Differentiating Multifocal Choroiditis and Punctate Inner Choroidopathy: A Cluster Analysis Approach

Abstract Purpose To develop a robust approach to clinical phenotyping of multifocal choroiditis (MFC) and punctate inner choroidopathy (PIC). Design Cross-sectional and longitudinal observational study. Methods . Setting Multicenter: UK and Israel Population A clinical database of 343 eyes of 185 subjects with hospital record diagnoses of MFC or PIC. Observation Procedure Eyes were observed over a period of 5 years for clinically relevant characteristics, including demographics and multi-modal imaging features, by observers masked to original diagnoses. Multivariate two-step cluster analysis was used to identify clusters of eyes in the database with similar clinical phenotypes, which were then analysed for between-group differences. Main Outcome Measure Differences between clinical phenotype clusters identified using clinical criteria from the multivariate cluster analysis. Results The subject age range was 11 to 89 years with a baseline best corrected visual acuity of 2.3 to -0.2 (LogMAR). Eighty-two percent of eyes were from females, 74% were myopic with a refractive error of +3.00 to -17.00D (spherical equivalent). Cluster analysis prioritised clinical criteria of chorio-retinal lesion location and intraocular inflammation and identified two distinct phenotype clusters resembling the original descriptions of MFC and PIC. During the 5-year period of observation the initial clinical diagnosis remained stable for the vast majority of eyes and only one eye (0.3%) changed diagnosis from PIC to MFC due to newly developed peripheral lesions. There were significant between-group differences in clinical characteristics, for example, in CNV development and treatment received. Conclusions Cluster analysis of this large cohort of eyes identified peripheral lesions and intra-ocular inflammation as distinct clinical phenotypes of MFC and PIC. The initial diagnosis remained stable for the vast majority of eyes. This methodology could be useful for future uveitis classification and management.