Discovery of factors influencing the growth of geographic atrophy in patients with age-related macular degeneration.

OBJECTIVES: Identifying factors influencing the growth of geographic atrophy (GA) in patients with age-related macular degeneration (AMD). METHODS: Data on the natural course and suspected modifying factors were collected as part of the multicenter, longitudinal, observational FAM-study in 178 eyes of 114 patients with atrophic AMD. The endpoint of interest - the size of GA - was measured in fundus autofluorescence images. The influence of different putative risk factors on progression of GA is investigated with a forward selection procedure based on the likelihood ratio test. In order to interpret non-significant results of the forward selection procedure, the power of the tests used was quantified by a parametric post-hoc bootstrap approach. RESULTS: A mean increase in GA of 1.75 mm(2) per year was estimated for the given population (95% CI: [1.46; 2.02]). Patient and eye-specific random effects could be assessed. Neither patient-specific risk factors nor ocular-specific risk factors show any significant influence on GA growth. The post-hoc bootstrap procedure shows that only very strong effects can be detected on the basis of the given data. For example, the hypercholesteremia which would result in an additional increase of GA by near 4 mm(2) per year can be detected with a power of 80%. CONCLUSIONS: The use of linear mixed effects regression models offers a convenient way to explore sources of variation in the natural course of GA. Data from further follow-up examinations and data about other putative risk factors than those investigated will be needed to further investigate of the GA growth process. The procedure described in this article is easily applicable to other putative risk factors as well as to other fields of application.

Modelling the natural history of geographic atrophy in patients with age-related macular degeneration.

PURPOSE: To model the natural course of geographic atrophy (GA) in patients with age-related macular degeneration (AMD). METHODS: Data on the natural course of GA were collected in the multi-center, longitudinal, prospective observational FAM study. The size of GA was measured by autofluorescence scanning laser ophthalmoscopy. The natural course of GA is modelled by two different mixed effect models (MEM). Both models are compared with respect to the correctness of the model assumptions, goodness of fit, and predictive behavior. RESULTS: The linear model results in better prediction, the non-linear model is more in agreement with the model assumptions. The non-linear model fits the data for small and large areas of GA better, while the linear model seems to be more adequate for the medial areas. More data will be needed to study the interplay of both models in more detail. CONCLUSIONS: The natural course of GA varies extremely between individuals. However, reliable factors for the explanation of this variability have so far not been established. MEM are useful for describing "inter-individual" as well as "intra-individual" influences without the need for precise knowledge of the influencing factors. Using MEM to evaluate data on the natural history of GA allows one to derive parameter estimates, which could be used to design interventional trials for modes of therapy with a potential to reduce or stop the progression of GA in patients with AMD.

Classification of abnormal fundus autofluorescence patterns in the junctional zone of geographic atrophy in patients with age related macular degeneration.

AIM: To describe and classify patterns of abnormal fundus autofluorescence (FAF) in the junctional zone of geographic atrophy (GA) in patients with age related macular degeneration. METHODS: Digital FAF images were recorded in 164 eyes of 107 patients using a confocal scanning laser ophthalmoscope (cSLO; excitation 488 nm, detection above 500 nm) as part of a prospective multicentre natural history study (FAM Study). FAF images were obtained in accordance with a standardised protocol for digital image acquisition and generation of mean images after automated alignment. RESULTS: Image quality was sufficient for classification of FAF patterns in 149 eyes (90.9%) with lens opacities being the most common reason for insufficient image quality. Abnormal FAF outside GA in 149 eyes was classified into four patterns: focal (12.1%), banded (12.8%), patchy (2.0%), and diffuse (57.0%), whereby 12.1% had normal background FAF in the junctional zone. In 4% there was no predominant pattern. The diffuse pattern was subdivided into four groups including reticular (4.7%), branching (27.5%), fine granular (18.1%), and fine granular with peripheral punctate spots (6.7%). CONCLUSIONS: Different phenotypic patterns of abnormal FAF in the junctional zone of GA can be identified with cSLO FAF imaging. These distinct patterns may reflect heterogeneity at a cellular and molecular level in contrast with a non-specific ageing process. A refined phenotypic classification may be helpful to identify prognostic determinants for the spread of atrophy and visual loss, for identification of genetic risk factors as well as for the design of future interventional trials.