• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5835-5838
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• 2014

Background: Gastric cancer is one of the most common causes of cancer death in Taiwan. The literature has previously shown that age, tumor site, T categories, and number of metastatic nodes significantly affect prognosis. The aim of this study was to determine the long-term survival of patients with gastric cancer, as well as the effect of particular prognostic factors on survival. Materials and Methods: This was a survival analysis study with retrospective design. We reviewed the records of 64 patients with adenocarcinoma of the stomach who had undergone gastrectomy with curative intent between 2009 and 2012 at a teaching hospital in southern Taiwan. Data extracted from patient documents included age, gender distribution, tumor location, and pathological grading. Results: The median follow-up time was 4 years, and there were 31 deaths attributed to gastric cancer. Kaplan-Meier analysis revealed that retrieval of less than 15 lymph nodes from a patient was a significant predictor of survival. A significant predictor of poorer survival was higher pathological grading. Conclusions: Our results indicate that the number of lymph nodes retrieved and pathological grading could be viewed as crucial prognostic factors affecting the survival of individuals with gastric cancer.

• Korean Journal of Adult Nursing
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• v.21 no.6
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• pp.603-616
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• 2009

Purpose: The purpose of this study was to examine the subjective opinions of first-generation Korean-Americans about survival. Methods: The Q-methodology which provides a method of analyzing the subjectivity of each item was used. The 34 selected Q-statements from each of 38 subjects were classified into a shape of normal distribution using a 9 point scale. The collected data was analyzed using a QUANL/WIN program. Results: Four types of survival attitudes from 38 first-generation Korean-Americans were identified. Type I was a satisfaction type based on belief, Type II was an effort type based on purpose, Type III was an isolation type based on ethnicity, and Type IV was a compromise type based on adaptation. Results of this study indicate that approaches to a minority's survival strategies need to be differentiated taking this typology and various subject characteristics into account. Conclusion: This information may provide a basic understanding for healthcare providers who work with first-generation Korean-Americans.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.727-735
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• 2008

Consider a clinical trial in which the main end-point is survival. Suppose after the start of the study an intermediate event occurs which may be influenced by a covariate(or treatment). In many clinical studies the occurrence of an intermediate event may change the survival distribution. This investigation develops two-stage model which, in the first stage, models the effect of covariate on the intermediate event and models the relationship between survival time and covariate as well as the intermediate event. In this paper, the two-stage model is presented in order to model intermediate event and a test based on this model is also provided. A numerical simulations are carried out to evaluate its overall significance level.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.151-161
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• 1998

We study the bootstrap interval estimation for survival function in the Koziol-Green model. We construct the approximate bootstrap confidence intervals for survival function and prove the strong consistency for the bootstrap estimator of survival function. Finally we show that the approximate bootstrap confidence intervals are better in terms of coverage probability than confidence intervals based on asymptotic normal distribution and transformations of survival function via Monte Carlo simulation study.

• Journal of Life Science
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• v.8 no.3
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• pp.339-347
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• 1998

As a part of a study on the development of microbiological methods for petroleum exploration, the distribution of the avarafe survival rate for heterotrophs to various heavy metal ions and hydrocarbons were surveyed and compared by the use of plate count method. In consequence of the avarage survival rate to heavy metal ions(2 hours treatment) and hydrocarbons(1 hour treatment) for heterotrophs isolatinf from soil samples(50cm depth) which located in Doum mountain(A, B and D site) and Aedowon(C site) at Pohang area, the survival rate of heterotrophs for nickel(600ppm), cobalt(500ppm), cadmiun(100ppm), mercury(20ppm), zinc(400 ppm) and lead(500ppm) were 73.7%, 82.6%, 76.8%, 9.5%, 77.8% and 73.6% at A site and 67.9%, 82.5%, 86.0%, 5.8%, 82.5% and 91.7% at B site, 87.8%, 79.8%, 87.5%, 7.0%, 84.2% AND 47.7% AT c SITE, AND 71.8%, 76%, 85.9%, 1,2%, 79.6% AND 88.3% AT D site, respectively. Also the survival rate of heterotrophs from A,B,C and D site to pentane and hexane(each concentration is 20%) were 26.7% and 42.5%, 11.8% and 8.1%, 44.3% and 36.2%, and 12% and 3.5%, respectively. therefore, heterotrophs from B and D site that alternated gravelstone, muddy sandstone and sandstone were higher survival rate to the heavy metal ions than heterotrophs from A site which mainly composed gravelstone. Also, heterotrophs from C site which mainly composed muddy sandstone and once produced natural gas were showed relatively higher survival rate to the heavy metal ions and hydrocarbons than the other sites. Consequently, we confirmed that the distributions of tolerant heterotrophs to heavy metal ions and hydrocarbons were differ from the lithological compositon.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.2
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• pp.151-162
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• 2014

This study proposes an optimization model to plan the patient distribution and medical resource allocation considering the diverse characteristics of disaster. For reflecting the particularity of disaster response, we configured a few scenarios such as availability of emergency surgery of non-major medical staff and the change in number of patients estimated reflecting the uncertainty, urgency and convergence of disaster. And we finally tested the effects of the scenarios' combination on the objective function defined as maximum number of survival patients. Our experimental results are expected to highlight the significance of the proposed model as well as the applicability of scenarios under disaster response.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.12
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• pp.5287-5294
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• 2016

Background: Breast cancer is a worldwide public health concern and is the most prevalent type of cancer in women in the United States. This study concerned the best fit of statistical probability models on the basis of survival times for nine state cancer registries: California, Connecticut, Georgia, Hawaii, Iowa, Michigan, New Mexico, Utah, and Washington. Materials and Methods: A probability random sampling method was applied to select and extract records of 2,000 breast cancer patients from the Surveillance Epidemiology and End Results (SEER) database for each of the nine state cancer registries used in this study. EasyFit software was utilized to identify the best probability models by using goodness of fit tests, and to estimate parameters for various statistical probability distributions that fit survival data. Results: Statistical analysis for the summary of statistics is reported for each of the states for the years 1973 to 2012. Kolmogorov-Smirnov, Anderson-Darling, and Chi-squared goodness of fit test values were used for survival data, the highest values of goodness of fit statistics being considered indicative of the best fit survival model for each state. Conclusions: It was found that California, Connecticut, Georgia, Iowa, New Mexico, and Washington followed the Burr probability distribution, while the Dagum probability distribution gave the best fit for Michigan and Utah, and Hawaii followed the Gamma probability distribution. These findings highlight differences between states through selected sociodemographic variables and also demonstrate probability modeling differences in breast cancer survival times. The results of this study can be used to guide healthcare providers and researchers for further investigations into social and environmental factors in order to reduce the occurrence of and mortality due to breast cancer.

• Journal of Veterinary Clinics
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• v.36 no.3
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• pp.150-154
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• 2019

The purpose of this study was to investigate the etiological distribution, therapeutic outcome, and survival time in canine epilepsy. The medical records of 57 epileptic dogs were reviewed for the evaluation of etiological distribution. Among them, 27 dogs (47%) and 30 dogs (52%) had idiopathic epilepsy (IdE) and structural epilepsy (StE), respectively. Twenty-nine dogs (IdE: 16 dogs, StE: 13 dogs) were evaluated for therapeutic outcome and survival time. The incidence of generalized epileptic seizure (IdE, 56% vs. StE, 44%; P = 0.043) and the median seizure frequency at the time of first presentation (IdE, 2.0/month vs. StE, 13.3/month; P < 0.01) were significantly different between the two groups. Although pre-treatment seizure frequency and duration were not different, the median duration of seizure in the IdE group (0.5 min) was significantly shorter than that in the StE group (3 min) after treatment (P < 0.01). In addition, the median frequency of seizure was relatively lower in the IdE group (0.25/month) compared to the StE group (2.00/month) following antiepileptic therapy (P = 0.053). The median survival time of the IdE group (1.5 years [95% CI, 1.0-2.3 years]) was significantly longer than that of the StE group (0.4 year [95% CI, 0.2-1.3 years]) (P < 0.01). The information on etiological data and intracranial lesions may be useful for predicting treatment response and prognosis in epileptic dogs.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.1715-1720
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• 2013

Background: The discovery that microRNAs (miRNAs) regulate proliferation, invasion and metastasis provides a principal molecular basis of tumor heterogeneity. Microvessel distribution is an important characteristic of solid tumors, with significant hypoxia occurring in the center of tumors with low blood flow. The distribution of miR-374a in breast tumors was examined as a factor likely to be important in breast cancer progression. Methods: Breast tissue samples from 40 patients with breast cancer were classified into two groups: a highly invasive and metastatic group (HIMG) and a low-invasive and metastatic Group (LIMG). Samples were collected from the center and edge of each tumor. In each group, six specimens were examined by microRNA array, and the remaining 14 specimens were used for real-time RT-qPCR, Western blot and immunohistochemical analyses. Correlation analysis was performed for the miRNAs and target proteins. Follow-up was carried out during 28 months to 68 months after surgery, and survival data were analyzed. Results: In the LIMG, the relative content of miR-374a was lower in the center of the tumor than at its edge; in the HIMG, it was lower at the edge of the tumor, and miR-374a levels were lower in breast cancer tissues than in normal tissues. There was no difference between VEGF-A and VCAM-1 mRNA levels at the edge and center of the tumor; however, we observed a significant difference between VEGF-A and VCAM-1 protein expression levels in these two regions. There was a negative correlation between miR-374a and target protein levels. The microvessel density (MVD) was lower in the center of the tumor than at its edge in HIMG, but the LIMG vessels were uniformly distributed. There was a significant positive correlation between MVD and the number of lymph node metastases (Pearson correlation, r=0.912, P<0.01). The median follow-up time was 48.5 months. LIMG had higher rate of disease-free survival (100%, P=0.013) and longer median survival time (66 months) than HIMG, which had a lower rate of 75% and shorter median survival time (54 months). Conclusions: Our data demonstrated miR-374a to be differentially distributed in breast cancer; VEGF-A and VCAM-1 mRNA had coincident distribution, and the distribution of teh respective proteins was uneven and opposite to that for the miR-374a. These data might explain the differences in the distribution of MVD in breast cancer and variation in breast cancer prognosis.

• Journal of the Korean Statistical Society
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• v.28 no.3
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• pp.359-370
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• 1999

We considered a change-point hazard rate model generalizing constant hazard rate model. This type of model is very popular in the sense that the Weibull and exponential distributions formulating survival time data are the special cases of it. Maximum likelihood estimation and the asymptotic properties such as the consistency and its limiting distribution of the change-point estimator were discussed. A parametric bootstrap method for finding confidence intervals of the unknown change-point was also suggested and the proposed method is explained through a practical example.