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SUMMARY:Individual dynamic predictions using landmarking and joint modelli
 ng: validation of estimators and robustness assessment - Dr Loic Ferrer\, 
 ISPED\, Bordeaux
DTSTART:20171031T143000Z
DTEND:20171031T153000Z
UID:TALK81631@talks.cam.ac.uk
CONTACT:Alison Quenault
DESCRIPTION:After the diagnosis of a disease\, one major objective is to p
 redict cumulative probabilities of events such as clinical relapse or deat
 h from the individual information collected up to a prediction time\, incl
 uding usually biomarker repeated measurements. Several competing estimator
 s have been proposed to calculate these individual dynamic predictions\, m
 ainly from two approaches: joint modelling and landmarking. These approach
 es differ by the information used\, the model assumptions and the complexi
 ty of the computational procedures. It is essential to properly validate t
 he estimators derived from the joint models and the landmark models\, quan
 tify their variability and compare them in order to provide key elements f
 or the development and use of individual dynamic predictions in clinical f
 ollow-up of patients. Motivated by the prediction of two competing causes 
 of progression of prostate cancer from the history of prostate-specific an
 tigen\, we conducted an in-depth simulation study to validate and compare 
 the dynamic predictions derived from these two methods. Specifically\, we 
 formally defined the quantity to estimate and its estimators\, proposed te
 chniques to assess the uncertainty around predictions and validated them. 
 We also compared the individual dynamic predictions derived from joint mod
 els and landmark models in terms of accuracy of prediction\, efficiency an
 d robustness to model assumptions. We show that these prediction tools sho
 uld be handled with care\, in particular by properly specifying models and
  estimators.
LOCATION:Small Seminar Room\, 1st Floor\, Institute of Public Health\, Uni
 versity Forvie Site\, Robinson Way\, Cambridge
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