Keratoconus Clinical Trial
Official title:
Identification of Disease Progression Specific Biomarkers and Their Pharmacologic Modulation for Keratoconus.
There is currently no medication for containing KC, nor any adequate biomarkers to predict the disease. Furthermore, there is considerable confusion in the field regarding the pathophysiology of the disease and involvement of inflammation. To that end, this study is designed to address some of these questions by determining the proteomic profiles of KC patients with different clinical grades. This relatively large cohort study is expected to yield significant information regarding the molecules that are deregulated during progression of KC and may provide a framework to assign diagnostic biomarkers and therapeutic intervention points.
The screening of keratoconus involves keratoconus related clinical signs like retinoscopy
scissors reflex, Munson sign, stromal thinning, Vogt's striae, and Fleischer's ring, but
corneal topography is the most useful method in the diagnosis of keratoconus, especially in
the absence of clinical signs.
Several devices are currently available for detecting early keratoconus by measuring
anterior and posterior corneal topography and elevation(Mihaltz et al. 2009; Ishii et al.
2012). Corneal topographic and tomographic techniques which generate color-coded maps and
topographic indices, are the most sensitive devices for confirming the diagnosis of
keratoconus(Rabinowitz 1998; Rao et al. 2002) were used for diagnosis in this study. In
addition, videokeratography has been shown to identify Forme fruste keratoconus (FFKC) in
the absence of clinical signs of keratoconus. Videokeratographic indices such as the
Klyce/Maeda criteria, the Rabinowitz criteria, and others have been developed to
quantitatively analyze videokeratography and screen for keratoconus(Rao et al. 2002). These
indices have been shown to identify keratoconus with a high degree of sensitivity and
specificity. The Orbscan II is a three-dimensional slit-scan topography system for analysis
of the corneal surfaces and anterior chamber and has been used on all patients in the study.
It uses calibrated video and a scanning slit beam to measure x, y, and z locations of
several thousand points. These points are used to construct topographic maps(Rao et al.
2002). The Pentacam (Oculus Inc) is a corneal tomographer technology which generates data on
topograophy and elevation of anterior and posterior using a rotating Scheimpflug camera
which has also been used on all subjects enrolled in this study. Various diagnostic
parameters are available for keratoconus diagnosis depending on what mode of topography is
being used. Maeda and Klyce designed a system to detect keratoconus. The system, which is
based on linear discriminant analysis and a binary decision tree, identifies the map as
representing keratoconus or nonkeratoconus and, based on a value from the discriminant
analysis (the KPI), assigns the map an index expressed as a percentage that suggests the
severity of keratoconus. At this time, however, Keratoconus Severity Index (KSI) and the
Amsler-Krumeich classification are the most popular methods for grading keratoconus
severity(Mihaltz et al. 2009; Ishii et al. 2012). KSI is based on indices estimated by a
curvature map using Placido disk-based corneal topography, and Amsler-Krumeich
classification defines the stage of keratoconus using biomicroscopy, mean central
keratometry reading, spherical and cylindrical refraction change, and corneal
thickness(Mihaltz et al. 2009; Ishii et al. 2012). This is the index that has been used for
the final gradation of keratoconus stages of all subjects in this study.
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Observational Model: Case Control, Time Perspective: Prospective
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