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Predicting pre-eclampsia in nulliparous women using routinely-collected maternal characteristics: A model development and validation study 1School of Medicine, The University of Notre Dame Australia, Australia; 2NHMRC Clinical Trial Centre, University of Sydney, Australia; 3Department of Obstetrics, Westmead Hospital, Australia; 4Department of Obstetrics, Auburn and Mount-Druitt and Blacktown Hospitals, Australia; 5Department of Medicine, St. Michael’s Hospital, Canada
Why are Machine Learning-based prediction models still unpopular in clinical practice? 1Julius Center for Health Sciences and Primary Care, UMC Utrecht, Utrecht University, The Netherlands; 2Cochrane Netherlands, UMC Utrecht, Utrecht University, The Netherlands; 3Center for Statistics in Medicine, University of Oxford, United Kingdom; 4School of Primary, Community and Social Care, Keele University, United Kingdom
Development of prediction models using competing risk models in big healthcare databases 1University of Oxford, United Kingdom; 2University of Keele, United Kingdom
Weighted variogram analyses for estimating within-patient variance components using routine data from biomarker monitoring programmes 1Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom; 2National Institute for Health Research Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, UK
Bayesian Hierarchical Models for Personalized Health Care ETH Zurich, Switzerland
Dealing with multiple thresholds in diagnostic test accuracy meta-analysis: application of two modelling strategies 1Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium; 2Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium; 3Clinical division of pediatrics, UZ Leuven, Leuven, Belgium; 4Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
Harnessing repeated measurements of predictor variables: A review of existing methods for clinical risk prediction 1Centre for Epidemiology Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Oxford Road, Manchester M13 9PL, UK; 2Centre for Biostatistics, Manchester Academic Health Science Centre, University of Manchester, Oxford Road, Manchester M13 9PL, UK; 3Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Oxford Road, Manchester M13 9PL, UK; 4National Institute for Health Research Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Oxford Road, Manchester M13 9PL, UK
Adaptive sample size determination for the development of clinical prediction models 1Department of Development & Regeneration, KU Leuven, Leuven, Belgium; 2University Hospitals Leuven, Leuven, Belgium; 3Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands; 4Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
Propensity-based standardization to enhance the interpretation of predictive performance in individual participant data meta-analysis 1Julius Center for Health Sciences and Primary Care, UMC Utrecht, Utrecht University, The Netherlands; 2Cochrane Netherlands, University Medical Center Utrecht, Utrecht, The Netherlands; 3Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark; 4Department of Pharmacy, University Hospital Centre of Nîmes and University of Montpellier, Nîmes, France
Exploring test accuracy of faecal calprotectin for IBD using primary care electronic health records 1University of Warwick, United Kingdom; 2Devon, United Kingdom; 3University of Birmingham, United Kingdom
Multiple screening tools, multiple thresholds, multiple clinical cohorts: Evaluating screening tools for obstructive sleep apnoea 1Department of Health Sciences, University of Leicester, Leicester, UK; 2Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester, UK; 3Brazilian Centre for Evidence-based Research/Centro Brasileiro de Pesquisas Baseadas em Evidências, Federal University of Santa Catarina, Florianopólis, Brazil; 4Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK; 5Department of Cardiovascular Sciences, University of Leicester, Leicester, UK; 6Community Health Services, Leicestershire Partnership NHS Trust, Leicester, UK
Only fools rush in! – initial data analysis is required for developing and validating prediction models 1Section for Clinical Biometrics, Center for Medical Statistics, Informatics, and Intelligent Systems; Medical University of Vienna, Vienna, Austria; 2Biostatistical Sciences and Pharmacometrics; Novartis Pharma AG, Basel, Switzerland; 3Department of Statistics and Probability, Michigan State University, East Lansing, MI, USA
Pertussis in Belgium - The challenge of using historical serial serological survey data 1Vaccine and Infectious Disease Institute, University of Antwerp, Belgium; 2Department of Epidemiology and Social Medicine, University of Antwerp, Belgium; 3Data Science Institute, Hasselt University, Belgium; 4SD Epidemiology and Public Health, Sciensano, Brussels, Belgium; 5SD Infectious Diseases in Humans, Sciensano, Brussels, Belgium
Diagnostic accuracy of C-reactive protein for appendicitis in primary care 1Department of General Practice and Elderly Care Medicine, University Medical Center Groningen, University of Groningen, PO Box 196, 9700 AD Groningen, the Netherlands; 2Department of Medical Informatics, Erasmus Medical Center, Rotterdam, the Netherlands
Developing and validating a warfarin dose prediction model for patients in sub-Saharan Africa University of Liverpool, United Kingdom
Collinearity in prognostic models for dysphagia Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht
Evaluating risk of bias and applicability in meta-analyses of individual participant data 1Centre for Prognosis Research, School of Primary, Community and Social Care, Keele University, Staffordshire, UK; 2Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK; 3Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, UK; 4Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
Selective Cutoff Reporting in Diagnostic Accuracy Studies of the PHQ-9 and EPDS Depression Screening Tools 1Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Québec, Canada; 2Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada; 3Centre for Prognosis Research, School of Primary, Community and Social Care, Keele University, Staffordshire, UK; 4Respiratory Epidemiology and Clinical Research Unit, McGill University Health Centre, Montréal, Québec, Canada; 5N/A
Estimating the prevalence of misdiagnosis of giant cell arteritis: using a genetic test as umpire 1University of Leeds, United Kingdom; 23. Instituo di Parasitologia y Biomedicina, Consejo Superior de Investigaciones Cientificas (Spanish National Research Council), Madrid, Spain
Bayesian latent class analysis versus composite reference standards for estimating tuberculosis meningitis diagnostic test accuracy 1McGill University, Canada; 2McGill International TB Centre
Measuring the impact of diagnostic tests on patient management decisions within three clinical trials UCL Centre for Medical Imaging, University College London, Charles Bell House, 43-45 Foley Street, W1W 7TS
Ambiguous baseline definitions affect automated AKI diagnosis at emergency department 1Central Diagnostic Laboratory, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands; 2SkylineDx, Lichtenauerlaan 40, 3062 ME Rotterdam, The Netherlands; 3Department of Internal Medicine, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
Real-time handling of Missing Predictor Values when implementing and using prediction models in daily practice 1Julius Center for Health Sciences and Primary Care, Utrecht University, Utrecht, The Netherlands; 2LogiqCare, Ortec B.V. Zoetermeer, The Netherlands; 3Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands; 4Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom; 5Health Data Research UK, Institute of Health Informatics, University College London, London, United Kingdom
intelligent Liver Function Testing (iLFT): an algorithm-based pathway to increase diagnosis of liver disease 1NHS Tayside, United Kingdom; 2University of Dundee, United Kingdom
Recommended labels for approaches to evaluate diagnostic accuracy: the STARD ReLabel project 1Dept. of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam Public Health Research Institute, Amsterdam University Medical Center, The Netherlands; 2Exeter Test Group, Institute of Health and Research, College of Medicine and Health, University of Exeter, UK
Frequencies and patterns of microbiology test requests from general practice 1Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK; 2NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; 3Nuffield Department of Medicine, University of Oxford, Oxford, UK
Patient and public involvement in methodological research: a case study 1Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom; 2NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, UK
A standardized framework for risk-based assessment of heterogeneity of treatment effect 1Erasmus Medical Center, Netherlands; 2Leiden University Medical Center, Netherlands; 3Tufts Medical Center, USA
A prognostic model for overall survival in sporadic Creutzfeldt-Jakob disease 1Institute for Epidemiology and Social Medicine, University of Münster, Domagkstraße 3, 48149 Münster, Germany; 2Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Institute Carlos III, Campus Bellvitge, Feixa LLarga s/n, 08907 L’Hospitalet de Llobregat, Barcelona, Spain; 3Bellvitge Biomedical Research Institute (IDIBELL), Avinguda de la Granvia de l’Hospitalet, 199, 08908 L’Hospitalet de Llobregat, Barcelona, Spain; 4Department of Neurology, University Medical School, Robert-Koch-Straße 40, 37075 Göttingen, Germany; 5German Center for Neurodegenerative Diseases (DZNE), Von-Siebold-Straße 3A, 37075 Göttingen, Germany
Novel method for assessing the effect of case-mix and model calibration on the ROC curve 1Faculty of Pharmaceutical Sciences, The University of British Columbia, Canada; 2Department of Epidemiology and Biostatistics, McGill University, Canada; 3Department of Statistics, The University of British Columbia, Canada
A Permutation Test Approach to Provide Exact Inference for Incremental Gain from Nested Regression Models 1University of Vermont, Burlington, USA; 2National Cancer Institute, USA
Probabilistic data standardisation of big heterogeneous datasets in biomedicine Division of Informatics, Imaging and Data Sciences University of Manchester, Manchester, UK
Predicting Biomarker success:a new toolkit Imperial College London, United Kingdom
Assessing the impact of test measurement uncertainty on clinical and health-economic outcomes: a case study 1Test Evaluation Group, Academic Unit of Health Economics, University of Leeds, Leeds, UK; 2NIHR Leeds In Vitro Diagnostic (IVD) Co-operative, Leeds, UK; 3Leeds Centre for Personalised Medicine and Health, University of Leeds, Leeds, UK; 4Health Economics Group, University of Exeter, Exeter, UK; 5Cancer Research UK Edinburgh Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
Beyond the laboratory: methods to assess the impact of test measurement uncertainty on outcomes 1Test Evaluation Group, Academic Unit of Health Economics, University of Leeds, Leeds, UK; 2NIHR Leeds In Vitro Diagnostic (IVD) Co-operative, Leeds, UK; 3Leeds Centre for Personalised Medicine and Health, University of Leeds, Leeds, UK; 4Health Economics Group, University of Exeter, Exeter, UK; 5Cancer Research UK Edinburgh Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
Impact of prediction models in obstetric care: the Expect study 1Department of Epidemiology, Maastricht University, The Netherlands; 2Department of Obstetrics and Gynecology, School for Oncology and Developmental Biology (GROW), Maastricht University Medical Centre, The Netherlands; 3Department of Clinical Epidemiology and Medical Technology Assessment (KEMTA), Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Centre, The Netherlands; 4Department of Obstetrics and Gynecology, Sint Jans Gasthuis Weert, The Netherlands.; 5Department of Obstetrics and Gynecology, VieCuri Medical Centre, Venlo, The Netherlands.; 6Department of Obstetrics and Gynecology, Zuyderland Medical Centre, Heerlen, The Netherlands.; 7Department of Obstetrics and Gynecology, Laurentius Hospital, Roermond, The Netherlands.
Development and validation of prediction models for pre-eclampsia: An Individual Participant Data Meta-analysis 1Barts Research Centre for Women’s Health, Queen Mary University of London, UK; 2Centre for Prognosis Research, Keele University, UK; 3Institute of Metabolism and Systems Research, University of Birmingham, UK
External validation of prognostic models to predict pre-eclampsia: An Individual Participant Data Meta-analysis 1Barts Research Centre for Women’s Health, Queen Mary University of London, UK; 2Centre for Prognosis Research, Keele University, UK; 3Institute of Metabolism and Systems Research, University of Birmingham, UK
Simulation-based sample size calculations for studies externally validating a prediction model 1Centre for Prognosis Research, School of Primary, Community and Social Care, Keele University, Keele, Staffordshire, UK; 2Department of Biostatistics, University of Liverpool, Liverpool, UK; 3Centre for Reviews and Dissemination, University of York, York, UK; 4Centre for Statistics in Medicine, University of Oxford, Oxford, UK
TRIPOD-SR: An extension to reporting guidelines for systematic reviews of prediction model studies 1Centre for Prognosis Research, School of Primary, Community and Social Care, Keele University, Keele, Staffordshire, UK; 2Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands; 3Centre for Statistics in Medicine, University of Oxford, Oxford, UK
Use and misuse of the "calibration" slope 1University of Oxford, United Kingdom; 2University of Auckland, New Zealand
Statistical methods for estimating sources of variability in count biomarkers 1Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK; 2NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
Statistical methods for the meta-analysis of reliability estimates reported in biological variability studies 1Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom; 2NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, UK
Pre-analytical error for three point of care venous blood testing platforms in acute ambulatory care 1Nuffield Department of Primary Care Health Sciences, University of Oxford; 2Oxford University Hospitals NHS Foundation Trust
Development of a model to predict the likelihood of a genetic variant causing familial hypercholesterolaemia 1Northern Medical Physics and Clinical Engineering, The Newcastle-upon-Tyne Hospitals NHS Foundation Trust, UK; 2The National Institute for Health Research Newcastle In Vitro Diagnostics Co-operative, Newcastle-upon-Tyne, UK; 3Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, UK; 4Laboratory Medicine, The Newcastle-upon-Tyne Hospitals NHS Foundation Trust, UK
Development of an application to support the identification of patients with familial hypercholesterolaemia 1Northern Medical Physics and Clinical Engineering, The Newcastle-upon-Tyne Hospitals NHS Foundation Trust, UK; 2The National Institute for Health Research Newcastle In Vitro Diagnostics Co-operative, Newcastle-upon-Tyne, UK; 3Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, UK; 4Laboratory Medicine, The Newcastle-upon-Tyne Hospitals NHS Foundation Trust, UK
The potential of ‘conceptually oriented’ pre-processing of covariates to improve prognostic models. A case study. 1Department of Sports Science and Clinical Biomechanics, University of Southern Denmark; 2Department of Management, Technology, and Economics, ETH Zurich; 3Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg; 4Basel Academy for Quality and Rsearch in Medicine; 5Nordic Institute of Chiropractic and Clinical Biomechanics
Visualizing the results of a diagnostic accuracy study using comparison regions Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
Using harmonised results of different tests for a single biomarker in test accuracy meta-analysis 1Department of Clinical Epidemiology, Biostatistics & Bioinformatics, Amsterdam University Medical Center, Amsterdam, The Netherlands; 2Hepato-Gastroenterology Department, Angers University Hospital, Angers, France; 3HIFIH Laboratory, UPRES EA3859, Angers University, Angers France
Large-scale validation of the Prediction model Risk Of Bias ASsessment Tool(PROBAST) using a short form 1Erasmus MC University Medical Center, Rotterdam, The Netherlands; 2Tufts Medical Center, Boston, MA, USA; 3Benha Faculty of Medicine, Benha, Egypt; 4Leiden University Medical Center, Leiden, The Netherlands
Network meta-analysis methods for ranking the accuracy of multiple diagnostic tests 1Department of Primary Education, School of Education, University of Ioannina, Ioannina, Greece; 2Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Ontario, Canada; 3Institute of Reproductive and Developmental Biology, Department of Surgery & Cancer, Faculty of Medicine, Imperial College, London, United Kingdom; 4Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, UK; 5NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK; 6Paris Descartes University, Sorbonne Paris Cité, Faculté de Médecine, Paris, France
Clinical Prediction Models for Patients with Acute Coronary Syndromes: Results from Independent External Validations 1Predictive Analytics and Comparative Effectiveness (PACE), Tufts Medical Center, United States of America; 2Division of Cardiology, Tufts Medical Center, Boston, MA; 3KU Leuven, Department of Development and Regeneration, Leuven, Belgium; 4Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, Netherlands
Survey for elucidating potential roles for sepsis diagnostics in the UK NHS 1National Institute for Heath Research Newcastle In vitro Diagnostics Co-operative, Newcastle University, Medical School, Framlington Place, Newcastle-upon-Tyne, UK; 2The Newcastle-upon-Tyne Hospitals NHS Foundation Trust, Royal Victoria Infirmary, Queen Victoria Road, Newcastle-upon-Tyne, UK; 3Department of Marketing, Audencia Business School, 8 Route de la Jonelière, B.P. 31222 44312 Nantes, Cedex 3, France; 4Translational and Clinical Research Institute, Newcastle University, Medical School, Framlington Place, Newcastle-upon-Tyne, UK; 5South Tyneside and Sunderland NHS Foundation Trust, Kayll Road, Sunderland, UK
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