Methods Inf Med 2001; 40(02): 127-131
DOI: 10.1055/s-0038-1634474
Original Article
Schattauer GmbH

Childhood Leukaemia Clustering – Fact or Artefact?

J. F. Bithell
1   University of Oxford, UK
› Author Affiliations
Further Information

Publication History

Publication Date:
07 February 2018 (online)

Abstract

There is a general belief that the clustering of childhood leukaemia is a widespread phenomenon and that it provides evidence for appreciable environmental influence on the incidence of the disease. We discuss this issue critically, identifying different kinds of clustering and their possible aetiological mechanisms and examining some analyses of British data. We argue that, in some cases, analyses have been used which lead to dubious conclusions, and that, allowing for multiple testing and anecdotal reporting, the total evidence for clustering is at best weak.

 
  • References

  • 1 Bithell JF. Leukaemia Clusters. Encyclopedia of Biostatistics. New York: Wiley; 1998
  • 2 Cook-Mozaffari PJ, Darby SC, Doll R, Forman D, Hermon C, Pike MC, Vincent T. Geographical variation in mortality from leukaemia and other cancers in England and Wales in relation to proximity to nuclear installations, 1969-1978. Br J Cancer 1989; 59: 476-85.
  • 3 Jablon S, Hrubec Z, Boice JD. Cancer in populations living near nuclear-facilities – a survey of mortality nationwide and incidence in 2 states. Journal of the American Medical Association 1991; 265 (Suppl. 11) 1403-8.
  • 4 Bithell JF, Dutton SJ, Draper GJ, Neary NM. The distribution of childhood leukaemias and non-Hodgkin’s lymphomas near nuclear installations in England and Wales. British Medical Journal 1994; 309 6953 501-5.
  • 5 Bithell JF. The choice of test for detecting raised disease risk near a point source. Stat Med 1995; 14 (Suppl. 21) 2309-22.
  • 6 Stone RA. Investigations of excess environmental risk around putative sources – statistical problems and a proposed test. Stat Med 1988; 7 (Suppl. 06) 649-60.
  • 7 Draper GJ, Vincent TJ, O’Connor CM, Stiller CA. Socio-economic factors and variations in incidence rates between County Districts. In: Draper GJ. ed. The Geographical Epidemiology of Childhood Leukaemia and non-Hodgkin Lymphomas in Great Britain, 1966-83. Studies on Medical and Population Subjects, No. 53. London: HMSO; 1991: 37-45.
  • 8 Bithell JF, Vincent TJ. Geographical Variations in Childhood Leukaemia. In: Elliott P, Wakefield JC, Best NG, Briggs DJ. (eds.). Spatial Epidemiology: Methods and Applications. Oxford: Oxford University Press; 2000
  • 9 Alexander FE, Boyle P, Carli P-M, Coebergh JW, Draper GJ, Ekbom A, Levi F, McKinney PA, McWhirter W, Michaelis J, Peris-Bonet R, Petridou E, Pompe-Kirn V, Plìsko I, Pukkala E, Rahu M, Storm H, Terracini B, Vatten L, Wray N. Spatial clustering of childhood leukaemia: summary results from the EUROCLUS project. Br J Cancer 1998; 77 (Suppl. 05) 818-24.
  • 10 Potthoff RF, Whittinghill M. Testing for homogeneity II. The Poisson distribution. Biometrika 1966; 53: 183-90.
  • 11 Bithell JF, Dutton SJ, Neary NM, Vincent TJ. Controlling for socio-economic confounding using regression methods. J Epidemiol Community Health 1995; 49 Suppl 2 S15-S19.
  • 12 Kinlen LJ. Epidemiological evidence for an infective basis in childhood leukaemia. Br J Cancer 1995; 71: 1-5.
  • 13 Stiller CA, Boyle J. Effect of population mixing and socioeconomic status in England and Wales, 1979-85, on lymphoblastic leukaemia in children. British Medical Journal 1996; 313 7068 1297-300.
  • 14 Dickinson HO, Parker L. Quantifying the effect of population mixing on childhood leukaemia risk: the Seascale cluster. Br J Cancer 1999; 81 (Suppl. 01) 144-51.
  • 15 Knox EG. The detection of space-time interactions. Applied Statistics 1964; 13: 25-9.
  • 16 Jacquez GM. A k nearest neighbour test for space-time interaction. Stat in Med 1996; 15 17-18 1935-49.
  • 17 Gilman EA, Knox EG. Temporal-spatial distribution of childhood leukaemias and non-Hodgkin lymphomas in Great Britain. In: Draper GJ. ed. The Geographical Epidemiology of Childhood Leukaemia and non-Hodgkin Lymphomas in Great Britain, 1966-83. Studies on Medical and Population Subjects, No. 53. London: HMSO; 1991: 77-99.
  • 18 Gilman EA, Knox EG. Childhood cancers: space-time distribution in Britain. J Epidemiol Community Health 1995; 49: 158-63.
  • 19 Abe O. A note on the methodology of Knox’s tests of Time and Space Interaction. Biometrics 1973; 29: 67-77.
  • 20 Kulldorf M. The Knox method and other tests for space-time interaction. Biometrics 1999; 55: 544-52.
  • 21 Tobler WR. A continuous transformation useful for districting. Annals New York Academy of Sciences 1973; 219: 215-20.
  • 22 Schulman J, Selvin S, Merrill DW. Density equalized map projections: a method for analysing clustering around a fixed point. Stat in Med 1988; 7: 491-505.
  • 23 Merrill DW, Selvin S, Close ER, Holmes HH. Use of density equalizing map projections (DEMP) in the analysis of childhood cancer in four California counties. Stat in Med 1996; 15: 1837-48.
  • 24 Merrill DW. Density Equalizing Map Projections (Cartograms) in Public Health Applications,. Appendix D: Comparison with earlier results. Report LBNL-41624, Lawrence Berkeley National Laboratory; California: [also published online at http://library.lbl.gov/docs/LBNL/416/24/HTML/index.html/and/appxd.html ].
  • 25 Bithell JF. A Classification of Disease Mapping Methods. Stat in Med 2000; 19: 2203-15.
  • 26 Knox EG. Leukaemia clusters in childhood: geographical analysis in Britain. J Epidemiol Community Health 1994; 48: 369-76.
  • 27 Bithell JF, Draper GJ. Apparent association between benzene and childhood leukaemia: Methodological doubts concerning a report by Knox. J Epidemiol Community Health 1995; 49 (Suppl. 04) 437-9.
  • 28 Oliver MA, Mann JR, Webster R, Muir KR. Analysing the spatial pattern of rare disease. In: Fabbri AG, Royer JJ. eds. 3rd CODATA Conference on Geomathematics and Geostatistics. Sci. de la Terre, Sér. Inf., Nancy 1994; 32: 433-47.
  • 29 Greaves MF. Aetiology of acute leukaemia. Lancet 1997; 349: 344-9.