Cancer map patterns: are they random or not?

BACKGROUND Maps depicting the geographic variation in cancer incidence, mortality or treatment can be useful tools for developing cancer control and prevention programs, as well as for generating etiologic hypotheses. An important question with every cancer map is whether the geographic pattern seen is due to random fluctuations, as by pure chance there are always some areas with more cases than expected, or whether the map reflects true underlying geographic variation in screening, treatment practices, or etiologic risk factors. METHODS Nine different tests for spatial randomness are evaluated in very practical settings by applying them to cancer maps for different types of data at different scales of spatial resolution: breast, prostate, and thyroid cancer incidence; breast cancer treatment and prostate cancer stage in Connecticut; and nasopharynx and prostate cancer mortality in the U.S. RESULTS Tango's MEET, Oden's Ipop, and the spatial scan statistic performed well across all the data sets. Besag-Newell's R, Cuzick-Edwards k-NN, and Turnbull's CEPP often perform well, but the results are highly dependent on the parameter chosen. Moran's I performs poorly for most data sets, whereas Swartz Entropy Test and Whittemore's Test perform well for some data sets but not for other. CONCLUSIONS When publishing cancer maps we recommend evaluating the spatial patterns observed using Tango's MEET, a global clustering test, and the spatial scan statistic, a cluster detection test.

[1]  Julian Besag,et al.  The Detection of Clusters in Rare Diseases , 1991 .

[2]  Troy C. Blanchard,et al.  A brief visual primer for the mapping of mortality trend data , 2004, International journal of health geographics.

[3]  M. Schader,et al.  New Approaches in Classification and Data Analysis , 1994 .

[4]  Martin Kulldorff,et al.  The geographic distribution of breast cancer incidence in Massachusetts 1988 to 1997, adjusted for covariates , 2004, International journal of health geographics.

[5]  William J. Blot,et al.  Atlas of Cancer Mortality in the United States 1950-94 , 2000 .

[6]  Peter J. Park,et al.  Power comparisons for disease clustering tests , 2003, Comput. Stat. Data Anal..

[7]  Robert Haining,et al.  Spatial Statistics and the Analysis of Health Data , 1998 .

[8]  Rainer Frentzel-Beyme,et al.  Atlas of Cancer Mortality in the Federal Republic of Germany , 1984 .

[9]  S. Jarcho.  Atlas of Cancer Mortality for U.S. Counties , 1976 .

[10]  M Kulldorff.  Mathematical formula for Swartz' Entropy Test Statistic. , 1999, Health & place.

[11]  Martin Kulldorff,et al.  Geographical Differences in Primary Therapy for Early-Stage Breast Cancer , 2001, Annals of Surgical Oncology.

[12]  T. Mason,et al.  Atlas of cancer mortality for U.S. counties, 1950-1969 , 1975 .

[13]  B. Turnbull,et al.  Monitoring for clusters of disease: application to leukemia incidence in upstate New York. , 1990, American journal of epidemiology.

[14]  J B Swartz,et al.  An entropy-based algorithm for detecting clusters of cases and controls and its comparison with a method using nearest neighbours. , 1998, Health & place.

[15]  T. Tango,et al.  A test for spatial disease clustering adjusted for multiple testing. , 2000, Statistics in medicine.

[16]  F. Boscoe,et al.  Visualization of the spatial scan statistic using nested circles. , 2003, Health & place.

[17]  Holly Jacobson,et al.  Evaluating the disparity of female breast cancer mortality among racial groups - a spatiotemporal analysis , 2004, International journal of health geographics.

[18]  M. Kulldorff,et al.  A geographic analysis of prostate cancer mortality in the United States, 1970–89 , 2002, International journal of cancer.

[19]  Olaf Berke,et al.  Exploratory disease mapping: kriging the spatial risk function from regional count data , 2004 .

[20]  G Molenberghs,et al.  Geographical differences in cancer incidence in the Belgian province of Limburg. , 2003, European journal of cancer.

[21]  M Smans,et al.  Analysis of spatial aggregation. , 1989, Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer.

[22]  N. Oden,et al.  Adjusting Moran's I for population density. , 1995, Statistics in medicine.

[23]  A. Whittemore,et al.  A test to detect clusters of disease , 1987 .

[24]  Linda W. Pickle,et al.  Atlas of United States Mortality , 1996 .

[25]  Mall Leinsalu,et al.  Eesti suremusatlas : Atlas of Mortality in Estonia , 1997 .

[26]  J. Cuzick,et al.  Spatial clustering for inhomogeneous populations , 1990 .

[27]  Martin Kulldorff,et al.  Lumping or splitting: seeking the preferred areal unit for health geography studies , 2005, International journal of health geographics.

[28]  Gonzalo López-Abente,et al.  Atlas de mortalidad por cáncer y otras causas en España, 1978-1992 , 2001 .

[29]  Anthony J. Swerdlow,et al.  Atlas of Cancer Incidence in England and Wales 1968-85: Based on data from the cancer registries of England and Wales, with the cooperation of the Office of Population Censuses and Surveys , 1994 .

[30]  G. Jacquez,et al.  Local clustering in breast, lung and colorectal cancer in Long Island, New York , 2003, International journal of health geographics.

[31]  I. Kemp,et al.  Atlas of cancer in Scotland, 1975-1980 : incidence and epidemiological perspective , 1985 .

[32]  Georges Schüler,et al.  Atlas der Krebsmortalität in der Schweiz 1970-1990 , 1996 .

[33]  L. Pickle,et al.  Exploring spatial patterns of mortality: the new atlas of United States mortality. , 1999, Statistics in medicine.

[34]  Bradley P Carlin,et al.  Late detection of breast and colorectal cancer in Minnesota counties: an application of spatial smoothing and clustering. , 2003, Statistics in medicine.

[35]  L. Pickle,et al.  Snuff dipping and oral cancer among women in the southern United States. , 1981, The New England journal of medicine.

[36]  Hunt Dc,et al.  Use of a behavioral risk survey by employers to identify leading health problems among employees and their dependents. , 2002 .

[37]  Martin Kulldorff,et al.  Power evaluation of disease clustering tests , 2003, International journal of health geographics.

[38]  T Tango,et al.  A class of tests for detecting 'general' and 'focused' clustering of rare diseases. , 1995, Statistics in medicine.

[39]  A. Gatrell,et al.  GIS and health , 1998 .

[40]  Peter A. Rogerson,et al.  The Detection of Clusters Using a Spatial Version of the Chi‐Square Goodness‐of‐Fit Statistic , 1999 .

[41]  G Rushton,et al.  Women with localized breast cancer selecting mastectomy treatment, Iowa, 1991-1996. , 1999, Public health reports.

[42]  P. Moran.  Notes on continuous stochastic phenomena. , 1950, Biometrika.

[43]  M Smans,et al.  Atlas of cancer incidence in the former German Democratic Republic 1978-1982. , 1993, IARC scientific publications.

[44]  M. Kulldorff.  A spatial scan statistic , 1997 .

[45]  Alan M. MacEachren,et al.  Visualizing Georeferenced Data: Representing Reliability of Health Statistics , 1998 .

[46]  Werner Vach,et al.  Locally optimal tests on spatial clustering , 1994 .

[47]  M Kulldorff,et al.  Geographic assessment of breast cancer screening by towns, zip codes, and census tracts. , 2000, Journal of public health management and practice : JPHMP.

[48]  Ric Skinner,et al.  Use of a geographic information system to identify and characterize areas with high proportions of distant stage breast cancer. , 2002, Journal of public health management and practice : JPHMP.

[49]  Martin Kulldorff,et al.  Geographic differences in invasive and in situ breast cancer incidence according to precise geographic coordinates, Connecticut, 1991–95 , 2002, International journal of cancer.

[50]  Martin Kulldorff,et al.  Geographic distribution of prostate cancer incidence in the era of PSA testing, Connecticut, 1984 to 1998. , 2004, Urology.

[51]  Cynthia A. Brewer,et al.  Mapping Mortality: Evaluating Color Schemes for Choropleth Maps , 1997 .