Cancer Causes & Control

, Volume 29, Issue 4–5, pp 445–453 | Cite as

A spatiotemporal analysis of invasive cervical cancer incidence in the state of Maryland between 2003 and 2012

  • Sally Peprah
  • Frank C. Curreiro
  • Jennifer H. Hayes
  • Kimberly Stern
  • Shalini Parekh
  • Gypsyamber D’Souza
Original paper



Invasive cervical cancer (ICC) rates have tremendously declined in the United States, yet new cases consistently occur in Maryland and throughout the United States. We hypothesized that although rates have generally declined, this decline is uneven across counties and over time.


Space–time cluster detection analysis was conducted to evaluate clusters of ICC incidence at the county level within Maryland between 2003 and 2012.


The most likely cluster was a cluster of low incidence, which included 6 counties in eastern Maryland for the period 2009–2012. A secondary cluster of low rates, comprising 2 metropolitan counties in northern Maryland, was observed for the period 2009–2012. Two of the three clusters of high ICC rates occurred in 2009–2012 in the large metropolitan area of Baltimore City and another cluster in Frederick County, in rural western Maryland. The third cluster of high rates was observed 2005–2008, in western Maryland.


In recent periods, some Maryland counties have experienced anomalously high or low ICC incidence. Clusters of high incidence are not explained by differences in screening rates and may be due to failures in follow-up care for cervical abnormalities that need to be investigated. Clusters of low incidence may represent areas of successful ICC control.


Space–time cluster detection Spatial epidemiology Cervical cancer Cancer surveillance SaTScan 



We acknowledge the State of Maryland, the Maryland Cigarette Restitution Fund, and the National Program of Cancer Registries of the Centers for Disease Control and Prevention for the funds that support the collection and availability of the cancer registry data. The findings and conclusions of this study do not necessarily represent views of the Maryland Cancer Registry.


Sally Peprah was supported by the National Cancer Institute’s T32 CA009314 training grant. This research was also supported by P30CA006973.

Compliance with ethical standards

Conflict of interest

The authors declare no potential conflicts of interest.

Ethical approval

The Institutional Review Boards of Johns Hopkins School of Public Health and the Maryland Department of Health and Mental Hygiene approved this study.

Supplementary material

10552_2018_1019_MOESM1_ESM.docx (61 kb)
Supplementary material 1 (DOCX 60 KB)
10552_2018_1019_MOESM2_ESM.png (1.9 mb)
Supplemental Figure 1. Choropleth map of average annual crude incidence of invasive cervical cancer per 100,000 women by county in Maryland, 2003-2012 (PNG 1926 KB)


  1. 1.
    Simard EP, Fedewa S, Ma J et al (2012) Widening socioeconomic disparities in cervical cancer mortality among women in 26 states, 1993–2007. Cancer 118:5110–5116. CrossRefPubMedGoogle Scholar
  2. 2.
    Downs LS, Smith JS, Scarinci I et al (2008) The disparity of cervical cancer in diverse populations. Gynecol Oncol 109:S22–S30. CrossRefPubMedGoogle Scholar
  3. 3.
    Cancer of the Cervix Uteri—Cancer Stat Facts. Accessed 11 Oct 2017
  4. 4.
    National Cancer Institute (2009) Cancer trends progress report—2009/2010 update. National Cancer Institute, BethesdaGoogle Scholar
  5. 5.
    Horner M-J, Altekruse SF, Zou J et al (2011) US geographic distribution of pre-vaccine era cervical cancer screening, incidence, stage, and mortality. Cancer Epidemiol Biomark Prev 20:591–599. CrossRefGoogle Scholar
  6. 6.
    Muñoz N, Castellsagué X, de González AB, Gissmann L (2006) Chap. 1: HPV in the etiology of human cancer. Vaccine 24:S1–S10. CrossRefGoogle Scholar
  7. 7.
    Akers AY, Newmann SJ, Smith JS (2007) Factors underlying disparities in cervical cancer incidence, screening, and treatment in the United States. Curr Probl Cancer 31:157–181. CrossRefPubMedGoogle Scholar
  8. 8.
    Smedley B, Stith A, Nelson A (2003) Unequal treatment: confronting racial and ethnic disparities in health care. J Natl Med Assoc. Google Scholar
  9. 9.
    Cancer|Healthy People 2020. Accessed 11 Oct 2017
  10. 10.
    Cancer Facts & Figures| Hispanics-Latinos | American Cancer Society. Accessed 15 Oct 2017
  11. 11.
    Cancer Facts & Figures for African Americans | American Cancer Society. Accessed 15 Oct 2017
  12. 12.
    Jemal A, Bray F, Center MM et al (2011) Global cancer statistics. CA Cancer J Clin 61:69–90. CrossRefPubMedGoogle Scholar
  13. 13.
    Rositch AF, Nowak RG, Gravitt PE (2014) Increased age and race-specific incidence of cervical cancer after correction for hysterectomy prevalence in the United States from 2000 to 2009. Cancer 120:2032–2038. CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Fleming S, Schluterman NH, Tracy JK, Temkin SM (2014) Black and white women in Maryland receive different treatment for cervical cancer. PLoS ONE 9:e104344. CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Maryland Department of Health and Mental Hygiene (2011) Maryland Comprehensive Cancer Control Plan 2011–2015. Accessed 11 Oct 2017
  16. 16.
    Maryland Department of Health and Mental Hygiene (2016) Maryland Comprehensive Cancer Control Plan 2016–2020. Accessed 11 Oct 2017
  17. 17.
    Center for Disease Control (2017) National breast and cervical cancer early detection program: screening program summaries, Maryland. Accessed 11 Oct 2017
  18. 18.
    Richardson K, Steinberger EK, Groves C, Lewis C (2014) An analysis of Behavioral Risk Factor Surveillance System Data. Department of Epidemiology and Public Health. University of Maryland School of Medicine, Baltimore, MD and Center for Cancer Prevention and Control, Maryland Department of Health and Mental Hygiene, BaltimoreGoogle Scholar
  19. 19.
    Maryland Department of Health and Mental Hygiene (2014) Maryland Cancer Report. Accessed 11 Oct 2017
  20. 20.
    Waller LA, Gotway CA (2004) Applied spatial statistics for public health data. Wiley, New YorkCrossRefGoogle Scholar
  21. 21.
    Boulos MNK (2004) Towards evidence-based, GIS-driven national spatial health information infrastructure and surveillance services in the United Kingdom. Int J Health Geogr 3:1. CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Salinas-Pérez JA, García-Alonso CR, Molina-Parrilla C et al (2012) Identification and location of hot and cold spots of treated prevalence of depression in Catalonia (Spain). Int J Health Geogr 11:36. CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Clarke KC, McLafferty SL, Tempalski BJ (1996) On epidemiology and geographic information systems: a review and discussion of future directions. Emerg Infect Dis 2:85–92CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Solano R, Gómez-Barroso D, Simón F et al (2014) Retrospective space-time cluster analysis of whooping cough re-emergence in Barcelona, Spain, 2000–2011. Geospatial Health 8:455–461CrossRefPubMedGoogle Scholar
  25. 25.
    Sherman RL, Henry KA, Tannenbaum SL et al (2014) Applying spatial analysis tools in public health: an example using SaTScan to detect geographic targets for colorectal cancer screening interventions. Prev Chronic Dis 11:E41. CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    US Census Bureau DID Small Area Income & Poverty Estimates (SAIPE). Accessed 11 Oct 2017
  27. 27.
  28. 28.
    ESRI (Environmental Systems Research Institute) (2011) ArcGIS desktop: release 10. Environmental Systems Research Institute. RedlandsGoogle Scholar
  29. 29.
    Kulldorff M (1997) A spatial scan statistic. Commun Stat 26:1481–1496. CrossRefGoogle Scholar
  30. 30.
    Space-Time Clusters with Flexible Shapes. Accessed 12 Oct 2017
  31. 31.
    Kulldorff M (2010) SaTScan user guide for version 9.0. Academic Press, CambridgeGoogle Scholar
  32. 32.
    Kulldorff M, Athas WF, Feurer EJ et al (1998) Evaluating cluster alarms: a space-time scan statistic and brain cancer in Los Alamos, New Mexico. Am J Public Health 88:1377–1380. CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Klassen AC, Kulldorff M, Curriero F (2005) Geographical clustering of prostate cancer grade and stage at diagnosis, before and after adjustment for risk factors. Int J Health Geogr 4:1. CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Jung I (2009) A generalized linear models approach to spatial scan statistics for covariate adjustment. Stat Med 28:1131–1143. CrossRefPubMedGoogle Scholar
  35. 35.
    StataCorp LP (2015) Stata Statistical software: release 14. USA StataCorp LP, College StationGoogle Scholar
  36. 36.
    Ingram DD, Franco SJ (2012) NCHS urban-rural classification scheme for counties. Vital Health Stat 2:1–65Google Scholar
  37. 37.
    Maryland Economy—Income. Accessed 12 Oct 2017
  38. 38.
    Sung H-Y, Kearney KA, Miller M et al (2000) Papanicolaou smear history and diagnosis of invasive cervical carcinoma among members of a large prepaid health plan. Cancer 88:2283–2289CrossRefPubMedGoogle Scholar
  39. 39.
    Spence AR, Goggin P, Franco EL (2007) Process of care failures in invasive cervical cancer: systematic review and meta-analysis. Prev Med 45:93–106. CrossRefPubMedGoogle Scholar
  40. 40.
    Wingrove BK, Center to Reduce Cancer Health Disparities (U.S.) (2005) Excess cervical cancer mortality: a marker for low access to health care in poor communities: an analysis. National Cancer Institute, Center to Reduce Cancer Health Disparities, RockvilleGoogle Scholar
  41. 41.
    Eggleston KS, Coker AL, Das IP et al (2007) Understanding Barriers for Adherence to Follow-Up Care for Abnormal Pap Tests. J Womens Health 16:311–330. CrossRefGoogle Scholar
  42. 42.
    Benard VB, Johnson CJ, Thompson TD et al (2008) Examining the association between socioeconomic status and potential human papillomavirus-associated cancers. Cancer 113:2910–2918. CrossRefPubMedGoogle Scholar
  43. 43.
    Tejeda S, Darnell JS, Cho YI et al (2013) Patient barriers to follow-up care for breast and cervical cancer abnormalities. J Womens Health 22:507–517. CrossRefGoogle Scholar
  44. 44.
    Vital signs: HIV Diagnosis, care, and treatment among persons living with HIV—United States, 2011. Accessed 12 Oct 2017
  45. 45.
    Women | Gender | HIV by Group | HIV/AIDS|CDC. Accessed 12 Oct 2017
  46. 46.
    Ryerson AB, Eheman CR, Altekruse SF et al (2016) Annual report to the nation on the status of cancer, 1975–2012, featuring the increasing incidence of liver cancer. Cancer 122:1312–1337. CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Klassen AC, Curriero FC, Hong JH et al (2004) The role of area-level influences on prostate cancer grade and stage at diagnosis. Prev Med 39:441–448. CrossRefPubMedGoogle Scholar
  48. 48.
    Macintyre S, Ellaway A, Cummins S (2002) Place effects on health: how can we conceptualise, operationalise and measure them? Soc Sci Med 55:125–139CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Sally Peprah
    • 1
  • Frank C. Curreiro
    • 1
  • Jennifer H. Hayes
    • 2
  • Kimberly Stern
    • 2
  • Shalini Parekh
    • 2
  • Gypsyamber D’Souza
    • 1
  1. 1.Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  2. 2.Maryland Cancer Registry, Center for Cancer Prevention and ControlMaryland Department of Health and Mental HygieneBaltimoreUSA

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