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Joint modelling of longitudinal and competing risks data
Author(s) -
Williamson P. R.,
KolamunnageDona R.,
Philipson P.,
Marson A. G.
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3451
Subject(s) - joint (building) , computer science , longitudinal data , econometrics , statistics , data mining , mathematics , engineering , architectural engineering
Available methods for joint modelling of longitudinal and survival data typically have only one failure type for the time to event outcome. We extend the methodology to allow for competing risks data. We fit a cause‐specific hazards sub‐model to allow for competing risks, with a separate latent association between longitudinal measurements and each cause of failure. The method is applied to data from the SANAD trial of anti‐epileptic drugs (AEDs), as a means of investigating the effect of drug titration on the relative effects of lamotrigine (LTG) and carbamazepine (CBZ) on treatment failure. Concern had been expressed that differential titration rates may have been to the disadvantage of CBZ. The beneficial effect of LTG on unacceptable adverse events leading to drug withdrawal did not lessen and indeed increased slightly when a calibrated dose was accounted for in the joint model. Adjustment for the titration rate of LTG relative to CBZ resulted in an unchanged effect of the former on drug withdrawals due to inadequate seizure control. LTG remains the AED of choice from this analysis. Copyright © 2008 John Wiley & Sons, Ltd.