Identification of Multidimensional Phenotypes Using Cluster Analysis in Sarcoid Uveitis Patients

Fermon, Cécile; El-Jammal, Thomas; Kodjikian, Laurent; Burillon, C.; Hot, A.; Pérard, L.; Mathis, Thibaud; Jamilloux, Yvan; Sève, P.

doi:10.1016/j.ajo.2022.06.001

Cited by 5 publications

(3 citation statements)

References 29 publications

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“…More recently Fermon et al 47 defined three phenotypic clusters in those with sarcoid uveitis among 299 patients in France. Cluster 1 typically consists of younger individuals (median age 43.0 years) of mixed ethnicity presenting with acute uveitis and associated systemic manifestations.…”

Section: Sarcoid Uveitismentioning

confidence: 99%

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Insights into the diagnosis and management of sarcoid uveitis: A review

Samalia,

Lim,

Niederer

2024

Clinical Exper Ophthalmology

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Sarcoidosis is a leading cause of non‐infectious uveitis that commonly affects middle‐aged individuals and has a female preponderance. The disease demonstrates age, sex and ethnic differences in clinical manifestations. A diagnosis of sarcoidosis is made based on a compatible clinical presentation, supporting investigations and histologic evidence of non‐caseating granulomas, although biopsy is not always possible. Multimodal imaging with widefield fundus photography, optical coherence tomography and angiography can help in the diagnosis of sarcoid uveitis and in the monitoring of treatment response. Corticosteroid remains the mainstay of treatment; chronic inflammation requires steroid‐sparing immunosuppression. Features on multimodal imaging such as vascular leakage may provide prognostic indicators of outcome. Female gender, prolonged and severe uveitis, and posterior involving uveitis are associated with poorer visual outcomes.

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Section: Sarcoid Uveitismentioning

confidence: 99%

“…p = 0.009). Caucasian individuals were also less likely to present with granulomatous anterior uveitis (26.4% vs. 51.7%, p = 0.001) and associated cutaneous manifestations (23.1% vs. 35.4%, p = 0.040).More recently Fermon et al47 defined three phenotypic clusters in those with sarcoid uveitis among 299 patients in France. Cluster 1 typically consists of…”

mentioning

confidence: 99%

Insights into the diagnosis and management of sarcoid uveitis: A review

Samalia,

Lim,

Niederer

2024

Clinical Exper Ophthalmology

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“…Multidimensional phenotyping is a state-of-the-art, comprehensive approach aimed at improving our understanding of disease mechanisms, diagnostic decision-making, and patient stratification and has the potential to provide clinicians with optimized therapeutic intervention strategies [10] . Multidimensional phenotyping has already informed clinical treatments for ocular diseases, including amblyopia and uveitis [14][15] . However, to our knowledge, no multidimensional phenotypic cluster analysis of patients with congenital cataracts has been performed.…”

Section: Introductionmentioning

confidence: 99%

Classification of congenital cataracts based on multidimensional phenotypes and its association with visual outcomes

Tan,

Yu,

et al. 2024

Int J Ophthalmol

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AIM: To establish a classification for congenital cataracts that can facilitate individualized treatment and help identify individuals with a high likelihood of different visual outcomes. METHODS: Consecutive patients diagnosed with congenital cataracts and undergoing surgery between January 2005 and November 2021 were recruited. Data on visual outcomes and the phenotypic characteristics of ocular biometry and the anterior and posterior segments were extracted from the patients’ medical records. A hierarchical cluster analysis was performed. The main outcome measure was the identification of distinct clusters of eyes with congenital cataracts. RESULTS: A total of 164 children (299 eyes) were divided into two clusters based on their ocular features. Cluster 1 (96 eyes) had a shorter axial length (mean±SD, 19.44±1.68 mm), a low prevalence of macular abnormalities (1.04%), and no retinal abnormalities or posterior cataracts. Cluster 2 (203 eyes) had a greater axial length (mean±SD, 20.42±2.10 mm) and a higher prevalence of macular abnormalities (8.37%), retinal abnormalities (98.52%), and posterior cataracts (4.93%). Compared with the eyes in Cluster 2 (57.14%), those in Cluster 1 (71.88%) had a 2.2 times higher chance of good best-corrected visual acuity [<0.7 logMAR; OR (95%CI), 2.20 (1.25–3.81); P=0.006]. CONCLUSION: This retrospective study categorizes congenital cataracts into two distinct clusters, each associated with a different likelihood of visual outcomes. This innovative classification may enable the personalization and prioritization of early interventions for patients who may gain the greatest benefit, thereby making strides toward precision medicine in the field of congenital cataracts.

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