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The correlation between the IR and the potential accuracy of a predictor was evaluated.
The proportional hazard assumption of the predictor was evaluated by applying Kaplan Meier Curves.
The status of each independent variable as a predictor was evaluated at the bivariate level through comparing means on the ADKS measure with ANOVA tests.
The discrimination ability of each predictor was evaluated using the area under the receiver operating characteristic curve (AUC for ROC), for which values ≥ 0.600 were considered clinically useful.
The 5-gene predictor was evaluated on cDNA samples from the Bevacizumab qPCR and Control sets with qPCR and hydrolysis probes (TaqMan® MGB probes, Applied Biosystems/Life Technologies).
The prognostic capacity of each predictor was evaluated using 10,000 cross-validation trials, with discrimination ability of each model measured by area under the curve (AUC) statistics generated from time-specific receiver operating characteristic (ROC) curves [ 58] (see Methods).
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Univariate models for each predictor were evaluated.
All possible splits for each predictor are evaluated and the best split for single predictor is chosen.
The performance of the predictors was evaluated using receiver operating characteristic (ROC) curves (see Methods).
Correlation among predictors was evaluated based on eigenvalues derived from principal component analysis of the predictor variables.
Significance of the predictors was evaluated using the Wald statistic and the logits of continuous variables were inspected for linearity.
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