• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7923-7927
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• 2015

Background: The Cox PH model is one of the most significant statistical models in studying survival of patients. But, in the case of patients with long-term survival, it may not be the most appropriate. In such cases, a cure rate model seems more suitable. The purpose of this study was to determine clinical factors associated with cure rate of patients with breast cancer. Materials and Methods: In order to find factors affecting cure rate (response), a non-mixed cure rate model with negative binomial distribution for latent variable was used. Variables selected were recurrence cancer, status for HER2, estrogen receptor (ER) and progesterone receptor (PR), size of tumor, grade of cancer, stage of cancer, type of surgery, age at the diagnosis time and number of removed positive lymph nodes. All analyses were performed using PROC MCMC processes in the SAS 9.2 program. Results: The mean (SD) age of patients was equal to 48.9 (11.1) months. For these patients, 1, 5 and 10-year survival rates were 95, 79 and 50 percent respectively. All of the mentioned variables were effective in cure fraction. Kaplan-Meier curve showed cure model's use competence. Conclusions: Unlike other variables, existence of ER and PR positivity will increase probability of cure in patients. In the present study, Weibull distribution was used for the purpose of analysing survival times. Model fitness with other distributions such as log-N and log-logistic and other distributions for latent variable is recommended.

• Polymer(Korea)
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• v.26 no.6
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• pp.728-736
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• 2002

The thermal and dielectric properties of unsaturated polyester resin system during cure were analyzed under Isothermal conditions. Both $varepsilon$′ and $varepsilon$" decreased and dipole relaxation was observed under isothermal conditions during cure. The ionic conductivity decreased linearly with the conversion according to the Kienle-Rate equation (ln($varepsilon$"$_{ionic}$we$_{0}$)=C$_{r}$$alpha$+C$_{0}$) up to $alpha$=0.15, after which it aparted from the relationship due to the entanglement of polymer chains. The effect of ionic conductivity was revealed to be larger than that of dipole motion during the whole cure through the electrical modulus analysis. Although dielectric motion was analyzed with Debye model, it was observed only at a narrow time region of middle stage of cure. In order to estimate the dielectric properties during the whole cure, the Havriliak-Negami model was considered and modified with the strong effect of ionic conductivity. The changes of $varepsilon$′ and $varepsilon$" were well estimated with this modified Havriliak-Negami model.

• 연구논문집
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• s.29
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• pp.151-162
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• 1999

In general, manufacturing processes of thermosetting composites consist of mold filling and resin cure. The important parameters used in modeling and designing mold filling are the permeability of the fibrous preform and the viscosity of the resin. To consolidate a composite, resin cure or chemical reaction plays an essential role. Cure kinetics. Therefore, is necessary to quantify the extent of chemical reaction or degree of cure. It is also important to predict resin viscosity which can change due to chemical reaction during mold filling. There exists a heat transfer between the mold and the composite during mold filling and resin cure. Cure kinetics is also used to predict a temperature profile inside composite. In this study, a new scheme which can determine cure kinetics from dynamic temperature scaning was proposed. The method was applied to epoxy resin system and was verified by comparing measurements and predictions.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.445-455
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• 1999

We modify the Gompertz regression model for estimation of cure rates from pediatric clinical trials by assuming different hazard rates on the different periods. A treatment period may be divided by the stages of treatments under the different treatment arms. The piecewise Gompertz models provide an efficient method for estimation of the cure rates and a method for testing the difference of the treatment effects in the given interval.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.21-30
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• 2014

Ordinary survival analysis cannot be applied when a significant fraction of patients may be cured. A cure rate model is the combination of cure fraction and survival model and can be applied to several types of cancer. In this article, the cure rate model is considered in the interval censored data with a cluster effect. A shared frailty model is introduced to characterize the cluster effect and an EM algorithm is used to estimate parameters. A simulation study is done to evaluate the performance of estimates. The proposed approach is applied to the smoking cessation study in which the event of interest is a smoking relapse. Several covariates (including intensive care) are evaluated to be effective for both the occurrence of relapse and the smoke quitting duration.

• Composites Research
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• v.28 no.3
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• pp.99-103
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• 2015

This paper presents the cure kinetics studies on the cure reaction of thermosetting resin. Above all, change in degree of cure and specific heat capacity according to temperature are observed using DSC and MDSC. The results are analyzed by cure kinetics and specific heat capacity model. Glass transition temperature was also measured to apply to the specific heat capacity model. Model parameters were gained from the modeling result. As a result, behavior of specific heat capacity can be calculated mathematically.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.16
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• pp.7359-7363
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• 2015

Background: As a result of significant progress made in treatment of many types of cancers during the last few decades, there have been an increased number of patients who do not experience mortality. We refer to these observations as cure or immune and models for survival data which include cure fraction are known as cure rate models or long-term survival models. Materials and Methods: In this study we used the data collected from 438 female patients with breast cancer registered in the Cancer Research Center in Shahid Beheshti University of Medical Sciences, Tehran, Iran. The patients had been diagnosed from 1992 to 2012 and were followed up until October 2014. We had to exclude some because of incomplete information. Phone calls were made to confirm whether the patients were still alive or not. Deaths due to breast cancer were regarded as failure. To identify clinical, pathological, and biological characteristics of patients that might have had an effect on survival of the patients we used a non-mixture cure rate model; in addition, a Weibull distribution was proposed for the survival time. Analyses were performed using STATA version 14. The significance level was set at $P{\leq}0.05$. Results: A total of 75 patients (17.1%) died due to breast cancer during the study, up to the last follow-up. Numbers of metastatic lymph nodes and histologic grade were significant factors. The cure fraction was estimated to be 58%. Conclusions: When a cure fraction is not available, the analysis will be changed to standard approaches of survival analysis; however when the data indicate that the cure fraction is available, we suggest analysis of survival data via cure models.

• Design & Manufacturing
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• v.16 no.3
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• pp.44-49
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• 2022

In this study, the simulation of the resin transfer molding process method using MoldFlow has been investigated. This work explains the thermoset material model, fabric permeability model, the flow model and the cure model. It has been shown that the simulation result can predict filling and cure performances.

• Polymer(Korea)
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• v.24 no.1
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• pp.105-112
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• 2000

Using a commercial epoxy/carbon fiber composite prepreg (DMS 2224) as a model system, the cure kinetics of vitrifying thermoset system were analyzed by isothermal and dynamic-heating experiments. Focusing on the processing condition of high performance composite systems, a phenomenological kinetic model was developed by using differential scanning calorimetry (DSC) and reaction kinetics theories. The model system exhibited a limited degree of cure as a function of isothermal temperature seemingly due to the diffusion-controlled reaction rates. The diffusion-controlled cure reaction was incorporated in the development of the kinetic model, and the model parameters were determined from isothermal experiments. The first order reaction was confirmed from the characteristic shape of isothermal cure thermograms, and the activation energy wes 78.43 kJ/mol. Finally, the proposed model was used to predict a complex autoclave thermal condition, which was composed of several isothermal and dynamic-heating stages.