• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.3767-3772
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• 2012

Objective: We estimated the total medical costs incurred during the 5 years following a cancer diagnosis and annual medical use status for the six most prevalent cancers in Korea. Methods: From January 1 to December 31, 2006, new patients registered with the six most prevalent cancers (stomach, liver, lung, breast, colon, and thyroid) were randomly selected from the Korea Central Cancer Registry, with 30% of patients being drawn from each cancer group. For the selected patients, cost data were generated using National Health Insurance claims data from the time of cancer diagnosis in 2006 to December 31, 2010. The total number of patients selected was 28,509. Five-year total medical costs by tumor site and Surveillance, Epidemiology, and End Results (SEER) stage at the time of diagnosis, and annual total medical costs from diagnosis, were estimated. All costs were calculated as per-patient net costs. Results: Mean 5-year net costs per patient varied widely, from $5,647 for thyroid cancer to $20,217 for lung cancer. Advanced stage at diagnosis was associated with a 1.8-2.5-fold higher total cost, and the total medical cost was highest during the first year following diagnosis and decreased by the third or fourth year. Conclusions: The costs of cancer care were substantial and varied by tumor site, annual phase, and stage at diagnosis. This indicates the need for increased prevention, earlier diagnosis, and new therapies that may assist in reducing medical costs.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.663-669
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• 2014

Background: With recent progress in health science administration, a huge amount of data has been collected from thousands of subjects. Statistical and computational techniques are very necessary to understand such data and to make valid scientific conclusions. The purpose of this paper was to develop a statistical probability model and to predict future survival times for male breast cancer patients who were diagnosed in the USA during 1973-2009. Materials and Methods: A random sample of 500 male patients was selected from the Surveillance Epidemiology and End Results (SEER) database. The survival times for the male patients were used to derive the statistical probability model. To measure the goodness of fit tests, the model building criterions: Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) were employed. A novel Bayesian method was used to derive the posterior density function for the parameters and the predictive inference for future survival times from the exponentiated Weibull model, assuming that the observed breast cancer survival data follow such type of model. The Markov chain Monte Carlo method was used to determine the inference for the parameters. Results: The summary results of certain demographic and socio-economic variables are reported. It was found that the exponentiated Weibull model fits the male survival data. Statistical inferences of the posterior parameters are presented. Mean predictive survival times, 95% predictive intervals, predictive skewness and kurtosis were obtained. Conclusions: The findings will hopefully be useful in treatment planning, healthcare resource allocation, and may motivate future research on breast cancer related survival issues.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5571-5575
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• 2014

Background: The ability to predict the survival time of breast cancer patients is important because of the potential high morbidity and mortality associated with the disease. To develop a predictive inference for determining the survival of breast cancer patients, we applied a novel Bayesian method. In this paper, we propose the development of a databased statistical probability model and application of the Bayesian method to predict future survival times for White Hispanic female breast cancer patients, diagnosed in the US during 1973-2009. Materials and Methods: A stratified random sample of White Hispanic female patient survival data was selected from the Surveillance Epidemiology and End Results (SEER) database to derive statistical probability models. Four were considered to identify the best-fit model. We used three standard model-building criteria, which included Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) to measure the goodness of fit. Furthermore, the Bayesian method was used to derive future survival inferences for survival times. Results: The highest number of White Hispanic female breast cancer patients in this sample was from New Mexico and the lowest from Hawaii. The mean (SD) age at diagnosis (years) was 58.2 (14.2). The mean (SD) of survival time (months) for White Hispanic females was 72.7 (32.2). We found that the exponentiated Weibull model best fit the survival times compared to other widely known statistical probability models. The predictive inference for future survival times is presented using the Bayesian method. Conclusions: The findings are significant for treatment planning and health-care cost allocation. They should also contribute to further research on breast cancer survival issues.

• 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.

• Journal of Navigation and Port Research
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• v.27 no.2
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• pp.185-191
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• 2003

The aim of this research is to overall analyze/classify characteristics of Asian major ports. To achieve this aim, we firstly pointed out critical problems on research methodology and research scope which most of previous research have, from related literature review. In order to overcome those problems, major ports in A냠 were selected by the objective indicators, and both algorithms of AHP(Analytic Hierarchical Process) and FCM(Fuzzy C-Means) that revise weakness in previous clustering method were used. Through these hybrid approach, it were found that only 10 ports of 16 major Asian ports had their own phases in Asian major ports. Those 10 ports were classified into 6 port groups, and also membership degree of each port within the 4 port groups and ranking of each ports seer analyzed. Finally, based on results of these analysis, present status and future direction of Busan port were discussed.

• Journal of Gastric Cancer
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• v.19 no.4
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• pp.393-407
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• 2019

Purpose: To identify the potential therapeutic role of postoperative radiotherapy (RT) in patients with locally advanced (stage II and stage III) gastric signet ring cell carcinoma (SRC). Materials and methods: Patients with locally advanced gastric SRC from the Surveillance, Epidemiology, and End Results program database between 2004 and 2012 were included in our study. Univariate and multivariate Cox proportional models were performed, and survival curves were generated to evaluate the prognostic effect of postoperative RT and surgery alone on SRC patients. Propensity score matching (PSM) was used to avoid selection bias among the study cohorts. Results: We found that patients with postoperative RT had better probability of survival compared with those who did not receive RT (overall survival [OS], P<0.001; cancer-specific survival [CSS], P<0.001). After PSM, analysis of both overall and CSS showed that patients who underwent postoperative RT had better prognosis than those receiving surgery alone in the matched cohort (OS, P=0.00079; CSS, P=0.0036). Multivariate Cox proportional model indicated that postoperative RT had better effect on prognosis compared with surgery alone with respect to both overall (hazard ratio [HR], 0.716; 95% confidence interval [95% CI], 0.590-0.87; P=0.001) and CSS (HR, 0.713; 95% CI, 0.570-0.890; P=0.003). Conclusions: Postoperative RT had better prognosis compared with surgery alone for both overall and CSS for patients with locally advanced gastric SRC.

• Health Policy and Management
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• v.31 no.1
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• pp.35-45
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• 2021

Background: As a descriptive study targeting 2,068 cancer patients as men of national merit in 2013, this study aims to provide the basic data for systematizing the early diagnosis and treatment of cancer by comparatively analyzing the 5-year survival rate. Methods: This study researched the survival of cancer patients through Electronic Medical Record and Patriots-Veterans Qualification Program, targeting 2,068 newly-diagnosed cancer patients verified in five veterans hospitals and consigned management system. This study verified differences between general characteristics of cancer patients as men of national merit and analyzed their survival rate. Results: The cancer patients as men of national merit were super-aged as their average age was 72.5. In the analysis of general characteristics of five major prevalent cancers, there were statistically significant differences according to age, region, cancer diagnostic path, differentiation, diagnostic method, treatment method, SEER stage, and survival period, except for the types of the man of national merit (p<0.001). The whole survival rate of cancer patients as men of national merit was 50%. The 5-year survival rates of predisposing cancers were shown as prostate cancer (79%), colorectal cancer (64%), gastric cancer (57%), liver cancer (32%), and lung cancer (12%). In the cancer diagnostic path, all the predisposing cancers showed the highest survival rate in medical examination. In the treatment method, the surgery showed the highest survival rate. The cancer patients as men of national merit showed a lower survival rate than the general cancer patients of Korea. Conclusion: It would be needed to guarantee the honorable and happy life through health recovery as special treatment of contribution and sacrifice of super-aged men of national merit by increasing the cancer survival rates through regular checkup, early diagnosis, and high-quality treatment system that could have important effects on the survival rate according to the occurrence of cancers.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.27 no.2
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• pp.151-157
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• 2023

Backgrounds/Aims: Cholangiocarcinoma (CCA) can be classified as intrahepatic CCA or extrahepatic CCA (eCCA). We intended to analyze and reports the survival outcomes for eCCA. Methods: Surveillance, epidemiology, and end results (SEER) registry, site recode C24.0, was used to select cases of eCCA from 2000 to 2018. Patients with incomplete data or ages <18 years were excluded. Results: Male (52.69%) and White race (77.99%) predominated. Compared with 2000-2006, survival increased in 2013 (adjusted hazard ratio [HRadj]: 0.68, 95% confidence interval [CI] 0.58-0.70; p < 0.01). Surgery with chemoradiotherapy (HRadj: 0.69, 95% CI 0.60-0.7; p < 0.01) and surgery with chemotherapy (HRadj: 0.72, 95% CI 0.62-0.83; p < 0.01) improved survival over surgery alone. Compared with surgery without lymph node (LN) removal, surgery of four or more regional LN reduced the risk of death by 58% (HRadj: 0.42, 95% CI 0.36-0.51; p < 0.01). Compared with patients without surgery, patients who underwent bile duct excision (HRadj: 0.82, 95% CI 0.72-0.94; p < 0.01), simple or extended lobectomy (HRadj: 0.85, 95% CI 0.75-0.95; p = 0.009), and hepatectomy (HRadj: 0.80, 95% CI 0.72-0.88; p < 0.01) significantly improved survival. Patients with distal CCA had a 17% higher survival than perihilar CCA (HRadj: 0.83, 95% CI 0.74-0.92; p < 0.01) and LN dissection was equally beneficial for both subgroups (p < 0.01). Conclusions: Surgery with chemoradiotherapy has a proven increase in the 5-year survival of the eCCA. LN resection, bile duct excision, lobectomy, and hepatectomy have better outcomes.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8371-8376
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• 2014

Background: The use of statistical methods has become an imperative tool in breast cancer survival data analysis. The purpose of this study was to develop the best statistical probability model using the Bayesian method to predict future survival times for the black non-Hispanic female breast cancer patients diagnosed during 1973-2009 in the U.S. Materials and Methods: We used a stratified random sample of black non-Hispanic female breast cancer patient data from the Surveillance Epidemiology and End Results (SEER) database. Survival analysis was performed using Kaplan-Meier and Cox proportional regression methods. Four advanced types of statistical models, Exponentiated Exponential (EE), Beta Generalized Exponential (BGE), Exponentiated Weibull (EW), and Beta Inverse Weibull (BIW) were utilized for data analysis. The statistical model building criteria, Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) were used to measure the goodness of fit tests. Furthermore, we used the Bayesian approach to obtain the predictive survival inferences from the best-fit data based on the exponentiated Weibull model. Results: We identified the highest number of black non-Hispanic female breast cancer patients in Michigan and the lowest in Hawaii. The mean (SD), of age at diagnosis (years) was 58.3 (14.43). The mean (SD), of survival time (months) for black non-Hispanic females was 66.8 (30.20). Non-Hispanic blacks had a significantly increased risk of death compared to Black Hispanics (Hazard ratio: 1.96, 95%CI: 1.51-2.54). Compared to other statistical probability models, we found that the exponentiated Weibull model better fits for the survival times. By making use of the Bayesian method predictive inferences for future survival times were obtained. Conclusions: These findings will be of great significance in determining appropriate treatment plans and health-care cost allocation. Furthermore, the same approach should contribute to build future predictive models for any health related diseases.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.10021-10025
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• 2014

Background: The study aimed to describe the age distribution of breast cancer diagnosis among Chinese females for comparison with the United States and the European Union, and provide evidence for the screening target population in China. Materials and Methods: Median age was estimated from hospital databases from 7 tertiary hospitals in China. Population-based data in China, United States and European Union was extracted from the National Central Cancer Registry, SEER program and GLOBOCAN 2008, respectively. Age-standardized distribution of breast cancer at diagnosis in the 3 areas was estimated based on the World Standard Population 2000. Results: The median age of breast cancer at diagnosis was around 50 in China, nearly 10 years earlier than United States and European Union. The diagnosis age in China did not vary between subgroups of calendar year, region and pathological characteristics. With adjustment for population structure, median age of breast cancer at diagnosis was 50~54 in China, but 55~59 in United States and European Union. Conclusions: The median diagnosis age of female breast cancer is much earlier in China than in the United States and the European Union pointing to racial differences in genetics and lifestyle. Screening programs should start at an earlier age for Chinese women and age disparities between Chinese and Western women warrant further studies.