Identifying Biomarkers for Papilledema and Pseudopapilledema

Abstract

Purpose : The diagnosis of papilledema, a medical emergency, often requires invasive testing to distinguish it from pseudopapilledema, a group of benign conditions. There is an unmet need for a rapid and non-invasive test to differentiate papilledema from pseudopapilledema, which to date, has not been assessed with a comprehensive set of optical coherence tomography (OCT) biomarkers. Moreover, previous studies have used control populations with no optic nerve head abnormalities, limiting their applicability to real-world clinical practice. We performed a case (papilledema)-control (pseudopapilledema) study to evaluate the diagnostic accuracy of a set of OCT biomarkers to determine if OCT can effectively differentiate papilledema from pseudopapilledema in a clinical setting.

Methods : To identify biomarkers, a systematic literature review was conducted. From a total of 17,575 patients who attended eye casualty or neuro-ophthalmology clinics at a hospital in the UK over the course of 12 months, we included patients with a confirmed diagnosis (n=211) of papilledema, optic disc drusen (ODD), crowded optic discs (COD), or tilted optic discs (TOD) and had volume and circular OCT scans performed on both eyes. Quantitative and qualitative biomarkers were analyzed on OCT scans. Receiver operating characteristic curves were plotted and areas under the curve (AUC) were calculated for qualitative biomarkers. Logistic regression models were developed for qualitative biomarkers and sensitivity and specificity for the detection of papilledema were calculated.

Results : The logistic regression model using qualitative biomarkers to differentiate papilledema from ODD and COD showed a sensitivity and specificity of 89%. Inclusion of TOD in the pseudopapilledema group showed a sensitivity of 66% and a specificity of 93% for detecting papilledema. AUCs for quantitative biomarkers ranged from 0.51 (95% CI=0.42-0.60) to 0.75 (95% CI=0.68-082). In a separate model differentiating papilledema from TOD, AUCs for quantitative biomarkers ranged from 0.53 (95% CI=0.42-0.63) to 0.83 (95% CI=0.76-0.90).

Conclusions : We identified a model with high sensitivity and specificity to differentiate papilledema from ODD and COD using qualitative biomarkers. In a separate model differentiating papilledema from TOD, quantitative biomarkers displayed high AUCs. These results show that OCT demonstrates promising diagnostic utility in differentiating papilledema from pseudopapilledema.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.