• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.605-616
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• 2004

In this paper we consider the proportional hazard models for survival analysis in the microarray data. For a given vector of response values and gene expressions (covariates), we address the issue of how to reduce the dimension by selecting the significant genes. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.615-618
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• 2004

The previous quantitative bankruptcy prediction models cannot include time dimension. To overcome this limit, various dynamic models using survival analysis are developed recently. This paper emphasizes that the proportionality assumption must be adapted with caution when the Cox's proportional hazard model is used to explain bankruptcy. It is shown that a non-proportional hazard model including a change point model is a proper alternative, when the proportionality assumption is violated by the change of macroeconomic environment, such as the financial crisis in 1997.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.16 no.4
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• pp.241-257
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• 2004

Global prognostic models based on NCOM(NCAR CSM Ocean Model) of NCAR which is generic from Bryan-Cox-Semtner model are established to study the ocean circulation in the neighboring seas of Korean peninsula. The model domain covers areas from $80.6{^\circ}S~88.6{^\circ}N$in meridional direction and the vertical water column is divided into 15 levels taking enhanced grid resolution of $0.3^\circ$ around Korean peninsula. Island option is used for 22 islands to simulate inshore circulation by hole-relaxation method and the restart hydrographic data are taken from NCAR(1998) CSM model that has been run for 300 years. The wind stress data are taken from Choi et al. (2002). Based on the model results, circulation patterns in the NW Pacific and global oceans are investigated. Volume transports calculated at five straits in the neighboring seas of Korean peninsula are compared with the results from Choi et al. (2002) and other observed data.

• Journal of Korean Biological Nursing Science
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• v.24 no.1
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• pp.17-25
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• 2022

Purpose: To determine the prognostic role of muscle area and muscle radiation attenuation in the erector spinae (ES) and multifidus (MF) muscles in patients undergoing gastrectomy. Methods: Patients with stage I-III gastric cancer undergoing gastrectomy were retrospectively enrolled in this study. Clinicopathologic characteristics were collected and analyzed. Both paraspinal muscle index of ES/MF muscles (PMI_EM) and paraspinal muscle radiation attenuation in the same muscles (PMRA_EM) were analyzed at the 3rd lumbar level using axial computed tomographic images. Cox regression analysis was applied to estimate overall survival (OS) and disease-free survival (DFS). Results: There was only a weak correlation between PMI_EM and PMRA_EM (r= 0.28). Multivariate Cox regression revealed that PMRA_EM, but not PMI_EM, was an important determinant of survival. PMRA_EM along with age, tumor-node-metastasis (TNM) stage, perineural invasion, and serum albumin level were significant determinants of both OS and DFS that constituted Model 1. Harrell's concordance index and integrated area under receiver operating characteristic curve were greater for Model 1 than for Model 2 (consisting of the same covariates as Model 1 except PMRA_EM) or Model 3 (consisting of only TNM stage). Conclusion: PMRA_EM, but not PMIEM, was an important determinant of survival. Because there was only a weak correlation between PMI_EM and PMRA_EM in this study, it was presumed that they were mutually exclusive. Model 1 consisting of age, TNM stage, perineural invasion, serum albumin level, and PMRA_EM was greater than nested models (i.e., Model 2 or Model 3) in predicting survival outcomes.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9453-9458
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• 2014

Background: Breast cancer is the second leading cause of cancer death for women in the United States. Differences in survival of breast cancer have been noted among racial and ethnic groups, but the reasons for these disparities remain unclear. This study presents the characteristics and the survival curve of two racial and ethnic groups and evaluates the effects of race on survival times by measuring the lifetime data-based half-normal model. Materials and Methods: The distributions among racial and ethnic groups are compared using female breast cancer patients from nine states in the country all taken from the National Cancer Institute's Surveillance, Epidemiology, and End Results cancer registry. The main end points observed are: age at diagnosis, survival time in months, and marital status. The right skewed half-normal statistical probability model is used to show the differences in the survival times between black Hispanic (BH) and black non-Hispanic (BNH) female breast cancer patients. The Kaplan-Meier and Cox proportional hazard ratio are used to estimate and compare the relative risk of death in two minority groups, BH and BNH. Results: A probability random sample method was used to select representative samples from BNH and BH female breast cancer patients, who were diagnosed during the years of 1973-2009 in the United States. The sample contained 1,000 BNH and 298 BH female breast cancer patients. The median age at diagnosis was 57.75 years among BNH and 54.11 years among BH. The results of the half-normal model showed that the survival times formed positive skewed models with higher variability in BNH compared with BH. The Kaplan-Meir estimate was used to plot the survival curves for cancer patients; this test was positively skewed. The Kaplan-Meier and Cox proportional hazard ratio for survival analysis showed that BNH had a significantly longer survival time as compared to BH which is consistent with the results of the half-normal model. Conclusions: The findings with the proposed model strategy will assist in the healthcare field to measure future outcomes for BH and BNH, given their past history and conditions. These findings may provide an enhanced and improved outlook for the diagnosis and treatment of breast cancer patients in the United States.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.27-40
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• 2023

This study analyzes the factors affecting the survival of young start-up companies. A youth start-up company was defined as a company with a founder's age under 39. The study was based on evaluation data from 3,540 companies evaluated by the Technology Guarantee Fund to support youth start-up guarantees during the period from 2012 to 2015. In this study, independent variables were defined as founder characteristics, start-up environment, and start-up strategy, and entrepreneurship, knowledge level, and development capabilities were set as variables for start-up characteristics, competition conditions and comparative advantage with alternatives in the start-up environment, and item novelty, commercialization plan and financing plan were set as variables. For variable measurement, the evaluation index of the youth start-up evaluation model of the Technology Guarantee Fund was used. Management performance was defined as the survival of a company, and the survival of 12, 36, 60, and 84 months was measured based on the occurrence of insolvency registered by the Korea Technology Guarantee Fund. The Cox proportional risk model was used for hypothesis testing. As a result of the analysis, knowledge level and development capability were statistically significant in the characteristics of the founder, and the financing plan in the start-up strategy was statistically significant regardless of the survival period. Among the start-up strategies, the novelty of the item had a positive effect on survival after 36 months. Entrepreneurship was significant only in 12-month survival. The most important order for survival was identified in the order of financing plan, knowledge level, item novelty and development capability, of which the founder's knowledge level in the beginning and the funding plan in the second half had the greatest impact.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.12
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• pp.4839-4842
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• 2014

Background: Although the Cox's proportional hazard model is the popular approach for survival analysis to investigate significant risk factors of cancer patient survival, it is not appropriate in the case of log-term disease free survival. Recently, cure rate models have been introduced to distinguish between clinical determinants of cure and variables associated with the time to event of interest. The aim of this study was to use a cure rate model to determine the clinical associated factors for cure rates of patients with breast cancer (BC). Materials and Methods: This prospective cohort study covered 305 patients with BC, admitted at Shahid Faiazbakhsh Hospital, Tehran, during 2006 to 2008 and followed until April 2012. Cases of patient death were confirmed by telephone contact. For data analysis, a non-mixed cure rate model with Poisson distribution and negative binomial distribution were employed. All analyses were carried out using a developed Macro in WinBugs. Deviance information criteria (DIC) were employed to find the best model. Results: The overall 1-year, 3-year and 5-year relative survival rates were 97%, 89% and 74%. Metastasis and stage of BC were the significant factors, but age was significant only in negative binomial model. The DIC also showed that the negative binomial model had a better fit. Conclusions: This study indicated that, metastasis and stage of BC were identified as the clinical criteria for cure rates. There are limited studies on BC survival which employed these cure rate models to identify the clinical factors associated with cure. These models are better than Cox, in the case of long-term survival.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.11
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• pp.1753-1758
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• 2013

A debate over the association between dietary patterns and obesity is not settled in the literature. Some studies suggest that there are significant differences in the mean body mass index (BMI) across dietary patterns, while others refute the result. Therefore, we extended this line of study to examine whether the influence of dietary pattern is strong enough to affect the incidence of obesity based on the criterion, BMI=25. We identified 3 dietary patterns using a cluster analysis of food intake data obtained from the food frequency survey conducted as a part of Korean genome epidemiologic study: 'variety', 'unrefined grain', and 'rice' dietary patterns. A Cox Hazard regression result showed that the all the dietary pattern variable parameters were not significant. Hence, it was concluded that the dietary patterns do not affect the incidence of obesity under the control of variables, such as age, energy intake, and etc.

• Nutrition Research and Practice
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• v.8 no.3
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• pp.267-271
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• 2014

BACKGROUND/OBJECTIVES: Overproduction of nitric oxide (NO) by the inducible nitric oxide synthase (iNOS) enzyme can cause inflammation. Cyclooxygenase-2 (COX-2) is also involved in the inflammatory response through regulation of nuclear factor-kappa B $NF-{\kappa}B$(). Areca catechu is one of the known fruit plants of the Palmaceae family. It has been used for a long time as a source of herbal medicine in Indonesia. In this study, we explored the effect of Indonesian Areca catechu leaf ethanol extract (ACE) in lipopolysaccharide (LPS)-induced inflammation and carrageenan-induced paw edema models. Recently, this natural extract has been in the spotlight because of its efficacy and limited or no toxic side effects. However, the mechanism underlying its anti-inflammatory effect remains to be elucidated. MATERIALS/METHODS: We measured NO production by using the Griess reagent, and determined the expression levels of inflammation-related proteins, such as iNOS, COX2, and $NF-{\kappa}B$, by western blot. To confirm the effect of ACE in vivo, we used the carrageenan-induced paw edema model. RESULTS: Compared to untreated cells, LPS-stimulated RAW 264.7 cells treated with ACE showed reduced NO generation and reduced iNOS and COX-2 expression. We found that the acute inflammatory response was significantly reduced by ACE in the carrageenan-induced paw edema model. CONCLUSION: Taken together, these results suggest that ACE can inhibit inflammation and modulate NO generation via downregulation of iNOS levels and $NF-{\kappa}B$ signaling in vitro and in vivo. ACE may have a potential medical benefit as an anti-inflammation agent.