Background: Predictor factors determining complete response to treatment are still not clearly defined. We aimed to evaluate clinicopathological features, risk factors, treatment responses, and survival analysis of patient with advanced nonseminomatous GCTs (NSGCTs). Materials and Methods: Between November 1999 and September 2011, 140 patients with stage II and III NSGCTs were referred to our institutions and 125 patients with complete clinical data were included in this retrospective study. Four cycles of BEP regimen were applied as a first-line treatment. Salvage chemotherapy and/or high-dose chemotherapy (HDCT) with autologous stem cell transplantation were given in patients who progressed after BEP chemotherapy. Post-chemotherapy surgery was performed in selected patients with incomplete radiographic response and normal tumor markers. Results: The median age was 28 years. For the good, intermediate and poor risk groups, compete response rates (CRR) were, 84.6%, 67.9% and 59.4%, respectively. Extragonadal tumors, stage 3 disease, intermediate and poor risk factors, rete testis invasion were associated with worse outcomes. There were 32 patients (25.6%) with non-CR who were treated with salvage treatment. Thirty-one patients died from GCTs and 94% of them had stage III disease. Conclusions: Even though response rates are high, some patients with GCTs still need salvage treatment and cure cannot be achieved. Non-complete response to platinium-based first-line treatment is a negative prognostic factor. Our study confirmed the need for a prognostic and predictive model and more effective salvage approaches.
Background: The study investigated the influence of culturally-based health beliefs on engagement in healthy lifestyle behaviour. Specifically, the study compared levels of engagement between Western and Chinese youth in Australia and assessed the extent to which culture-specific attributions about the causes of illness, and health beliefs, predict engagement in healthy lifestyle behaviour. Materials and Methods: Ninety-four Western and 95 Chinese (N=189; Mean Age=20.8 years, SD=3 years) young adults completed an online questionnaire. Predictor variables were cultural health beliefs measured by the Chinese Cultural Views on Health and Illness scale (CCVH, Liang et al., 2008), and illness attributions beliefs measured by the Cause of Illness Questionnaire (CIQ, Armstrong and Swartzman, 1999). Outcomes variables were levels of engagement in healthy lifestyle behaviour. Results: Results indicated that Chinese participants have a significantly lower exercising rate and healthy dietary habits compared to the Western sample. Moreover, Chinese participants were found to believe more strongly than Westerners that cancer was associated with factors measured by the Traditional-Chinese-Model (TCM). Finally, the observed relationship between cultural health beliefs and physical inactivity was mediated by attributions of illness, in particular to the supernatural subscale, with the Sobel Test showing a significant mediation (z=-2.63, p=0.004). Conclusions: Mainstream approaches to encourage healthy lifestyles are unlikely to be effective when educating Chinese youth. Instead, health promotion programs should attempt to address the illness attribution beliefs and educate Chinese youth about the role of diet and exercise in prevention of diseases such as cancer.
Recent studies have shown that high consumption of processed meat may be associated with increasing risk of metabolic syndrome, which have been suggested as a predictor of diabetes and cardiovascular disease. However, limited studies have investigated this association in Korean population. The purpose of this study was to investigate the cross-sectional association between processed meat/unprocessed (beef, pork, chicken) intakes and the prevalence of metabolic syndrome. Using data from 2007-2008 Korean National Health and Nutrition Examination Survey (KNHANES), we analyzed data including 5,545 men and women who were aged older than 20 years, and who were free of chronic disease such as hypertension, type 2 diabetes and cardiovascular disease. Subjects who frequently consumed processed meat tended to be younger and more likely to be current smokers. In addition, men were more likely to consume processed meat than women. Although higher processed/unprocessed meat intakes were significantly associated with the lower risk of metabolic syndrome in a crude model, these associations were no longer significant after adjustment for potential confounding factors. For example, comparing subjects in the highest intake quartile of processed meat with the lowest intake group, the multivariate-adjusted odds ratio (OR) of metabolic syndrome was 0.92 (95% CI: 0.58-1.46) for processed meat, 1.09 (95% CI: 0.76-1.56) for beef, 1.10 (95% CI: 0.74-1.62) for pork and 0.75 (95% CI: 0.51-1.12) for chicken. In conclusion, we found no evidence of any adverse effects of frequent processed or unprocessed meat intakes on the prevalence of metabolic syndrome among Korean adults at the exposure levels seen in this study.
Purpose: D-dimer levels are known to be associated with poor outcomes in patients with various cancers, but their significance at the end of life remains unclear. This study investigated D-dimer levels as a prognostic indicator for terminal cancer patients in the last hours of life. Methods: The retrospective study was conducted at a palliative care unit of a tertiary cancer center, using a database to analyze the records of patients treated from January 1, 2010 to December 31, 2018. In total, 67 terminal cancer patients with available data on D-dimer levels were included. Patients' demographic data, clinical information, and laboratory values, including D-dimer levels, were collected. Survival was analyzed using the Kaplan-Meier method and the log-rank test. A Cox proportional-hazards model was used to identify prognostic factors of poor survival. Results: The most common site of cancer was the lung (32.8%) and the median survival time was 5 days. Most laboratory results, particularly D-dimer levels, deviated from the normal range. Patients with high D-dimer levels had a significantly shorter survival time than those with low D-dimer levels (4 days vs. 7 days; P=0.012). In the Cox regression analysis, only a high D-dimer level was identified as a predictor of a poor prognosis (hazard ratio, 1.83; 95% confidence interval, 1.09~3.07). Conclusion: Our results suggest that at the very end of life, D-dimer levels may serve as a prognostic factor for survival in cancer patients.
Journal of the Korea Society of Computer and Information
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v.18
no.3
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pp.141-152
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2013
This study investigates the determinants of users' continuance intention in mobile application market, and examines the structural relationships between predictors and users' continuance intention. Based on the intensive review of prior research related to Internet and mobile services, mobile application richness, brand awareness, user habit, user loyalty were selected as the predictors of users' continuance intention. Using 259 surveys, the research model was assessed and the research hypotheses were tested. The findings show that mobile application richness is positively related with brand awareness and user loyalty. Brand awareness is proven to be a key predictor of user habit and user loyalty. Futhermore, it is shown that user habit has a direct impact on user loyalty and users' continuance intention. Finally, it was proven that user loyalty is a pretty important determinant of users' continuance intention.
The unsustainable human activities like increased use of automobiles, heavy industrialization and the use of large volumes of fertilizers, chemicals and pesticides in the agricultural land cause climate change problems in one way or another. Under normal circumstances, the heat radiations from the sun will be reflected back. An excessive volume of GHGs in the atmosphere would prevent these radiations from reflecting back. East Asia is facing severe climate change issues in recent times. A lot of climate change problems such as hurricanes and floods have been reported from this region in the last couple of decades. The study aimed at investigating the climate change in East Asia with changing Sea Surface Temperature (SST). The study adopted a quantitative research method with a case study research design where a deliberate focus was made on the East Asia Region. Secondary data was gathered and analyzed to yield both descriptive and inferential statistics. The study concluded that the impact of East Asia Climate variability was significant mainly for some extreme events. Also, the study concluded that there was a significant link between the change of the East Asia climate variability and that of the sea surface temperature. Further, the study concluded that a linear relationship existed between the sea surface temperature and the climate of East Asia. Hence, a linear regression was a significant predictor of the East Asia Climate (EAC) based on changing sea surface temperature. The model revealed that 37.4% of the variations in the climate change index were explained by the changes in the sea surface temperature. The climate was expected to change with a value of 49.48 for a unit change in the sea surface temperature.
Although shipbuilding workers were exposed to a variety of genotoxic compounds including polycyclic aromatic hydrocarbons (PAHs), limited number of studies were conducted to evaluate the biomarkers related to PAH exposure in painting workers in shipbuilding industry. One hundred and thirty three workers including 73 employees using coal tar paints were recruited from a shipbuilding company located in South Korea. Urinary 1-hydroxypyrene glucuronide (1-OHPG), as internal dose of PAH exposure, were measured by synchronous fluorescence spectroscopy after immunoaffinity purification using monoclonal antibody 8E11. Glutathione S-transferase (GST)M1 and GSTT1 genotypes were assessed by multiplex PCR. Information on demographic characteristics, smoking gabit, diet, job title, use of personal protective equipments were collected by self-administered questionnaire. Urinary 1-OHPG were higher in workers using coal tar paints than in workers using general paints, however, the difference was not statistically significant (p=0.20, Mann-Whitney U test). Urinary 1-OHPG levels in smokers were higher than in non-smokers (p<0.05 by Mann-Whitney U test) and there was a significant increase in urinary 1-OHPG levels with the numbers of cigarettes consumed per day (Spearman's correlation coefficient = 0.28, p=0.02). Genetic polymorphisms of GSTM1 and GSTT1 did not influence the level of 1-OHPG in study subjects. Multiple regression analysis show that smoking is the only significant predictor for lon-transformed 1-OHPG (overall model R2=0.1). These results suggest that workers using coal tar paints were exposed to significant amount of PAHs and individual difference in xenobiotic metabolism might affect the levels of internal dose of PAHs.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2015.10a
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pp.123-124
/
2015
Recently, with the economy and the information communication technology developed, the smartphone market grows continuously. The market outlook on the wireless rechargeable technology grows rapidly so that the market size is increased about six times bigger than that of the last year, and it will grow about 18 billion dollars in 2014. Because of that, as the interest on this area out focused, many kinds of technology and new product are being exploited in this field. In this research, we aim to analyze factors influencing of the wireless battery charger on continue using intention of Smartphone. Predictor factors were selected perceived usefulness, perceived ease of use and perceived design suggested based extended the technology acceptance model. IBM SPSS Statistics 19 were employed for descriptive statistics, Smart PLS(partial least squares) was employed for confirmatory factor analysis and path analysis of casual relationship among variables and effect. This study suggests practical and theoretical implications based on the results.
Journal of Korean Society of Industrial and Systems Engineering
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v.38
no.3
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pp.56-63
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2015
Several fields of science have demanded large-scale workflow support, which requires thousands of CPU cores or more. In order to support such large-scale scientific workflows, high capacity parallel systems such as supercomputers are widely used. In order to increase the utilization of these systems, most schedulers use backfilling policy: Small jobs are moved ahead to fill in holes in the schedule when large jobs do not delay. Since an estimate of the runtime is necessary for backfilling, most parallel systems use user's estimated runtime. However, it is found to be extremely inaccurate because users overestimate their jobs. Therefore, in this paper, we propose a novel system for the runtime prediction based on workload-aware clustering with the goal of improving prediction performance. The proposed method for runtime prediction of parallel applications consists of three main phases. First, a feature selection based on factor analysis is performed to identify important input features. Then, it performs a clustering analysis of history data based on self-organizing map which is followed by hierarchical clustering for finding the clustering boundaries from the weight vectors. Finally, prediction models are constructed using support vector regression with the clustered workload data. Multiple prediction models for each clustered data pattern can reduce the error rate compared with a single model for the whole data pattern. In the experiments, we use workload logs on parallel systems (i.e., iPSC, LANL-CM5, SDSC-Par95, SDSC-Par96, and CTC-SP2) to evaluate the effectiveness of our approach. Comparing with other techniques, experimental results show that the proposed method improves the accuracy up to 69.08%.
Journal of Korea Society of Industrial Information Systems
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v.12
no.5
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pp.173-182
/
2007
e-Learning can be seen as not only one of Internet based information systems which can provide education services, but also one of teaching-learning methods which can implement self-directed learning. This paper tests factors affecting the e-Learning performance based on information systems success model and self-efficacy theory using a field study. Questionnaires are collected from 216 students who are enrolling a e-learning class using online survey. The results are following: first, the service quality and self-efficacy are significant predictors of use intention, but system quality and information quality are not. second, the system quality, information quality, service quality and self-efficacy are significant predictors of user satisfaction. Third, use intention and user satisfaction are found to be a strong predictor of the learning performance.
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