ArticleSpatial and spatio-temporal epidemiology2012
Performance of cancer cluster Q-statistics for case-control residential histories.
Article in Spatial and spatio-temporal epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Clustering patterns in Finnish type 1 diabetes patients: a nationwide register-based study.BMJ open diabetes research & care · 2025Article
- Clustering of childhood acute leukemia in Finland: a nationwide register-based study.Cancer causes & control : CCC · 2025Article
- Presymptomatic geographical distribution of ALS patients suggests the involvement of environmental factors in the disease pathogenesis.Journal of neurology · 2023Article
- Clustering of pediatric onset inflammatory bowel disease in Finland: a nationwide register-based study.BMC gastroenterology · 2022Article
- GIScience and cancer: State of the art and trends for cancer surveillance and epidemiology.Cancer · 2019Review
- Incorporating Spatial Statistics into Examining Equity in Health Workforce Distribution: An Empirical Analysis in the Chinese Context.International journal of environmental research and public health · 2018Article
- Investigation of spatio-temporal cancer clusters using residential histories in a case-control study of non-Hodgkin lymphoma in the United States.Environmental health : a global access science source · 2015Article
- Local bladder cancer clusters in southeastern Michigan accounting for risk factors, covariates and residential mobility.PloS one · 2015Article
- Space-time analysis of testicular cancer clusters using residential histories: a case-control study in Denmark.PloS one · 2015Article
- Space-time clusters of breast cancer using residential histories: a Danish case-control study.BMC cancer · 2014Article
- Space-time clustering of non-hodgkin lymphoma using residential histories in a Danish case-control study.PloS one · 2013Article
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Authors and funding
7 authors.
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Abstract
Few investigations of health event clustering have evaluated residential mobility, though causative exposures for chronic diseases such as cancer often occur long before diagnosis. Recently developed Q-statistics incorporate human mobility into disease cluster investigations by quantifying space- and time-dependent nearest neighbor relationships. Using residential histories from two cancer case-control studies, we created simulated clusters to examine Q-statistic performance. Results suggest the intersection of cases with significant clustering over their life course, Q(i), with cases who are constituents of significant local clusters at given times, Q(it), yielded the best performance, which improved with increasing cluster size. Upon comparison, a larger proportion of true positives were detected with Kulldorf's spatial scan method if the time of clustering was provided. We recommend using Q-statistics to identify when and where clustering may have occurred, followed by the scan method to localize the candidate clusters. Future work should investigate the generalizability of these findings.
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