• Clinical and Experimental Pediatrics
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• v.45 no.12
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• pp.1559-1570
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• 2002

Purpose : There has been no exact answer to the question of when to discontinue antiepileptic drugs(AEDs) in children with well-controlled epilepsy for a long period. This study is about the risk factors of relapse after withdrawal of AEDs in seizure(Sz)-free patients to show a guideline for discontinuation of AEDs. Methods : One hundred and sixty-nine children were diagnosed as epileptic at the Pediatric Dept. of Kyung-Hee Univ. between 1993 to 1998, in whom AEDs had been withdrawn after at least two years of Sz-free period. Univariate analysis using Kaplan-Meier survival analysis and multivariate analysis using Cox-proportional hazard model were performed for sixteen risk factors. Results : Forty-nine of the 169 patients(28.9%) had recurrence of Szs. The mean follow-up after withdrawal of AEDs was 4.1 years, mean treatment period was 4.1 years, and the mean Sz-free period was 3.3 years. Factors associated with an increased risk of relapse were young age at onset, symptomatic Sz, Sz type in West and Lennox-Gastaut syndrome, neurologic deficit, longer Sz-controlling period, shorter total treatment period, number of AEDs used(more than one drug), age at withdrawal of AEDs, and Sz-free period less than two years in univariate analysis using Kaplan-Meier mothod. From multivariate analysis, the factors indicating a significantly higher relapse risk were pre-treatment period after first Sz attack, Sz-controlling period, Sz-free period, number of AEDs used, neurologic abnormalities. Conclusion : For epileptic children who were Sz-free for more than two years, and were more than six-years-old, the discontinuation of AEDs should be considered positively, according to age of onset, Sz type, age at withdrawal of AEDs, total treatment period, Sz-controlling period, number of AEDs used, etiology, neurologic deficit, and the wishes of the patients and the their parents.

• The Journal of Korean Academy of Prosthodontics
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• v.55 no.3
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• pp.272-278
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• 2017

Purpose: The aim of the present prospective clinical study was to assess the cumulative survival rate (CSR) of Neobiotech implants restored with fixed partial prosthesis in relation to its potential risk factors. Materials and methods: Thirty six partially edentulous patients received Neobiotech implants and implant supported fixed partial prosthesis at Korea University Guro Hospital Dental Center from November 2009 until November 2011. The observation period was set from the implant placement and the last clinical visit until December 2015. Implant survival rate was determined using the Kaplan-Meier method. The relationship between implant survival rate and the potential risk factors were analysed using the multi Cox proportional analysis (P<.05). Results: A total of 69 implants were placed in 36 patients after a mean observation period of 45.9 months. Two out of 69 implants failed before loading, yielding a 5-year cumulative survival rate of 97.1%. The maxillary implants have a lesser CSR than the mandibular implants based on log rank test analysis (maxilla=91.3%; mandible=100% P<.05). However, the multi Cox proportional analysis showed that implant location has no significant correlation with implant failure (P>.05). Conclusion: Neobiotech implants showed predictable results with a 5 year cumulative survival rate of 97.1%.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.8
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• pp.3513-3518
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• 2014

The 14-3-3 protein has been shown to be involved in the cancer process. However, there is no understanding of the relationship between 14-3-$3{\gamma}$ (14-3-3 gamma) expression and prognosis in advanced non-small cell lung cancer. In this study, we therefore investigated the association between protein levels by immunohistochemistry and clinicopathological features of advanced NSCLC patients. Survival curves were estimated using the Kaplan-Meier method and tested by log-rank. Multivariate analysis was conducted with the Cox's regression model to determine independence of factors. p values less than 0.05 were considered significant. A total 153 patients were studied, with 54.3% being stage III and 45.8% stage IV. Fifty-one cases (33.3%) were squamous cell carcinomas, and 98 cases (64.1%) were adenocarcinomas. High 14-3-$3{\gamma}$ expression was seen in 59.5% and significantly correlated with lymph node metastasis (p=0.010) and distant metastasis (p=0.017). On Kaplan-Meier analysis, high 14-3-$3{\gamma}$ expression was associated with poorer survival with a marginal trend toward significance (p=0.055). On multivariate analysis, age, treatment, and 14-3-$3{\gamma}$ expression proved to be independent prognostic parameters. In vitro experiments indicated that 14-3-$3{\gamma}$ overexpression also played a potential role in cancer invasion. In conclusion, our data suggest that 14-3-$3{\gamma}$ overexpression is associated with invasion and a poor prognosis. Therefore, 14-3-$3{\gamma}$ may be a potential prognostic marker of advanced non-small cell lung cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.999-1003
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• 2014

Objective: To validate the relationship between MACC1 and 6-phosphofructo-2-kinase/fructose 2, 6 bisphosphatase (PFKFB2) expression as well as its clinicopathological features and prognostic significance in hepatocellular carcinoma. Methods: By using immunohistochemistry, we investigated the MACC1 and PFKFB2 protein expression in 60 pairs of hepatocellular carcinoma and corresponding non-tumor tissues. Using the Mann-Whitney U test, the Chi-square test, Kaplan-Meier survival analysis, Cox proportional hazard regression analysis and Spearman analysis, we studied the relationship between MACC1 and PFKFB2 protein expression and postoperative overall survival (OS) of the HCC patients. Results: MACC1 and PFKFB2 positive staining rates were significantly higher in hepatocellular carcinoma than in the corresponding nontumor tissues (P=0.012 and 0.04, respectively). The clinicopathological features evaluation revealed that positive expression of MACC1 was associated with a high Edmondson classification (P=0.007) and advanced TNM stage (P=0.027). Similar findings were evident for PFKFB2 expression (P=0.002 and P=0.027). MACC1 and PFKFB2 positive expression was associated with a lower OS rate (P=0.004 and 0.03, respectively). Kaplan-Meier survival and Cox proportional hazard regression analyses revealed MACC1 positive expression to be a prognostic factor for postoperative OS, but PFKFB was not. Conclusion: Highly expressed MACC1 and PFKFB2 protein were associated with TNM stage, Edmondson-Steier classification and overall survival. MACC1 may affect tumor metabolism partly through expression and phophorylation of PFKFB2.

• Journal of Chest Surgery
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• v.40 no.10
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• pp.680-684
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• 2007

Background: Complete surgical resection is the most effective treatment for stage IB non-small cell lung cancer (NSCLC). Recurrence accounts for the disappointing survival rates after resection. There has been renewed interest in adjuvant therapy after complete resection. Appropriate selection of effective adjuvant therapy will depend on the prognostic factors for recurrence. Material and Method: The study included 114 patients with completely resected stage IB NSCLC. The variables selected for the study were gender, age, the type of resection, cell type, the degree of differentiation, the tumor size and the presence of visceral pleura invasion. The Kaplan-Meier method was used to estimate the survival and disease-free survival rate. The results were compared using the log rank test. Multivariate analysis was performed by Cox's proportional hazard model. Two-sided p-valves < 0.05 were considered to be statistically significant. Result: The 3-year overall survival and the disease-free survival rates were 87.0% and 79.4%, respectively. The degree of differentiation showed a significant influence on disease-free survival according to the univariate analysis. According to the multivariate analysis, a poor grade of differentiation was a significant poor prognostic factor. Conclusion: These results demonstrate that poor differentiation may be a poor prognostic factor for patients with completely resected IB NSCLC. Therefore, the patients with a poor grade of differentiation may require adjuvant therapies.

• Journal of Pathology and Translational Medicine
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• v.52 no.6
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• pp.396-403
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• 2018

Background: In the current American Joint Committee on Cancer staging system of breast cancer, only tumor size determines T-category regardless of whether the tumor is single or multiple. This study evaluated if tumor multiplicity has prognostic value and can be used to subclassify breast cancer. Methods: We included 5,758 patients with invasive breast cancer who underwent surgery at Samsung Medical Center, Seoul, Korea, from 1995 to 2012. Results: Patients were divided into two groups according to multiplicity (single, n=4,744; multiple, n=1,014). Statistically significant differences in lymph node involvement and lymphatic invasion were found between the two groups (p<.001). Patients with multiple masses tended to have luminal A molecular subtype (p<.001). On Kaplan-Meier survival analysis, patients with multiple masses had significantly poorer disease-free survival (DFS) (p=.016). The prognostic significance of multiplicity was seen in patients with anatomic staging group I and prognostic staging group IA (p=.019 and p=.032, respectively). When targeting patients with T1-2 N0 M0, hormone receptor-positive, and human epidermal growth factor receptor 2 (HER2)-negative cancer, Kaplan-Meier survival analysis also revealed significantly reduced DFS with multiple cancer (p=.031). The multivariate analysis indicated that multiplicity was independently correlated with worse DFS (hazard ratio, 1.23; 95% confidence interval, 1.03 to 1.47; p=.025). The results of this study indicate that tumor multiplicity is frequently found in luminal A subtype, is associated with frequent lymph node metastasis, and is correlated with worse DFS. Conclusions: Tumor multiplicity has prognostic value and could be used to subclassify invasive breast cancer at early stages. Adjuvant chemotherapy would be necessary for multiple masses of T1-2 N0 M0, hormone-receptor-positive, and HER2-negative cancer.

• The Korean Journal of Medicine
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• v.93 no.6
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• pp.548-555
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• 2018

Background/Aims: Assessment of fluid status in hemodialysis patents is very important. Overhydration in hemodialysis is associated with generalized edema, cardiovascular complications, and hypertension. The aim of this study was to determine the factors correlated with mortality of hemodialysis patients, assessing body muscle mass and fluid status using bioelectrical impedance analysis (BIA). Methods: This study enrolled 93 patients who underwent hemodialysis between January 2010 and May 2015 at CHA Bundang Medical Center. Medical records of enrollees up to June 2017 were reviewed retrospectively. These included laboratory results (serum albumin, C-reactive protein [CRP], lipid profile, etc.) and BIA data (extracellular water, intracellular water, total body water, soft lean mass, fat free mass, skeletal muscle mass, etc.). Results: Eleven of 93 patients had expired by May 2017. Among the surviving subjects, mean age was younger, CRP levels were lower, albumin levels were higher, and extracellular water/total body water (ECW/TBW) ratios were lower than in the expired patient group. Kaplan-Meier survival analysis revealed that overhydration (ECW/TBW > 0.4) was associated with higher mortality. Conclusions: In hemodialysis patients, overhydration is an important factor in mortality, and BIA could be a reliable modality in its assessment. We suggest that, for hemodialysis patients, overhydration is more of a risk factor for mortality than is muscle wasting.

• Journal of the Korean Society of Radiology
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• v.82 no.4
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• pp.876-888
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• 2021

Purpose The aim of this study was to compare the diameter and volume of liver metastases on CT images in relation to overall survival and tumor response in patients with gastric cancer liver metastases (GCLM) treated with chemotherapy. Materials and Methods We recruited 43 patients with GCLM who underwent chemotherapy as a first-line treatment. We performed a three-dimensional quantification of the metastases for each patient. An independent survival analysis using the Response Evaluation Criteria in Solid Tumors (RECIST) was performed and compared to volumetric measurements. Overall survival was evaluated using Kaplan-Meier analysis and compared using Cox proportional hazard ratios following univariate analyses. Results When patients were classified as responders or non-responders based on volumetric criteria, the median overall survival was 23.6 months [95% confidence interval (CI), 8.63-38.57] and 7.6 months (95% CI, 3.78-11.42), respectively (p = 0.039). The volumetric analysis and RECIST of the non-progressing and progressing groups showed similar results based on the Kaplan-Meier method (p = 0.006) and the Cox proportional hazard model (p = 0.008). Conclusion Volumetric assessment of liver metastases could be an alternative predictor of overall survival for patients with GCLM treated with chemotherapy.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.425-434
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• 2021

Objective: To investigate the potential value of ¹⁸F-fluorodeoxyglucose (FDG) PET/CT in predicting the survival of patients with primary tracheal malignant tumors. Materials and Methods: An analysis of FDG PET/CT findings in 37 primary tracheal malignant tumor patients with a median follow-up period of 43.2 months (range, 10.8-143.2 months) was performed. Cox proportional hazards regression analyses were used to assess the associations between quantitative ¹⁸F-FDG PET/CT parameters, other clinic-pathological factors, and overall survival (OS). A risk prognosis model was established according to the independent prognostic factors identified on multivariate analysis. A survival curve determined by the Kaplan-Meier method was used to assess whether the prognosis prediction model could effectively stratify patients with different risks factors. Results: The median survival time of the 37 patients with tracheal tumors was 38.0 months, with a 95% confidence interval of 10.8 to 65.2 months. The 3-year, 5-year and 10-year survival rate were 54.1%, 43.2%, and 16.2%, respectively. The metabolic tumor volume (MTV), total lesion glycolysis (TLG), maximum standardized uptake value, age, pathological type, extension categories, and lymph node stage were included in multivariate analyses. Multivariate analysis showed MTV (p = 0.011), TLG (p = 0.020), pathological type (p = 0.037), and extension categories (p = 0.038) were independent prognostic factors for OS. Additionally, assessment of the survival curve using the Kaplan-Meier method showed that our prognosis prediction model can effectively stratify patients with different risks factors (p < 0.001). Conclusion: This study shows that ¹⁸F-FDG PET/CT can predict the survival of patients with primary tracheal malignant tumors. Patients with an MTV > 5.19, a TLG > 16.94 on PET/CT scans, squamous cell carcinoma, and non-E1 were more likely to have a reduced OS.

• Genomics & Informatics
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• v.17 no.4
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• pp.41.1-41.12
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• 2019

Survival analysis mainly deals with the time to event, including death, onset of disease, and bankruptcy. The common characteristic of survival analysis is that it contains "censored" data, in which the time to event cannot be completely observed, but instead represents the lower bound of the time to event. Only the occurrence of either time to event or censoring time is observed. Many traditional statistical methods have been effectively used for analyzing survival data with censored observations. However, with the development of high-throughput technologies for producing "omics" data, more advanced statistical methods, such as regularization, should be required to construct the predictive survival model with high-dimensional genomic data. Furthermore, machine learning approaches have been adapted for survival analysis, to fit nonlinear and complex interaction effects between predictors, and achieve more accurate prediction of individual survival probability. Presently, since most clinicians and medical researchers can easily assess statistical programs for analyzing survival data, a review article is helpful for understanding statistical methods used in survival analysis. We review traditional survival methods and regularization methods, with various penalty functions, for the analysis of high-dimensional genomics, and describe machine learning techniques that have been adapted to survival analysis.