Is it a good way to present updated model coefficients by refitting the model using both derivation and validation data?

Question

I am conducting a research on the development and external validation of a prediction model. I have developed a regression-based prediction model using derivation set data and externally validated it using independent validation data. The discriminative performance and calibration of the model were good. I presented the model as a regression equation with model coefficients as well as a nomogram.

My question is whether the regression coefficients in the presented model should be derived from the derivation data only, or re-fitting the model and updating the coefficients using entire data (i.e. derivation + validation data) is allowed or is even a better way to present the final model?

Answer 1

In the end, you want to end up with the best model possible, the most predictive one regarding brand new data inputs in the future. And, you develop such a model by including all the data you have.