A friend and I had a discussion around the following scenario and I’m interested in some outsider opinions.
Suppose you build a prediction model or models that allow you to predict that a patient with characteristics [X] under treatment course Y would have a survival of 3 years, and a patient with those same characteristics [X] under treatment course Z would have a survival of 5 years.
- Are you using your model “in a causal way” if you switch all patients with characteristics [X] to treatment course Z?
- Is this a reasonable thing to do, given that the prediction models were developed following best practices for development of a prediction model?