• Journal of Periodontal and Implant Science
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• 제54권2호
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• pp.122-135
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• 2024

Purpose: This retrospective study aimed to assess the long-term cumulative survival rate of titanium, sandblasted, large-grit, acid-etched implants over a 10-year follow-up period and investigate the factors affecting the survival rate and change in marginal bone loss (MBL). Methods: The study included 400 patients who underwent dental implant placement at the Department of Periodontology of Seoul National University Dental Hospital (SNUDH) between 2005 and 2015. Panoramic radiographic images and dental records of patients were collected and examined using Kaplan-Meier analysis, Cox proportional hazards regression analysis, and multiple regression analysis to determine the survival rates and identify any factors related to implant failure and MBL. Results: A total of 782 implants were placed with a follow-up period ranging from 0 to 16 years (mean: 8.21±3.75 years). Overall, 25 implants were lost, resulting in a cumulative survival rate of 96.8%. Comparisons of the research variables regarding cumulative survival rate mostly yielded insignificant results. The mean mesial and distal MBLs were 1.85±2.31 mm and 1.59±2.03 mm, respectively. Factors influencing these values included age, diabetes mellitus (DM), jaw location, implant diameter, bone augmentation surgery, and prosthetic unit. Conclusions: This study found that the implant survival rates at SNUDH fell within the acceptable published criteria. The patients' sex, age, DM status, implant location, implant design, implant size, surgical type, bone augmentation, and prosthetic unit had no discernible influence on long-term implant survival. Sandblasted, large-grit, acid-etched implants might offer advantages in terms of implant longevity and consistent clinical outcomes.

• Genomics & Informatics
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• 제8권4호
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• pp.212-218
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• 2010

An accurate system for predicting the survival of patients with oral squamous cell carcinoma (OSCC) will be useful for selecting appropriate therapies. A nomogram for predicting survival was constructed from 96 patients with primary OSCC who underwent surgical resection between January 1994 and June 2003 at the Yonsei Dental Hospital in Seoul, Korea. We performed univariate and multivariate Cox regression to identify survival prognostic factors. For the early stage patients group, the nomogram was able to predict the 5 and 10 year survival from OSCC with a concordance index of 0.72. The total point assigned by the nomogram was a significant factor for predicting survival. This nomogram was able to accurately predict the survival after treatment of an individual patient with OSCC and may have practical utility for deciding adjuvant treatment.

• Communications for Statistical Applications and Methods
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• 제24권2호
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• pp.115-127
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• 2017

This paper proposes a Bayesian test for the equivalence of survival functions in multiple groups. Proposed Bayesian test use the model of Cox's regression with time-varying coefficients. B-spline expansions are used for the time-varying coefficients, and the proposed test use only the partial likelihood, which provides easier computations. Various simulations of the proposed test and typical tests such as log-rank and Fleming and Harrington tests were conducted. This result shows that the proposed test is consistent as data size increase. Specifically, the power of the proposed test is high despite the existence of crossing hazards. The proposed test is based on a Bayesian approach, which is more flexible when used in multiple tests. The proposed test can therefore perform various tests simultaneously. Real data analysis of Larynx Cancer Data was conducted to assess applicability.

• 대한한의학회지
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• 제23권4호
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• pp.91-97
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• 2002

Objective: This study was conducted to know the survival probability of the patients with cerebrovascular disease. Method: 1,341 patients who were suspected of having cerebrovascular disease clinically were investigated by telephone and NHIC (National Health Insurance Corporation) data. Conclusion: 1. The study population was grouped as 'Negative Brain CT findings' (11.8%), 'Hemorrhage' (12.4%) and 'Infarction' (75.7%). 2. The survival probabilities calculated by the Life Table method were statistically significant among brain CT finding groups (P<0.01). 3. The mean survival time calculated by the Kaplan-Meier method were also statistically significant among brain CT finding groups (P<0.01). 4. The result of Cox regression model was that sex (OR=0.7), age (OR=1.07), diabetes mellitus (OR=1.38), and heart disease (OR=1.69) affected the survival of the patients with cerebrovascular disease.

• 응용통계연구
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• 제29권7호
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• pp.1231-1246
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• 2016

경쟁위험에 대한 연구 중 주로 쓰이는 방법은 Cause-specific 위험 모형과 subdistribution을 이용한 비례 위험 모형 방법이다. 그 이후에도 많은 모형이 제시되었지만, 추정 방법 면에서 설명력이 부족하거나 알고리즘으로 구현하기 어려운 단점을 가지고 있어서 잘 활용되고 있지 않다. 이 논문에서는 Cause-specific 위험 모형, subdistribution을 이용한 비례 위험 모형과 비교적 최근에 제시된 이항 회귀 모형(direct binomial model), 절대 위험 회귀 모형(absolute risk regression model), Eriksson 등 (2015)의 비례 오즈 모형(proportional odds model)을 소개하고 추정 방법을 간단히 설명하고자 한다. 각 모형에 대하여 SAS와 R을 이용한 활용 방법을 제시하고, 두 가지 경쟁위험이 존재하는 데이터를 R을 이용하여 분석하였다.

• Asian Pacific Journal of Cancer Prevention
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• 제17권1호
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• pp.159-163
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• 2016

Background: Colorectal cancer (CRC) is the third most common cancer in the world, and the fourth in Iran in both genders. The aim of this study was to find predictive factors for CRC survival. Materials and Methods: Medical records of 570 patients referred to the radiotherapy oncology department of Shiraz Namazi hospital from 2005 to 2010 were retrospectively analysed. Data were collected by reviewing medical records, and by telephone interviews with patients. Survival analysis was performed using the Cox's regression model with survival probability estimated with Kaplan-Meier curve. The log-rank test was used to compare survival between strata. Data was analyzed with Stata 12. Results: The five-year survival rate and the mean survival time after cancer diagnosis were 58.5% and $67{\pm}4months$. On multivariate analysis, age of diagnosis, disease stage and primary tumor site, lymphovascular invasion and type of treatment (in colon cancer) were significant factors for survival. Conclusions: Age of diagnosis and type of treatment (adjuvant therapy in patients with colon cancer) were two modifiable factors related to survival of CRC patients. Therefore earlier diagnosis might help increase survival.

• Asian Pacific Journal of Cancer Prevention
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• 제13권3호
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• pp.1053-1057
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• 2012

Objective: Identifying cancer-related genes or proteins is critical in preventing and controlling colorectal cancer (CRC). This study was to investigate the clinicopathological and prognostic value of activating transcription factor 1 (ATF1) in CRC. Methods: Protein expression of ATF1 was detected using immunohistochemistry in 66 CRC tissues. Clinicopathological association of ATF1 in CRC was analyzed with chi-square test or Fisher's exact test. The prognostic value of ATF1 in CRC is estimated using the Kaplan-Meier analysis and Cox regression models. Results: The ATF1 protein expression was significantly lower in tumor tissues than corresponding normal tissues (51.5% and 71.1%, respectively, P = 0.038). No correlation was found between ATF1 expression and the investigated clinicopathological parameters, including gender, age, depth of invasion, lymph node status, metastasis, pathological stage, vascular tumoral emboli, peritumoral deposits, chemotherapy and original tumor site (all with P > 0.05). Patients with higher ATF1 expression levels have a significantly higher survival rate than that with lower expression (P = 0.026 for overall survival, P = 0.008 for progress free survival). Multivariate Cox regression model revealed that ATF1 expression and depth of invasion were the predictors of the overall survival (P = 0.008 and P = 0.028) and progress free survival (P = 0.002 and P = 0.005) in CRC. Conclusions: Higher ATF1 expression is a predictor of a favorable outcome for the overall survival and progress free survival in CRC.

• 한국컴퓨터정보학회논문지
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• 제24권9호
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• pp.103-108
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• 2019

The purpose of this study is to identify the factors that may affect the 5-year survival of colon cancer through network model and to use it as a clinical decision supporting system for colorectal cancer patients. This study was conducted using data from 2,540 patients who underwent colorectal cancer surgery from 1996 to 2018. Eleven factors related to survival of colorectal cancer were selected by consulting medical experts and previous studies. Analysis was proceeded from the data sorted out into 1,839 patients excluding missing values and outliers. Logistic regression analysis showed that age, BMI, and heart disease were statistically significant in order to identify factors affecting 5-year survival of colorectal cancer. Additionally, a correlation analysis was carried out age, BMI, heart disease, diabetes, and other diseases were correlated with 5-year survival of colorectal cancer. Sex was related with BMI, lung disease, and liver disease. Age was associated with heart disease, heart disease, hypertension, diabetes, and other diseases, and BMI with hypertension, diabetes, and other diseases. Heart disease was associated with hypertension, diabetes, hypertension, diabetes, and other diseases. In addition, diabetes and kidney disease were associated. In the correlation analysis, the network model was constructed with the Network Correlation Coefficient less than p <0.001 as the weight. The network model showed that factors directly affecting survival were age, BMI levels, heart disease, and indirectly influencing factors were diabetes, high blood pressure, liver disease and other diseases. If the network model is used as an assistant indicator for the treatment of colorectal cancer, it could contribute to increasing the survival rate of patients.

• Asian Pacific Journal of Cancer Prevention
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• 제14권6호
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• pp.3881-3885
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• 2013

Objective: The objective of this study was to identify clinical predictive factors for tumor response after neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). Methods: All factors were evaluated in 88 patients with LARC treated with nCRT. After a long period of 4-8 weeks of chemoradiotherapy, 3 patients achieved clinical complete response (cCR) and thus aggressive surgery was avoided, and the remaining 85 patients underwent a curative-intent operation. The response to nCRT was evaluated by tumor regression grade (TRG) system. Results: There were 32 patients (36.4%) with good tumor regression (TRG 3-4) and 56 (63.6%) with poor tumor regression (TRG 0-2). Lymphocyte counts and ratios were higher in good response cases (P=0.01, 0.03, respectively) while neutrophil ratios and N/L ratios were higher in poor response cases (P=0.04, 0.02, respectively). High lymphocyte ratios before nCRT and good tumor regression (TRG3-4) were significantly associated with improved 5-year disease-free survival (P<0.05). Pretreatment nodal status was also significantly associated with 5-year disease-free survival and 5-year overall survival (P<0.05). Multivariate analysis confirmed that the pretreatment lymphocyte ratio and lymph nodal status were independent prognostic factors. Conclusion: Our study suggested that LARC patients with high lymphocyte ratios before nCRT would have good tumor response and high 5-year DFS and OS.

• 대한산업공학회지
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• 제40권3호
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• pp.283-290
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• 2014

In the flat panel display industry, to meet production target quantities and the deadline of production, the scheduler and dispatching systems are major production management systems which control the order of facility production and the distribution of WIP (Work In Process). Especially the delivery time is a key factor of the dispatching system for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors of the delivery time and to build the delivery time forecasting model. To select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the accelerated failure time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the mean square error (MSE) criteria, the AFT model decreased by 33.8% compared to the statistics prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing the delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.