Background: The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier) detection) has not been thoroughly investigated.
BackgroundInvestigation of global clustering patterns across regions is very important in spatial data analysis. Moran's I is a widely used spatial statistic for detecting global spatial patterns such as an east-west trend or an unusually large cluster. Here, we intend to improve Moran's I for evaluating global clustering patterns by including the weight function in the variance, introducing a population density (PD) weight function in the statistics, and conducting Monte Carlo simulation for testing. We compare our modified Moran's I with Oden's I*pop for simulated data with homogeneous populations. The proposed method is applied to a census tract data set.MethodsWe present a modified version of Moran's I which includes information about the strength of the neighboring association when estimating the variance for the statistic. We provide a power analysis on Moran's I, a modified version of Moran's I, and I*pop in a simulation study. Data were simulated under two common spatial correlation scenarios of local and global clustering.ResultsFor simulated data with a large cluster pattern, the modified Moran's I has the highest power (43.4%) compared to Moran's I (39.9%) and I*pop (12.4%) when the adjacent weight function is used with 5%, 10%, 15%, 20%, or 30% of the total population as the geographic range for the cluster.For two global clustering patterns, the modified Moran's I (power > 25.3%) performed better than both Moran's I (> 24.6%) and I*pop (> 7.9%) with the adjacent weight function. With the population density weight function, all methods performed equally well.In the real data example, all statistics indicate the existence of a global clustering pattern in a leukemia data set. The modified Moran's I has the lowest p-value (.0014) followed by Moran's I (.0156) and I*pop (.011).ConclusionsOur power analysis and simulation study show that the modified Moran's I achieved higher power than Moran's I and I*pop for evaluating global and local clustering patterns on geographic data with homogeneous populations. The inclusion of the PD weight function which in turn redefines the neighbors seems to have a large impact on the power of detecting global clustering patterns. Our methods to improve the original version of Moran's I for homogeneous populations can also be extended to some alternative versions of Moran's I methods developed for heterogeneous populations.
Our findings suggest that more research is needed on possible disparities in access to mammography between rural and non-rural areas in California. Therefore, data adequately powered to examine rural populations and to compare them with urban populations are needed.
Introduction: The small proportion of cancers diagnosed at the local disease stage, resectable at the time diagnosis, and responsive to chemotherapy contribute to poor survival making pancreatic cancer the fourth leading cause of cancer death among Americans. This emphasizes the importance of receiving appropriate palliative care. Racial=ethnic cancer treatment disparities have been observed for many cancer sites. We examine patterns of care in a population-based sample of African American, Hispanic and non-Hispanic white patients diagnosed with pancreatic cancer. Methods: Eligible cases were age 20 or older and newly diagnosed in 1998 with primary adenocarcinoma of the pancreas reported to the National Cancer Institute's Surveillance Epidemiology and End Results (SEER) program and selected for the NCI Patterns of Care=Quality of Care (POC=QOC) project (n ¼ 697). Results: Chemotherapy, the most frequently received treatment was less frequently received by African American patients (odds ratio [OR] 0.61, 95% confidence interval [CI] 0.37-0.95) and radiation less frequently received by Hispanic compared to non-Hispanic white white patients (OR 0.50, 95% CI, 0.27-0.95) after adjustment for age, stage, size of tumor, and insurance status in a multivariate regression model. Cancer-directed surgery of the primary site was received by 14.1% of patients, which did not significantly differ by race= ethnicity. Uninsured patients less often were recommended for or received surgery (OR 0.09, 95% CI 0.01-0.62) and (OR 0.07, 95% CI, 0.01-0.49), respectively. Conclusion: Differences in primary tumor size, stage and insurance status contributed to racial=ethnic differences in the receipt of cancer-directed surgery but did not explain differences in the receipt of chemotherapy for African American or radiation for Hispanic patients. More population-based research is needed to examine race=ethnicity, insurance status and receipt of treatment and palliative care for pancreatic cancer.
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