Cancer Causes & Control

, Volume 27, Issue 10, pp 1261–1271 | Cite as

The effect of time on racial differences in epithelial ovarian cancer (OVCA) diagnosis stage, overall and by histologic subtypes: a study of the National Cancer Database

  • Anna B. Beckmeyer-Borowko
  • Caryn E. Peterson
  • Katherine C. Brewer
  • Mary A. Otoo
  • Faith G. Davis
  • Kent F. Hoskins
  • Charlotte E. Joslin
Original paper



Previous studies assessing racial and ethnic differences in ovarian cancer (OVCA) diagnosis stage fail to present subtype-specific results and provide historic data on cases diagnosed between 10 and 20 years ago. The purpose of this analysis is to assess non-Hispanic Black (NHB) and non-Hispanic White (NHW) differences in late-stage diagnosis including; (1) factors associated with late-stage diagnosis of invasive epithelial OVCA overall and by histologic subtypes, (2) potential changes across time and (3) current patterns of trends in a national cancer registry in the USA and Puerto Rico between 1998 and 2011.


NHB and NHW OVCA cases were derived from the National Cancer Database (NCDB). Diagnosis stage was analyzed as a dichotomous and a four level-category variable, respectively; early (stages I and II; localized) versus late (stages III and IV; regional and distant) and stages I, II, III and IV. Diagnosis period was trichotomized (1998–2002, 2003–2007, 2008–2011). Racial differences in stage were tested using Chi-square statistics. Odds ratios (OR) and 95 % confidence intervals (95 % CI) were estimated using multivariable binomial and generalized ordered logistic regressions. Interactions between race and diagnosis period were evaluated.


Between 1998 and 2011, 11,562 (7.8 %) NHB and 137,106 (92.2 %) NHW were diagnosed with OVCA. In adjusted models, NHB were significantly more likely diagnosed with late-stage OVCA than NHW (ORadj 1.26, 95 % CI 1.19–1.33). Interaction between race and diagnosis period was marginally significant (p value = 0.09), with racial differences in stage decreasing over time (1998–2002: ORadj 1.36, 95 % CI 1.23–1.49; 2003–2007: ORadj 1.27, 95 % CI 1.15–1.39; 2008–2011; ORadj 1.15, 95 % CI 1.05–1.27). NHB were also more likely to be diagnosed with stage 4 high-grade serous (ORadj 1.46, 95 % CI 1.22–1.74), clear cell (ORadj 2.71, 95 % CI 1.94–3.79) and mucinous (ORadj 2.78, 95 % CI 2.24–3.46) carcinomas than NHW.


Racial differences in late-stage OVCA diagnosis exist; however, these differences are decreasing with time. Within NCDB, NHB are significantly more likely diagnosed with late-stage OVCA and more specifically high-grade serous, clear cell and mucinous carcinomas than NHW.


Ovarian cancer Racial differences Racial disparities Time-trend Diagnosis stage Non-Hispanic Black Non-Hispanic White High-grade serous 



American Cancer Society Research Scholar Grant RSG-13-380-01-CPHPS. The CoC’s NCDB and the hospitals participating in the CoC NCDB are the source of the de-identified data used herein; they have not been verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors.


A.B. Beckmeyer-Borowko: National Cancer Institute, National Institute of Health Grant NCI NIH R25CA057699. A.B. Beckmeyer-Borowko, C.E. Peterson, K.C. Brewer, M.A. Otoo, F.G. Davis, K.F. Hoskins, C.E. Joslin: American Cancer Society Research Scholar Grant RSG-13-380-01-CPHPS. C.E. Joslin: Departmental awards NIH/NEI EY01792 and Research to Prevent Blindness, Inc.

Compliance with ethical standards

Conflict of interest

The authors have no potential conflict of interest to disclose.


  1. 1.
    Siegel R, Ma J, Zou Z, Jemal A (2014) Cancer statistics, 2014. CA Cancer J Clin 64(1):9–29CrossRefPubMedGoogle Scholar
  2. 2.
    American Cancer Society (2015) Ovarian cancer. What are the key statistics about ovarian cancer? Accessed 12 Jan 2015
  3. 3.
    Moyer VA (2012) Screening for Ovarian Cancer: US preventive services task force reaffirmation recommendation statement. Ann Intern Med 157(12):900–904CrossRefPubMedGoogle Scholar
  4. 4.
    Chan JK, Zhang M, Hu JM, Shin JY, Osann K, Kapp DS (2008) Racial disparities in surgical treatment and survival of epithelial ovarian cancer in USA. J Surg Oncol 97(2):103–107CrossRefPubMedGoogle Scholar
  5. 5.
    Terplan M, Temkin S, Tergas A, Lengyel E (2008) Does equal treatment yield equal outcomes? The impact of race on survival in epithelial ovarian cancer. Gynecol Oncol 111(2):173–178CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Alvarez RD, Karlan BY, Strauss JF (2016) Ovarian cancers: evolving paradigms in research and care. Report from the Institute of Medicine, Gynecologic oncologyGoogle Scholar
  7. 7.
    Braicu EI, Sehouli J, Richter R, Pietzner K, Denkert C, Fotopoulou C (2011) Role of histological type on surgical outcome and survival following radical primary tumour debulking of epithelial ovarian, fallopian tube and peritoneal cancers. Br J Cancer 105(12):1818–1824CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Seidman JD, Kurman RJ, Ronnett BM (2003) Primary and metastatic mucinous adenocarcinomas in the ovaries: incidence in routine practice with a new approach to improve intraoperative diagnosis. Am J Surg Pathol 27(7):985–993CrossRefPubMedGoogle Scholar
  9. 9.
    National Cancer Institute (2015) SEER stat fact sheets: ovary cancer, surveillance, epidemiology, and end results. Accessed 12 Jan 2015
  10. 10.
    Centers for Disease Control and Prevention (2014) CDC—ovarian cancer rates by race and ethnicity. Gynecologic Cancers. Accessed 30 Nov 2015
  11. 11.
    Clarke-Pearson DL (2009) Screening for ovarian cancer. N Engl J Med 361(2):170–177CrossRefPubMedGoogle Scholar
  12. 12.
    Halpern MT, Ward EM, Pavluck AL, Schrag NM, Bian J, Chen AY (2008) Association of insurance status and ethnicity with cancer stage at diagnosis for 12 cancer sites: a retrospective analysis. Lancet Oncol 9(3):222–231CrossRefPubMedGoogle Scholar
  13. 13.
    Morris CR, Sands MT, Smith LH (2010) Ovarian cancer: predictors of early-stage diagnosis. Cancer Causes Control 21(8):1203–1211CrossRefPubMedGoogle Scholar
  14. 14.
    Barnholtz-Sloan JS, Tainsky MA, Abrams J, Severson RK, Qureshi F, Jacques SM, Levin N, Schwartz AG (2002) Ethnic differences in survival among women with ovarian carcinoma. Cancer 94(6):1886–1893CrossRefPubMedGoogle Scholar
  15. 15.
    Parham GP, Hicks ML (1997) The national cancer data base report on malignant epithelial ovarian carcinoma in African-American women. Cancer 80(4):816–826CrossRefPubMedGoogle Scholar
  16. 16.
    American College of Surgeons (2016) National cancer data base. Accessed 12 Jan 2016
  17. 17.
    Winchester DP, Stewart AK, Phillips JL, Ward EE (2010) The National Cancer Data Base: past, present, and future. Ann Surg Oncol 17(1):4–7CrossRefPubMedGoogle Scholar
  18. 18.
    American College of Surgeons (2016) Patients demographics. National Cancer Database. Accessed 12 Jan 2016
  19. 19.
    Baldwin LA, Huang B, Miller RW, Tucker T, Goodrich ST, Podzielinski I, DeSimone CP, Ueland FR, van Nagell JR, Seamon LG (2012) Ten-year relative survival for epithelial ovarian cancer. Obstet Gynecol 120(3):612–618CrossRefPubMedGoogle Scholar
  20. 20.
    Cliby WA, Powell MA, Al-Hammadi N, Chen L, Philip Miller J, Roland PY, Mutch DG, Bristow RE (2015) Ovarian cancer in the USA: contemporary patterns of care associated with improved survival. Gynecol Oncol 136(1):11–17CrossRefPubMedGoogle Scholar
  21. 21.
    Pollack CE, Bekelman JE, Epstein AJ, Liao K, Wong YN, Armstrong K (2011) Racial disparities in changing to a high-volume urologist among men with localized prostate cancer. Med Care 49(11):999–1006PubMedPubMedCentralGoogle Scholar
  22. 22.
    Zevallos JP, Mitra N, Swisher-McClure S (2016) Patterns of care and perioperative outcomes in transoral endoscopic surgery for oropharyngeal squamous cell carcinoma. Head Neck 38(3):402–409CrossRefPubMedGoogle Scholar
  23. 23.
    Ayanian JZ, Weissman JS, Schneider EC, Ginsburg JA, Zaslavsky AM (2000) UNmet health needs of uninsured adults in the united states. JAMA 284(16):2061–2069CrossRefPubMedGoogle Scholar
  24. 24.
    Ioannou GN, Chapko MK, Dominitz JA (2003) Predictors of colorectal cancer screening participation in the United States. Am J Gastroenterol 98(9):2082–2091CrossRefPubMedGoogle Scholar
  25. 25.
    Potosky AL, Breen N, Graubard BI, Parsons PE (1998) The Association between Health Care Coverage and the Use of Cancer Screening Tests: results from the 1992 National Health Interview Survey. Med Care 36(3):257–270CrossRefPubMedGoogle Scholar
  26. 26.
    Reid BC, Rozier RG (2006) Continuity of care and early diagnosis of head and neck cancer. Oral Oncol 42(5):510–516CrossRefPubMedGoogle Scholar
  27. 27.
    Kirsner RS, Wilkinson JD, Ma F, Pacheco H, Federman DG (2005) THe association of medicare health care delivery systems with stage at diagnosis and survival for patients with melanoma. Arch Dermatol 141(6):753–757CrossRefPubMedGoogle Scholar
  28. 28.
    National Healthcare Quality and Disparities Reports (2015) Accessed 13 Nov 2015
  29. 29.
    Siminoff LA, Graham GC, Gordon NH (2006) Cancer communication patterns and the influence of patient characteristics: disparities in information-giving and affective behaviors. Patient Educ Couns 62(3):355–360CrossRefPubMedGoogle Scholar
  30. 30.
    Sommers BD, Baicker K, Epstein AM (2012) Mortality and access to care among adults after state medicaid expansions. N Engl J Med 367(11):1025–1034CrossRefPubMedGoogle Scholar
  31. 31.
    Sorkin DH, Ngo-Metzger Q, De Alba I (2010) Racial/ethnic discrimination in health care: impact on perceived quality of care. J Gen Intern Med 25(5):390–396CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Sarto GE, Brasileiro J, Franklin DJ (2013) Women’s health: racial and ethnic health inequities. Glob Adv Health Med 2(5):50–53CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Diez-Roux AV, Nieto FJ, Muntaner C, Tyroler HA, Comstock GW, Shahar E, Cooper LS, Watson RL, Szklo M (1997) Neighborhood environments and coronary heart disease: a multilevel analysis. Am J Epidemiol 146(1):48–63CrossRefPubMedGoogle Scholar
  34. 34.
    Krieger N, Chen JT, Waterman PD, Soobader M-J, Subramanian SV, Carson R (2002) Geocoding and monitoring of US socioeconomic inequalities in mortality and cancer incidence: does the choice of area-based measure and geographic level matter?: The Public Health Disparities Geocoding Project. Am J Epidemiol 156(5):471–482CrossRefPubMedGoogle Scholar
  35. 35.
    Søgaard M, Thomsen RW, Bossen KS, Sørensen HT, Nørgaard M (2013) The impact of comorbidity on cancer survival: a review. Clin Epidemiol 5(Suppl 1):3–29CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Aune G, Torp SH, Syversen U, Hagen B, Tingulstad S (2012) Ten years’ experience with centralized surgery of Ovarian Cancer in One Health Region in Norway. Int J Gynecol Cancer 22(2):226–231CrossRefPubMedGoogle Scholar
  37. 37.
    Vernooij F, Heintz APM, Coebergh J-W, Massuger LFAG, Witteveen PO, van der Graaf Y (2009) Specialized and high-volume care leads to better outcomes of ovarian cancer treatment in the Netherlands. Gynecol Oncol 112(3):455–461CrossRefPubMedGoogle Scholar
  38. 38.
    Bristow RE, Palis BE, Chi DS, Cliby WA (2010) The National Cancer Database report on advanced-stage epithelial ovarian cancer: impact of hospital surgical case volume on overall survival and surgical treatment paradigm. Gynecol Oncol 118(3):262–267CrossRefPubMedGoogle Scholar
  39. 39.
    NCI SEER Public-Use Data: Applications and Limitations in Oncology Research | Cancer Network, 18 Mar 2009. Accessed 12 Jan 2016
  40. 40.
    Surveillance, Epidemiology, and End Results Program Turning Cancer Data Into Discovery, 18 Mar 2009. Accessed 24 Nov 2015
  41. 41.
    Frey WH (2010) New racial segregation measures for states and large metropolitan areas: analysis of the 2005–2009 American Community Survey. Brookings Institute, Washington, DCGoogle Scholar
  42. 42.
    Cancer Incidence-Surveillance, Epidemiology, and End Results (SEER) Registries Research Data.
  43. 43.
    Number of Persons by Race and Hispanic Ethnicity for SEER Participants (2010) Census data, 18 Mar 2009. Accessed 24 Nov 2015

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Epidemiology and BiostatisticsUniversity of Illinois at ChicagoChicagoUSA
  2. 2.Department of Ophthalmology and Visual SciencesUniversity of Illinois at ChicagoChicagoUSA
  3. 3.3-317 Edmonton Clinic Health AcademyUniversity of Alberta School of Public HealthEdmontonCanada
  4. 4.Cancer Control and Population Science Research ProgramUniversity of Illinois at Chicago Cancer CenterChicagoUSA
  5. 5.Institute for Health Research and PolicyChicagoUSA
  6. 6.College of Medicine, Department of Hematology/OncologyUniversity of Illinois at ChicagoChicagoUSA

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