On the impact of different approaches to classify age-related macular degeneration: Results from the German AugUR study

Brandl, Caroline; Zimmermann, Martina E.; Günther, Felix; Barth, Teresa; Olden, Matthias; Schelter, Sabine C.; Kronenberg, Florian; Loss, Julika; Küchenhoff, Helmut ; Helbig, Horst; Weber, Bernhard H. F.; Stark, Klaus J. und Heid, Iris M. (2018): On the impact of different approaches to classify age-related macular degeneration: Results from the German AugUR study. In: Scientific Reports, Bd. 8, 8675

Abstract

While age-related macular degeneration (AMD) poses an important personal and public health burden, comparing epidemiological studies on AMD is hampered by differing approaches to classify AMD. In our AugUR study survey, recruiting residents from in/around Regensburg, Germany, aged 70+, we analyzed the AMD status derived from color fundus images applying two different classification systems. Based on 1,040 participants with gradable fundus images for at least one eye, we show that including individuals with only one gradable eye (n = 155) underestimates AMD prevalence and we provide a correction procedure. Bias-corrected and standardized to the Bavarian population, late AMD prevalence is 7.3% (95% confidence interval = [5.4;9.4]). We find substantially different prevalence estimates for "early/intermediate AMD" depending on the classification system: 45.3% (95%-CI = [41.8;48.7]) applying the Clinical Classification (early/intermediate AMD) or 17.1% (95%-CI = [14.6;19.7]) applying the Three Continent AMD Consortium Severity Scale (mild/moderate/severe early AMD). We thus provide a first effort to grade AMD in a complete study with different classification systems, a first approach for bias-correction from individuals with only one gradable eye, and the first AMD prevalence estimates from a German elderly population. Our results underscore substantial differences for early/intermediate AMD prevalence estimates between classification systems and an urgent need for harmonization.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Mathematik, Informatik und Statistik > Statistik
• Themengebiete: 500 Naturwissenschaften und Mathematik > 510 Mathematik
• ISSN: 2045-2322
• Sprache: Englisch