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. 2021 Aug:228:220-230.
doi: 10.1016/j.ajo.2021.03.047. Epub 2021 May 11.

Classification Criteria for Sarcoidosis-Associated Uveitis

Standardization of Uveitis Nomenclature (SUN) Working Group
Collaborators

Classification Criteria for Sarcoidosis-Associated Uveitis

Standardization of Uveitis Nomenclature (SUN) Working Group. Am J Ophthalmol. 2021 Aug.

Abstract

Purpose: The purpose of this study was to determine classification criteria for sarcoidosis-associated uveitis.

Design: Machine learning of cases with sarcoid uveitis and 15 other uveitides.

Methods: Cases of anterior, intermediate, and panuveitides were collected in an informatics-designed preliminary database, and a final database was constructed including cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were analyzed by anatomic class, and each class was split into a training set and a validation set. Machine learning using multinomial logistic regression was used in the training sets to determine a parsimonious set of criteria that minimized the misclassification rate among the uveitides. The resulting criteria were evaluated in the validation sets.

Results: A total of 1,083 cases of anterior uveitides, 589 cases of intermediate uveitides, and 1,012 cases of panuveitides, including 278 cases of sarcoidosis-associated uveitis, were evaluated by machine learning. Key criteria for sarcoidosis-associated uveitis included a compatible uveitic syndrome of any anatomic class and evidence of sarcoidosis, either 1) tissue biopsy results demonstrating non-caseating granulomata or 2) bilateral hilar adenopathy on chest imaging. The overall accuracy of the diagnosis of sarcoidosis-associated uveitis in the validation set was 99.7% (95% confidence interval: 98.8-99.9). The misclassification rates for sarcoidosis-associated uveitis in the training sets were 3.2% in anterior uveitis, 2.6% in intermediate uveitis, and 1.2% in panuveitis; in the validation sets, the misclassification rates were 0% in anterior uveitis, 0% in intermediate uveitis, and 0% in panuveitis.

Conclusions: The criteria for sarcoidosis-associated uveitis had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

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Conflict of interest statement

Conflict of Interest: Douglas A. Jabs: none; Nisha A. Acharya: none; Alastair K. Denniston; none; Susan L. Lightman: none; Peter McCluskey: none; Neal Oden: none; Annabelle A. Okada: consultant: AbbVie Japan, Astellas Pharma Japan, Bayer AG, Daiichi Sankyo; lecture fees: Alcon Pharma Japan, Mitsubishi Tanabe Pharma, Novartis Pharma Japan, Santen Pharmaceutical Corporation, Senju Pharmaceutical Corporation; grant support from Alcon Pharma Japan, Bayer Yakuhin, Mitsubishi Tanabe Pharma; Alan G. Palestine: none; Jennifer E. Thorne: Dr. Thorne engaged in a part of this research as a consultant and was compensated for the consulting service; Brett E. Trusko: none; Albert Vitale: none.

Figures

Figure 1.
Figure 1.
Sarcoidosis-associated anterior uveitis with mutton-fat keratic precipitates.
Figure 2.
Figure 2.
Sarcoidosis-associated uveitis with vitritis.
Figure 3.
Figure 3.
Sarcoidosis-associated uveitis with a focal choroidal nodule.
Figure 4.
Figure 4.
Sarcoidosis-associated uveitis with multifocal choroiditis.
Figure 5.
Figure 5.
Sarcoidosis-associated uveitis with retinal vascular sheathing.
See this image and copyright information in PMC

References

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