sharita T, Lane M, Latus J, Rodgers J, Ivey K (2017) Health disparities in appalachia. Creating a culture of health in appalachia. Appalachian Regional Commission. The University of North Carolina at Chapel Hill, Chapel HillGoogle Scholar
  7. 7.
    Pollard K, Jacobsen LA, Population Reference Bureau (2017) The Appalachian Region: A Data Overview from the 2011–2015 American Community Survey. Population Reference BureauGoogle Scholar
  8. 8.
    McGarvey EL, Leon-Verdin M, Killos LF, Guterbock T, Cohn WF (2011) Health disparities between Appalachian and non-Appalachian counties in Virginia USA. J Community Health 36:348–356.  https://doi.org/10.1007/s10900-010-9315-9 CrossRefGoogle Scholar
  9. 9.
    Borak J, Salipante-Zaidel C, Slade MD, Fields CA (2012) Mortality disparities in Appalachia: reassessment of major risk factors. J Occup Environ Med 54:146–156.  https://doi.org/10.1097/JOM.0b013e318246f395 CrossRefGoogle Scholar
  10. 10.
    Meit M, Heffernan M, Tanenbaum E, Hoffmann T, The Walsh Center for Rural Health Analysis (2007) Final report: appalachian diseases of despair. https://www.arc.gov/assets/research_reports/AppalachianDiseasesofDespairAugust2017.pdf
  11. 11.
    Lengerich EJ, Tucker TC, Powell RK, Colsher P, Lehman E, Ward AJ, Siedlecki JC, Wyatt SW (2005) Cancer incidence in Kentucky, Pennsylvania, and West Virginia: disparities in Appalachia. J Rural Health 21:39–47CrossRefGoogle Scholar
  12. 12.
    Wilson RJ, Ryerson AB, Singh SD, King JB (2016) Cancer incidence in Appalachia, 2004–2011. Cancer Epidemiology, Biomarkers Prev 25:250–258  https://doi.org/10.1158/1055-9965.Epi-15-0946 CrossRefGoogle Scholar
  13. 13.
    Yao N, Alcala HE, Anderson R, Balkrishnan R (2017) Cancer disparities in rural Appalachia: incidence, early detection, and survivorship. J Rural Health 33:375–381.  https://doi.org/10.1111/jrh.12213 CrossRefGoogle Scholar
  14. 14.
    Paskett ED, Fisher JL, Lengerich EJ, Schoenberg NE, Kennedy SK, Conn ME, Roberto KA, Dwyer SK, Fickle D, Dignan M (2011) Disparities in underserved white populations: the case of cancer-related disparities in Appalachia. Oncologist 16:1072–1081.  https://doi.org/10.1634/theoncologist.2011-0145 CrossRefGoogle Scholar
  15. 15.
    Fisher JL, Engelhardt HL, Stephens JA, Smith BR, Haydu GG, Indian RW, Paskett ED (2008) Cancer-related disparities among residents of Appalachia Ohio. J Health Disparities Res Pract 2:61–74Google Scholar
  16. 16.
    Huang B, Luo A, Durbin EB, Lycan E, Tucker T, Chen Q, Horbinski C, Villano JL (2017) Incidence of CNS tumors in Appalachian children. J Neurooncol 132:507–512.  https://doi.org/10.1007/s11060-017-2403-2 CrossRefGoogle Scholar
  17. 17.
    Aldrich TE, Freitas SJ, Ling L, McKinney P (2008) Brain cancer survival in Kentucky: 1996–2000. J Ky Med Assoc 106:489–493Google Scholar
  18. 18.
    U.S. Cancer Statistics Working Group (2018) United States Cancer Statistics: 1999–2015 Incidence and Mortality Web-based Report. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute,. http://www.cdc.gov/uscs
  19. 19.
    Appalachian Regional Commission Subregions in Appalachia. https://www.arc.gov/research/MapsofAppalachia.asp?MAP_ID=31
  20. 20.
    Surveillance Epidemiology and End Results (SEER) Program (2016) SEER*Stat software version 8.3.2. National Cancer Institute, DCCPS, Surveillance Research Program. http://www.seer.cancer.gov/seerstat
  21. 21.
    Fay MP, Tiwari RC, Feuer EJ, Zou Z (2006) Estimating average annual percent change for disease rates without assuming constant change. Biometrics 62:847–854.  https://doi.org/10.1111/j.1541-0420.2006.00528.x CrossRefGoogle Scholar
  22. 22.
    Surveillance Epidemiology and End Results (SEER) Program SEER*Stat Database: Mortality - All COD, Aggregated With State, Total U.S. (1969–2015) < Katrina/Rita Population Adjustment>, National Cancer Institute, DCCPS, Surveillance Research Program, Surveillance Systems Branch, released April 2018. Underlying mortality data provided by NCHS (http://www.cdc.gov/nchs).
  23. 23.
    Surveillance Epidemiology and End Results (SEER) Program overview of the SEER program. Natl Cancer Inst http://seer.cancer.gov/about/overview.html
  24. 24.
    Surveillance Epidemiology and End Results (SEER) Program (2015) Number of Persons by Race and Hispanic Ethnicity for SEER Participants (2010 Census Data). http://seer.cancer.gov/registries/data.html
  25. 25.
    Surveillance Epidemiology and End Results (SEER) Program (2017) SEER*Stat Database: Incidence - SEER 18 Regs Custom Data (with additional treatment fields), Nov 2016 Sub (2000–2014) < Katrina/Rita Population Adjustment> - Linked To County Attributes - Total U.S., 1969–2015 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2017, based on the November 2016 submission.Google Scholar
  26. 26.
    Noone AM, Lund JL, Mariotto A, Cronin K, McNeel T, Deapen D, Warren JL (2016) Comparison of SEER treatment data with medicare claims. Med Care 54:e55–e64.  https://doi.org/10.1097/mlr.0000000000000073 CrossRefGoogle Scholar
  27. 27.
    R Core Team (2018) R: A language and environment for statistical computing. R Foundation for Statistical Computing. http://www.R-project.org/
  28. 28.
    Program JR, Version 4.2.0.2 - June 2015; Statistical methodology and applications branch, surveillance research program, National Cancer InstituteGoogle Scholar
  29. 29.
    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  https://doi.org/10.1001/jamaoncol.2018.1789 Google Scholar
  30. 30.
    Porter AB, Lachance DH, Johnson DR (2015) Socioeconomic status and glioblastoma risk: a population-based analysis. Cancer Causes Control: CCC 26:179–185.  https://doi.org/10.1007/s10552-014-0496-x CrossRefGoogle Scholar
  31. 31.
    Khanolkar AR, Ljung R, Talback M, Brooke HL, Carlsson S, Mathiesen T, Feychting M (2016) Socioeconomic position and the risk of brain tumour: a Swedish national population-based cohort study. J Epidemiol Community Health.  https://doi.org/10.1136/jech-2015-207002 Google Scholar
  32. 32.
    Plascak JJ, Fisher JL (2013) Area-based socioeconomic position and adult glioma: a hierarchical analysis of surveillance epidemiology and end results data. PLoS ONE 8:e60910.  https://doi.org/10.1371/journal.pone.0060910 CrossRefGoogle Scholar
  33. 33.
    Wigertz A, Lonn S, Hall P, Feychting M (2010) Non-participant characteristics and the association between socioeconomic factors and brain tumour risk. J Epidemiol Community Health 64:736–743.  https://doi.org/10.1136/jech.2008.085845 CrossRefGoogle Scholar
  34. 34.
    Deb S, Pendharkar AV, Schoen MK, Altekruse S, Ratliff J, Desai A (2017) The effect of socioeconomic status on gross total resection, radiation therapy and overall survival in patients with gliomas. J Neuro-Oncol 132:447–453.  https://doi.org/10.1007/s11060-017-2391-2 CrossRefGoogle Scholar
  35. 35.
    Nilsson J, Holgersson G, Jaras J, Bergstrom S, Bergqvist M (2018) The role of income in brain tumor patients: a descriptive register-based study: no correlation between patients’ income and development of brain cancer. Med Oncol 35:52.  https://doi.org/10.1007/s12032-018-1108-5 CrossRefGoogle Scholar
  36. 36.
    Megwalu UC (2017) Impact of county-Level socioeconomic status on oropharyngeal cancer survival in the United States. Otolaryngol–Head Neck Surg 156:665–670.  https://doi.org/10.1177/0194599817691462 CrossRefGoogle Scholar
  37. 37.
    Underwood JM, Richards TB, Henley SJ, Momin B, Houston K, Rolle I, Holmes C, Stewart SL (2015) Decreasing trend in tobacco-related cancer incidence, United States 2005–2009. J Community Health 40:414–418.  https://doi.org/10.1007/s10900-014-9951-6 CrossRefGoogle Scholar
  38. 38.
    Woolley SM, Meacham SL, Balmert LC, Talbott EO, Buchanich JM (2015) Comparison of mortality disparities in central Appalachian coal- and non-coal-mining counties. J Occup Environ Med 57:687–694.  https://doi.org/10.1097/jom.0000000000000435 CrossRefGoogle Scholar
  39. 39.
    Krometis LA, Gohlke J, Kolivras K, Satterwhite E, Marmagas SW, Marr LC (2017) Environmental health disparities in the central Appalachian region of the United States. Rev Environ Health 32:253–266.  https://doi.org/10.1515/reveh-2017-0012 CrossRefGoogle Scholar
  40. 40.
    Ferdosi H, Lamm SH, Afari-Dwamena NA, Dissen E, Chen R, Li J, Feinleib M (2018) Small-for-gestational age prevalence risk factors in central Appalachian states with mountain-top mining. Int J Occup Med Environ Health 31:11–23.  https://doi.org/10.13075/ijomeh.1896.01042 Google Scholar
  41. 41.
    Spector LG, Puumala SE, Carozza SE, Chow EJ, Fox EE, Horel S, Johnson KJ, McLaughlin CC, Reynolds P, Von Behren J, Mueller BA (2009) Cancer risk among children with very low birth weight. Pediatrics 124:96–104.  https://doi.org/10.1542/peds.2008-3069 CrossRefGoogle Scholar
  42. 42.
    Shiels MS, Engels EA, Linet MS, Clarke CA, Li J, Hall HI, Hartge P, Morton LM (2013) The epidemic of non-Hodgkin lymphoma in the United States: disentangling the effect of HIV, 1992–2009. Cancer Epidemiol Biomark Prev 22:1069–1078.  https://doi.org/10.1158/1055-9965.epi-13-0040 CrossRefGoogle Scholar
  43. 43.
    Moorman JP, Krolikowski MR, Mathis SM, Pack RP (2018) HIV/HCV Co-infection: burden of disease and care strategies in Appalachia. Curr HIV/AIDS Rep.  https://doi.org/10.1007/s11904-018-0404-1 Google Scholar
  44. 44.
    Hall HI, Li J, McKenna MT (2005) HIV in predominantly rural areas of the United States. J Rural Health 21:245–253CrossRefGoogle Scholar
  45. 45.
    Macleod LC, Cannon SS, Ko O, Schade GR, Wright JL, Lin DW, Holt SK, Gore JL, Dash A (2018) Disparities in access and regionalization of care in testicular cancer. Clin Genitourin Cancer 16:e785–e793.  https://doi.org/10.1016/j.clgc.2018.02.014 CrossRefGoogle Scholar
  46. 46.
    Bos D, Poels MM, Adams HH, Akoudad S, Cremers LG, Zonneveld HI, Hoogendam YY, Verhaaren BF, Verlinden VJ, Verbruggen JG, Peymani A, Hofman A, Krestin GP, Vincent AJ, Feelders RA, Koudstaal PJ, van der Lugt A, Ikram MA, Vernooij MW (2016) Prevalence, clinical management, and natural course of incidental findings on brain mr images: the population-based rotterdam scan study. Radiology 281:507–515.  https://doi.org/10.1148/radiol.2016160218 CrossRefGoogle Scholar
  47. 47.
    Ezzat S, Asa SL, Couldwell WT, Barr CE, Dodge WE, Vance ML, McCutcheon IE (2004) The prevalence of pituitary adenomas: a systematic review. Cancer 101:613–619.  https://doi.org/10.1002/cncr.20412 CrossRefGoogle Scholar
  48. 48.
    Morris Z, Whiteley WN, Longstreth WT Jr, Weber F, Lee YC, Tsushima Y, Alphs H, Ladd SC, Warlow C, Wardlaw JM, Al-Shahi Salman R (2009) Incidental findings on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 339:b3016.  https://doi.org/10.1136/bmj.b3016 CrossRefGoogle Scholar
  49. 49.
    Bruner JM, Louis DN, McLendon R, Rosenblum MK, Archambault WT, Most S, Tihan T (2017) The utility of expert diagnosis in surgical neuropathology: analysis of consultations reviewed at 5 national comprehensive cancer network institutions. J Neuropathol Exp Neurol 76:189–194.  https://doi.org/10.1093/jnen/nlw122 Google Scholar
  50. 50.
    Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, Ohgaki H, Wiestler OD, Kleihues P, Ellison DW (2016) The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol 131:803–820.  https://doi.org/10.1007/s00401-016-1545-1 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Central Brain Tumor Registry of the United StatesHinsdaleUSA
  2. 2.Department of Medicine, Section of Epidemiology and Population Sciences, Dan L. Duncan Comprehensive Cancer CenterBaylor College of MedicineHoustonUSA
  3. 3.Department of Population and Quantitative Health Sciences, Case Comprehensive Cancer Center,Case Western Reserve University School of MedicineClevelandUSA

Personalised recommendations