Figure 5.

C-Index evaluations of the various models analyzed. (A) Performance of clinical, genomic and combined models in the testing sets of all patients and ER-positive patients. Each patient subset was randomly split into a training set (~2/3 of cases) and a testing set (~1/3 of cases). We then used the model built from the training set to calculate the C-index of the testing set. We repeated this procedure 200 times and then calculated the mean of the C-index for each model. The performance of established prognostic predictors (OncoTypeDX RS, NKI 70-gene signature, 76-gene Rotterdam index, the risk of relapse based on intrinsic subtyping [ROR_S]) with or without the addition of clinical variables was also estimated. (B) Frequency of superiority of the C-Index for each model (rows) when compared to the other models (columns) in 200 testing sets of all patients. Each row represents a model, which is then compared to all other models/columns, where a higher number indicates that the row model was superior to the model in the column that fraction of the 200 times tested.

Fan et al. BMC Medical Genomics 2011 4:3   doi:10.1186/1755-8794-4-3
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