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Table 2 Superpc continuous prediction results from breast cancer data analysis

From: A network module-based method for identifying cancer prognostic signatures

  Principal component
  1st 2nd 3rd
   HR 5.21E+00 2.28E+00 1.98E+00
   95% HR CI 3.18 to 8.56 1.19 to 4.34 1.02 to 3.83
   P-value 6.68E-11 1.25E-02 4.26E-02
   HR 7.35E+00 2.05E-01 2.66E-02
   95% HR CI 2.11 to 25.6 0.0091 to 4.62 6.5e-4 to 1.08
   P-value 1.73E-03 3.19E-01 5.51E-02
   HR 7.27E+02 6.10E-03 1.70E+00
   95% HR CI 8.1 to 6.5e+4 1.8e-4 to 0.21 1.1 to 2.6
   P-value 4.12E-03 4.61E-03 1.19E-02
   HR 5.34E+00 7.20E+00 9.31E-01
   95% HR CI 2.63 to 10.9 1.73 to 30.0 0.30 to 2.90
   P-value 3.63E-06 6.66E-03 9.01E-01
   HR 1.50E+02 1.45E+02 6.03E+00
   95% HR CI 17 to 1287 1.66 to 1.26e+4 0.034 to 1057
   P-value 5.00E-06 2.91E-02 4.96E-01
  1. The results were generated by using the Nejm data set as the training data set and four independent data sets as validation data with a threshold value of 1.20 and 8 selected MCL modules. P-values less than 0.05 are in bold. CI, confidence interval; HR, hazard ratio.