Graphics and statistics for cardiology: clinical prediction rules.
Graphs and tables are indispensable aids to quantitative research. When developing a clinical prediction rule that is based on a cardiovascular risk score, there are many visual displays that can assist in developing the underlying statistical model, testing the assumptions made in this model, evaluating and presenting the resultant score. All too often, researchers in this field follow formulaic recipes without exploring the issues of model selection and data presentation in a meaningful and thoughtful way. Some ideas on how to use visual displays to make wise decisions and present results that will both inform and attract the reader are given. Ideas are developed, and results tested, using subsets of the data that were used to develop the ASSIGN cardiovascular risk score, as used in Scotland.
The George Institute for Global Health, University of Oxford, Oxford, UK.|The George Institute for Global Health, University of Sydney, Sydney, Australia.|Cardiovascular Epidemiology Unit, Institute of Cardiovascular Research, University of Dundee, Dundee, UK.|Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, USA.
Mark
M
Woodward
Cardiovascular Epidemiology Unit, Institute of Cardiovascular Research, University of Dundee, Dundee, UK.
Hugh
H
Tunstall-Pedoe
The George Institute for Global Health, University of Oxford, Oxford, UK.
Sanne Ae
SA
Peters
D019540:Area Under Curve; D001296:Audiovisual Aids; D002309:Cardiology / Q000379:methods* / Q000706:statistics & numerical data; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000628:therapy*; D000066491:Clinical Decision-Making; D003627:Data Interpretation, Statistical; D003661:Decision Support Techniques; D006801:Humans; D007600:Judgment; D015233:Models, Statistical; D011237:Predictive Value of Tests; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors