ArticleBMJ open2021
Novel observational study protocol to develop a prediction model that identifies patients with Graves' ophthalmopathy insensitive to intravenous glucocorticoids pulse therapy.
Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 13 citations in OpenAlex.
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- Oculoplastics and Augmented Intelligence: A Literature Review.Journal of clinical medicine · 2025Article
- AI-based assessment of Clinical Activity Score and detection of active thyroid eye disease using facial images: validation of Glandy CAS.BMJ open ophthalmology · 2025Article
- Multimodal MRI radiomics-clinical fusion model predicts intravenous glucocorticoid response in thyroid eye disease.Frontiers in endocrinology · 2025Article
- Advances in artificial intelligence in thyroid-associated ophthalmopathy.Frontiers in endocrinology · 2024Review
- Clinical outcomes and antibody transfer in a cohort of infants with in utero or perinatal exposure to SARS-CoV-2 (Coronascope Study).European journal of pediatrics · 2023Article
- Predictive markers for anti-inflammatory treatment response in thyroid eye disease.Frontiers in endocrinology · 2023Review
- Research progress and application of artificial intelligence in thyroid associated ophthalmopathy.Frontiers in cell and developmental biology · 2023Review
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Authors and funding
7 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
introductionIntravenous glucocorticoids pulse therapy is the first-line treatment for moderate-to-severe and active Graves' ophthalmopathy, with a large proportion of patients having poor efficacy and exposed to the risk of glucocorticoids adverse effects. We introduce a novel protocol to develop a prediction model designed to identify patients with Graves' ophthalmopathy who are not likely to benefit from intravenous glucocorticoids pulse therapy before administration, so that these patients can advance the time to receive appropriate treatment. Existing prediction models for prognosis of Graves' ophthalmopathy have usually focused on traditional clinical indicators without adequate consideration of orbital soft tissue changes. Our protocol for model development will address this limitation by using artificial intelligence models to quantify facial morphological changes. METHODS AND ANALYSIS: This study is a single-centre, prospective and observational study. A sample size of 278 patients with moderate-to-severe and active Graves' ophthalmopathy will be prospectively recruited at ophthalmology clinic of Shanghai Ninth People's Hospital to collect clinical and artificial intelligence model's baseline data as potential variables to develop the prediction model. They will receive 12-week intravenous glucocorticoids pulse therapy according to the 2021 European Group on Graves' Orbitopathy treatment guideline. After standard medication course and following 12-week observation, patients will be evaluated for the effectiveness of treatment in our ophthalmology clinic and divided into glucocorticoids-sensitive and glucocorticoids-insensitive groups. The model will be developed by means of multivariate logistic regression to select the best variables for the prediction of glucocorticoids treatment efficacy before administration. The result of the study will provide evidence for the use of a prediction model to personalise treatment options for patients with moderate-to-severe and active Graves' ophthalmopathy. ETHICS AND DISSEMINATION: The study received approval from the Ethics Committee of Shanghai Ninth People's Hospital (ethical approval number: SH9H-2020-T211-1. Findings will be disseminated via peer-reviewed publications and conference presentations. TRIAL REGISTRATION NUMBER: ChiCTR2000036584 (Pre-results).
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