• Title/Summary/Keyword: survival regression

Search Result 620, Processing Time 0.023 seconds

Kasai Operation for Extrahepatic Biliary Atresia - Survival and Prognostic Factors (간외담도폐쇄에 대한 Kasai 술식 후 생존 결과 및 예후인자)

  • Yoon, Chan-Seok;Han, Seok-Joo;Park, Young-Nyun;Chung, Ki-Sup;Oh, Jung-Tak;Choi, Seung-Hoon
    • Advances in pediatric surgery
    • /
    • v.12 no.2
    • /
    • pp.202-212
    • /
    • 2006
  • The prognostic factors for extrahepatic biliary atresia (EHBA) after Kasai portoenterostomy include the patient's age at portoenterostomy (age), size of bile duct in theporta hepatis (size), clearance of jaundice after operation (clearance) and the surgeon's experience. The aim of this study is to examine the most significant prognostic factor of EHBA after Kasai portoenterostomy. This retrospective study was done in 51 cases of EHBA that received Kasai portoenterostomy by one pediatric surgeon. For the statistical analysis, Kaplan-Meier method, Logrank test and Cox regression test were used. A p value of less than 0.05 was considered to be significant. Fifteen patients were regarded as dead in this study, including nine cases of liver transplantation. There was no significant difference of survival to age. The age is also not a significant risk factor for survival in this study (Cox Regression test; p = 0.63). There was no significant difference in survival in relation to the size of bile duct. However, bile duct size was a significant risk factor for survival (Cox Regression test; p = 0.002). There was a significant difference in relation to survival and clearance (Kaplan-Meier method; p = 0.02). The clearing was also a significant risk factor for survival (Cox Regression test; p = 0.001). The clearance of jaundice is the most significant prognostic factor of EHBA after Kasai portoenterostomy.

  • PDF

Preoperative chemoradiation for locally advanced rectal cancer: comparison of three radiation dose and fractionation schedules

  • Park, Shin-Hyung;Kim, Jae-Chul
    • Radiation Oncology Journal
    • /
    • v.34 no.2
    • /
    • pp.96-105
    • /
    • 2016
  • Purpose: The standard radiation dose for patients with locally rectal cancer treated with preoperative chemoradiotherapy is 45-50 Gy in 25-28 fractions. We aimed to assess whether a difference exists within this dose fractionation range. Materials and Methods: A retrospective analysis was performed to compare three dose fractionation schedules. Patients received 50 Gy in 25 fractions (group A), 50.4 Gy in 28 fractions (group B), or 45 Gy in 25 fractions (group C) to the whole pelvis, as well as concurrent 5-fluorouracil. Radical resection was scheduled for 8 weeks after concurrent chemoradiotherapy. Results: Between September 2010 and August 2013, 175 patients were treated with preoperative chemoradiotherapy at our institution. Among those patients, 154 were eligible for analysis (55, 50, and 49 patients in groups A, B, and C, respectively). After the median follow-up period of 29 months (range, 5 to 48 months), no differences were found between the 3 groups regarding pathologic complete remission rate, tumor regression grade, treatment-related toxicity, 2-year locoregional recurrence-free survival, distant metastasis-free survival, disease-free survival, or overall survival. The circumferential resection margin width was a prognostic factor for 2-year locoregional recurrence-free survival, whereas ypN category was associated with distant metastasis-free survival, disease-free survival, and overall survival. High tumor regression grading score was correlated with 2-year distant metastasis-free survival and disease-free survival in univariate analysis. Conclusion: Three different radiation dose fractionation schedules, within the dose range recommended by the National Comprehensive Cancer Network, had no impact on pathologic tumor regression and early clinical outcome for locally advanced rectal cancer.

Survival Analysis of Gastric Cancer Patients with Incomplete Data

  • Moghimbeigi, Abbas;Tapak, Lily;Roshanaei, Ghodaratolla;Mahjub, Hossein
    • Journal of Gastric Cancer
    • /
    • v.14 no.4
    • /
    • pp.259-265
    • /
    • 2014
  • Purpose: Survival analysis of gastric cancer patients requires knowledge about factors that affect survival time. This paper attempted to analyze the survival of patients with incomplete registered data by using imputation methods. Materials and Methods: Three missing data imputation methods, including regression, expectation maximization algorithm, and multiple imputation (MI) using Monte Carlo Markov Chain methods, were applied to the data of cancer patients referred to the cancer institute at Imam Khomeini Hospital in Tehran in 2003 to 2008. The data included demographic variables, survival times, and censored variable of 471 patients with gastric cancer. After using imputation methods to account for missing covariate data, the data were analyzed using a Cox regression model and the results were compared. Results: The mean patient survival time after diagnosis was $49.1{\pm}4.4$ months. In the complete case analysis, which used information from 100 of the 471 patients, very wide and uninformative confidence intervals were obtained for the chemotherapy and surgery hazard ratios (HRs). However, after imputation, the maximum confidence interval widths for the chemotherapy and surgery HRs were 8.470 and 0.806, respectively. The minimum width corresponded with MI. Furthermore, the minimum Bayesian and Akaike information criteria values correlated with MI (-821.236 and -827.866, respectively). Conclusions: Missing value imputation increased the estimate precision and accuracy. In addition, MI yielded better results when compared with the expectation maximization algorithm and regression simple imputation methods.

Extensive Lymph Node Dissection Improves Survival among American Patients with Gastric Adenocarcinoma Treated Surgically: Analysis of the National Cancer Database

  • Naffouje, Samer A.;Salti, George I.
    • Journal of Gastric Cancer
    • /
    • v.17 no.4
    • /
    • pp.319-330
    • /
    • 2017
  • Introduction: The extent of lymphadenectomy in the surgical treatment of gastric cancer is a topic of controversy among surgeons. This study was conducted to analyze the American National Cancer Database (NCDB) and conclude the optimal extent of lymphadenectomy for gastric adenocarcinoma. Methods: The NCDB for gastric cancer was utilized. Patients who received at least a partial gastrectomy were included. Patients with metastatic disease, unknown TNM stages, R1/R2 resection, or treated with a palliative intent were excluded. Joinpoint regression was used to identify the extent of lymphadenectomy that reflects the optimal survival. Cox regression analysis and Bayesian information criterion were used to identify significant survival predictors. Kaplan-Meier was applied to study overall survival and stage migration. Results: 40,281 patients of 168,377 met the inclusion criteria. Joinpoint analysis showed that dissection of 29 nodes provides the optimal median survival for the overall population. Regression analysis reported the cutoff ${\geq}29$ to have a better fit in the prognostic model than that of ${\geq}15$. Dissection of ${\geq}29$ nodes in the higher stages provides a comparable overall survival to the immediately lower stage. Nonetheless, the retrieval of ${\geq}15$ nodes proved to be adequate for staging without a significant stage migration compared to ${\geq}29$ nodes. Conclusion: The extent of lymphadenectomy in gastric adenocarcinoma is a marker of improved resection which reflects in a longer overall survival. Our analysis concludes that the dissection of ${\geq}15$ nodes is adequate for staging. However, the dissection of 29 nodes might be needed to provide a significantly improved survival.

Screening for Patients with Non-small Cell Lung Cancer Who Could Survive Long Term Chemotherapy

  • Wu, Xue-Yan;Huang, Xin-En
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.16 no.2
    • /
    • pp.647-652
    • /
    • 2015
  • Background: Lung cancer was one of the most common cancers in both men and women all over the world. In this study, we aimed to clarify who could survive after long term chemotherapy in patients with advanced non-small cell lung cancer (NSCLC). Methods: We enrolled 186 patients with stage IV NSCLC after long term chemotherapy from Jun 2006 to Nov 2014 diagnosed in Jiangsu Cancer Hospital. Multiple variables like age, gender, smoking, histology of adenocarcinoma and squamous-cell cancer, number of metastatic sites, metastatic sites (e.g. lung, brain, bone, liver and pleura), hemoglobin, lymphocyte rate (LYR), Change of LYR during multiple therapies, hypertension, diabetes, chronic bronchitis, treatments (e.g.radiotherapy and targeted therapy) were selected. For consideration of factors influencing survival and response for patients with advanced NSCLC, logistic regression analysis and Cox regression analysis were used in an attempt to develop a screening module for patients with elevated survival after long term chemotherapy become possible. Results: Of the total of 186 patients enrolled, 69 survived less than 1 year (short-term group), 45 one to two years, and 72 longer than 3 years (long-term group). For logistic regression analysis, the short-term group was taken as control group and the long-term group as the case group. We found that age, histology of adenocarcinoma, metastatic site (e.g. lung and liver), treatments (e.g. targeted therapy and radiotherapy), LYR, a decreasing tendency of LYR and chronic bronchitis were individually associated with overall survival by Cox regression analysis. A multivariable Cox regression model showed that metastatic site (e.g. lung and liver), histology of adenocarcinoma, treatments (e.g. targeted therapy and radiotherapy) and chronic bronchitis were associated with overall survival. Thus metastatic site (e.g. lung and liver) and chronic bronchitis may be important risk factors for patients with advanced NSCLC. Gender, metastatic site (e.g. lung and liver), LYR and the decreasing tendency of LYR were significantly associated with long-term survival in the individual-variable logistic regression model (P<0.05). On multivariate logistic regression analysis, gender, metastatic site (e.g. lung and liver) and the decreasing tendency of LYR associated with long-term survival. Conclusions: In conclusion, female patients with stage IV adenocarcinoma of NSCLC who had decreasing tendency of LYR during the course therapy and had accepted multiple therapies e.g. more than third-line chemotherapy, radiotherapy and/or targeted therapy might be expected to live longer.

Comparison of Survival Function Estimators for the Cox's Regression Model using Bootstrap Method (Cox 회귀모형(回歸模型)에서 붓스트랩방법(方法)에 의한 생존함수추정량(生存函數推定量)의 비교연구(比較硏究))

  • Cha, Young-Joon
    • Journal of the Korean Data and Information Science Society
    • /
    • v.4
    • /
    • pp.1-11
    • /
    • 1993
  • The Cox's regression model is frequently used for covariate effects in survival data analysis, But, much of the statistical work has focused on asymptotic behavior so the small sample evaluation has been neglected. In this paper, we compare the small or moderate sample performances of the survival function estimators for the Cox's regression model using bootstrap method. The smoothed PL type estimator and the Link estimator are slightly better than corresponding the PL type estimator and the Nelson type estimator in the sense of the achieved error rates.

  • PDF

On the analysis of multistate survival data using Cox's regression model (Cox 회귀모형을 이용한 다중상태의 생존자료분석에 관한 연구)

  • Sung Chil Yeo
    • The Korean Journal of Applied Statistics
    • /
    • v.7 no.2
    • /
    • pp.53-77
    • /
    • 1994
  • In a certain stochastic process, Cox's regression model is used to analyze multistate survival data. From this model, the regression parameter vectors, survival functions, and the probability of being in response function are estimated based on multistate Cox's partial likelihood and nonparametric likelihood methods. The asymptotic properties of these estimators are described informally through the counting process approach. An example is given to likelihood the results in this paper.

  • PDF

Expression Profiles of Loneliness-associated Genes for Survival Prediction in Cancer Patients

  • You, Liang-Fu;Yeh, Jia-Rong;Su, Mu-Chun
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.15 no.1
    • /
    • pp.185-190
    • /
    • 2014
  • Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high-lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness-associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.

Logistic Regression Method in Interval-Censored Data

  • Yun, Eun-Young;Kim, Jin-Mi;Ki, Choong-Rak
    • The Korean Journal of Applied Statistics
    • /
    • v.24 no.5
    • /
    • pp.871-881
    • /
    • 2011
  • In this paper we propose a logistic regression method to estimate the survival function and the median survival time in interval-censored data. The proposed method is motivated by the data augmentation technique with no sacrifice in augmenting data. In addition, we develop a cross validation criterion to determine the size of data augmentation. We compare the proposed estimator with other existing methods such as the parametric method, the single point imputation method, and the nonparametric maximum likelihood estimator through extensive numerical studies to show that the proposed estimator performs better than others in the sense of the mean squared error. An illustrative example based on a real data set is given.

Analysis of flexural fatigue failure of concrete made with 100% coarse recycled and natural aggregates

  • Murali, G.;Indhumathi, T.;Karthikeyan, K.;Ramkumar, V.R.
    • Computers and Concrete
    • /
    • v.21 no.3
    • /
    • pp.291-298
    • /
    • 2018
  • In this study, the flexural fatigue performance of concrete beams made with 100% Coarse Recycled Concrete Aggregates (RCA) and 100% Coarse Natural Aggregates (NA) were statistically commanded. For this purpose, the experimental fatigue test results of earlier researcher were investigated using two parameter Weibull distribution. The shape and scale parameters of Weibull distribution function was evaluated using seven numerical methods namely, Graphical method (GM), Least-Squares (LS) regression of Y on X, Least-Squares (LS) regression of X on Y, Empherical Method of Lysen (EML), Mean Standard Deviation Method (MSDM), Energy Pattern Factor Method (EPFM) and Method of Moments (MOM). The average of Weibull parameters was used to incorporate survival probability into stress (S)-fatigue life (N) relationships. Based on the Weibull theory, as single and double logarithm fatigue equations for RCA and NA under different survival probability were provided. The results revealed that, by considering 0.9 level survival probability, the theoretical stress level corresponding to a fatigue failure number equal to one million cycle, decreases by 8.77% (calculated using single-logarithm fatigue equation) and 6.62% (calculated using double logarithm fatigue equation) in RCA when compared to NA concrete.