Mortality rate of gastric cancer is about 20.93/100000 which is the highest malignancy in China. The scientist of our country are at present interested in studying the postoperative survival model by multivariate anal...Mortality rate of gastric cancer is about 20.93/100000 which is the highest malignancy in China. The scientist of our country are at present interested in studying the postoperative survival model by multivariate analysis method just as stepwise regression model. The proportional hazard model initiated by Cox (1972) is more advanced than other regression method which is unneccessary to suppose the distribution of survival time and easy to analyse censoring data (the latter is difficult). This paper presented the first time application of Cox model in survival analysis of gastric cancer in China. The survival analysis system (SAS-Ⅰ) software complied by the author includes multivariate anlysis by Cox model, PV analysis and estimation of survival function which could provide useful information to surgeon for treatment of cancer patients.展开更多
In the applications of COX regression models, we always encounter data sets t<span>hat contain too many variables that only a few of them contribute to the</span> model. Therefore, it will waste much more ...In the applications of COX regression models, we always encounter data sets t<span>hat contain too many variables that only a few of them contribute to the</span> model. Therefore, it will waste much more samples to estimate the “noneffective” variables in the inference. In this paper, we use a sequential procedure for constructing<span><span><span style="font-family:;" "=""> </span></span></span><span><span><span style="font-family:;" "="">the fixed size confidence set for the “effective” parameters to the model based on an adaptive shrinkage estimate such that the “effective” coefficients can be efficiently identified with the minimum sample size. Fixed design is considered for numerical simulation. The strong consistency, asymptotic distributions and convergence rates of estimates under the fixed design are obtained. In addition, the sequential procedure is shown to be asymptotically optimal in the sense of Chow and Robbins (1965).</span></span></span>展开更多
AIM:To investigate the efficiency of Cox proportional hazard model in detecting prognostic factors for gastric cancer.METHODS:We used the log-normal regression model to evaluate prognostic factors in gastric cancer an...AIM:To investigate the efficiency of Cox proportional hazard model in detecting prognostic factors for gastric cancer.METHODS:We used the log-normal regression model to evaluate prognostic factors in gastric cancer and compared it with the Cox model.Three thousand and eighteen gastric cancer patients who received a gastrectomy between 1980 and 2004 were retrospectively evaluated.Clinic-pathological factors were included in a log-normal model as well as Cox model.The akaike information criterion (AIC) was employed to compare the efficiency of both models.Univariate analysis indicated that age at diagnosis,past history,cancer location,distant metastasis status,surgical curative degree,combined other organ resection,Borrmann type,Lauren's classification,pT stage,total dissected nodes and pN stage were prognostic factors in both log-normal and Cox models.RESULTS:In the final multivariate model,age at diagnosis,past history,surgical curative degree,Borrmann type,Lauren's classification,pT stage,and pN stage were significant prognostic factors in both log-normal and Cox models.However,cancer location,distant metastasis status,and histology types were found to be significant prognostic factors in log-normal results alone.According to AIC,the log-normal model performed better than the Cox proportional hazard model (AIC value:2534.72 vs 1693.56).CONCLUSION:It is suggested that the log-normal regression model can be a useful statistical model to evaluate prognostic factors instead of the Cox proportional hazard model.展开更多
Background: The Center of Molecular Immunology (CIM) is a center in Cuba devoted to the research, development and manufacturing of biotechnological products. CIMAvax?EGF is a vaccine for the treatment of non-small cel...Background: The Center of Molecular Immunology (CIM) is a center in Cuba devoted to the research, development and manufacturing of biotechnological products. CIMAvax?EGF is a vaccine for the treatment of non-small cell lung cancer patients (NSCL). Purpose: The aim of this work is to evaluate the effects of some potential prognostic factors on the overall survival of patients treated with CIMAvax?EGF vaccine, based on data collected in a phase II and a phase III clinical trials. Methods: The stratified Cox regression model is used to evaluate the effects of these prognostic factors, based on separate analysis for each trial, and on the combined data from both trials. Results: Patients with Performance status 0 or 1, with IV stage of tumor and male under 60 years obtain more benefit in terms of overall survival if they receive CIMAvax?EGF. Conclusions: Vaccinated group has a better performance if patients have a performance status 0 or 1, stage IV and age under 60 years. These prognostic factors influence overall survival in a positive way for those patients that received CIMAvax?EGF.展开更多
电力电缆故障信息的深层次挖掘可提高对电缆故障影响因素的分析。因此,针对某供电公司10 k V电力电缆故障数据,运用统计学模型—Cox比例风险模型,定量分析了电缆故障影响因素,用以指导电缆采购、施工、运行和维护。为确保数据分析的准确...电力电缆故障信息的深层次挖掘可提高对电缆故障影响因素的分析。因此,针对某供电公司10 k V电力电缆故障数据,运用统计学模型—Cox比例风险模型,定量分析了电缆故障影响因素,用以指导电缆采购、施工、运行和维护。为确保数据分析的准确性,提出了电缆数据预处理原则,探讨了合适的样本量大小。运用Cox比例风险模型对电缆故障影响因素进行单因素分析;运用Logistic回归模型确定了电缆故障影响因素类别,并统计计算了各电缆故障影响因素对应的电缆故障率,确定了各影响因素组成元素的相对危险程度,最终证明了Cox比例风险模型分析结果的正确性。结果表明:本体生产厂家M1、附件生产厂家N1、施工单位I3对应的电缆故障率最高分别为0.33、0.29、0.218,企业在进行电缆采购、施工、维护时应着重关注这3家单位。展开更多
文摘Mortality rate of gastric cancer is about 20.93/100000 which is the highest malignancy in China. The scientist of our country are at present interested in studying the postoperative survival model by multivariate analysis method just as stepwise regression model. The proportional hazard model initiated by Cox (1972) is more advanced than other regression method which is unneccessary to suppose the distribution of survival time and easy to analyse censoring data (the latter is difficult). This paper presented the first time application of Cox model in survival analysis of gastric cancer in China. The survival analysis system (SAS-Ⅰ) software complied by the author includes multivariate anlysis by Cox model, PV analysis and estimation of survival function which could provide useful information to surgeon for treatment of cancer patients.
文摘In the applications of COX regression models, we always encounter data sets t<span>hat contain too many variables that only a few of them contribute to the</span> model. Therefore, it will waste much more samples to estimate the “noneffective” variables in the inference. In this paper, we use a sequential procedure for constructing<span><span><span style="font-family:;" "=""> </span></span></span><span><span><span style="font-family:;" "="">the fixed size confidence set for the “effective” parameters to the model based on an adaptive shrinkage estimate such that the “effective” coefficients can be efficiently identified with the minimum sample size. Fixed design is considered for numerical simulation. The strong consistency, asymptotic distributions and convergence rates of estimates under the fixed design are obtained. In addition, the sequential procedure is shown to be asymptotically optimal in the sense of Chow and Robbins (1965).</span></span></span>
基金Supported by the Gastric Cancer Laboratory and Pathology Department of Chinese Medical University,Shenyang,Chinathe Science and Technology Program of Shenyang,No. 1081232-1-00
文摘AIM:To investigate the efficiency of Cox proportional hazard model in detecting prognostic factors for gastric cancer.METHODS:We used the log-normal regression model to evaluate prognostic factors in gastric cancer and compared it with the Cox model.Three thousand and eighteen gastric cancer patients who received a gastrectomy between 1980 and 2004 were retrospectively evaluated.Clinic-pathological factors were included in a log-normal model as well as Cox model.The akaike information criterion (AIC) was employed to compare the efficiency of both models.Univariate analysis indicated that age at diagnosis,past history,cancer location,distant metastasis status,surgical curative degree,combined other organ resection,Borrmann type,Lauren's classification,pT stage,total dissected nodes and pN stage were prognostic factors in both log-normal and Cox models.RESULTS:In the final multivariate model,age at diagnosis,past history,surgical curative degree,Borrmann type,Lauren's classification,pT stage,and pN stage were significant prognostic factors in both log-normal and Cox models.However,cancer location,distant metastasis status,and histology types were found to be significant prognostic factors in log-normal results alone.According to AIC,the log-normal model performed better than the Cox proportional hazard model (AIC value:2534.72 vs 1693.56).CONCLUSION:It is suggested that the log-normal regression model can be a useful statistical model to evaluate prognostic factors instead of the Cox proportional hazard model.
基金supported by a UICC International Cancer Technology Transfer Fellowship.
文摘Background: The Center of Molecular Immunology (CIM) is a center in Cuba devoted to the research, development and manufacturing of biotechnological products. CIMAvax?EGF is a vaccine for the treatment of non-small cell lung cancer patients (NSCL). Purpose: The aim of this work is to evaluate the effects of some potential prognostic factors on the overall survival of patients treated with CIMAvax?EGF vaccine, based on data collected in a phase II and a phase III clinical trials. Methods: The stratified Cox regression model is used to evaluate the effects of these prognostic factors, based on separate analysis for each trial, and on the combined data from both trials. Results: Patients with Performance status 0 or 1, with IV stage of tumor and male under 60 years obtain more benefit in terms of overall survival if they receive CIMAvax?EGF. Conclusions: Vaccinated group has a better performance if patients have a performance status 0 or 1, stage IV and age under 60 years. These prognostic factors influence overall survival in a positive way for those patients that received CIMAvax?EGF.
文摘电力电缆故障信息的深层次挖掘可提高对电缆故障影响因素的分析。因此,针对某供电公司10 k V电力电缆故障数据,运用统计学模型—Cox比例风险模型,定量分析了电缆故障影响因素,用以指导电缆采购、施工、运行和维护。为确保数据分析的准确性,提出了电缆数据预处理原则,探讨了合适的样本量大小。运用Cox比例风险模型对电缆故障影响因素进行单因素分析;运用Logistic回归模型确定了电缆故障影响因素类别,并统计计算了各电缆故障影响因素对应的电缆故障率,确定了各影响因素组成元素的相对危险程度,最终证明了Cox比例风险模型分析结果的正确性。结果表明:本体生产厂家M1、附件生产厂家N1、施工单位I3对应的电缆故障率最高分别为0.33、0.29、0.218,企业在进行电缆采购、施工、维护时应着重关注这3家单位。
