• Asian Pacific Journal of Cancer Prevention
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• 제13권8호
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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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• 제15권2호
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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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• 제15권14호
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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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• 제28권2호
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• pp.349-359
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• 2017

본 논문에서는 미국 국립암연구소의 SEER 프로그램에서 제공하는 우측 대장암 3기 자료에 Cox 비례위험모형을 적합하여 생존분석을 하였다. 우측 대장암 3기 환자의 사망률에 유의한 영향을 미치는 공변량들을 파악하고, 관심있는 공변량들을 가진 환자의 생존율을 추정하였다. Schoenfeld 잔차를 기반한 검정과 Schoenfeld 잔차 도표, $log[-log\{{\hat{S}}(t)\}]$ 도표를 이용하여 분석에 사용된 공변량들이 비례위험 가정을 만족함을 확인하였다. 적합된 Cox 비례위험모형의 타당성을 검증하기 위해 10-fold 교차 검증을 이용하여 calibration 도표와 시간에 의존하는 ROC 곡선 아래 면적을 계산하였다. 이를 통해 적합된 Cox 비례위험모형의 타당성을 확인하였다.

• 한국항해항만학회지
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• 제27권2호
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• pp.185-191
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• 2003

본 연구의 목적은 아시아 주요항만의 특성을 종합적으로 분석/분류하는 것이다. 특히, 본 연구에서는 기존연구가 지닌 연구대상 선정과 관련한 문제점을 극복하기 위해, 객관적인 지표에 의거하여 부산항이 속한 아시아 주요 대상 항만을 선정했다. 그리고, 연구 방법론의 측면에서 기존연구의 계층평가 알고리즘을 이용한 항만평가와 군집분석법을 이용한 연구의 경우 상호보완적인 장/단점을 지니고 있어, 두 가지 알고리즘을 연계하여 아시아 항만의 전체적인 판도와 항만의 경쟁력 순위 등을 종합적으로 고찰했다. 또한, 본 연구에서는 일반군집분석법에 퍼지 알고리즘을 적용한 FC<(Fuzzy C-Means)법을 이용하여, 기존 방법보다 다양한 고찰이 가능케 하였다. 분석결과, 아시아 16개 주요 항만들 중 10개 항만이 독자적이 위상을 가지고 6가지 항만군을 형성하고 있었으며, 순위면에서 싱가폴항, 홍콩항, 부산항 카오슝항이 높은 경쟁력을 가지고 있었다. 특히, 부산항과 카오슝은 여러 가지 특성에서 유사하여 동일 항만군으로 분류되었고, 싱가폴하엥 이어 2번째로 높은 경쟁력을 보유한 항만군을 형성하고 있는 것으로 파악되었으나, 경쟁력 면에서 싱가폴항과의 격차는 큰 것으로 파악되었다.

• Journal of Gastric Cancer
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• 제19권4호
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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.

• 보건행정학회지
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• 제31권1호
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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.

• Asian Pacific Journal of Cancer Prevention
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• 제15권19호
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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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• 제15권22호
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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.

• 보건행정학회지
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• 제20권4호
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• pp.58-73
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• 2010

Background : Cancer is a disease that not only places a significant burden on patients clinically but also requires significant expense for diagnosis and treatment. Although the cancer coverage of health insurance has recently been expended, the need for financial assistance among cancer patients and their families is still expected to be significant. In this study, cancer patients' need for financial assistance in Korea was examined and its influence factors were analyzed. Methods : Target study subjects were those who are over 18 years of age and were diagnosed with cancer more than four months prior at the National Cancer Center and 9 Regional Cancer Centers in Korea during the period from July to August of 2008. Quarter sampling was conducted according to the ratio of the type of each cancer. A face to face interview survey was conducted. A total of 2,661 cancer patients finished the survey. Medical charts were reviewed in order to obtain the cancer type and SEER stage of cancer patients. An ordered logistic regression model was used to examine the level of need for financial assistance according to the demographical, clinical, and socio-economic variables of cancer patients. Result : The percentage of cancer patients who needed financial assistance was 69.0%, and 36.9% needed significant financial assistance. The need for financial assistance was perceived to be greater in males, younger age group, low income group, low education group, medical aid recipients, those who were diagnosed recently, those with a low level of quality of life measured through EQ5D, and those with decreased income after cancer diagnosis. Conclusion : In spite of the current policy to increase health insurance coverage, the majority of cancer patients and their families in Korea still need financial assistance due to cancer. In particular, there were more vulnerable groups, such as the low income, or low education group. In the future, policies that focus on the disadvantaged, which strengthen social security, should be considered for achievement of a substantially better quality of life for cancer patients and their families.