Reappraisal of geographic atrophy patterns seen on fundus autofluorescence using a latent class analysis approach

Invest Ophthalmol Vis Sci. 2014 Nov 18;55(12):8302-8. doi: 10.1167/iovs.13-13542.


Purpose: To reappraise fundus autofluorescence (FAF) patterns in patients with geographic atrophy (GA) with the aim of simplifying the existing classification and to evaluate their stability with time using a data-driven approach, latent class analysis (LCA).

Methods: One hundred seventy-one patients in the prospective, natural history study on GA (GAIN, NCT01694095) with a minimum follow-up of 12 months were screened. Five experienced observers independently evaluated FAF patterns according to the original classification, and LCA was used to determine the new, emerging categories (classes). A set of prespecified FAF features was then used to characterize each resulting class.

Results: Seventy-five eyes of 59 subjects with a median follow-up of 19 months were included. The optimal LCA model resulted in five classes, which showed an association with GA size, among others. The classes did not change in a given individual during the study period, but the time frame may have been too short to evaluate hypothetical transitions.

Conclusions: The original description of FAF patterns, which is based exclusively on distribution of hyperautofluorescence around GA, ultimately classifies patients according to area of atrophy. These results suggest that FAF patterns are not true phenotypes and that they rather represent different stages of the disease. This may have implications regarding the role of lipofuscin on disease pathogenesis.

Keywords: age-related macular degeneration; fundus autofluorescence; geographic atrophy; latent class analysis.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Disease Progression
  • Female
  • Fluorescein Angiography*
  • Follow-Up Studies
  • Geographic Atrophy / diagnosis*
  • Humans
  • Male
  • Middle Aged
  • Phenotype
  • Predictive Value of Tests
  • Prospective Studies
  • Spain

Associated data