Management of Paediatric Coats disease: A Systematic Review
Creators: name: Taylor, Michael
name: Schwartz, Roy
name: Amjad, Muhammad
name: Wong, Sui Chien
Publisher: name: Open Science Framework
Year: 2022
Subjects: subject: Medicine and Health Sciences
subject: Medical Specialties
subject: Ophthalmology
subject: Coats Disease

description: Sponsor: No sponsor Authors and affiliations: 1. Michael Taylor: University of Nottingham, Nottingham, United Kingdom 2. Roy Schwartz: Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom; Institute of Health Informatics, University College London, London, United Kingdom 3. Muhammad Amjad: Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom 4. Sui Chien Wong: Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom; Royal Free Hospital NHS Foundation Trust, London, United Kingdom; Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom Information provided by: Michael Taylor Study type: Systematic review (mixed methods: qualitative synthesis plus pooled analysis of binary outcome denoting whether visual acuity improved following treatment) Official title: Management of Paediatric Coats disease: A Systematic Review and Meta-Analysis of Case Series Brief summary of study: Coats Disease is a progressive condition affecting the retinal vasculature that usually presents unilaterally in males in early childhood. The disease causes telangiectasias and exudates and can lead to reduced visual acuity and, in later stages, retinal detachment. Treatment has traditionally involved ablation and surgery, and more recently, intra ocular antiVEGF agents and steroids have been used. We are doing a literature review of studies describing treatments of paediatric Stage 1-3b Coats disease to explore potential for newer treatments potentially leading to improved visual acuity outcomes. What has been done so far: At the time of writing (04/02/21), database searches have been carried out as described in the Methodology section to retrieve studies published until May 2020. Two authors have independently checked the list of retrieved studies to ensure that all have been appropriately included or excluded according to the inclusion and exclusion criteria as listed below. Additionally, and one author has coded the data from retrieved studies, has assessed quality of retrieved studies using the JBI assessment tool for case series, and has carried out preliminary pooled analyses and narrative synthesis as described in the analytic strategy section. A second author is in the process of independently extracting data and assessing quality from these studies. What there is yet to do: A final search (of articles published since May 2020) and final analysis of all included studies is yet to be done. At least two authors will check the results of this search to ensure all papers fitting inclusion criteria are included. At least two authors will also independently assess quality of the papers using the JBI tool and extract data from papers retrieved in this final search. After independent coding of extracted data and independent coding of quality of included studies is complete, authors will discuss their independent coding of the data and of quality and disagreements will be resolved by consensus. After the final search and the final decision on coding and which studies to include, analysis will be conducted as described in the analytic strategy section. Methodology Search Strategy: Searching Medline and EMBASE databases using “Coat’s Disease”, “Coats’ Disease”, and “Coats Disease” (no year of publication restrictions) Study inclusion criteria: published in a peer-reviewed journal; describes observational or interventional trials focussing Coats disease treatment; includes more than three paediatric participants with up to Stage 3b disease, for whom study findings could be distinguished from other patients described. Exclusion criteria: Articles written in a language other than English; case reports, letters, conference abstracts, commentaries, review articles, studies where it was not possibly to differentiate results from paediatric patients with up to Stage 3b Coats disease from those of other patients. Data collection: The following will be collected from included studies: study year, study country, study design, outcomes of the study, treatment methods used, best corrected visual acuity (BCVA) pre- and post-treatment, follow-up time, age of patients, and gender of patients. The BCVA measures will be used to calculate the primary outcome (whether visual acuity improved after treatment). Quality assessment: The Joanna Biggs Institute checklist for case series will be used to assess quality of included studies (https://joannabriggs.org/sites/default/files/2020-08/Checklist_for_Case_Series.pdf) Analytic strategy: 1) A narrative review of descriptions of Coats Disease treatments described in all studies retrieved that fit the eligibility criteria. 2) A pooled analysis of the proportion of times patients who were given different classes of treatments (antiVEGF, steroids, or treatment that did not involve either of these) experienced improved visual acuity at the final follow-up compared to the first documented measurement. As most of the studies in this field are case series, standard meta-analysis techniques for assessment of randomised trials are not appropriate here. A random effects model will be used to assess proportions of visual acuity improvement according to stage of disease (1, 2a, 2b, 3a, or 3b) and to treatment category. The Freeman-Tukey double arcsine transformation(2) will be used to stabilise the variance in the proportions before study results are pooled. The statistical software used for the meta-analysis will be Stata(1), and specifically, the ‘Metaprop’(3) command will be used References 1) StataCorp. Stata Statistical Software: Release 16. TX: StataCorp LLC: College Station; 2019. 2) Lin L, Xu C. Arcsine-based transformations for meta-analysis of proportions: Pros, cons, and alternatives. Heal Sci Reports. 2020;3(3):e178. 3) Nyaga VN, Arbyn M, Aerts M. Metaprop: a Stata command to perform meta-analysis of binomial data. Arch Public Heal. 2014;72(1):39.