• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4653-4659
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• 2012

This study was performed to investigate the factors related failure in continuity of smoking cessation among persons who were initially successful in quitting smoking for at least 6 months in smoking cessation clinic of public health center. Data were collected with the telephone questionnaire survey and the registered cards from 347 of 6 months quitters from 2006 to 2008 year. Data were analyzed by life table method and Cox-proportional hazard model. In Cox-proportional hazard model, Eup Myeon of residence(HR 2.50, 95% CI 1.69-3.68), without chronic diseases(HR 1.92, 95% CI 1.21-3.04), without another smoker in household(HR 1.93, 95% CI 1.21-3.09) and usage of supplement agent(HR 2.17, 95% CI 1.01-4.68) were independently associated with the failure in continuing to stay smoke-free. The cumulative rate of failure in the continuity of smoking cessation was 28.6% at 6 month and 36.1% at 24 month. For operating a clinic program for smoking cessation, Public health center should makes strategies that a person is continuing smoking cessation for over 6 months after the first 6 momth's smoking cessation.

• Industry Promotion Research
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• v.5 no.1
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• pp.1-11
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• 2020

The purpose of this study is to analyze the industrial accidents data with survival model. EDA approach is used to explore the relationship between two variables and among three variables for the past 10 years of industrial accidents data. Survival models are also tried. Survival curve drops more rapidly for the business with fewer employees as time goes by. Industrial accidents occur more often as the total number of industrial accidents gets larger and as the number of employees gets smaller. Agriculture, fishing and forestry have a higher level of industrial accidents than construction while service industry and 'transportation·storage and telecommunication' have a fewer number of industrial accidents than construction. Korea Safety and Health Agency's and Ministry of Employment and Labor's involvement were not effective but Civilian's was. Recurrent event data analysis reveals all most the same result as for non-recurrent data analysis.

• Journal of Korean Society of Forest Science
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• v.113 no.2
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• pp.187-197
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• 2024

In this study, we aimed to identify the factors influencing post-fire mortality in Korean red pine (Pinus densiflora) using Cox's proportional hazards model and analyze the impact of these factors. We monitored the mortality rate of fire-damaged pine trees for seven years after a forest fire. Our survival analysis revealed that the risk of mortality increased with higher values of the delta normalized difference vegetation index (dNDVI), delat normalized burn ratio (dNBR), bark scorch index (BSI), bark scorch height (BSH) and slope. Conversely, the risk of mortality decreased with higher elevation, greater diameter at breast height (DBH), and higher value of delta moisture stress index (dMSI) (p < 0.01). Verification of the proportional hazards assumption for each variable showed that all factors, except slope aspect, were suitable for the model and significantly influenced fire occurrence. Among the variables, BSI caused the greatest change in the survival curves (p < 0.0001). The environmental change factors determined through remote sensing also significantly influenced the survival rates (p < 0.0001). These results will be useful in establishing restoration plans considering the potential mortality risk of Korean red pine after a forest fire.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.529-538
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• 2018

Tuberculosis causes high morbidity and mortality. However, Korea still has the highest tuberculosis (TB) incidence and mortality among OECD countries despite decreasing incidence and mortality due to the development of modern medicine. Korea has now implemented various policy projects to prevent and control tuberculosis. This study analyzes the effects of public-private mix (PPM) tuberculosis control program on treatment outcomes and identifies the factors that affecting the success of TB treatment. We analyzed 130,000 new tuberculosis patient cohort from 2012 to 2015 using data of tuberculosis patient reports managed by the Disease Control Headquarters. A cumulative incidence function (CIF) compared the cumulative treatment success rates for each factor. We compared the results of the analysis using two popular types of competition risk models (cause-specific Cox's proportional hazards model and subdistribution hazard model) that account for the main event of interest (treatment success) and competing events (death).

• 대한예방의학회:학술대회논문집
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• 2003.04a
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• pp.30-37
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• 2003

o Cohort study became the major approach to study of chronic diseases such as CVD and cancer o Cohort can be population-based or volunteer-based o Types of be population-be categorized by source population and selection mechanism o More and more cohort studies involve biological specimens, such as blood, urine, toenail, cheek cells, etc. o Multi-center and multi-national collaboration is an effective way to increase sample size. o Current statistical method typically use time-to-event analysis by Cox proportional hazard model.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7835-7838
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• 2014

Background: Neuroendocrine tumors have widespread and different clinical presentations and prognoses. This study was conducted to assess their survival time and prognostic factors in Iran. Materials and Methods: In a retrospective cohort study, 189 patients diagnosed of having neuroendocrine carcinoma were chosen. The tumor and clinical characteristics of the patients were modeled with a Cox proportional hazard approach. Survival was assessed using Kaplan-Meyer curves. Results: Crude median survival time was 30 months. Women survived longer than men (the median survival time for women was 40 and for men was 24 months). Age (<60 vs >60 years old with hazard ratio (HR) of 2.43, 95% CI 1.3-4.5), primary pathology report (carcinoid vs. others with HR 5.85 cm, 95% CI 2.4-14.3), tumor size cm (for 5-10, HR of 3.1, 95% CI 1.6 and for >10 HR of 8.2, 95% with 95% CI 3.1-21.9), and chemotherapy with single drug (taking vs. not taking with a HR 2.2, 95% CI 1.1-4.8) had significant effects on overall survival of patients. Conclusions: Survival time in patients with neuroendocrine carcinomas is related to demographics, clinical characteristics, tumor histology, and subtype specific treatment.

• Journal of agricultural medicine and community health
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• v.32 no.1
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• pp.13-26
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• 2007

Objectives: This study was conducted to investigate the association between health risk factors and mortality in Juam cohort. Methods: The subjects were 1,447 males and 1,889 females who had been followed up for 68.5 months to 1 January 2001. Whether they were alive or not was confirmed by the mortality data of the National Statistical Office. A total of 289 persons among them died during the follow-up period. The Cox's proportional hazard regression model was used for survival analysis. Results: Age, type of medical insurance, self cognitive health level, habit of alcohol drinking, smoking, exercise and BMI level were included in Cox's proportional hazard model by gender. The hazard ratio of age was 1.07(95% CI: 1.05-1.10) in men, 1.09(95% CI: 1.06-1.12) in women. The hazard ratio of medical aid(lower socioeconomic state) was 1.43(95% CI 1.02-2.19) in women. The hazard ratios of current alcohol drinking and current smoking were respectively 1.69(95% CI: 1.01-2.98), 1.52(95% CI: 1.02-2.28) in women. The hazard ratio of underweight was 1.56(95% CI 1.08-2.47) in men. The hazard ratios of underweight, normoweight, overweight, and obesity were respectively 1.63(95% CI: 1.02-2.67), 1.0(referent), 0.62(95% CI: 0.32-1.63), 1.27(95% CI: 0.65-3.06), which supported the U-shaped relationship between body mass index and mortality among the men over 65. Conclusions: The health risk factors increasing mortality were age, underweight in male, age, lower socioeconomic state, current alcohol drinking, current smoking in female. To evaluate long-term association between health risk factors and mortality, further studies need to be carried out.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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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.

• Journal of Korean Biological Nursing Science
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• v.22 no.4
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• pp.249-259
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• 2020

Purpose: Carbapenemase-producing Enterobacteriaceae (CPE) are associated with considerable mortality. This study was aimed to identify survival factors among medical care unit patients with CPE. Methods: We conducted a retrospective cohort; data were collected from September 2017 to June 2019 through electronic medical records. The data collected were general characteristics, disease-related characteristics, severity-related characteristics, and treatment-related characteristics. Data were analyzed based on frequency, mean, standard deviation, Chi-square test, Fisher's exact test, t-test, Pearson's correlation coefficient, and Cox proportional hazard model using SPSS/WIN 21.0 program. Results: Seventy-seven patients were included (59 survivors and 18 deceased) in the study. Univariate analysis identified factors for survival associated with acquired CPE as age (t= -1.56, p= .037), simplified acute physiology 3 (SAPS3) score of admission date (t= -2.85, p= .006), Glasgow coma scale (GCS) of CPE acquisition date (t= 2.38, p= .020), artery catheter at CPE acquisition date (χ²= 4.58, p= .032), vasoconstrictor agents use at CPE acquisition date (χ²= 6.81, p= .009), platelet at CPE acquisition date (t= 2.27, p= .025), lymphocyte at CPE acquisition date (t= 2.01, p= .048), calcium at CPE acquisition date (t= 2.68, p= .009), albumin at CPE acquisition date (t= 2.29, p= .025), and creatinine at CPE acquisition date (t= 2.24, p= .028). Multivariate Cox proportional hazard model showed that GCS at CPE acquisition date (HR= 1.14, 95% CI= 1.05-1.22), lymphocyte at CPE acquisition date (HR= 1.05, 95% CI= 1.00-1.10), and creatinine at CPE acquisition date (HR= 1.25, 95% CI= 1.04-1.49) were independent survival factors among medical intensive care unit patients with CPE. Conclusion: Based on the study results, it is necessary to develop nursing interventions that can aid in the management of patients with CPE and identify their effects.

• The Journal of Advanced Prosthodontics
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• v.9 no.3
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• pp.195-199
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• 2017

PURPOSE. The objective of this study was to determine the cumulative survival rate (CSR) and associated risk factors of Implantium implants by retrospective clinical study. MATERIALS AND METHODS. Patients who received Implantium implants (Dentium Co., Seoul, Korea) at Korea University Guro Hospital from 2004 to 2011 were included. The period between the first surgery and the last hospital visit until December 2015 was set as the observation period for this study. Clinical and radiographic data were collected from patient records, including all complications observed during the follow-up period. Kaplan-Meier analysis was performed to examine CSR. Multiple Cox proportional hazard model was employed to assess the associations between potential risk factors and CSR. RESULTS. A total of 370 implants were placed in 121 patients (mean age, 56.1 years; range, 19 to 75 years). Of the 370 implants, 13 failed, including 7 implants that were lost before loading. The 10-year cumulative survival rate of implants was 94.8%. The multiple Cox proportional hazard model revealed that significant risk factor of implant failure were smoking and maxillary implant (P<.05). CONCLUSION. The 10-year CSR of Implantium implants was 94.8%. Risk factors of implant failure were smoking and maxillary implant.