Methods for Evaluating Medical Tests and Biomarkers

Abstract

O1 User testing of Test-Treatment Pathway derivation to help formulating focused diagnostic questions Gowri Gopalakrishna1, Miranda Langendam1, Rob Scholten2, Patrick Bossuyt1, Mariska Leeflang1 1Department of Clinical Epidemiology, Biostatistics & Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; 2Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands Correspondence: Mariska Leeflang (m.m.leeflang@amc.uva.nl) Background: The Test-Treatment Pathway has been proposed as a method to link test accuracy to downstream outcomes. O2 Using machine learning and crowdsourcing for the identification of diagnostic test accuracy Anna Noel-Storr1, James Thomas2, Iain Marshall3, Byron Wallace4 1Cochrane Dementia and Cognitive Improvement Group, University of Oxford, Oxford, UK; 2EPPI-Centre, Department of Social Science, University College London, London, UK; 3Division of Health and Social Care Research, King’s College London, London, UK; 4College of Computer and Information Science, Northeastern University, Boston, USA Correspondence: Anna Noel-Storr (anna.noel-storr@rdm.ox.ac.uk) Identifying studies of diagnostic test accuracy (DTA) is challenging. O3 Developing plain language summaries for diagnostic test accuracy (DTA) reviews Penny Whiting1, Clare Davenport2, Mariska Leeflang3, Gowri GopalaKrishna3, Isabel de Salis4 1University Hospitals Bristol NHS Foundation Trust, School of Social and Community Medicine, Bristol, UK; 2Institute of Applied Health Research, University of Birmingham, Birmingham, UK; 3Department of Clinical Epidemiology, Biostatistics & Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; 4School of Social and Community Medicine, University of Bristol, Bristol, UK Correspondence: Penny Whiting (Penny.whiting@bristol.ac.uk) A plain language summary (PLS) is a stand-alone summary of a Cochrane systematic review and should provide rapid access to its content. O4 Prediction model study risk of bias assessment tool (PROBAST) Sue Mallett1, Robert Wolff2, Penny Whiting3, Richard Riley4, Marie Westwood2, Jos Kleinen2, Gary Collins5, Hans Reitsma6,7, Karel Moons6 1Institute of Applied Health Research, University of Birmingham, Birmingham, UK; 2Kleijnen Systematic Reviews Ltd, York, UK; 3University Hospitals Bristol NHS Foundation Trust, School of Social and Community Medicine, Bristol, UK; 4Research Institute for Primary Care and Health Sciences, Keele University, Keele, UK; 5Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK; 6Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; 7Cochrane Netherlands, University Medical Center Utrecht, Utrecht, The Netherlands Correspondence: Sue Mallett (s.mallett@bham.ac.uk) Background: Quality assessment of included studies is a crucial step in any systematic review.