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Spatial–Temporal Cluster Analysis of Childhood Cancer in California

Francis, Stephen Starkoa,b,*; Enders, Catherinec; Hyde, Rebeccac; Gao, Xingc; Wang, Rongd; Ma, Xiaomeid; Wiemels, Joseph L.e; Selvin, Stevec; Metayer, Catherinec

doi: 10.1097/EDE.0000000000001121
Original Article: PDF Only

Background: The observance of non-random space–time groupings of childhood cancer has been a concern of health professionals and the general public for decades. Many childhood cancers are suspected to have initiated in utero; therefore, we examined the spatial–temporal randomness of the birthplace of children who later developed cancer.

Methods: We performed a space–time cluster analysis using birth addresses of 5,896 cases and 23,369 population-based, age-, sex- and race/ethnicity-matched controls in California from 1997-2007, evaluating 20 types of childhood cancer and three a priori designated subgroups of childhood acute lymphoblastic leukemia (ALL). We analyzed data using a newly designed semiparametric analysis program, ClustR, and a common algorithm, SaTScan.

Results: We observed evidence for non-random space–time clustering for ALL diagnosed at 2-6 years of age in the South San Francisco Bay Area (ClustR p=0.04, SaTScan p=0.07), and malignant gonadal germ cell tumors in a region of Los Angeles (ClustR p=0.03, SaTScan p=0.06). ClustR did not identify evidence of clustering for other childhood cancers, though SaTScan suggested some clustering for Hodgkin lymphoma (p=0.09), astrocytoma (p=0.06) and retinoblastoma (p=0.06).

Conclusion: Our study provides evidence that childhood ALL diagnosed at 2-6 years and malignant gonadal germ cell tumors sporadically occurs in non-random space–time clusters. Further research is warranted to identify epidemiologic features that may inform the underlying etiology.

a Department of Neurological Surgery, University of California, San Francisco, USA

b Division of Epidemiology, University of Nevada, Reno, USA

c Division of Epidemiology, University of California, Berkeley, USA

d Department of Chronic Disease Epidemiology, School of Public Health, Yale University, USA

e Department of Genetic Epidemiology, University of Southern California, USA

Conflicts of Interest: None declared.

Financial Support: The research was supported by a grant from Alex’s Lemonade Stand Foundation. The collection of cancer incidence data used in this study was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885; the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under contract HHSN261201000140C awarded to the Cancer Prevention Institute of California, contract HHSN261201000035C awarded to the University of Southern California, and contract HHSN261201000034C awarded to the Public Health Institute; and the Centers for Disease Control and Prevention’s National Program of Cancer Registries, under agreement U58DP003862-01 awarded to the California Department of Public Health. The ideas and opinions expressed herein are those of the author(s) and endorsement by the State of California, Department of Public Health, the National Cancer Institute, and the Centers for Disease Control and Prevention or their Contractors and Subcontractors is not intended nor should be inferred.

Corresponding Author:Stephen S. Francis email:

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