I'm currently doing a prediction model using Cox regression on a dataset coming from an ongoing clinical database and containing information about patients who all have the same genetic disease.
In it, I have several binary variables for clinical manifestations of the disease(Present/absent), a birth date, a binary variable for my outcome(present/absent), a diagnosis date for my outcome, and a date of the last follow-up.
My binary variable for the outcome is my event variable, for the time-to-event variable it's the time from when patients are ten years old to either the event or censoring.
Knowing all of that, how is an age variable in a model defined in a situation like mine, if it is used at all?
Being a genetic disease, patients are born with it, so the age of onset can't be used. The age at recruitment has no value since the database is ongoing, and patients of all ages are recruited.
Am I missing something or age cannot really be a meaningful covariate in my model?