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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.

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    $\begingroup$ Some units may fail before the end of the study (say 5 years) and with the logistic regression, there is no way you can account for this. $\endgroup$
    – utobi
    Nov 14, 2022 at 10:38

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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.

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  • $\begingroup$ Thank you, this makes sense. I guess it will depend on the outcome then? If the outcome is looking at a dichotomous risk of either developing the event or not, LR could be used despite the limitation of not accounting for censoring. Otherwise, the outcome of the study using a Cox model would be more along the lines of event-free survival within 5 years or each year out to 5 years if using a discrete-time survival analysis. Let me know if I understood this correctly. $\endgroup$
    – Savannah
    Nov 14, 2022 at 17:18
  • $\begingroup$ @Savannah there are many dangers in not accounting for censoring. This review by Leung et al., Annu. Rev. Public Health 18:83–104 (1997) is still a good reference. Other than that, you seem to understand correctly. $\endgroup$
    – EdM
    Nov 14, 2022 at 17:38

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