• 한국안전학회지
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• 제32권5호
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• pp.115-121
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• 2017

This paper is to introduce the main modeling assumptions and data structures associated with right-censored data to describe the successful methodological ideas for analyzing such a field-failure-data when components operating in different environments. The Kaplan - Meier method is the most popular method used for survival analysis. Together with the log-rank test, it may provide us with an opportunity to estimate survival probabilities and to compare survival between groups. An important advantage of the Kaplan - Meier curve is that the method can take into account some types of censored data, particularly right-censoring. The above non-parametric method was used to verify the equality of parts life used in different environments. After that, we performed the life distribution analysis using the parametric method. We simulated data from three distributions: exponential, normal, and Weibull. This allowed us to compare the results of the estimates to the known true values and to quantify the reliability indices. Here we used the Akaike information criterion to find a suitable life time distribution. If the Akaike information criterion is the smallest, the best model of failure data is presented. In this paper, no-nparametrics and parametrics methods are analyzed using R program which is a popular statistical program.

• Asian Pacific Journal of Cancer Prevention
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• 제15권21호
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• pp.9453-9458
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• 2014

Background: Breast cancer is the second leading cause of cancer death for women in the United States. Differences in survival of breast cancer have been noted among racial and ethnic groups, but the reasons for these disparities remain unclear. This study presents the characteristics and the survival curve of two racial and ethnic groups and evaluates the effects of race on survival times by measuring the lifetime data-based half-normal model. Materials and Methods: The distributions among racial and ethnic groups are compared using female breast cancer patients from nine states in the country all taken from the National Cancer Institute's Surveillance, Epidemiology, and End Results cancer registry. The main end points observed are: age at diagnosis, survival time in months, and marital status. The right skewed half-normal statistical probability model is used to show the differences in the survival times between black Hispanic (BH) and black non-Hispanic (BNH) female breast cancer patients. The Kaplan-Meier and Cox proportional hazard ratio are used to estimate and compare the relative risk of death in two minority groups, BH and BNH. Results: A probability random sample method was used to select representative samples from BNH and BH female breast cancer patients, who were diagnosed during the years of 1973-2009 in the United States. The sample contained 1,000 BNH and 298 BH female breast cancer patients. The median age at diagnosis was 57.75 years among BNH and 54.11 years among BH. The results of the half-normal model showed that the survival times formed positive skewed models with higher variability in BNH compared with BH. The Kaplan-Meir estimate was used to plot the survival curves for cancer patients; this test was positively skewed. The Kaplan-Meier and Cox proportional hazard ratio for survival analysis showed that BNH had a significantly longer survival time as compared to BH which is consistent with the results of the half-normal model. Conclusions: The findings with the proposed model strategy will assist in the healthcare field to measure future outcomes for BH and BNH, given their past history and conditions. These findings may provide an enhanced and improved outlook for the diagnosis and treatment of breast cancer patients in the United States.

• 한국간담췌외과학회지
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• 제27권3호
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• pp.251-257
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• 2023

Backgrounds/Aims: This is a retrospective analysis of whether the 8th edition American Joint Committee on Cancer (AJCC) was a significant improvement over the 7th AJCC distal extrahepatic cholangiocarcinoma classification. Methods: In total, 111 patients who underwent curative resection of mid-distal bile duct cancer from 2002 to 2019 were included. Cases were re-classified into 7th and 8th AJCC as well as clinicopathological univariate and multivariate, and Kaplan-Meier survival curve and log rank were calculated using R software. Results: In patient characteristics, pancreaticoduodenectomy/pylorus preserving pancreaticoduodenectomy had better survival than segmental resection. Only lymphovascular invasion was found to be significant (hazard ratio 2.01, p = 0.039) among all clinicopathological variables. The 8th edition AJCC Kaplan Meier survival curve showed an inability to properly segregate stage I and IIA, while there was a large difference in survival probability between IIA and IIB. Conclusions: The 8th distal AJCC classification did resolve the anatomical issue with the T stage, as T1 and T3 showed improvement over the 7th AJCC, and the N stage division of the N1 and N2 category was found to be justified, with poorer survival in N2 than N1. Meanwhile, in TMN staging, the 8th AJCC was able differentiate between early stage (I and IIA) and late stage (IIB and III) to better explain the patient prognosis.

• Asian Pacific Journal of Cancer Prevention
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• 제15권4호
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• pp.1563-1566
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• 2014

Background: Esophageal squamous cell carcinoma (ESCC) accounts for most esophageal cancer in Asia, and is the sixth common cause of cancer-related deaths worldwide. Previous studies indicated HOXB7 is overexpressed in ESCC tissues, but data on prognostic value are limited. Methods: A total of 76 advanced ESCC cases were investigated. Immunohistochemistry (IHC) was used to detect the expression levels of HOXB7 and Kaplan-Meier curves and Cox regression models to determine prognostic significance. Stratified analysis was also performed according to lymph node (LN) status. Results: Kaplan-Meier curve analysis indicated that HOXB7 positive patients had significantly shorter overall survival (OS) than HOXB7 negative patients. Multivariate analysis using the Cox proportional hazards model indicated only TNM stage and HOXB7 expression to be independent predictors of overall survival of advanced ESCC patients. HOXB7 indicated poor OS in both lymph node negative (LN-) and lymph node positive (LN+) patients. Conclusion: HOXB7 predicts poor prognosis of advanced ESCC patients and can be applied as an independent prognostic predictor.

• Asian Pacific Journal of Cancer Prevention
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• 제14권4호
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• pp.2567-2570
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• 2013

Background: This study analyzed Surveillance, Epidemiology and End Results (SEER) data to assess if socio-economic factors (SEFs) impact on endometrial cancer survival. Materials and Methods: Endometrial cancer patients treated from 2004-2007 were included in this study. SEER cause specific survival (CSS) data were used as end points. The areas under the receiver operating characteristic (ROC) curve were computed for predictors. Time to event data were analyzed with Kaplan-Meier method. Univariate and multivariate analyses were used to identify independent risk factors. Results: This study included 64,710 patients. The mean follow up time (S.D.) was 28.2 (20.8) months. SEER staging (ROC area of 0.81) was the best pretreatment predictor of CSS. Histology, grade, race/ethnicity and county level family income were also significant pretreatment predictors. African American race and low income neighborhoods decreased the CSS by 20% and 3% respectively at 5 years. Conclusions: This study has found significant endometrial survival disparities due to SEFs. Future studies should focus on eliminating socio-economic barriers to good outcomes.

• Asian Pacific Journal of Cancer Prevention
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• 제14권1호
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• pp.159-163
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• 2013

Background: This study used Surveillance, Epidemiology and End Results (SEER) pancreatic cancer data to identify predictive models and potential socio-economic disparities in pancreatic cancer outcome. Materials and Methods: For risk modeling, Kaplan Meier method was used for cause specific survival analysis. The Kolmogorov-Smirnov's test was used to compare survival curves. The Cox proportional hazard method was applied for multivariate analysis. The area under the ROC curve was computed for predictors of absolute risk of death, optimized to improve efficiency. Results: This study included 58,747 patients. The mean follow up time (S.D.) was 7.6 (10.6) months. SEER stage and grade were strongly predictive univariates. Sex, race, and three socio-economic factors (county level family income, rural-urban residence status, and county level education attainment) were independent multivariate predictors. Racial and socio-economic factors were associated with about 2% difference in absolute cause specific survival. Conclusions: This study s found significant effects of socio-economic factors on pancreas cancer outcome. These data may generate hypotheses for trials to eliminate these outcome disparities.

• 대한정형외과학회지
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• 제54권5호
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• pp.427-434
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• 2019

목적: 본 연구의 목적은 단일 술자가 시행한 슬관절 부분 치환술의 장기 임상적, 방사선적 결과 및 생존율을 분석하는 것이다. 또한 치환물의 생존에 영향을 미치는 인자를 분석하고 그에 따른 생존 곡선을 비교하는 것이다. 대상 및 방법: 1982년 12월부터 1996년 1월까지 시행된 슬관절 부분 치환술 99예를 대상으로 하였다. Modular II 10예, Microloc 44예, Allegretto 45예였다. 평균 추시기간은 16.5년이었다. 임상적 평가로 술 전, 술 후 1년, 최종 추시 hospital for special surgery(HSS) 점수와 관절운동범위를 조사하였다. 방사선적 평가로 술 전, 술 후 2주, 최종 추시 대퇴 경골각을 조사하였다. Kaplan-Meier 생존 분석을 이용하여 생존율을 분석하였다. Cox 비례위험모형을 이용하여 나이, 성별, 체질량 지수, 술 전 진단, 치환물의 종류 중 생존에 영향을 미치는 요인을 조사하였다. 생존에 영향을 미치는 인자에 따라 군을 나누어 생존 곡선을 비교하였다. 결과: 전체 HSS 점수는 평균 술 전 57.7점, 술 후 1년 92.7점, 최종 추시 79.1점이었다(p<0.001). 관절운동범위는 평균 술 전 134.3도, 술 후 1년 138.4도, 최종 추시 129.3도였다(p<0.001). 전체 대퇴 경골각은 평균 술 전 내반 0.8도, 술 후 2주 외반 4.1도, 최종 추시 외반 3.0도였다(p=0.003). 전체 생존율은 5년 91.8%, 10년 82.9%, 15년 71.0%, 20년 67.0%였다. 부분 치환술의 생존에 영향을 미치는 요인은 환자의 나이와 치환물의 종류였다. 나이가 높을수록 실패 위험이 낮았으며(hazard ratio=0.933), Microloc 사용 시 Modular II와 Allegretto에 비해 위험률이 높았다(hazard ratio=0.202, 0.430, respectively) 60세 미만군의 생존 곡선이 60세 이상 군에 비해 의미 있게 낮았다(p=0.003). Microloc 사용군의 생존 곡선이 Modular II와 Allegretto 사용군에 비해 낮았다(p=0.025). 결론: 고정형 치환물을 사용한 슬관절 부분 치환술의 장기 임상적, 방사선적 결과 및 생존율은 만족스러웠다. 부분 치환물의 장기 생존을 위해 적절한 환자와 치환물의 선택이 중요할 것이다.

• Asian Pacific Journal of Cancer Prevention
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• 제16권6호
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• pp.2245-2250
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• 2015

Background: The interaction between tumor cells and inflammatory cells has not been systematically investigated in esophageal squamous cell carcinoma (ESCC). The aim of the present study was to evaluate whether preoperative the lymphocyte-monocyte ratio (LMR), the neutrophil-lymphocyte ratio (NLR), and the platelet-lymphocyte ratio (PLR) could predict the prognosis of ESCC patients undergoing esophagectomy. Materials and Methods: Records from 218 patients with histologically diagnosed ESCC who underwent attempted curative surgery from January 2007 to December 2008 were retrospectively reviewed. Besides clinicopathological prognostic factors, we evaluated the prognostic value of the LMR, the NLR, and the PLR using Kaplan-Meier curves and Cox regression models. Results: The median follow-up was 38.6 months (range 3-71 months). The cut-off values of 2.57 for the LMR, 2.60 for the NLR and 244 for the PLR were chosen as optimal to discriminate between survival and death by applying receiver operating curve (ROC) analysis. Kaplan-Meier survival analysis of patients with low preoperative LMR demonstrated a significant worse prognosis for DFS (p=0.004) and OS (p=0.002) than those with high preoperative LMR. The high NLR cohort had lower DFS (p=0.004) and OS (p=0.011). Marginally reduced DFS (p=0.068) and lower OS (p=0.039) were found in the high PLR cohort. On multivariate analysis, only preoperative LMR was an independent prognostic factor for both DFS (p=0.009, HR=1.639, 95% CI 1.129-2.381) and OS (p=0.004, HR=1.759, 95% CI 1.201-2.576) in ESCC patients. Conclusions: Preoperative LMR better predicts cancer survival compared with the cellular components of systemic inflammation in patients with ESCC undergoing esophagectomy.

• Korean Journal of Radiology
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• 제22권3호
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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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• 제17권4호
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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.