Development and Application of the Ocular Immune-mediated Inflammatory Diseases Ontology Enhanced with Synonyms from Online Patient Support Forum Conversation

Overview

Journal Comput Biol Med

Publisher Elsevier

Specialties Biology
General Medicine
Medical Informatics

Date 2021 Jun 17

PMID 34139439

Citations 1

Authors

Samantha C Pendleton

Karin Slater

Andreas Karwath

Rose M Gilbert

Nicola Davis

Konrad Pesudovs

Xiaoxuan Liu

Alastair K Denniston

Georgios V Gkoutos

Tasanee Braithwaite

Affiliations

Soon will be listed here.

Abstract

Background: Unstructured text created by patients represents a rich, but relatively inaccessible resource for advancing patient-centred care. This study aimed to develop an ontology for ocular immune-mediated inflammatory diseases (OcIMIDo), as a tool to facilitate data extraction and analysis, illustrating its application to online patient support forum data.

Methods: We developed OcIMIDo using clinical guidelines, domain expertise, and cross-references to classes from other biomedical ontologies. We developed an approach to add patient-preferred synonyms text-mined from oliviasvision.org online forum, using statistical ranking. We validated the approach with split-sampling and comparison to manual extraction. Using OcIMIDo, we then explored the frequency of OcIMIDo classes and synonyms, and their potential association with natural language sentiment expressed in each online forum post.

Findings: OcIMIDo (version 1.2) includes 661 classes, describing anatomy, clinical phenotype, disease activity status, complications, investigations, interventions and functional impacts. It contains 1661 relationships and axioms, 2851 annotations, including 1131 database cross-references, and 187 patient-preferred synonyms. To illustrate OcIMIDo's potential applications, we explored 9031 forum posts, revealing frequent mention of different clinical phenotypes, treatments, and complications. Language sentiment analysis of each post was generally positive (median 0.12, IQR 0.01-0.24). In multivariable logistic regression, the odds of a post expressing negative sentiment were significantly associated with first posts as compared to replies (OR 3.3, 95% CI 2.8 to 3.9, p < 0.001).

Conclusion: We report the development and validation of a new ontology for inflammatory eye diseases, which includes patient-preferred synonyms, and can be used to explore unstructured patient or physician-reported text data, with many potential applications.

Citing Articles

Talking about diseases; developing a model of patient and public-prioritised disease phenotypes.

Slater K, Schofield P, Wright J, Clift P, Irani A, Bradlow W NPJ Digit Med. 2024; 7(1):263.

PMID: 39349692 PMC: 11443070. DOI: 10.1038/s41746-024-01257-8.

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