[R] interpreting bootstrap corrected slope [rms package]

[apeer]

One last thing.  At the outset of this discussion I provided the results of a
validation procedure on a model (see below).  As discussed previously, the
model overall seems to fair well, with the exception of the slope.  With
that in mind, is there a way to correct the coefficients of the model to
account for the corrected slope so that future predictions on a new data set
are more accurate?  Or is that not recommended at all?

          index.orig training    test optimism index.corrected   n
Dxy          0.9932   0.9940  0.9905   0.0035          0.9897 363
R2            0.9291   0.9364  0.9163   0.0202          0.9089 363
Intercept   0.0000   0.0000  0.0233  -0.0233          0.0233 363
Slope       1.0000   1.0000  0.7836   0.2164          0.7836 363
Emax       0.0000   0.0000  0.0582   0.0582          0.0582 363
D              0.9118   0.9190  0.8915   0.0275          0.8844 363
U             -0.0110  -0.0110  0.0124  -0.0234          0.0124 363
Q              0.9228   0.9299  0.8791   0.0508          0.8720 363
B              0.0205   0.0172  0.0239  -0.0067          0.0272 363 

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