• Asian Pacific Journal of Cancer Prevention
• /
• 제15권12호
• /
• pp.4839-4842
• /
• 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
• /
• 제16권17호
• /
• pp.7923-7927
• /
• 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.

• 응용통계연구
• /
• 제27권1호
• /
• pp.21-30
• /
• 2014

치유율 모형(cure rate model)은 위험 그룹의 단조 감소에 대한 가정이 부적절한 경우에 적용될 수 있다. 예를 들어, 생존 분석에서 위험 그룹은 시간이 경과함에 따라 점점 감소하여 무한대의 시간대에는 영으로 수렴하며 이는 곧 생존 함수가 영으로 수렴함을 의미한다. 하지만 이러한 가정이 적합하지 못한 자료가 의약학, 사회학, 경제학 등에서 종종 발생된다. 즉, 어느 시점에 이르러 더 이상의 생존함수는 감소하지 않고 평행선을 보여주는 경우에 로그 순위검정(log rank test)과 Cox's 비례위험모형(proportional hazard model)의 적용은 바람직하지 못한 결론을 가져오게 된다. 이러한 자료에 대해 치유율 모형(cure rate model)에서는 사건 발생 취약 그룹(susceptible group)과 비취약 그룹(insusceptible group)으로 나누어 취약그룹에 대해서만 일반적인 생존 분석 방법을 적용하는 혼합 모형(mixture model)을 적용해왔다 (Berkson과 Gage, 1952). 본 연구에서는 이러한 치유율 모형을 군집화 구간 중도 절단 자료(clustered interval censored data)에 적용해 보고자 한다. 최근에 Kim과 Jhun (2008)은 구간 중도 절단자료에 대해 치유율 모형을 적용하였으며 본 연구에서는 그들의 방법을 군집화 자료로 확장할 것이다. 실제 자료 분석의 예로 금연자료를 분석할 것이다.

• Asian Pacific Journal of Cancer Prevention
• /
• 제16권16호
• /
• pp.7359-7363
• /
• 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.

• Journal of the Korean Data and Information Science Society
• /
• 제10권2호
• /
• pp.445-455
• /
• 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.

• Communications for Statistical Applications and Methods
• /
• 제27권1호
• /
• pp.37-46
• /
• 2020

Recurrent event data frequently occur in clinical studies, demography, engineering reliability and so on (Cook and Lawless, The Statistical Analysis of Recurrent Events, Springer, 2007). Sometimes, two or more different but related type of recurrent events may occur simultaneously. In this study, our interest is to estimate the covariate effect on bivariate recurrent event times with zero inflations. Such zero inflation can be related with susceptibility. In the context of bivariate recurrent event data, furthermore, such susceptibilities may be different according to the type of event. We propose a joint model including both two intensity functions and two cure rate functions. Bivariate frailty effects are adopted to model the correlation between recurrent events. Parameter estimates are obtained by maximizing the likelihood derived under a piecewise constant hazard assumption. According to simulation results, the proposed method brings unbiased estimates while the model ignoring cure rate models gives underestimated covariate effects and overestimated variance estimates. We apply the proposed method to a set of bivariate recurrent infection data in a study of child patients with leukemia.

• 폴리머
• /
• 제26권6호
• /
• pp.728-736
• /
• 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.

• Asian Pacific Journal of Cancer Prevention
• /
• 제15권22호
• /
• pp.9673-9678
• /
• 2014

Background: Breast cancer is a fatal disease and the most frequently diagnosed cancer in women with an increasing pattern worldwide. The burden is mostly attributed to metastatic cancers that occur in one-third of patients and the treatments are palliative. It is of great interest to determine factors affecting time from cancer diagnosis to secondary metastasis. Materials and Methods: Cure rate models assume a Poisson distribution for the number of unobservable metastatic-component cells that are completely deleted from the non-metastasis patient body but some may remain and result in metastasis. Time to metastasis is defined as a function of the number of these cells and the time for each cell to develop a detectable sign of metastasis. Covariates are introduced to the model via the rate of metastatic-component cells. We used non-mixture cure rate models with Weibull and log-logistic distributions in a Bayesian setting to assess the relationship between metastasis free survival and covariates. Results: The median of metastasis free survival was 76.9 months. Various models showed that from covariates in the study, lymph node involvement ratio and being progesterone receptor positive were significant, with an adverse and a beneficial effect on metastasis free survival, respectively. The estimated fraction of patients cured from metastasis was almost 48%. The Weibull model had a slightly better performance than log-logistic. Conclusions: Cure rate models are popular in survival studies and outperform other models under certain conditions. We explored the prognostic factors of metastatic breast cancer from a different viewpoint. In this study, metastasis sites were analyzed all together. Conducting similar studies in a larger sample of cancer patients as well as evaluating the prognostic value of covariates in metastasis to each site separately are recommended.

• Communications for Statistical Applications and Methods
• /
• 제24권6호
• /
• pp.605-625
• /
• 2017

This paper presents proportional odds cure models to allow spatial correlations by including spatial frailty in the interval censored data setting. Parametric cure rate models with independent and dependent spatial frailties are proposed and compared. Our approach enables different underlying activation mechanisms that lead to the event of interest; in addition, the number of competing causes which may be responsible for the occurrence of the event of interest follows a Geometric distribution. Markov chain Monte Carlo method is used in a Bayesian framework for inferential purposes. For model comparison some Bayesian criteria were used. An influence diagnostic analysis was conducted to detect possible influential or extreme observations that may cause distortions on the results of the analysis. Finally, the proposed models are applied for the analysis of a real data set on smoking cessation. The results of the application show that the parametric cure model with frailties under the first activation scheme has better findings.

• 응용통계연구
• /
• 제17권2호
• /
• pp.253-267
• /
• 2004

임상시험중에는 소아암연구에서와 같이 환자 중의 상당수에서 사망 또는 재발이 오랜 기간 일어나지 않고 완치된 것으로 보이는 경우가 있다. 이 경우 연구자는 생존함수의 전반적인 비교보다는 치료율의 비교에 더 관심이 있을 것이다. 본고에서는 치료율의 비교를 위한 여러 모수적, 비모수적 방법들을 소개하고, 생존분포, 치료율, 중도절단을 등을 다양하게 설정한 모의실험을 통하여 각 방법들의 검정력과 유의수준을 비교하였다.