• Asian Pacific Journal of Cancer Prevention
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• 제13권9호
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• pp.4281-4284
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• 2012

Background: Osteosarcoma is the most common bone cancer in children, responsible for a high rate of amputation and death. This is the first long-term, population-based, epidemiologic and survival study in Thailand. Objective: To study the incidence and survival rates of pediatric osteosarcoma in Khon Kaen. Method: Childhood osteosarcoma cases (0-19 years) diagnosed between 1985-2010 were reviewed. The data were retrieved from the population-based data set of the Khon Kaen Cancer Registry and medical records from Srinagarind Hospital, Faculty of Medicine, Khon Kaen University. All cases were censored until the end of April 2012. The age-standardized incidence rate (ASR) was calculated using the standard method. Survival experience was analyzed using the standard survival function (STATA 9.0) and presented with a Kaplan-Meier curve. Results: 58 cases were enrolled. The overall ASR was 14.1 per million. Males and females were equally affected. The peak incidence was for 15-19 year-olds in both sexes (ASR=10.4 per million in males and 8.5 in females). The 5-year overall survival rate was 27.6% (95% CI: 15.8-40.8%). The median survival time was 1.6 years (95% CI: 1.2-2.1). In a subgroup analysis, the patients who received only chemotherapy survived longer (5-year survival 45.7%, median survival time 4.1 years, p=0.12). Conclusion: The incidence rate for childhood osteosarcoma was slightly less than those reported for Western countries. The survival rate was also lower than reports from developed countries. Further evaluation of the treatment protocol and risk factor stratification is needed.

• Communications for Statistical Applications and Methods
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• 제20권3호
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• pp.169-174
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• 2013

The ROC curve is drawn with two conditional cumulative distribution functions (or survival functions) of the univariate random variable. In this work, we consider joint cumulative distribution functions of k random variables, and suggest a ROC curve for multivariate random variables. With regard to the values on the line, which passes through two mean vectors of dichotomous states, a joint cumulative distribution function can be regarded as a function of the univariate variable. After this function is modified to satisfy the properties of the cumulative distribution function, a ROC curve might be derived; moreover, some illustrative examples are demonstrated.

• Communications for Statistical Applications and Methods
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• 제21권6호
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• pp.487-500
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• 2014

A new method to calculate the transmittable prevalence of an epidemic disease is proposed based on a back-calculation formula. We calculated the probabilities of reactivation and of parasitemia as well as transmittable prevalence (the number of persons with parasitemia in the incubation period) of malaria in South Korea using incidence of 12 years(2001-2012). For this computation, a new probability function of transmittable condition is obtained. The probability of reactivation is estimated by the least squares method for the back-calculated longterm incubation period. The probability of parasitemia is calculated by a convolution of the survival function of the short-term incubation function and the probability of reactivation. Transmittable prevalence is computed by a convolution of the infected numbers and the probabilities of transmission. Confidence intervals are calculated using the parametric bootstrap method. The method proposed is applicable to other epidemic diseases in other countries where incidence and a long incubation period are available. We found the estimated transmittable prevalence in South Korea was concentrated in the summer with 276 cases on a peak at the $31^{st}$ week and with about a 60% reduction in the peak from the naive prevalence. The statistics of transmittable prevalence can be used for malaria prevention programs and to select blood transfusion donors.

• 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.

• Communications for Statistical Applications and Methods
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• 제9권3호
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• pp.825-834
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• 2002

Poisson processes are widely used in reliability and survival analysis. In particular, multiple event time data in survival analysis are routinely analyzed by use of Poisson processes. In this paper, we consider large sample properties of nonparametric Bayesian models for Poisson processes. We prove that the posterior distribution of the cumulative intensity function of Poisson processes is consistent under regularity conditions on priors which are Levy processes.

• Journal of applied mathematics & informatics
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• 제18권1_2호
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• pp.311-320
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• 2005

Studies in the evolutionary biology of aging require good estimates of the age-dependent mortality rate coefficient (one of the Gompertz parameters). In this paper we introduce an alternative algorithm for estimating this parameter. And we discuss the sensitivity of the estimates to changes in the other model parameters.

• 한국어병학회지
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• 제15권1호
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• pp.37-42
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• 2002

Effect of mercury (Hg) toxicity on survival, growth, feed efficiency and oxygen consumption were examined in the juvenile olive flounder. Paralichthys olivaceus. Fishes were exposed to sublethal concentrations of Hg ranging from 0 to 0.13mg/L for 6 weeks. Hg reduced survival rate in a concentration and exposure period-dependent way and suddenly reduction occurred at Hg concentrations greater than 0.05mg/L after 6 weeks. Growth rate and feed efficiency also significantly decreased at greater than 0.028 and 0.05 mg/L respectively. Oxygen consumption rate was significantly decreased to 25 and 32% than that of the control at the Hg concentration of 0.05 and 0.13 mg/L respectively. These results suggest that Hg toxicity inhibit physiological function including growth, feed efficiency and oxygen consumption in the juvenile olive flounder, resulting in survival failure at high concentration.

• Journal of the Korean Data and Information Science Society
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• 제7권2호
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• pp.263-272
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• 1996

임의의 기계에 대한 수명의 분포는 와이블분포를 하는 경우가 흔하다. 그리고 현실적으로 기계의 수명시간을 검정할 때, 시험시간및 여러 환경적인 제약에 의하여 표본으로 주어진 기계의 수명을 모두 관측하기는 어렵다. 그래서, 본 연구에서는 임의 중단모형 하에서 와이블분포의 모수를 최소제곱법(least squares method)을 이용하여 추정하고 기존의 최대우도추정량(maximum likelihood estimates)과 효율성의 측면에서 비교하고자 한다.

• 한국농공학회논문집
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• 제50권6호
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• pp.61-71
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• 2008

An advanced model for assessing life cycle cost of the facility containing several subdivisions has been proposed with systems engineering approach. This model evaluates the maintenance cost in the sphere of the safety as well as in that of its functionality. The proposed approach has been shown to be more reasonable and practical than existing models. The serviceability and reasonability have been proved through evaluating life cycle cost of the reservoir which is a representative agricultural facility. In addition, the proposed method is helpful to make a maintenance strategy using the survival probability in the point of safety and functionality.

• Journal of the Korean Data and Information Science Society
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• 제8권1호
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• pp.99-109
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• 1997

The estimation procedure of mean residual life function has been placed an important role in the study of survival analysis. In this paper, the product limit estimator on left truncated and right censoring model is proposed with asymptotic properties. Also, the small sample properties are investigated through the Monte Carlo study and the proposed product limit type estimator is compared with ordinary Kaplan-Meier type estimator.