Development of a Nationally Agreed Core Clinical Dataset for Childhood Onset Uveitis

Ameenat Lola Solebo; Salomey Kellett; Jugnoo Rahi; Reshma Pattani; Clive Edelsten; Andrew D Dick; Alastair Denniston; Pediatric Ocular Inflammation UNICORN Study Group

doi:10.3389/fped.2022.881398

Development of a Nationally Agreed Core Clinical Dataset for Childhood Onset Uveitis

Front Pediatr. 2022 Jun 21:10:881398. doi: 10.3389/fped.2022.881398. eCollection 2022.

Authors

Ameenat Lola Solebo^{1

2

3}, Salomey Kellett¹, Jugnoo Rahi^{1

2

3

4

5}, Reshma Pattani³, Clive Edelsten³, Andrew D Dick^{5

6

7}, Alastair Denniston^{8

9}; Pediatric Ocular Inflammation UNICORN Study Group

Collaborators

Pediatric Ocular Inflammation UNICORN Study Group:
Ms Ameenat Lola Solebo, Ms Salomey Kellett, Professor Andrew D Dick, Professor Jugnoo Rahi, Professor Alastair Denniston, Mr Damien Cm Yeo, Mr Jose Gonzalez-Martin, Ms Eibhlin McLoone, Prof Rachel Pilling, Mr John Bradbury, Prof Athimalaipet V Ramanan, Ms Catherine Guly, Ms Brinda Muthusamy, Mr Patrick Watts, Ms Christine Twomey, Ms Reshma Pattani, Mr Clive Edelsten, Mr Daniel Pharoah, Mr Vernon Long, Mr Adam Bates, Ms Elisabetta Scoppettuolo, Prof Jane Ashworth, Ms Laura Steeples, Mr Harry Petrushkin, Ms Dhanes Thomas, Mr Alan John Connor, Dr Una O'Colmain, Mr Anas Injarie, Mr Narman Puvanachandra, Ms Archana Pradeep, Ms Srilakshmi Sharma, Dr Conrad Schmoll, Dr Eoghan Millar, Mrs Kate Bush, Mr M Ashwin Reddy, Ms Jessy Choi, Ms Gisella Cooper, Ms Kristina May, Mr Ed Hughes, Ms Ailsa Ritchie

Affiliations

¹ Population, Policy and Practice Programme, UCL GOS Institute of Child Health, London, United Kingdom.
² National Institute for Health Research Biomedical Research Center at UCL Great Ormond Street Institute of Child Health and Great Ormond Street Hospital, London, United Kingdom.
³ Great Ormond Street Hospital for Children NHS Trust, London, United Kingdom.
⁴ Ulverscroft Vision Research Group, Institute of Child Health, University College London, London, United Kingdom.
⁵ National Institute for Health Research Biomedical Research Center at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom.
⁶ Bristol Eye Hospital, University Hospitals Bristol NHS Foundation Trust, Bristol, United Kingdom.
⁷ Translational Health Sciences, Faculty of Health Sciences, University of Bristol, Bristol, United Kingdom.
⁸ University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom.
⁹ Academic Unit of Ophthalmology, Institute of Inflammation & Aging, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom.

Abstract

Background: Childhood onset uveitis comprises a group of rare inflammatory disorders characterized by clinical heterogeneity, chronicity, and uncertainties around long term outcomes. Standardized, detailed datasets with harmonized clinical definitions and terminology are needed to enable the clinical research necessary to stratify disease phenotype and interrogate the putative determinants of health outcomes. We aimed to develop a core routine clinical collection dataset for clinicians managing children with uveitis, suitable for multicenter and national clinical and experimental research initiatives.

Methods: Development of the dataset was undertaken in three phases: phase 1, a rapid review of published datasets used in clinical research studies; phase 2, a scoping review of disease or drug registries, national cohort studies and core outcome sets; and phase 3, a survey of members of a multicenter clinical network of specialists. Phases 1 and 2 provided candidates for a long list of variables for the dataset. In Phase 3, members of the UK's national network of stakeholder clinicians who manage childhood uveitis (the Pediatric Ocular Inflammation Group) were invited to select from this long-list their essential items for the core clinical dataset, to identify any omissions, and to support or revise the clinical definitions. Variables which met a threshold of at least 95% agreement were selected for inclusion in the core clinical dataset.

Results: The reviews identified 42 relevant studies, and 9 disease or drug registries. In total, 138 discrete items were identified as candidates for the long-list. Of the 41 specialists invited to take part in the survey, 31 responded (response rate 78%). The survey resulted in inclusion of 89 data items within the final core dataset: 81 items to be collected at the first visit, and 64 items at follow up visits.

Discussion: We report development of a novel consensus core clinical dataset for the routine collection of clinical data for children diagnosed with non-infectious uveitis. The development of the dataset will provide a standardized approach to data capture able to support observational clinical studies embedded within routine clinical care and electronic patient record capture. It will be validated through a national prospective cohort study, the Uveitis in childhood prospective national cohort study (UNICORNS).

Keywords: child; consensus; data collection; dataset; electronic health record; uveitis.

Abstract

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