Clustered survival data are widely observed in a variety of setting. Most survival models incorporate clustering and grouping of data accounting for between-cluster variability that creates correlation in order to pre...Clustered survival data are widely observed in a variety of setting. Most survival models incorporate clustering and grouping of data accounting for between-cluster variability that creates correlation in order to prevent underestimate of the standard errors of the parameter estimators but do not include random effects. In this study, we developed a mixed-effect parametric proportional hazard (MEPPH) model with a generalized log-logistic distribution baseline. The parameters of the model were estimated by the application of the maximum likelihood estimation technique with an iterative optimization procedure (quasi-Newton Raphson). The developed MEPPH model’s performance was evaluated using Monte Carlo simulation. The Leukemia dataset with right-censored data was used to demonstrate the model’s applicability. The results revealed that all covariates, except age in PH models, were significant in all considered distributions. Age and Townsend score were significant when the GLL distribution was used in MEPPH, while sex, age and Townsend score were significant in MEPPH model when other distributions were used. Based on information criteria values, the Generalized Log-Logistic Mixed-Effects Parametric Proportional Hazard model (GLL-MEPPH) outperformed other models.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
Seedling establishment on fallen logs is a major regeneration system for tree species in boreal forests. Seedling survival on fallen logs is affected not only by the microsite environment but also by the genetic facto...Seedling establishment on fallen logs is a major regeneration system for tree species in boreal forests. Seedling survival on fallen logs is affected not only by the microsite environment but also by the genetic factors of individuals. To quantify the genetic effects on seedling longevity, we identified seedlings using a number tag system and collected needles of Picea jezoensis and Abies sachalinensis established on fallen logs in spring 2006. Survival or death of each seedling was investigated during 2006-2012. We genotyped seedlings with microsatellite markers and calculated individual-based multilocus heterozygosity (MLH) for each seedling. A Cox proportional hazards model was applied to evaluate the effects of MLH on seedling longevity of the two species considering the fallen log conditions. The model indicated that MLH positively affected seedling longevity in P. jezoensis, whereas the effects of MLH were not significant in A. sachalinensis. Here, we discuss differences in the effects of MLH on seedling longevity between the two species, considering species characteristics and MLH frequency distribution.展开更多
文摘Clustered survival data are widely observed in a variety of setting. Most survival models incorporate clustering and grouping of data accounting for between-cluster variability that creates correlation in order to prevent underestimate of the standard errors of the parameter estimators but do not include random effects. In this study, we developed a mixed-effect parametric proportional hazard (MEPPH) model with a generalized log-logistic distribution baseline. The parameters of the model were estimated by the application of the maximum likelihood estimation technique with an iterative optimization procedure (quasi-Newton Raphson). The developed MEPPH model’s performance was evaluated using Monte Carlo simulation. The Leukemia dataset with right-censored data was used to demonstrate the model’s applicability. The results revealed that all covariates, except age in PH models, were significant in all considered distributions. Age and Townsend score were significant when the GLL distribution was used in MEPPH, while sex, age and Townsend score were significant in MEPPH model when other distributions were used. Based on information criteria values, the Generalized Log-Logistic Mixed-Effects Parametric Proportional Hazard model (GLL-MEPPH) outperformed other models.
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.
文摘Seedling establishment on fallen logs is a major regeneration system for tree species in boreal forests. Seedling survival on fallen logs is affected not only by the microsite environment but also by the genetic factors of individuals. To quantify the genetic effects on seedling longevity, we identified seedlings using a number tag system and collected needles of Picea jezoensis and Abies sachalinensis established on fallen logs in spring 2006. Survival or death of each seedling was investigated during 2006-2012. We genotyped seedlings with microsatellite markers and calculated individual-based multilocus heterozygosity (MLH) for each seedling. A Cox proportional hazards model was applied to evaluate the effects of MLH on seedling longevity of the two species considering the fallen log conditions. The model indicated that MLH positively affected seedling longevity in P. jezoensis, whereas the effects of MLH were not significant in A. sachalinensis. Here, we discuss differences in the effects of MLH on seedling longevity between the two species, considering species characteristics and MLH frequency distribution.
