Geographic distribution of prostate cancer incidence in the era of PSA testing, Connecticut, 1984 to 1998

Gregorio, David I.; Kulldorff, Martin; Sheehan, T. Joseph; Samociuk, Holly

doi:10.1016/j.urology.2003.08.008

Cited by 31 publications

(26 citation statements)

References 7 publications

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“…The findings for prostate cancer survival are consistent with the observed variation in prostate cancer incidence in Connecticut during a roughly similar period (Gregorio et al, 2004). Areas that exhibited greater than expected incidence appear here to have experienced better than expected survival.…”

Section: Discussionsupporting

confidence: 84%

A Spatial Scan Statistic for Survival Data

2007

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Spatial scan statistics with Bernoulli and Poisson models are commonly used for geographical disease surveillance and cluster detection. These models, suitable for count data, were not designed for continuous outcome data. We propose a spatial scan statistic based on an exponential model to be used for uncensored or censored continuous survival data. The power and sensitivity of the developed model are investigated through intensive simulations. The method performs well for different survival distribution functions including the exponential, gamma and log normal distributions. How to adjust the analysis for covariates is described in detail. The method is illustrated using survival data for men diagnosed with prostate cancer in Connecticut from 1984 to 1995.

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Section: Discussionsupporting

confidence: 84%

A Spatial Scan Statistic for Survival Data

2007

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“…The incidence rate of prostate cancer varies because of the widespread prostate specific antigen (PSA) testing in some developed countries (27)(28)(29). In some studies, no evidence of an increase in the incidence along with an increase in the rate of PSA testing (30) was found, but it was higher in the urban and more prosperous areas (31-33); however, this result was not compatible for all areas (34).…”

Section: Discussionmentioning

confidence: 99%

Cancer Incidence Rate in the Elderly Inhabitants of Tehran: Is there Really any Cluster?

Rohani-Rasaf

Nazari

et al. 2017

Int J Cancer Manag

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Background: The number of new cancer cases in the elderly is growing because of the aging population. Methods: Cancer data of the elderly (65 years and older) were collected from Iran cancer registry in 2007. Local Moran's I was used as a measure of spatial analysis to identify the cluster patterns. Results: The overall cancer incidence rates were 862.4 and 474.8 per 100,000 in men and women, respectively. Prostate cancer and breast cancer were the most common types of cancer in men and women, correspondingly. Using the Local Moran's I tool, we identified more spatial clusters among men than women. Districts 1, 2, 3 and 6 in the north of Tehran were hot spots for prostate cancer and district 16 in the south of Tehran was the cool spot for this type of cancer, and districts 1 and 3 were the hot spots for breast cancer. Conclusions: More cancer hot spots were located in the north of Tehran where districts are more privileged, and more cool spots were located in the south of the city where districts are more underprivileged.

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“…In analysing spatial clustering of cancer, many researchers have used the spatial scan statistic to detect cluster locations Jemal et al, 2002;Thomas and Carlin, 2003;Gregorio et al, 2004;Pollack et al, 2006).The spatial scan statistic is a "local" spatial clustering test that identifies the locations and characteristics of statistically significant clusters of cases within a study area (Kulldorff, 1997). Studies have utilised spatial scan statistics to examine spatial disparities in cancer incidence and mortality Gregorio et al, 2002Gregorio et al, , 2004Jemal et al, 2002;Roche et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

“…Studies have utilised spatial scan statistics to examine spatial disparities in cancer incidence and mortality Gregorio et al, 2002Gregorio et al, , 2004Jemal et al, 2002;Roche et al, 2002). Several studies have applied spatial scan statistics to identify areas with high or low incidence rates of breast cancer (Gregorio and Samociuk, 2003) and to detect areas with an elevated proportion of late-stage breast cancer cases (Roche et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

Impact of spatial aggregation error on the spatial scan analysis: a case study of colorectal cancer

Luo

2013

Geospat Health

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Abstract. The paper aims to estimate the level and impact of spatial aggregation error for spatial scan statistics where disaggregated data below the zip code level are not available. Data on colorectal cancer cases in Cook county, Illinois, USA with a 5-year interval were used. An innovative procedure using SAS and Java was designed to make SaTScan auto-run. Characteristics of clusters at each reference level were compared to those at zip code level to observe differences related to spatial aggregation. The comparison reveals that spatial scan statistic at the zip code level can generate reliable clusters in areas with a large number of cases, but fail to detect clusters in areas where there are a sparse number of cases, since the spatial aggregation error is minimised in areas with sizeable numbers of cases. Without localised cancer data, zip code level data can be used effectively to identify dominant clusters. However, smaller clusters located in low-density areas may be missed.

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Geographic distribution of prostate cancer incidence in the era of PSA testing, Connecticut, 1984 to 1998

Cited by 31 publications

References 7 publications

A Spatial Scan Statistic for Survival Data

A Spatial Scan Statistic for Survival Data

Cancer Incidence Rate in the Elderly Inhabitants of Tehran: Is there Really any Cluster?

Impact of spatial aggregation error on the spatial scan analysis: a case study of colorectal cancer

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