I would like to construct a survival curve from retrospectively gathered data that represents the time to onset (t$t$) of disease (d$d$) after some specific event (x$x$).
We know that x$x$ predisposes to d$d$ so we want to explore how t$t$ and d$d$ are related after x$x$ occurs.
The problem is that x$x$ can occur at any age and the risk of d$d$ (even without x$x$ occurring) increases with age. Furthermore, some of the study population already had d$d$ when x$x$ occurred.
Below is a plot I constructed that represents the diagnosis of d$d$ in all patients that were not already diagnosed with d$d$ and suffered x$x$ at t=0$t=0$.
However, some of these patients likely would have developed d$d$ anyway just given the age of that patient at t=0$t=0$. I am unsure of the most responsible way to control for this confounding variable in my survival analysis.
I'm sure this is actually a more complicated question than what I am making it out to be. Additional resources would great.
