Using logistic regression vs Cox regression Say I am interested in looking at the 5 year occurrence of an serious adverse drug reaction including mortality occurring in a group of patients being treated for a disease.
I would imagine that because we are looking at the odds of whether someone is alive or not/experienced hospitalisation for the ADR or not at the time point of 5 years, then that would require logistic regression.
I imagine Cox may be more suited to a question asking what the survival is post-cancer, as it looks at the time to event.
However, when I look at papers modelling adverse drug reactions, I see a Cox proportional hazards model is frequently used to estimate hazard ratios.
Any guidance on what I am misunderstanding would be much appreciated.

Survival analysis allows for individuals who are lost to follow up or haven't yet finished 5 years of observation to provide data. It also provides information about time-to-event that a simple logistic regression can't provide.
That said, such data are sometimes evaluated with a set of logistic regressions over a set of defined time intervals (e.g., each year out to 5 years). That's discrete-time survival analysis, which does provide information about time-to-event (at a coarse time scale) and incorporates some information from those lost to follow up or not yet ruching 5 years.
