• Journal of Preventive Medicine and Public Health
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• v.52 no.2
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• pp.140-144
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• 2019

Objectives: Investigating the survival of patients with cancer is vitally necessary for controlling the disease and for assessing treatment methods. This study aimed to compare various statistical models of survival and to determine the survival rate and its related factors among patients suffering from lung cancer. Methods: In this retrospective cohort, the cumulative survival rate, median survival time, and factors associated with the survival of lung cancer patients were estimated using Cox, Weibull, exponential, and Gompertz regression models. Kaplan-Meier tables and the log-rank test were also used to analyze the survival of patients in different subgroups. Results: Of 102 patients with lung cancer, 74.5% were male. During the follow-up period, 80.4% died. The incidence rate of death among patients was estimated as 3.9 (95% confidence [CI], 3.1 to 4.8) per 100 person-months. The 5-year survival rate for all patients, males, females, patients with non-small cell lung carcinoma (NSCLC), and patients with small cell lung carcinoma (SCLC) was 17%, 13%, 29%, 21%, and 0%, respectively. The median survival time for all patients, males, females, those with NSCLC, and those with SCLC was 12.7 months, 12.0 months, 16.0 months, 16.0 months, and 6.0 months, respectively. Multivariate analyses indicated that the hazard ratios (95% CIs) for male sex, age, and SCLC were 0.56 (0.33 to 0.93), 1.03 (1.01 to 1.05), and 2.91 (1.71 to 4.95), respectively. Conclusions: Our results showed that the exponential model was the most precise. This model identified age, sex, and type of cancer as factors that predicted survival in patients with lung cancer.

• Tuberculosis and Respiratory Diseases
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• v.43 no.5
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• pp.709-719
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• 1996

Background: Surgical resection is the only way to cure non-small cell lung cancer(NSCLC) and the prognosis of NSCLC in patients who undergo a complete resection is largely influenced by the pathologic stage. After surgical resection, recurrences in distant sites is more common than local recurrences. An effective postoperative adjuvant therapy which can prevent recurrences is necessary to improve long tenn survival Although chemotherapy and radiotherapy are still the mainstay in adjuvant therapy, the benefits of such therapies are still controversial. We initiated this retrospective study to evaluate the effects of adjuvant therapies and analyze the prognostic factors for survival after curative resection. Method: From 1990 to 1995, curative resection was perfomled in 282 NSCLC patients with stage I, II, IIIa, Survival analysis of 282 patients was perfonned by Kaplan-Meier method. The prognostic factors, affecting survival of patients were analyzed by Cox regression model. Results: Squamous cell carcinoma was present in 166 patients(59%) ; adenocarcinoma in 86 pmients(30%) ; adenosquamous carcinoma in II parients(3.9%); and large cell undifferentiated carcinoma in 19 patients(7.1%). By TNM staging system, 93 patients were in stage I; 58 patients in stage II ; and 131 patients in stage rna. There were 139 postoperative recurrences which include 28 local and 111 distant failures(20.1% vs 79.9%). The five year survival rate was 50.1% in stage I ; 31.3% in stage II ; and 24.1% in stage IIIa(p <0.0001). The median survival duration was 55 months in stage I ; 27 months in stage II ; and 16 months in stage rna. Among 131 patients with stage rna, the median survival duration was 19 months for 81 patients who received postoperative adjuvant chemotherapy only or cherne-radiotherapy and 14 months for the other 50 patients who received surgery only or surgery with adjuvant radiotherapy(p=0.2982). Among 131 patients with stage IIIa, the median disease free survival duration was 16 months for 21 patients who received postop. adjuvant chemotherapy only and 4 months for 11 patients who received surgery only(p=0.0494). In 131 patients with stage IIIa, 92 cases were in N2 stage. The five year survival rate of the 92 patients with N2 was 25% and their median survival duration was 15 months. The median survival duration in patients with N2 stage was 18 months for those 62 patients who received adjuvant chemotherapy and 14 months for the other 30 patients who did not(p=0.3988). The median survival duration was 16 months for those 66 patients who received irradiation and 14 months for the other 26 patients who did not(p=0.6588). We performed multivariate analysis to identify the factors affecting prognosis after complete surgical resection, using the Cox multiple regression model. Only age(p=0.0093) and the pathologic stage(p<0.0001) were significam prognostic indicators. Conclusion: The age and pathologic stage of the NSCLC parients are the significant prognostic factors in our study. Disease free survival duration was prolonged with statistical significance in patients who received postoperative adjuvant chemotherapy but overall survival duration was not affected according to adjuvant therapy after surgical resection.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1045-1054
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• 2012

Support vector machine is known to be the very useful statistical method in classification and nonlinear function estimation. In this paper we propose a monotone support vector regression (SVR) for the estimation of monotonically decreasing function. The proposed monotone SVR is applied to smooth the Kaplan-Meier estimate of survival function. Experimental results are then presented which indicate the performance of the proposed monotone SVR using survival functions obtained by exponential distribution.

• The Journal of Korean Academy of Prosthodontics
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• v.45 no.1
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• pp.48-59
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• 2007

Statement of problems: There are few studies which reported the survival rates of the specific dental implant systems in the Korean population with the follow-up periods longer than 5 years. Purpose: This retrospective clinical study was aimed to evaluate cumulative survival rate (CSR) of $Br{\aa}nemark$ implants followed for 10 years and to determine risk factors for implant failure. Material and methods: A total of 271 $Br{\aa}nemark$ implants in 83 patients were investigated with several identified risk factors. Life table analysis was undertaken to examine the CSR. Cox regression method was conducted to assess the association between potential risk factors and overall CSR. Results: Thirty implants failed. The 10-year implant CSR was 82.5%. Cox regression analysis demonstrated a significant predictive association between overall CSR and implant length (P<.05). Conclusion: An acceptable long-term result of $Br{\aa}nemark$ implant was achieved and implant length showed a significant association with the CSR.

• Journal of Family Resource Management and Policy Review
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• v.26 no.3
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• pp.65-85
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• 2022

This study aims to contribute to social work practice in understanding marriage and divorce as transitions and in helping women make meaningful decisions on whether to stay or leave the marriage by examining the factors that impact women's divorce decision making over time. This is a longitudinal study that used survival analysis by Korean Longitudinal Survey of Women and Families' panel data. Finally, cox regression analysis was used to evaluate the impact of each factor on divorce decision making, and accordingly, all regression models were appropriate for analysis.

• Journal of Dental Rehabilitation and Applied Science
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• v.31 no.1
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• pp.10-19
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• 2015

Purpose: The aim of the present study was to evaluate the long-term survival of implants retrospectively and determine the risk factors associated with implant failure. Materials and Methods: Of all implants that were placed at the Department of Periodontology of the Dental Hospital of Gangneung-Wonju National University from January 1998 to December 2012, 2265 implants that were followed up until June 2013 were included in this study. Data were collected from clinical and radiographic examinations from previous visits. The information gathered included gender, age, smoking status, implant diameter, implant length, surface of implant, location of implant within the dental arch, surgical techniques and existence of complications. Results: The survival rate before loading was 98.9%. The cumulative survival rate after 5 years of loading was 97.2%, and after 15 years of loading was 95.2%. In a simple logistic regression analysis, gender (P = 0.016), smoking status (P = 0.001), location of implant (P = 0.020) and existence of complications (P = 0.002) were statistically associated with implant failure and included in the multiple regression analysis. As a result of multiple logistic regression analysis, the variables statistically associated with implant failure (P < 0.05) were smoking status (P = 0.049) and existence of complications (P < 0.001). Conclusion: The cumulative survival rate of dental implants after 15 years of loading was 95.2% and that the variables statistically associated with implant failure were smoking status and existence of complications.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.255-266
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• 2021

The purpose of this study is to compare the effects of treatment on stage III stomach cancer data obtained from the SEER program of the National Cancer Institute and to identify the significant risk factors for the survival rates of stage III stomach cancer. Since the proportional hazards assumption was violated for treatment, we used the restricted mean survival time as an alternative to the proportional hazards model. The restricted mean survival time was estimated using pseudo-observations, and the effects of treatment were compared using a test statistic based on the estimated restricted mean survival times. We conducted the regression analysis using a generalized linear model to investigate the significant predictors for the restricted mean survival time of patients with stage III stomach cancer. We found that there was a significant difference between the restricted mean survival times of treatment groups. Age at diagnosis, race, substage, grade, tumor size, surgery, and treatment were significant predictors for the restricted mean survival time of patients with stage III stomach cancer. Surgery was the most significant predictor for increasing the restricted mean survival time of patients with stage III stomach cancer.

• Restorative Dentistry and Endodontics
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• v.46 no.2
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• pp.29.1-29.11
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• 2021

Objectives: This study was conducted to compare the post-fracture survival rate of endodontically treated molar endodontically treated teeth (molar ETT) restored with resin composites or crowns and to identify potential risk factors, using a retrospective cohort design. Materials and Methods: Dental records of molar ETT with crowns or composite restorations (recall period, 2015-2019) were collected based on inclusion and exclusion criteria. The incidence of unrestorable fractures was identified, and molar ETT were classified according to survival. Information on potential risk factors was collected. Survival rates and potential risk factors were analyzed using the Kaplan-Meier log-rank test and Cox regression model. Results: The overall survival rate of molar ETT was 87% (mean recall period, 31.73 ± 17.56 months). The survival rates of molar ETT restored with composites and crowns were 81.6% and 92.7%, reflecting a significant difference (p < 0.05). However, ETT restored with composites showed a 100% survival rate if only 1 surface was lost, which was comparable to the survival rate of ETT with crowns. The survival rates of ETT with composites and crowns were significantly different (97.6% vs. 83.7%) in the short-term (12-24 months), but not in the long-term (> 24 months) (87.8% vs. 79.5%). Conclusions: The survival rate from fracture was higher for molar ETT restored with crowns was higher than for ETT restored with composites, especially in the first 2 years after restoration. Molar ETT with limited tooth structure loss only on the occlusal surface could be successfully restored with composite restorations.

• Communications for Statistical Applications and Methods
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• v.25 no.4
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• pp.385-396
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• 2018

Competing risks are commonly encountered in biomedical research. Regression models for competing risks data can be developed based on data routinely collected in hospitals or general practices. However, these data sets usually contain the covariate missing values. To overcome this problem, multiple imputation is often used to fit regression models under a MAR assumption. Here, we introduce a multivariate imputation in a chained equations algorithm to deal with competing risks survival data. Using pseudo-observations, we make use of the available outcome information by accommodating the competing risk structure. Lastly, we illustrate the practical advantages of our approach using simulations and two data examples from a coronary artery disease data and hepatocellular carcinoma data.

• Communications for Statistical Applications and Methods
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• v.23 no.3
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• pp.189-201
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• 2016

In survival analysis, the Nelson-Aalen estimator and Peterson estimator are often used to estimate a cumulative hazard function in randomly right censored data. In this paper, we suggested the smoothing version of the cumulative hazard function estimators using a Bezier curve. We compare them with the existing estimators including a kernel smooth version of the Nelson-Aalen estimator and the Peterson estimator in the sense of mean integrated square error to show through numerical studies that the proposed estimators are better than existing ones. Further, we applied our method to the Cox regression where covariates are used as predictors and suggested a survival function estimation at a given covariate.