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Spatial cluster analysis of early stage breast cancer: a method for public health practice using cancer registry data

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Abstract

Objectives

Cancer registries are increasingly mapping residences of patients at time of diagnosis, however, an accepted protocol for spatial analysis of these data is lacking. We undertook a public health practice–research partnership to develop a strategy for detecting spatial clusters of early stage breast cancer using registry data.

Methods

Spatial patterns of early stage breast cancer throughout Michigan were analyzed comparing several scales of spatial support, and different clustering algorithms.

Results

Analyses relying on point data identified spatial clusters not detected using data aggregated into census block groups, census tracts, or legislative districts. Further, using point data, Cuzick-Edwards’ nearest neighbor test identified clusters not detected by the SaTScan spatial scan statistic. Regression and simulation analyses lent credibility to these findings.

Conclusions

In these cluster analyses of early stage breast cancer in Michigan, spatial analyses of point data are more sensitive than analyses relying on data aggregated into polygons, and the Cuzick-Edwards’ test is more sensitive than the SaTScan spatial scan statistic, with acceptable Type I error. Cuzick-Edwards’ test also enables presentation of results in a manner easily communicated to public health practitioners. The approach outlined here should help cancer registries conduct and communicate results of geographic analyses.

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Acknowledgments

This research was supported in part by CDC Grant 5U58DP000812 and by NCI Grants 1R43CA112743, 1R43CA132347, and 1R43CA135818. The perspectives are those of the authors and do not necessarily represent the official position of the funding agencies.

Author information

Authors and Affiliations

  1. Graduate Program in Public Health, Department of Preventive Medicine, Stony Brook University Medical Center, HSC L3, Rm 071, Stony Brook, NY, 11794-8338, USA

    Jaymie R. Meliker

  2. BioMedware, Inc, Ann Arbor, MI, USA

    Jaymie R. Meliker, Geoffrey M. Jacquez & Pierre Goovaerts

  3. Michigan Department of Community Health, Michigan Cancer Surveillance Program, Lansing, MI, USA

    Glenn Copeland

  4. Cancer Control Services Program, Michigan Public Health Institute, Okemos, MI, USA

    May Yassine

Authors
  1. Jaymie R. Meliker
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  2. Geoffrey M. Jacquez
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  4. Glenn Copeland
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  5. May Yassine
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Correspondence to Jaymie R. Meliker.

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Meliker, J.R., Jacquez, G.M., Goovaerts, P. et al. Spatial cluster analysis of early stage breast cancer: a method for public health practice using cancer registry data. Cancer Causes Control 20, 1061–1069 (2009). https://doi.org/10.1007/s10552-009-9312-4

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  • DOI: https://doi.org/10.1007/s10552-009-9312-4

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