title: Spatial clustering of childhood leukaemia: summary results from the EUROCLUS project.
abstract: The interpretation of reports of clusters of childhood leukaemia is difficult, first because little is known about the causes of the disease, and second because there is insufficient information on whether cases show a generalized tendency to cluster geographically. The EUROCLUS project is a European collaborative study whose primary objective is to determine whether the residence locations of cases at diagnosis show a general tendency towards spatial clustering. The second objective is to interpret any patterns observed and, in particular, to see if clustering can be explained in terms of either infectious agents or environmental hazards as aetiological agents. The spatial distribution of 13351 cases of childhood leukaemia diagnosed in 17 countries between 1980 and 1989 has been analysed using the Potthoff-Whittinghill method. The overall results show statistically significant evidence of clustering of total childhood leukaemia within small census areas (P=0.03) but the magnitude of the clustering is small (extra-Poisson component of variance (%) = 1.7 with 90% confidence interval 0.2-3.1). The clustering is most marked in areas that have intermediate population density (150-499 persons km[-2]). It cannot be attributed to any specific age group at diagnosis or cell type and involves spatial aggregation of cases of different ages and cell types. The results indicate that intense clusters are a rare phenomenon that merit careful investigation, although aetiological insights are more likely to come from investigation of large numbers of cases. We present a method for detecting clustering that is simple and readily available to cancer registries and similar groups.
authors.affiliation: Department of Public Health Sciences, The University of Edinburgh, Medical School, UK.
authors.forename: F E
authors.initials: FE
authors.lastname: Alexander
authors.forename: P
authors.initials: P
authors.lastname: Boyle
authors.forename: P M
authors.initials: PM
authors.lastname: Carli
authors.forename: J W
authors.initials: JW
authors.lastname: Coebergh
authors.forename: G J
authors.initials: GJ
authors.lastname: Draper
authors.forename: A
authors.initials: A
authors.lastname: Ekbom
authors.forename: F
authors.initials: F
authors.lastname: Levi
authors.forename: P A
authors.initials: PA
authors.lastname: McKinney
authors.forename: W
authors.initials: W
authors.lastname: McWhirter
authors.forename: J
authors.initials: J
authors.lastname: Michaelis
authors.forename: R
authors.initials: R
authors.lastname: Peris-Bonet
authors.forename: E
authors.initials: E
authors.lastname: Petridou
authors.forename: V
authors.initials: V
authors.lastname: Pompe-Kirn
authors.forename: I
authors.initials: I
authors.lastname: Plìsko
authors.forename: E
authors.initials: E
authors.lastname: Pukkala
authors.forename: M
authors.initials: M
authors.lastname: Rahu
authors.forename: H
authors.initials: H
authors.lastname: Storm
authors.forename: B
authors.initials: B
authors.lastname: Terracini
authors.forename: L
authors.initials: L
authors.lastname: Vatten
authors.forename: N
authors.initials: N
authors.lastname: Wray
mesh_terms: D000293:Adolescent; D000367:Age Factors; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D004781:Environmental Exposure; D005060:Europe / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D007239:Infections / Q000150:complications; D007938:Leukemia / Q000145:classification / Q000453:epidemiology* / Q000209:etiology; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000453:epidemiology / Q000209:etiology; D012306:Risk; D012424:Rural Population; D014505:Urban Population