ArticleJournal of ophthalmic inflammation and infection2025
Common data elements for observational studies in ocular toxoplasmosis: a Delphi consensus.
Article in Journal of ophthalmic inflammation and infection, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeOcular toxoplasmosis (OT) is the most common cause of posterior uveitis globally, with a significant risk of visual impairment. However, the lack of standardized data collection hinders meaningful comparisons across studies. This study aimed to develop a consensus-based set of Common Data Elements (CDEs) for observational studies in OT using a Delphi approach.
designA set of CDEs was developed through a combination of a comprehensive literature review, a hybrid workshop, and a Delphi consensus process. This effort was led by an international panel of experts in OT to define a standardized CDE set for research and clinical purposes.
methodsA multidisciplinary steering committee identified an initial list of candidate CDEs through a targeted literature review. A panel of 30 international experts participated in a structured, one-round Delphi process to evaluate and refine these CDEs. Consensus was determined based on predefined thresholds for inclusion, exclusion, and modification.
resultsA total of 139 CDEs were categorized across nine domains: Demographic and Background Information, Medical and Ocular History, Clinical Presentation, Clinical Findings, Lesion Characteristics, Diagnostics, Imaging Findings, Treatment and Interventions, and Outcomes. All 139 CDEs met the inclusion criteria, with 79.8% rated as "very important". The consensus underscores the importance of a comprehensive, standardized dataset for OT research.
conclusionsThis study establishes the first expert-derived standardized dataset requested for reporting OT outcomes, providing a framework to standardize data collection for future observational studies. Adopting these CDEs will enhance data comparability, improve meta-analyses, and strengthen the evidence base for clinical decision-making in OT. Future work will focus on real-world validation and refinement of this dataset.
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