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A stepwise variable selection was performed with Akaike Information Criteria in multivariate analysis.
Variables that showed a significant association with survival were included in multivariate analysis based on the Cox proportional hazard model with a stepwise method (forward selection).
In multivariate analysis, a backward stepwise selection procedure was used.
Variables that were significant on univariate analysis at P<0.10 were included in multivariate analysis by forward stepwise manner.
In multivariate analysis, we used the method of stepwise multivariate linear regression for each subgroup.
In multivariate analysis, we used logistic regression analysis (stepwise backwards logistic regression, 99%).
Variables were subjected to multivariate analysis with a logistic regression and forward stepwise selection after univariate analysis.
Data were analyzed using the Cox regression, backward stepwise method in the multivariate analysis.
In evaluating factors affecting OS, the Cox regression model with stepwise variable selection was used for multivariate analysis.
Bivariate analysis was performed with all factors and covariates, and then backward stepwise selection was applied in multivariate weighted generalized estimating equation models, starting with all variables that reached P < 0.2 in the bivariate analysis.
Variables that achieved statistical significance in the univariate analysis were included in a stepwise COX regression model for multivariate analysis.
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