• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1193-1201
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• 2016

In epidemiology or etiology, we are often interested in identifying areas of elevated risk, so called, hot spot or cluster. Many existing clustering methods only tend to a result if there exists any clustering pattern in study area. Recently, however, lots of newly introduced clustering methods can identify the location, size, and shape of clusters and test if the clusters are statistically significant as well. In this paper, one of most commonly used clustering methods, scan statistic, and its implementation SaTScan software, which is freely available, will be introduced. To exemplify the usage of SaTScan software, we used cancer data from the SEER program of National Cancer Institute of U.S.A.We aimed to help researchers and practitioners, who are interested in spatial cluster detection, using female lung cancer mortality data of the SEER program.

• Research in Community and Public Health Nursing
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• v.33 no.2
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• pp.237-246
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• 2022

Purpose: The aim of this study was to investigate the relationship between the 5-year survival rate, socioeconomic status, and SEER (Surveillance Epidemiology and End Results) stage of stomach, colorectal, breast and cervical cancer patients. Methods: A total of 11,770 cases of four target cancers, which were diagnosed during 2005-2007, were extracted from the database of Gwangju-Jeonnam Regional Cancer Registry. The subjects of the study were 11,770 including stomach (n=5,479), colorectal (n=3,565), breast (n=1,516) and cervical cancers (n=710). Cox's proportional hazards model was used to obtain the hazards ratio (HR) according to the SEER stage and socioeconomic status. Results: Stomach cancer had a significantly higher HR in the medical aid recipients (HR=1.39), and the group below 20% (HR=1.20) compared to the group with the highest income level. Colorectal cancer had a significantly higher HR in the medical aid recipients (HR=1.26) than in the group with the highest income level. In addition, stomach, colorectal, breast and cervical cancers had a significantly higher HR according to the SEER stage in regional direct (stomach=4.10, colorectal=1.76, breast=12.90, cervical=3.10), regional lymph only(stomach=2.58, colorectal=2.33, breast=4.32, cervical=4.43), regional both (stomach=6.74 colorectal=3.04, breast=15.57 cervical=6.50), and regional NOS (Not Otherwise Specified)/distant (stomach=17.53, colorectal=11.53, breast=25.34, cervical=26.51) than in situ and localized only. Conclusion: In order to increase the cancer survival rate, a support system for early detection and early treatment of cancer should be established for groups with low individual income levels, and regular health checkups and management measures should be actively implemented through the National Cancer Screening Program.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.255-266
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• 2021

The purpose of this study is to compare the effects of treatment on stage III stomach cancer data obtained from the SEER program of the National Cancer Institute and to identify the significant risk factors for the survival rates of stage III stomach cancer. Since the proportional hazards assumption was violated for treatment, we used the restricted mean survival time as an alternative to the proportional hazards model. The restricted mean survival time was estimated using pseudo-observations, and the effects of treatment were compared using a test statistic based on the estimated restricted mean survival times. We conducted the regression analysis using a generalized linear model to investigate the significant predictors for the restricted mean survival time of patients with stage III stomach cancer. We found that there was a significant difference between the restricted mean survival times of treatment groups. Age at diagnosis, race, substage, grade, tumor size, surgery, and treatment were significant predictors for the restricted mean survival time of patients with stage III stomach cancer. Surgery was the most significant predictor for increasing the restricted mean survival time of patients with stage III stomach cancer.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.349-359
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• 2017

In this paper, we conducted survival analyses by fitting the Cox proportional hazards model to stage III proximal colon cancer data obtained from the Surveillance, Epidemiology, and End Results program of the National Cancer Institute. We investigated the effect of covariates on the hazard function for death from proximal colon cancer in stage III with surgery performed and estimated the survival probability for a patient with specific covariates. We showed that the proportional hazards assumption is satisfied for covariates that were used to analyses, using a test based on the Schoenfeld residuals and plots of the Schoenfeld residuals and $log[-log\{{\hat{S}}(t)\}]$. We evaluated the model calibration and discriminatory accuracy by calibration plot and time-dependent area under the ROC curve, which were calculated using 10-fold cross validation.