cross validation


I need some help with the following problem:

I have a group of patients and I would like to classify them either in responders/non-responders to a certain treatment.
For each person in the group a certain variable X was evaluated. By the use of ROC curves I have calculates the sensitivity and specificity of the method, the AUC value and corresponding p-value (which was statistically significant).
Now I would like to cross validate my model. I think this is a logistic regression model which I could analyze based on a v-fold cross validation, is this correct?
My sample is very small, could you give me some indication about what procedure to use to cross validate my model?

Thank you very much. Any suggestion/comment is more than welcome!

Thank you very much for your answer and help!

As you can see, I'm not at all an expert in statistics, but my model is very simple like the one you wrote above: logit(Pr(responder))=XB.
I used it to test the capability of a certain continous variable X to classify my group of patients in responders (1) or non responders (0) to a certain treatment.
To do the analysis I used a software called STATISTICA and I have calculated the ROC curve and correspondendt AUC value.
Now, I would need to know how my results are affected by the particular sample I have used. In other words, how my model would behave if I have another dataset/sample?
By reading the literature I understood that I might use a cross validation method called v-fold cross validation, or leave-one-out cross validation. Am I wrong?

Best regards,