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SUMMARY:“Identifying and evaluating personalised treatment recommendatio
 ns” - Prof Richard Emsley\, Centre for Biostatistics\, The University of
  Manchester\, Manchester Academic Health Science Centre
DTSTART:20170523T133000Z
DTEND:20170523T143000Z
UID:TALK72531@talks.cam.ac.uk
CONTACT:Alison Quenault
DESCRIPTION:Abstract: Stratified or personalised medicine is an attempt to
  move beyond a `one size fits all’ approach based on comparing group-lev
 el average outcomes to improve patient-level outcomes by identifying perso
 nalised treatment recommendations (PTR). A PTR maps a set of predictive ma
 rkers to a decision of whether or not to treat an individual patient. A PT
 R can be estimated from a weighted sum of predictive markers and the treat
 ment effect using either regression models\, inverse probability weighting
  (IPW)\, augmented IPW\, or classification methods.\n\nOnce estimated\, PT
 Rs can be evaluated by testing if the expected outcome under the PTR impro
 ves on the expected outcome under an alternative policy – such as one wh
 ere either every patient receives the treatment or every patient receives 
 the control condition. Evaluating a PTR differs from the evaluation of pro
 gnostic or diagnostic models because the object of inference (whether a su
 bject benefited from treatment) remains unobserved.\n\nIn this talk\, we w
 ill describe the statistical methods for estimating a PTR. Monte-Carlo sim
 ulations are used to compare the statistical properties of the estimation 
 methods under a range of data generating scenarios. These methods will be 
 demonstrated with application to data from a randomised controlled trial i
 n Chronic Fatigue Syndrome\, using our new user-written Stata command -ptr
 -.
LOCATION:Large  Seminar Room\, 1st Floor\, Institute of Public Health\, Un
 iversity Forvie Site\, Robinson Way\, Cambridge
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