title: Development of a decision analytic model to support decision making and risk communication about thrombolytic treatment.
abstract: BACKGROUND
  Individualised prediction of outcomes can support clinical and shared decision making. This paper describes the building of such a model to predict outcomes with and without intravenous thrombolysis treatment following ischaemic stroke.
  
  
  METHODS
  A decision analytic model (DAM) was constructed to establish the likely balance of benefits and risks of treating acute ischaemic stroke with thrombolysis. Probability of independence, (modified Rankin score mRS ≤ 2), dependence (mRS 3 to 5) and death at three months post-stroke was based on a calibrated version of the Stroke-Thrombolytic Predictive Instrument using data from routinely treated stroke patients in the Safe Implementation of Treatments in Stroke (SITS-UK) registry. Predictions in untreated patients were validated using data from the Virtual International Stroke Trials Archive (VISTA). The probability of symptomatic intracerebral haemorrhage in treated patients was incorporated using a scoring model from Safe Implementation of Thrombolysis in Stroke-Monitoring Study (SITS-MOST) data.
  
  
  RESULTS
  The model predicts probabilities of haemorrhage, death, independence and dependence at 3-months, with and without thrombolysis, as a function of 13 patient characteristics. Calibration (and inclusion of additional predictors) of the Stroke-Thrombolytic Predictive Instrument (S-TPI) addressed issues of under and over prediction. Validation with VISTA data confirmed that assumptions about treatment effect were just. The C-statistics for independence and death in treated patients in the DAM were 0.793 and 0.771 respectively, and 0.776 for independence in untreated patients from VISTA.
  
  
  CONCLUSIONS
  We have produced a DAM that provides an estimation of the likely benefits and risks of thrombolysis for individual patients, which has subsequently been embedded in a computerised decision aid to support better decision-making and informed consent.
authors.affiliation: Institute of Health and Society, Newcastle University, Newcastle Upon Tyne, UK. peter.mcmeekin@northumbria.ac.uk.|School of Health, Community and Education Studies, Northumbria University, Newcastle upon Tyne, UK. peter.mcmeekin@northumbria.ac.uk.|Department of Healthcare, Northumbria University, Newcastle Upon Tyne, UK. peter.mcmeekin@northumbria.ac.uk.
authors.forename: Peter
authors.initials: P
authors.lastname: McMeekin
authors.affiliation: Institute of Health and Society, Newcastle University, Newcastle Upon Tyne, UK.
authors.forename: Darren
authors.initials: D
authors.lastname: Flynn
authors.affiliation: Institute for Ageing and Health (Stroke Research Group), Newcastle University, Newcastle Upon Tyne, UK.
authors.forename: Gary A
authors.initials: GA
authors.lastname: Ford
authors.affiliation: Institute for Ageing and Health (Stroke Research Group), Newcastle University, Newcastle Upon Tyne, UK.
authors.forename: Helen
authors.initials: H
authors.lastname: Rodgers
authors.affiliation: Department of Healthcare, Northumbria University, Newcastle Upon Tyne, UK.
authors.forename: Jo
authors.initials: J
authors.lastname: Gray
authors.affiliation: Institute of Health and Society, Newcastle University, Newcastle Upon Tyne, UK.
authors.forename: Richard G
authors.initials: RG
authors.lastname: Thomson
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002545:Brain Ischemia / Q000150:complications / Q000628:therapy*; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012042:Registries; D020521:Stroke / Q000209:etiology / Q000628:therapy*; D015912:Thrombolytic Therapy / Q000009:adverse effects / Q000592:standards*