# Computing AUC (or Somers' D) for ordinal logistic regression out-of-sample (cross-validation)

I have fit a proportional odds model with an ordinal response using Harrell's rms package. Now I want to measure the quality of prediction by computing Somers' D (or a generalized AUC) for this model. I have seen that the rms package has the validate() function to do this, but it operates by resampling. I have out-of-sample data I wish to use. Is there a way to use this data with the rms (or any alternative) package?