Childhood uveitis, a group of inflammatory eye disorders characterized by overlapping clinical phenotypes, chronicity, and ongoing risk of visual morbidity, is a rare ‘disease' with an estimated incidence of up to 14 per 100,000 children (1–6). Between 10–25% of affected children reach adulthood having permanently lost some vision in at least one eye due to the complications which follow uncontrolled inflammation (1, 7, 8). Typically, disease activity continues into mid adulthood (9–11). The key to preventing uveitis-related blindness is prompt control of disease (1, 7, 8). Disease control is achieved using a combination of topical and systemic corticosteroids, systemic disease modifying immunomodulatory agents, and biologic therapies (12). There are several areas of uncertainty including etiology, disease subtype, disease burden (with studies reporting a 20-fold difference in incidence rates) (1–6), and uncertainties around the predictors of disease outcome (1–6). Several large but methodologically heterogenous studies have reached differing conclusions on the predictors of ocular outcome or therapeutic response, including conflicting findings on gender (13–15), the role of topical steroids (16, 17) and age at onset, analysis of which is typically confounded by disease duration and ANA status (8, 18–21). There is a need for research evidence to inform health policy and clinical practice, particularly for non-JIA associated disease, by identifying the predictors and mediators of disease risk, and of poor disease outcome.

Clinical research on rare disorders, such as childhood uveitis, faces the challenge typical to all rare disease research: reaching sufficiently large study sizes to allow robust statistical analysis. This challenge is usually addressed by undertaking multicenter studies, whose success relies not only on increased sample size, but also on standardized collection of the granular data necessary to interrogate variables of interest. We aimed to develop a core clinical dataset for specialists managing children with uveitis, to facilitate routine standardized data collection.

We undertook a three phase process to develop the core dataset. The phases comprised:

We report an expert consensus core clinical dataset for the routine collection of clinical data for children diagnosed with non-infectious uveitis, including data items on demographic details, mode of detection, ocular disease phenotype, ocular disease activity and severity, co-existent systemic disease, management, and laboratory and imaging findings. Although this has been anchored in clinical practice across centers throughout one particular country (UK), the standardization provided through the dataset may be helpful in supporting multicenter research collaboration not only at national, but potentially at international level. Many clinical variables on the ‘long-list' which were not included in the core dataset will still be collected by the majority of centers, supporting ongoing development of the dataset.

The core clinical dataset developed here was based on a three-phase approach which culminated in a single survey of clinician experts resulting in selection based on pre-defined inclusion threshold. This work was designed to serve as a baseline tool for further exploration and validation in a prospective study (Uveitis in Childhood National Prospective Cohort, UNICORN study) in which multistakeholder input will be gathered, and in which the tool could be revised as needed. Our approach to the development of this core clinical dataset is aligned to other work in this field (34–36). Our work represents a key step toward this future validated, multi-stakeholder consensus core dataset including providing the ‘long list', definitions and data structure. Consensus based clinical datasets are strengthened through regular review and updates, and this work has created the infrastructure necessary for that activity at a national level. Only one pediatric rheumatologist was involved at this stage, with resultant possible omission of key extra-ophthalmic variables, despite the review including pediatric rheumatology evidence. Future work will involve a broader panel of child health specialists. This study was strengthened by the support of a multicenter group of specialists who represented practice across the four member states of the United Kingdom (England, Scotland, Northern Ireland and Wales). The striking level of consensus across the network is reflective of the collaborative nature of the group, who have previously undertaken a Delphi exercise and surveys on childhood inflammatory eye disease (31, 37).

There are a number of interesting and potentially important omissions in our core clinical dataset, that future work is likely to address. First, the process did not identify and include any patient reported outcome measures (PROMs). Our work and that of others has highlighted the importance of a child-centered approach to clinical care, including the field of eye health, and the supporting power of PROMs. Childhood uveitis confers significant risk of psychosocial morbidity due to the impact of chronicity, visual impairment, treatment related adverse experiences, and the uncertainties of outcome and treatment choice inherent to these rare and complex diseases (38). It may be that a metric as simple as a single patient reported visual analog score may be sufficient to reliably and repeatably capture a child's or family's perceptions of disease state. However, internationally, there is a paucity of appropriate validated tools for use as PROMs in childhood uveitis (39). Quality of life metrics are particularly important in uveitis, with the burden conferred by the use of multiple systemic therapies. A recently validated tool for use in North American populations (the EYE-Q) has been shown to reliably, repeatably and responsively capture patient centered outcomes (quality of life) in childhood uveitis (40, 41), but this tool has not yet been translated for a British setting or validated for use in British populations. Such work (validation of the translation) as well as the increasing routine capture of patient reported outcomes in clinical practice will lead to an update in the clinical dataset presented here.

Objective metrics of anterior chamber inflammation are absent from this dataset. Anterior uveitis is the most common form of disease in childhood (6, 42), and currently, the only validated objective metric of disease state for anterior uveitis is laser flare photometry (LFP) (43). Our findings of low adoption of LFP across the UK is consistent with other evidence of poor uptake of the technology internationally (44). Anterior segment optical coherence tomography (AS-OCT) scanning may, in future, provide validated objective metrics of disease activity (45, 46), with AS-OCT being another potential addition in an updated dataset.

In recognition of the need to provide a “standardized language” for clinical care, outcome analysis, clinical audit and research (30), the UK's Royal College of Ophthalmologists has developed a recommended minimum mandatory dataset for clinical data collection in the management of uveitis (30). This mandatory dataset covers the definition of the type of uveitis (according to anatomical classification, onset, course and etiology), the severity of disease, the major therapeutic interventions and current disease status including logMAR acuity. Whilst the work presented here was informed by that dataset, there was a clear consensus about the need to build on this dataset in order to generate more detailed data, and to make it suitable for pediatric practice. For example, the categorization of disease as recurrent and chronic, or as sudden versus insidious, may not be possible for many children with asymptomatic anterior uveitis. Measures of function such as visual field testing and Snellen acuity may not be appropriate for younger children because of their inability to comply with such tests. There was also a consensus amongst survey responders on the need for standardized documentation of non-ophthalmic features, which have not yet been adopted in the RCOphth uveitis dataset.

Although our core clinical dataset is not designed as an outcome set, it is useful to review the items selected for inclusion within our dataset in the context of any published or proposed core outcome sets relevant to the field of childhood uveitis. One such outcome set undergoing development is the JIA associated uveitis outcome measure set from the Multinational Interdisciplinary Working Group for Uveitis in Childhood (MIWGUC) (23). Outside of the use of PROMS, there is strong alignment with the core clinical dataset presented here, which can be used to populate an outcome set such as that proposed by MIWGUC, and can support the interrogation of which factors determine these clinically important outcomes.

The wider adoption of a variety of electronic patient record systems across different health care settings brings opportunities to standardize the ‘real world' data being collected across these systems. A standardized language will underpin the development and optimization of electronic patient records, and supports ‘FAIR' (Findable, Accessible, Interoperable Reusable) clinical data. Future validation of this consensus-based clinical dataset and the harmonization of multi-center data collection will be provided by the currently underway UNICORN study, a national prospective inception cohort of children (aged <18yrs) newly diagnosed with non-infectious uveitis, with clinical, sociodemographic and patient reported data collection, enabling investigation of possible disease determinants, and the interrogation of patient centered outcomes. The work presented here should support the creation of research-ready datasets from routinely collected data, for use in the UNICORN study but also for use in future studies of clinical care, natural history, and outcomes.

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.

Ms Ameenat Lola Solebo, NIHR Clinician Scientist and Consultant Ophthalmologist, UCL GOS Institute of Child Health, London, UK; Ms Salomey Kellett, Researcher, UCL GOS Institute of Child Health, London, UK; Professor Andrew D Dick, Professor of Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Professor Jugnoo Rahi, Professor of Ophthalmic Epidemiology, UCL GOS Institute of Child Health, London, UK; Professor Alastair Denniston, Professor of Ocular Inflammation, University of Birmingham, UK; Mr Damien C.M.Yeo, Consultant Ophthalmologist, Alder Hey Children's NHS Foundation Trust, Liverpool; Mr Jose Gonzalez-Martin, Consultant Ophthalmologist, Alder Hey Children's NHS Foundation Trust, Liverpool; Ms Eibhlin McLoone, Consultant Ophthalmologist, Belfast Royal Victoria Hospital NHS Foundation Trust; Prof Rachel Pilling, Consultant Ophthalmologist, School of Optometry and Vision Science, University of Bradford; Mr John Bradbury, Consultant Ophthalmologist, Bradford Teaching Hospitals NHS Foundation Trust, Bradford Royal Infirmary; Prof Athimalaipet V Ramanan, Consultant Pediatric Rheumatologist, University Hospitals Bristol NHS Foundation Trust; Ms Catherine Guly, Consultant Ophthalmologist, University Hospitals Bristol NHS Foundation Trust; Ms Brinda Muthusamy, Consultant Ophthalmologist, Cambridge University Hospital NHS Foundation Trust; Mr Patrick Watts, Consultant Ophthalmologist, Cardiff and Vale University Health Board Hospitals; Ms Christine Twomey, Clinical Nurse Specialist, Great Ormond Street Hospital NHS Foundation Trust; Ms Reshma Pattani, Specialist Optometrist, Great Ormond Street Hospital NHS Foundation Trust; Mr Clive Edelsten, Consultant Ophthalmologist, Great Ormond Street Hospital NHS Foundation Trust; Mr Daniel Pharoah, Consultant Ophthalmologist, James Paget University Hospitals NHS Foundation Trust; Mr Vernon Long, Leeds Teaching Hospitals NHS Trust, St. James's University Hospital; Mr Adam Bates, Consultant Ophthalmologist, Maidstone and Tunbridge Wells NHS Trust; Ms Elisabetta Scoppettuolo, Consultant Ophthalmologist, Maidstone and Tunbridge Wells NHS Trust; Prof Jane Ashworth, Consultant Ophthalmologist, Manchester University NHS Foundation Trust; Ms Laura Steeples, Consultant Ophthalmologist, Manchester University NHS Foundation Trust; Mr Harry Petrushkin, Consultant Ophthalmologist, Moorfields Eye Hospital NHS Foundation Trust and Great Ormond Street Hospital NHS Foundation Trust; Ms Dhanes Thomas, Consultant Ophthalmologist, Moorfields Eye Hospital NHS Foundation Trust; Mr Alan John Connor, Consultant Ophthalmologist, Newcastle Upon Tyne Hospitals NHS Foundation Trust; Dr Una O'Colmain, Consultant Ophthalmologist, Ninewells Hospital, Tayside Scotland NHS Board; Mr Anas Injarie, Consultant Ophthalmologist, Norfolk and Norwich University Hospitals NHS Foundation Trust; Mr Narman Puvanachandra, Consultant Ophthalmologist, Norfolk and Norwich University Hospitals NHS Foundation Trust; Ms Archana Pradeep, Consultant Ophthalmologist, Nottingham University Hospitals NHS Trust; Ms Srilakshmi Sharma, Consultant Ophthalmologist, Oxford University Hospitals NHS Foundation Trust; Dr Conrad Schmoll, Consultant Ophthalmologist, Princess Alexandra Eye Pavilion / Royal Hospital for Children and Young People, Edinburgh, Lothian NHS Board; Dr Eoghan Millar, Consultant Ophthalmologist, Royal Children's Hospital, NHS Greater Glasgow and Clyde; Mrs Kate Bush, Consultant Ophthalmologist, Royal Bournemouth Christchurch Hospitals NHS Foundation Trust; Mr M. Ashwin Reddy, Consultant Ophthalmologist, Royal London Hospital, Barts Health NHS Trust; Ms Jessy Choi, Consultant Ophthalmologist, Sheffield Children's Hospitals NHS Foundation Trust, and Sheffield Teaching Hospitals NHS Foundation Trust; Ms Gisella Cooper, Clinical Nurse Specialist, Sheffield Children's Hospitals NHS Foundation Trust, and Sheffield Teaching Hospitals NHS Foundation Trust; Ms Kristina May, Consultant Ophthalmologist, University Hospital Southampton NHS Foundation Trust, Southampton General Hospital; Mr Ed Hughes, Consultant Ophthalmologist, Sussex Eye Hospital, University Hospitals Sussex NHS Foundation Trust; Ms Ailsa Ritchie, Consultant Ophthalmologist, St Thomas' Hospital, Guys and St Thomas' NHS Trust

AS conceptualized, designed the study, and drafted the manuscript. AS, JR, ADD, AD, RP, and CE contributed to study design. AS and SK undertook analyses. All authors contributed to data collection. All authors critically reviewed the manuscript. All authors contributed to the article and approved the submitted version.

AS and SK are supported by an NIHR Clinician Scientist award CS-2018-18-ST2-005). This work is part supported by a Wellcome Grant 204841/Z/16/Z. JR is supported in part by the NIHR BRC based at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, and an NIHR Senior Investigator award. This work was undertaken at UCL Institute of Child Health/Great Ormond Street Hospital for children which received a proportion of funding from the Department of Health's NIHR Biomedical Research Centers funding scheme.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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