• Title/Summary/Keyword: Kaplan Meier analysis

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HOXB7 Predicts Poor Clinical Outcome in Patients with Advanced Esophageal Squamous Cell Cancer

  • Long, Qing-Yun;Zhou, Jun;Zhang, Xiao-Long;Cao, Jiang-Hui
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.4
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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.

Competing Risks Regression Analysis (경쟁적 위험하에서의 회귀분석)

  • Baik, Jaiwook
    • Journal of Applied Reliability
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    • v.18 no.2
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    • pp.130-142
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    • 2018
  • Purpose: The purpose of this study is to introduce regression method in the presence of competing risks and to show how you can use the method with hypothetical data. Methods: Survival analysis has been widely used in biostatistics division. But the same method has not been utilized in reliability division. Especially competing risks, where more than a couple of causes of failure occur and the occurrence of one event precludes the occurrence of the other events, are scattered in reliability field. But they are not utilized in the area of reliability or they are analysed in the wrong way. Specifically Kaplan-Meier method is used to calculate the probability of failure in the presence of competing risks, thereby overestimating the real probability of failure. Hence, cumulative incidence function is introduced. In addition, sample competing risks data are analysed using cumulative incidence function along with some graphs. Lastly we compare cumulative incidence functions with regression type analysis briefly. Results: We used cumulative incidence function to calculate the survival probability or failure probability in the presence of competing risks. We also drew some useful graphs depicting the failure trend over the lifetime. Conclusion: This research shows that Kaplan-Meier method is not appropriate for the evaluation of survival or failure over the course of lifetime in the presence of competing risks. Cumulative incidence function is shown to be useful in stead. Some graphs using the cumulative incidence functions are also shown to be informative.

Black Hispanic and Black Non-Hispanic Breast Cancer Survival Data Analysis with Half-normal Model Application

  • Khan, Hafiz Mohammad Rafiqullah;Saxena, Anshul;Vera, Veronica;Abdool-Ghany, Faheema;Gabbidon, Kemesha;Perea, Nancy;Stewart, Tiffanie Shauna-Jeanne;Ramamoorthy, Venkataraghavan
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.21
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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.

One-year Survival Rate of Patients with Primary Malignant Central Nervous System Tumors after Surgery in Kazakhstan

  • Akshulakov, Serik;Igissinov, Nurbek;Aldiyarova, Nurgul;Akhmetzhanova, Zauresh;Ryskeldiyev, Nurzhan;Auezova, Raushan;Zhukov, Yevgeniy
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.16
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    • pp.6973-6976
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    • 2014
  • This study was conducted to evaluate the one-year survival rate of patients with primary malignant central nervous system (CNS) tumors after surgical treatment in Kazakhstan. Retrospective data of patients undergoing operations in the Department of Central Nervous System Pathology in the JSC National Centre for Neurosurgery in the period from 2009 to 2011 were used as the research material. Kaplan-Meier survival analysis was performed with the following information: gender, date of birth, place of residence, diagnosis according to ICD-10, the date of the operation, the morphological type of tumor, clinical stage, state at the end of the first year of observation, and the date of death. The study was approved by the ethical committee of the JSC National Centre for Neurosurgery. The overall one-year overall survival rate (n=152) was 56.5% (95% confidence interval (CI): 50.2-62.7), and 79.5% (95% CI 72.2-86.8) and 33.1% (95% CI: 21.0-42.3) for Grades I-II (n=76) and Grades III-IV (n=76), respectively. Significant prognostic factors which affected the survival rate were age and higher tumor grade (Grades III-IV), corresponding with results described elsewhere in the world.

Tests based on EDF statistics for randomly censored normal distributions when parameters are unknown

  • Kim, Namhyun
    • Communications for Statistical Applications and Methods
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    • v.26 no.5
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    • pp.431-443
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    • 2019
  • Goodness-of-fit techniques are an important topic in statistical analysis. Censored data occur frequently in survival experiments; therefore, many studies are conducted when data are censored. In this paper we mainly consider test statistics based on the empirical distribution function (EDF) to test normal distributions with unknown location and scale parameters when data are randomly censored. The most famous EDF test statistic is the Kolmogorov-Smirnov; in addition, the quadratic statistics such as the $Cram{\acute{e}}r-von$ Mises and the Anderson-Darling statistic are well known. The $Cram{\acute{e}}r-von$ Mises statistic is generalized to randomly censored cases by Koziol and Green (Biometrika, 63, 465-474, 1976). In this paper, we generalize the Anderson-Darling statistic to randomly censored data using the Kaplan-Meier estimator as it was done by Koziol and Green. A simulation study is conducted under a particular censorship model proposed by Koziol and Green. Through a simulation study, the generalized Anderson-Darling statistic shows the best power against almost all alternatives considered among the three EDF statistics we take into account.

The Wear Rate and Survivorship in Total Hip Arthroplasty Using a Third-generation Ceramic Head on a Conventional Polyethylene Liner: A Minimum of 15-year Follow-up

  • Bum-Jin Shim;Sung-Jin Park;Chan Ho Park
    • Hip & pelvis
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    • v.34 no.2
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    • pp.115-121
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    • 2022
  • Purpose: The purpose of this study was to evaluate the wear and survival rates of third-generation ceramic heads on a conventional ultra-high molecular weight polyethylene liner. Materials and Methods: A total of 160 hips (147 patients with a mean age of 55.9 years) who underwent total hip arthroplasty using the third-generation ceramic head on a conventional polyethylene liner from March 1998 to August 2003 were reviewed retrospectively. Evaluation of the wear rate for 56 hips (49 patients) followed-up for at least 15 years was performed using the PolyWare program version 8 (Draftware Developers, USA). The Kaplan-Meier survivorship was also evaluated. Results: Linear wear and volumetric wear rates were 0.11±0.47 mm/year and 32.75±24.50 mm3/year, respectively. Nine revisions were performed during the follow-up period because of cup or stem loosening. The Kaplan-Meier survival rate, using cup revision or total revision total hip arthroplasty (THA) as the endpoint of analysis, was 93.7% at 15 years and 73.6% at 20 years. Conclusion: Because all revisions were performed between 15 and 20 years in our study, surgeons should pay greater attention to patients who underwent THA with ceramic-on-polyethylene bearing from 15 years postoperatively. Contemporary alumina ceramic on highly cross-linked polyethylene could certainly be a good alternative bearing couple providing better longevity.

An Empirical Study on Factors Affecting the Survival of Social Enterprises Using Non-Financial Information (비재무정보를 이용한 사회적기업의 생존에 영향을 미치는 요인에 관한 실증연구)

  • Hyeok Kim;Dong Myung Lee;Gi Jung Nam
    • Journal of Industrial Convergence
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    • v.21 no.1
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    • pp.111-122
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    • 2023
  • The purpose of this study is to verify the factors affecting survival time by estimating survival rate and survival time using non-financial information of social enterprises using credit guarantee in credit guarantee institutions, and provide information to stakeholders to improve survival rate and employ to contribute to maintaining and expanding the As a research method, survival analysis was performed using a non-parametric analysis method, Kaplan-Meier Analysis. As a sample, 621 companies (577 normal companies, 44 insolvent companies) established between 2009 and 2018 were selected as the target companies. As a result of examining the factors affecting survival time by classifying social enterprise representative information and corporate information, representative credit rating, representative home ownership, credit transaction period, and corporate credit rating were derived as significant variables affecting survival time. In the future, financial institutions will be able to induce corporate soundness by reflecting factors that affect survival when examining loans for social enterprises, contributing to job retention and reduction of social costs. Supporting organizations such as the government and private organizations will be able to use it in various ways, such as policy establishment and education and training for the growth and sustainability of social enterprises. With this study as an opportunity, I hope that research will continue with more interest in the factors influencing social enterprise performance as well as corporate insolvency.

Prognostic Value of an Immune Long Non-Coding RNA Signature in Liver Hepatocellular Carcinoma

  • Rui Kong;Nan Wang;Chun li Zhou;Jie Lu
    • Journal of Microbiology and Biotechnology
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    • v.34 no.4
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    • pp.958-968
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    • 2024
  • In recent years, there has been a growing recognition of the important role that long non-coding RNAs (lncRNAs) play in the immunological process of hepatocellular carcinoma (LIHC). An increasing number of studies have shown that certain lncRNAs hold great potential as viable options for diagnosis and treatment in clinical practice. The primary objective of our investigation was to devise an immune lncRNA profile to explore the significance of immune-associated lncRNAs in the accurate diagnosis and prognosis of LIHC. Gene expression profiles of LIHC samples obtained from TCGA database were screened for immune-related genes. The optimal immune-related lncRNA signature was built via correlational analysis, univariate and multivariate Cox analysis. Then, the Kaplan-Meier plot, ROC curve, clinical analysis, gene set enrichment analysis, and principal component analysis were performed to evaluate the capability of the immune lncRNA signature as a prognostic indicator. Six long non-coding RNAs were identified via correlation analysis and Cox regression analysis considering their interactions with immune genes. Subsequently, tumor samples were categorized into two distinct risk groups based on different clinical outcomes. Stratification analysis indicated that the prognostic ability of this signature acted as an independent factor. The Kaplan-Meier method was employed to conduct survival analysis, results showed a significant difference between the two risk groups. The predictive performance of this signature was validated by principal component analysis (PCA). Additionally, data obtained from gene set enrichment analysis (GSEA) revealed several potential biological processes in which these biomarkers may be involved. To summarize, this study demonstrated that this six-lncRNA signature could be identified as a potential factor that can independently predict the prognosis of LIHC patients.

Hepatocellular Carcinoma: Texture Analysis of Preoperative Computed Tomography Images Can Provide Markers of Tumor Grade and Disease-Free Survival

  • Jiseon Oh;Jeong Min Lee;Junghoan Park;Ijin Joo;Jeong Hee Yoon;Dong Ho Lee;Balaji Ganeshan;Joon Koo Han
    • Korean Journal of Radiology
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    • v.20 no.4
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    • pp.569-579
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    • 2019
  • Objective: To investigate the usefulness of computed tomography (CT) texture analysis (CTTA) in estimating histologic tumor grade and in predicting disease-free survival (DFS) after surgical resection in patients with hepatocellular carcinoma (HCC). Materials and Methods: Eighty-one patients with a single HCC who had undergone quadriphasic liver CT followed by surgical resection were enrolled. Texture analysis of tumors on preoperative CT images was performed using commercially available software. The mean, mean of positive pixels (MPP), entropy, kurtosis, skewness, and standard deviation (SD) of the pixel distribution histogram were derived with and without filtration. The texture features were then compared between groups classified according to histologic grade. Kaplan-Meier and Cox proportional hazards analyses were performed to determine the relationship between texture features and DFS. Results: SD and MPP quantified from fine to coarse textures on arterial-phase CT images showed significant positive associations with the histologic grade of HCC (p < 0.05). Kaplan-Meier analysis identified most CT texture features across the different filters from fine to coarse texture scales as significant univariate markers of DFS. Cox proportional hazards analysis identified skewness on arterial-phase images (fine texture scale, spatial scaling factor [SSF] 2.0, p < 0.001; medium texture scale, SSF 3.0, p < 0.001), tumor size (p = 0.001), microscopic vascular invasion (p = 0.034), rim arterial enhancement (p = 0.024), and peritumoral parenchymal enhancement (p = 0.010) as independent predictors of DFS. Conclusion: CTTA was demonstrated to provide texture features significantly correlated with higher tumor grade as well as predictive markers of DFS after surgical resection of HCCs in addition to other valuable imaging and clinico-pathologic parameters.

Correlation of Protumor Effects of Leucine-Rich Repeat Kinase 2 with Interleukin-10 Expression in Lung Squamous Cell Carcinoma (폐 편평세포암종 내 Leucine-Rich Repeat Kinase 2 암촉진 효과와 Interleukin-10 발현과의 연관성)

  • Sung Won LEE;Sangwook PARK
    • Korean Journal of Clinical Laboratory Science
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    • v.55 no.2
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    • pp.105-112
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    • 2023
  • Leucine-rich repeat kinase 2 (LRRK2) is known to play a crucial role in the pathophysiology of neurodegenerative disorders such as Parkinson's disease. LRRK2 is predominantly expressed in the lung as well as the brain. However, it is unclear whether LRRK2 expression correlates with the pathogenesis of lung squamous cell carcinoma (LUSC). This study analyzes the prognostic significance of LRRK2 in LUSC using the Kaplan-Meier plotter tool. High expression of LRRK2 is known to be associated with a bad prognosis in patients with LUSC. Patients with high LRRK2 expression, tumor mutational burden, high neoantigen load, and even gender correlation reportedly have the worse survival rates. In the gene expression profiling interactive analysis (GEPIA) database, the severity of pathogenesis in LUSC with high LRRK2 expression positively corresponds to a high expression of anti-inflammatory cytokines but not inflammatory cytokines. Similarly, the increased expression of interleukin (IL)10-related genes was shown to be significantly linked in LRRK2-high LUSC patients having a poor prognosis. Moreover, the tumor immune estimation resource (TIMER) database suggests that macrophages are one of the cellular sources of IL10 in LRRK2-high LUSC patients. Collectively, our results demonstrate that the postulated LRRK2-IL10 axis is a potential therapeutic target and prognostic biomarker for LUSC.