RESILIENCE (Retrospective Linkage Study of Autoimmune Encephalitis): protocol for an Australian retrospective cohort study of outcomes in autoimmune encephalitis using data linkage techniques
David Brown,
Wendyl D’Souza,
Mark Cook,
Andrew McLean-Tooke,
David Gillis,
Udaya Seneviratne,
James Boyd,
John Dunne,
Nicholas Lawn,
Ximena Camacho,
Christine Bundell,
Nerissa Jordan,
Sudarshini Ramanathan,
Fabienne Brilot,
Kerri M Prain,
Elaine Pang,
Katrina Lambert,
Russell Dale,
Lisa Gillinder,
Emma Whitham,
Saxon Douglass,
Amy Jean Halliday,
Greg Bryson,
Alan Lai,
Wendyl Jude D’Souza
Affiliations
David Brown
1 Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
Wendyl D’Souza
Mark Cook
Andrew McLean-Tooke
4 Department of Laboratory Immunology, Clinical Immunology, PathWest, Nedlands, Western Australia, Australia
David Gillis
6 Autoimmune-Immunobiology Laboratory, Division of Immunology, Queensland Public Health and Scientific Services, Queensland Health, Herston, Queensland, Australia
Udaya Seneviratne
James Boyd
3 Department of Public Health, School of Psychology and Public Health, La Trobe University, Melbourne, Victoria, Australia
John Dunne
1 Neurology, WA Adult Epilepsy Service, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
Nicholas Lawn
18 Western Australian Adult Epilepsy Service, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
Ximena Camacho
20 School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
Christine Bundell
4 Department of Laboratory Immunology, Clinical Immunology, PathWest, Nedlands, Western Australia, Australia
Nerissa Jordan
17 Department of Neurology, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
Sudarshini Ramanathan
10 Translational Neuroimmunology Group, Kids Neuroscience Centre, Kids Research at the Children’s Hospital at Westmead, Westmead, New South Wales, Australia
Fabienne Brilot
11 Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
Kerri M Prain
6 Autoimmune-Immunobiology Laboratory, Division of Immunology, Queensland Public Health and Scientific Services, Queensland Health, Herston, Queensland, Australia
Elaine Pang
Katrina Lambert
3 Department of Public Health, School of Psychology and Public Health, La Trobe University, Melbourne, Victoria, Australia
Russell Dale
11 Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
Lisa Gillinder
7 Queensland Brain Institute, The University of Queensland, St Lucia, Queensland, Australia
Emma Whitham
Saxon Douglass
Amy Jean Halliday
1 Department of Clinical Neurosciences, St Vincent`s Hospital Melbourne, Fitzroy, Victoria, Australia
Greg Bryson
6 Autoimmune-Immunobiology Laboratory, Division of Immunology, Queensland Public Health and Scientific Services, Queensland Health, Herston, Queensland, Australia
Alan Lai
2 Department of Medicine, St Vincent`s Hospital Melbourne, The University of Melbourne, Fitzroy, Victoria, Australia
Wendyl Jude D’Souza
1 Department of Clinical Neurosciences, St Vincent`s Hospital Melbourne, Fitzroy, Victoria, Australia
Introduction The autoimmune encephalitides (AE) are a heterogeneous group of neurological disorders with significant morbidity and healthcare costs. Despite advancements in understanding their pathophysiology, uncertainties persist regarding long-term prognosis and optimal management. This study aims to address these gaps, focusing on immunotherapeutic strategies, neoplastic associations and functional outcomes.Methods and analysis The Retrospective Linkage Study of Autoimmune Encephalitis project will use data linkage techniques to establish a retrospective 10-year population cohort of Australian patients with AE. Two cohorts will be analysed, the Reference Cohort (clinically confirmed AE cases obtained from hospital medical records, n=145) and the Operationally Defined Cohort (AE cases identified through administrative coding data, n≈5000). Univariate statistical methods will identify candidate coding elements for use in the operational case definition and multivariate models and evaluation methods used to identify and internally validate the optimal coding algorithms. The two study cohorts will be analysed separately due to the high likelihood of overlap. Primary outcomes include relapse rate, prevalence and control of epilepsy, cognitive disability, poor educational attainment, delayed tumour diagnosis and mortality. Statistical analyses, including random mixed-effects regression models, will assess treatment effects, covariates and outcomes.Ethics and dissemination This project has been approved by the leading investigators’ institutional Human Research Ethics Committee (HREC), the St Vincent’s Hospital Melbourne HREC, as well as the Australian Institute of Health and Welfare HREC and relevant jurisdictional HRECs where required. The dissemination of findings through peer-reviewed publications and patient advocacy channels will maximise the impact of this research.
