Detection of spatial clusters: application to cancer survival as a continuous outcome.
In this article, we develop the first detailed illustration of the use of a cluster detection method using a spatial scan statistic based on an exponential survival model. We use this approach to study the spatial patterns of survival of patients with stage III or stage IV colorectal cancer or with stage I/II, stage III, or stage IV lung cancer in the State of California and the County of Los Angeles (LA) diagnosed during 1988 through 2002. We present the location of the detected clusters of short survival or long survival and compute nonparametric estimates of survival inside and outside of those detected clusters confirming the survival pattern detected by the spatial scan statistic in both areas. In LA County, we investigate the possible relationship between the cluster locations and race, sex, and histology using nonparametric methods, and we compare socioeconomic factors such as education, employment, income, and health insurance inside and outside of the detected clusters. Finally, we evaluate the effect of related covariates on statistically significant long and short survival clusters detected in LA County using logistic regression models. This article illustrates a new way to understand survival patterns that may point to health disparities in terms of diagnosis and treatment patterns.
Huang
Lan
L
Statistical Research and Application Branch, Division of Cancer Control and Population Science, National Cancer Institute, Rockville, MD, USA. huangla@mail.nih.gov
Pickle
Linda W
LW
Stinchcomb
David
D
Feuer
Eric J
EJ
D002140:California / Q000453:epidemiology; D016000:Cluster Analysis; D015179:Colorectal Neoplasms / Q000401:mortality*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008962:Models, Theoretical; D012959:Socioeconomic Factors; D016019:Survival Analysis; D019371:Topography, Medical / Q000706:statistics & numerical data