BEGIN:VCALENDAR VERSION:2.0 PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4// BEGIN:VEVENT UID:20250712T071215EDT-9586zPRLbi@132.216.98.100 DTSTAMP:20250712T111215Z DESCRIPTION:Title:Global Measures for Capacity of Subgroup-Defining Variabl es to Yield Efficient Treatment Rules\n\nAbstract: Mohsen is an epidemiolo gist who is interested in the application of decision theory in Precision Medicine. He runs the Respiratory Evaluation Sciences Program where he app lies such methods in the context of chronic respiratory conditions. For hi s work he has received multiple awards including The Canadian Institutes o f Health Research’s New Investigator Award and Michael Smith Foundation fo r Health Research Scholar Award. A fuller bio is available at http://resp. core.ubc.ca/team/Mohsen_SadatsafaviDecision theory provides a consistent f ramework for efficient treatment selection. Nevertheless\, a full applicat ion of decision theory requires context-specific valuations that might be impractical or even off-putting in many fast-paced areas such as Precision Medicine. As such\, a potential way forward is to apply such principles t o agreed-upon ‘salient’ clinical outcomes while letting more nuanced valua tions to take place over their due course. We are motivated by solutions t o a similar problem in (bio)marker discovery: at early stages of marker de velopment\, the interest is\, appropriately\, on the global discriminatory capacity of the marker rather than its performance given a specific posit ivity rule. This is perhaps why AUC has remained such a popular metric for communicating marker performance. The purpose of this work is to propose novel\, global\, ‘AUC-type’ metrics that quantify the capacity of subgroup -defining variables in finding individuals who benefit the most from treat ments. The proposed metrics have intuitive interpretations and enable comp arison of arbitrary sets of covariates on the same scale. They can be esti mated with relative ease for a wide class of regression models and can acc ompany conventional metrics for subgroup analysis when reporting the resul ts of clinical trials. • This work is developed in collaboration with Paul Gustafson\, The University of British Columbia\, and Mohammad Mansournia\ , Tehran University of Medical Sciences.\n DTSTART:20190115T203000Z DTEND:20190115T213000Z LOCATION:Room 24\, Purvis Hall\, CA\, QC\, Montreal\, H3A 1A2\, 1020 avenue des Pins Ouest SUMMARY:Mohsen Sadatsafavi (University of British Columbia) URL:/mathstat/channels/event/mohsen-sadatsafavi-univer sity-british-columbia-293081 END:VEVENT END:VCALENDAR