spatial clustering in the incidence of selected cancers in ... · time trends in selected cancers...
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Spatial Clustering in the Spatial Clustering in the Incidence of Selected Cancers in Incidence of Selected Cancers in
New JerseyNew Jersey
Jerald Fagliano MPH PhDJerald Fagliano MPH PhDMichael Berry MPH, Barbara Michael Berry MPH, Barbara GounGoun MPH PhD, Kevin Henry PhD, MPH PhD, Kevin Henry PhD,
Richard Richard OpiekunOpiekun MS MA PhD, Lisa Roche PhDMS MA PhD, Lisa Roche PhD
New Jersey Department of Health and Senior ServicesNew Jersey Department of Health and Senior Services
Environmental Public Health Tracking ConferenceEnvironmental Public Health Tracking ConferenceAtlanta, GAAtlanta, GAApril 2005April 2005
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Purpose and ContextPurpose and Context
ContextContextNJ Cancer Cluster Task ForceNJ Cancer Cluster Task ForceEPHT demonstration projectEPHT demonstration project
What can we learn from spatial analysis of What can we learn from spatial analysis of the incidence of selected cancers in New the incidence of selected cancers in New Jersey?Jersey?
MethodsMethodsIssues and interpretationIssues and interpretation
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Cancer Types ExaminedCancer Types Examined
Spatial and TemporalSpatial and TemporalMesotheliomaMesotheliomaLeukemiasLeukemiasBrain and other Brain and other nervous systemnervous systemThyroidThyroidUrinary bladderUrinary bladderBone and joint
TemporalTemporalSoft tissue sarcomaSoft tissue sarcomaNonNon--Hodgkin lymphomaHodgkin lymphomaLarynxLarynxNasopharynxNasopharynxNose, nasal cavity and Nose, nasal cavity and middle ear middle ear Kidney and renal pelvisKidney and renal pelvisLung and bronchusLung and bronchusLiver
Bone and joint
Liver
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Time Trends in Selected CancersTime Trends in Selected CancersLung Cancer Incidence, NJ
1979-2001
0.020.040.060.080.0
100.0120.0140.0
1979
1982
1985
1988
1991
1994
1997
2000
MaleFemale
Thyroid Cancer Incidence, NJ1979-2001
0.0
5.0
10.0
15.0
20.0
1979
1982
1985
1988
1991
1994
1997
2000
MaleFemale
Bladder Cancer Incidence, NJ1979-2001
0102030405060
1979
1982
1985
1988
1991
1994
1997
2000
Year
Rat
e pe
r 10
0,00
0MaleFemale
Non-Hodgkin Lymphoma Incidence, NJ, 1979-2001
05
1015202530
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
Year
Rat
e pe
r 10
0,00
0
MaleFemale
Rates per 100,000, age-adjusted to the year 2000 U.S. standard population
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Method to Detect Spatial ClusteringMethod to Detect Spatial Clustering
SaTScanSaTScan software (software (KulldorffKulldorff 2004) 2004) Spatial scan statistic tests for “the existence Spatial scan statistic tests for “the existence of statistically significant localized clusters of statistically significant localized clusters while at the same time pinpointing their while at the same time pinpointing their locations.” (locations.” (KulldorffKulldorff 1999)1999)Identifies “the cluster that is least likely to Identifies “the cluster that is least likely to have occurred by chance” and secondary have occurred by chance” and secondary clusters tooclusters too
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Input Data for Input Data for SaTScanSaTScan AnalysisAnalysis
Case data: NJ State Cancer RegistryCase data: NJ State Cancer RegistryIncident cases, 1979Incident cases, 1979--20012001GeocodingGeocoding to census tract to census tract
Population data: US CensusPopulation data: US CensusCensus tract by age group and sex Census tract by age group and sex GeoLyticsGeoLytics, Inc. file, 1980, 1990, 2000, Inc. file, 1980, 1990, 2000
Coordinate (spatial reference) dataCoordinate (spatial reference) dataYear 2000 census tracts (n=1,950) Year 2000 census tracts (n=1,950)
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SaTScanSaTScan SettingsSettings
Spatial and spatialSpatial and spatial--temporal analysestemporal analysesPoisson probability model (SIR)Poisson probability model (SIR)Scan for high relative ratesScan for high relative ratesMonte Carlo simulation generates pMonte Carlo simulation generates p--valuevalueSet maximum cluster sizeSet maximum cluster size
Default 50% of population at riskDefault 50% of population at riskNo geographical overlap for secondary No geographical overlap for secondary cluster reportingcluster reporting
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SaTScanSaTScan Process Process
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Example: Example: MesotheliomaMesothelioma
Known to Known to cluster cluster geographicallygeographicallyHistoric Historic occupational occupational exposures to exposures to asbestosasbestos
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Spatial vs. SpatialSpatial vs. Spatial--Temporal ClusteringTemporal Clustering
Spatial Spatial-Temporal
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SpatialSpatial--Temporal vs. Temporal vs. Spatial Clustering through Time, ISpatial Clustering through Time, I
1979-1983 1984 -1989
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SpatialSpatial--Temporal vs. Temporal vs. Spatial Clustering through Time, IISpatial Clustering through Time, II
1990-1995 1996 - 2001
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Spatial Clustering: Spatial Clustering: Setting Maximum SizeSetting Maximum Size
Max Cluster Base 50% of Pop Max Cluster Base 1% of Pop
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Loss of Case Data Due to Loss of Case Data Due to Inaccurate Inaccurate GeocodingGeocoding
Leukemia Cases Used in Spatial Analysis,1979-2001
Included81%
Excluded - Hospital
10%
Excluded - Death
certificate9%
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Geographic Variation in Geographic Variation in Loss Due to Loss Due to GeocodingGeocoding InaccuracyInaccuracy
1991-20011979-1990
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Preliminary Spatial Cluster ResultsPreliminary Spatial Cluster Results
Cancer TypeCancer Type Spatial Clustering?Spatial Clustering?MesotheliomaMesothelioma Local clustering, high RRLocal clustering, high RR
LeukemiasLeukemias Large area, low increase in RRLarge area, low increase in RRChildren: no significant clustersChildren: no significant clusters
Brain and Other Brain and Other Nervous SystemNervous System
Large area, low increase in RRLarge area, low increase in RRChildren: no significant clustersChildren: no significant clusters
ThyroidThyroid Large area, low increase in RRLarge area, low increase in RR
Urinary BladderUrinary Bladder Local clustering, low increase in Local clustering, low increase in RRRR
Bone and JointBone and Joint No significant clustersNo significant clusters
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ConclusionsConclusions
Geographic cluster analysis may be Geographic cluster analysis may be informative in combination with other informative in combination with other descriptive analysesdescriptive analysesInterpretation and communication issuesInterpretation and communication issuesGeocodingGeocoding is an important technical is an important technical obstacle for historic cancer incidence dataobstacle for historic cancer incidence dataNext stepsNext steps
Further investigation of spatial analytic toolsFurther investigation of spatial analytic toolsLinking (ecologic studies)Linking (ecologic studies)