Classification criteria for acute posterior multifocal placoid pigment epitheliopathy

The Standardization Of Uveitis Nomenclature Sun Working Group, Douglas A Jabs, Antoine P Brezin, Andrew D Dick, Ralph D Levinson, Lyndell L Lim, Peter McCluskey, Neal Oden, Alan G Palestine, Jennifer E Thorne, Brett E Trusko, Albert Vitale, Susan E Wittenberg

Research output: Contribution to journalArticle (Academic Journal)peer-review

14 Citations (Scopus)


PURPOSE: To determine classification criteria for acute posterior multifocal placoid pigment epitheliopathy (APMPPE).

DESIGN: Machine learning of cases with APMPPE and 8 other posterior uveitides.

METHODS: Cases of posterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the infectious posterior/panuveitides. The resulting criteria were evaluated on the validation set.

RESULTS: One thousand sixty-eight cases of posterior uveitides, including 82 cases of APMPPE, were evaluated by machine learning. Key criteria for APMPPE included: 1) choroidal lesions with a plaque-like or placoid appearance and 2) characteristic imaging on fluorescein angiography (lesions "block early and stain late diffusely"). Overall accuracy for posterior uveitides was 92.7% in the training set and 98.0% (95% confidence interval 94.3, 99.3) in the validation set. The misclassification rates for APMPPE were 5% in the training set and 0% in the validation set.

CONCLUSIONS: The criteria for APMPPE had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

Original languageEnglish
Pages (from-to)174-181
Number of pages8
JournalAmerican Journal of Ophthalmology
Early online date9 Apr 2021
Publication statusPublished - Aug 2021

Bibliographical note

Funding Information:
Supported by grant R01 EY026593 from the National Eye Institute, National Institutes of Health, Bethesda, Maryland, USA; the David Brown Fund, New York, New York, USA; the Jillian M. and Lawrence A. Neubauer Foundation, New York, New York, USA; and the New York Eye and Ear Foundation, New York, New York, USA.

Publisher Copyright:
© 2021 Elsevier Inc.


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