• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.357-371
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• 2007

For the time-to-failure data with competing risks, cumulative incidence functions (CIFs) are commonly estimated using nonparametric methods. If the cases of events due to the cause of primary interest are infrequent relative to other cause of failure, nonparametric methods may result in rather imprecise estimates for CIF. In such cases, Bryant et al. (2004) suggested to model the cause-specific hazard of primary interest parametrically, while accounting for the other modes of failure using nonparametric estimator. We represented the semiparametric cumulative incidence estimator and extended to the model of Weibull and log-normal distribution. We also conducted simulations to access the performance of the semiparametric cumulative incidence estimators and to investigate the impact of model misspecification in log-normal cause-specific hazard model.

• Journal of Chest Surgery
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• v.55 no.1
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• pp.69-76
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• 2022

Background: While the use of bioprosthetic valves for mitral valve replacement (MVR) is increasing, very few studies have compared bovine pericardial and porcine valves in the mitral position to help guide bioprosthetic selection. Methods: In the present study, patients who underwent MVR using bovine pericardial valves were compared with those who underwent MVR with porcine bioprostheses between January 1996 and July 2018. Those with prior MVR, infective endocarditis, congenital mitral valve disease, or ischemic mitral regurgitation were excluded. The primary outcomes were structural valve deterioration (SVD) and mitral valve reoperation from any cause, and death was regarded as a competing risk. Competing risk analysis and propensity score-matching were used for comparisons. Results: Among the 388 patients enrolled, pericardial and porcine bioprostheses were implanted in 217 (55.9%) and 171 (44.1%), respectively. Propensity score-matching yielded 122 pairs of patients that were well-balanced for all baseline covariates. No significant differences were observed between the groups in unadjusted (p=0.09) and adjusted overall survival (hazard ratio [HR], 1.13; 95% confidence interval [CI], 0.72-1.76; p=0.60). Competing risk analysis revealed no significant differences in the risks of mitral reoperation (HR, 1.07; 95% CI, 0.50-2.27; p=0.86) and development of SVD (HR, 1.57; 95% CI, 0.56-4.36; p=0.39) between the groups. Matched population analysis confirmed similar results regarding reoperation (HR, 0.99; 95% CI, 0.40-3.22; p=0.98) and SVD (HR, 1.39; 95% CI, 0.41-4.73; p=0.60). Conclusion: No significant differences in survival or valve durability were observed between bovine pericardial and porcine bioprosthetic MVR. These findings require further validation through studies with larger sample sizes.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1784-1787
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• 2006

In the risk capital market there are various types of investors competing each other. In the past, venture capital firms depended on government subsidies to stay in business. In order to be survived in today's competitive market, they need to have had the necessary knowledge and organizational resources to build their own competitive advantages. We examine the relationship between organizational characteristics, human resources, and investment strategies of venture capital firms in Korea.

• Journal of Chest Surgery
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• v.57 no.3
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• pp.242-251
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• 2024

Background: This study compared the outcomes of surgical aortic valve replacement (AVR) in patients aged 50 to 70 years based on the type of prosthetic valve used. Methods: We compared patients who underwent mechanical AVR to those who underwent bioprosthetic AVR at our institution between January 2000 and March 2019. Competing risk analysis and the inverse probability of treatment weighting (IPTW) method based on propensity score were employed for comparisons. Results: A total of 1,580 patients (984 patients with mechanical AVR; 596 patients with bioprosthetic AVR) were enrolled. There was no significant difference in early mortality between the mechanical AVR and bioprosthetic AVR groups (0.9% vs. 1.7%, p=0.177). After IPTW adjustment, the risk of all-cause mortality was significantly higher in the bioprosthetic AVR group than in the mechanical AVR group (hazard ratio [HR], 1.39; 95% confidence interval [CI], 1.07-1.80; p=0.014). Competing risk analysis revealed lower risks of stroke (sub-distributional hazard ratio [sHR], 0.44; 95% CI, 0.28-0.67; p<0.001) and anticoagulation-related bleeding (sHR, 0.35; 95% CI, 0.23-0.53; p<0.001) in the bioprosthetic AVR group. Conversely, the risk of aortic valve (AV) reintervention was higher in the bioprosthetic AVR group (sHR, 6.14; 95% CI, 3.17-11.93; p<0.001). Conclusion: Among patients aged 50 to 70 years who underwent surgical AVR, those receiving mechanical valves showed better survival than those with bioprosthetic valves. The mechanical AVR group exhibited a higher risk of stroke and anticoagulation-related bleeding, while the bioprosthetic AVR group showed a higher risk of AV reintervention.

• 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).

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.2
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• pp.131-137
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• 2016

In reliability analysis, it is quite common for the failure of any individual or item to be attributable to more than one cause. Moreover, observed data are often censored. Recently, progressive hybrid censoring schemes have become quite popular in life-testing problems and reliability analysis. However, a limitation of the progressive hybrid censoring scheme is that it cannot be applied when few failures occur before time T. Therefore, generalized progressive hybrid censoring schemes have been introduced. In this article, we derive the likelihood inference of the unknown parameters under the assumptions that the lifetime distributions of different causes are independent and exponentially distributed. We obtain the maximum likelihood estimators of the unknown parameters in exact forms. Asymptotic confidence intervals are also proposed. Bayes estimates and credible intervals of the unknown parameters are obtained under the assumption of gamma priors on the unknown parameters. Different methods are compared using Monte Carlo simulations. One real data set is analyzed for illustrative purposes.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.1
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• pp.121-128
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• 2013

The concern for dissolved phosphate in water/wastewater has been increasing because of the risk for eutrophication. A variety of conventional and advanced technologies were applied to meet the enforced new regulation of phosphate around the world. However, there still remained a lot of challenge because most introduced/developed method, for example, biological and physic-chemical treatment is not easy to satisfy the new regulation of phosphate in water. In order to meet the new regulation, the application of ion exchanger has been tried which showed that the removal efficiency for phosphate was strongly determined by in the presence of the competing ion, especially sulfate. As results, a new class of ion exchanger governed by ligand exchange was developed and investigated to increase the selectivity for phosphate. The current study using organic/inorganic anion exchanger developed with Lewis acid-base interaction confirms the selectivity for phosphate over sulfate. According to isotherm test and column test, the value of the maximum phosphate uptake (Q) showed 64 mg/g as $po{_4}^{3-}$ and the breakthrough for phosphate occurs after 1000 min and completely finishes at 2500 min, respectively.

• Acta Via Serica
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• v.7 no.1
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• pp.105-130
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• 2022

This paper argues that the war in Syria is partly the result of a global Islamist wave that contributed to fuelling conflict across large regions of Asia and Africa. Of course, the war that has consumed Syria since 2011 most certainly has multiple interrelated causes and driving forces, and any attempt to isolate one or even two or three runs the risk of advancing an overly simplistic interpretation of history. This essay, therefore, does not aim to offer an appraisal of the multiple variables that contributed to the war in Syria. Instead, it zeroes in on how political Islam came to impact Syria and its people. In doing so, it demonstrates how competing varieties of political Islam represented leading causes of conflict. Indeed, different Islamist movements contributed to the outbreak of the war in 2011, fuelled the conflict for years on end, and to this day represent major obstacles to the achievement of sustainable peace. Four broad Islamist currents are especially relevant to the case of Syria: the Muslim Brotherhood; the Shia revivalist movement at the nexus of the alliance between Iran, Hezbollah, and Syria; Salafi jihadism and its volatile and fractious underworld of competing armed groups, from Al-Qaeda to the Islamic State; and Recep Tayyip Erdoğan's market-friendly Islamism, which induced Turkey to intervene in Syria's civil war.

• Annals of dermatology
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• v.30 no.6
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• pp.668-675
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• 2018

Background: Drug survival, defined as the time until discontinuation, is a parameter reflecting real-world therapeutic effectiveness. Few studies have examined the influence of economic factors on the drug survival of biologic agents for psoriasis, particularly in Asian countries. Objective: To determine the drug survival for ustekinumab in real-life settings and investigate the factors affecting drug survival for psoriasis patients in Korea. Methods: We evaluated 98 psoriasis patients who were treated with ustekinumab at a single center. We analyzed the efficacy and drug survival of ustekinumab. Cox proportional hazard analysis and competing risk regression analysis were performed to reveal the factors affecting the drug survival of ustekinumab. Results: The overall mean drug survival was 1,596 days (95% confidence interval [CI], 904~2,288). Among the 39 cessations of ustekinumab treatment, 9 (23.1%) patients discontinued treatment after experiencing satisfactory results. Multivariate Cox proportional hazard analysis revealed that paying on patients' own expense was the major predictor for the discontinuation of ustekinumab (hazard ratio [HR], 9.696; 95% CI, 4.088~22.998). Competing risk regression analysis modeling of discontinuation because of factors other than satisfaction of an event also revealed that ustekinumab treatment at the patient's expense (HR, 4.138; 95% CI, 1.684~10.168) was a predictor of discontinuation rather than satisfaction. Conclusion: The results of our study revealed that the cost of biologics treatment affects the drug survival of ustekinumab and suggested that economic factors affect the drug survival of ustekinumab treatment in Korea.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.225-237
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• 2024

In the analysis of competing risks data, some of covariates may not be fully observed for some subjects. In such cases, excluding subjects with missing covariate values from the analysis may result in biased estimates and loss of efficiency. In this paper, we studied multiple imputation and the augmented inverse probability weighting method for regression parameter estimation in the cause-specific proportional hazards model with missing covariates. The performance of estimators obtained from multiple imputation and the augmented inverse probability weighting method is evaluated by simulation studies, which show that those methods perform well. Multiple imputation and the augmented inverse probability weighting method were applied to investigate significant risk factors for the risk of death from breast cancer and from other causes for breast cancer data with missing values for tumor size obtained from the Prostate, Lung, Colorectal, and Ovarian Cancer Screen Trial Study. Under the cause-specific proportional hazards model, the methods show that race, marital status, stage, grade, and tumor size are significant risk factors for breast cancer mortality, and stage has the greatest effect on increasing the risk of breast cancer death. Age at diagnosis and tumor size have significant effects on increasing the risk of other-cause death.