Logistic Regression Classification of Primary Vitreoretinal Lymphoma vs. Uveitis by IL-6 and IL-10 Levels

Abstract

ABSTRACT Objective In this study, we assess the diagnostic performance and generalizability of logistic regression in classifying primary vitreoretinal lymphoma (PVRL) vs. uveitis from intraocular cytokine levels in a single-center retrospective cohort, comparing a logistic regression model and the previously published ISOLD score against the IL-10/IL-6 ratio. Design Retrospective cohort study Participants Patient histories, pathology reports, and intraocular cytokine levels from 2339 patient entries in the NEI Histopathology Core database Methods Patient diagnoses of PVRL vs. uveitis and associated aqueous or vitreous IL-6 and IL-10 levels were retrospectively collected. From this data, cytokine levels were compared between diagnoses with the Mann-Whitney U test. A logistic regression model was trained to classify PVRL vs. uveitis from aqueous and vitreous IL-6 and IL-10 and compared with the ISOLD score and IL-10/IL-6 ratio. Main Outcome Measures Area under the curve (AUC) for each classifier; sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) at the optimal cut-off (maximal Youden index) for each classifier Results 77 lymphoma patients (10 aqueous, 67 vitreous) and 84 uveitis patients (19 aqueous, 65 vitreous) between 10/5/1999 and 9/16/2015 were included in the study. IL-6 was higher and IL-10 was lower in uveitis patients compared to lymphoma patients (p Conclusion The accuracy of the logistic regression model and generalizability of the ISOLD score to an independent patient cohort suggest that intraocular cytokine analysis by logistic regression may be a promising adjunct to cytopathology, the gold standard, for the early diagnosis of primary vitreoretinal lymphoma. Further validation studies are merited.