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Assessing intergrader variability in incomplete outer retinal atrophy (iRORA) grading.

Lorenzo Ferro Desideri¹, Davide Scandella², Rodrigo Anguita³

¹Department of Ophthalmology, Inselspital, Bern University Hospital, and University of Bern, Bern, Switzerland lorenzo.ferrodesideri@insel.ch.

The British Journal of Ophthalmology

|May 14, 2026

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This summary is machine-generated.

Intergrader agreement for detecting incomplete outer retinal atrophy (iRORA) in age-related macular degeneration (AMD) using optical coherence tomography (OCT) was limited. Improving iRORA detection reliability is crucial for clinical trials and practice.

Area of Science:

Ophthalmology
Medical Imaging
Biomarker Research

Background:

Incomplete outer retinal atrophy (iRORA) is a key biomarker for early age-related macular degeneration (AMD).
Accurate detection of iRORA is vital for monitoring disease progression and evaluating treatments.
Current grading criteria present challenges for consistent intergrader assessment.

Purpose of the Study:

To evaluate the intergrader variability in detecting iRORA using optical coherence tomography (OCT) scans.
To assess the reliability of iRORA as a biomarker and potential clinical trial endpoint.

Main Methods:

A cross-sectional study involving five international retinal experts grading 60 OCT B-scans for iRORA.
Utilized the Classification of Atrophy Meeting (CAM) criteria and a standardized online annotation platform.

Keywords:

Age-Related Macular Degeneration

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Assessed intergrader agreement using Cohen's Kappa and analyzed classification accuracy, sensitivity, and specificity.

Main Results:

Mean pairwise Cohen's Kappa was 0.425, indicating mild agreement among graders.
Agreement with the majority vote ranged from κ=0.48 to 0.67, with classification accuracy between 0.73 and 0.83.
High specificity (0.85-0.96) was observed, but sensitivity varied (0.59-0.83).

Conclusions:

Intergrader reproducibility for iRORA detection remains limited despite standardized CAM definitions.
Challenges exist in consistently identifying early atrophic changes in AMD.
Refining grading guidelines and incorporating automated detection systems are recommended to enhance reliability.