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Editors Selection IGR 24-3

Risk Factors in Glaucoma: Corneal Hysteresis as a Predictor for Glaucoma

Comment by Steve Mansberger on:

75661 A Prospective Longitudinal Study to Investigate Corneal Hysteresis as a Risk Factor for Predicting Development of Glaucoma, Susanna CN; Diniz-Filho A; Daga FB et al., American Journal of Ophthalmology, 2018; 187: 148-152

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Studies evaluating glaucoma risk factors help predict and prevent visual impairment from glaucoma. This study by Susanna and colleagues investigates the role of corneal hysteresis (CH) as a risk factor for the development of glaucoma. The study includes 287 eyes of 199 patients suspected of having glaucoma with a follow-up time of 3.9 ± 1.8 years.

The study found that lower CH was associated with the development of repeatable visual field defects (a pattern standard deviation (PSD) with P < .05 or a Glaucoma Hemifield Test result outside normal limits) in a univariate (9.5 ± 1.5 mm Hg vs 10.2 ± 2.0 mm Hg; P = .012), and multivariate model including age, intraocular pressure (IOP), central corneal thickness, PSD, and treatment (hazard ratio = 1.20; 95% CI: 1.01-1.42; P = .040). Overall, this suggests that CH is an independent risk factor for development of glaucoma even when including central corneal thickness (CCT) as a known risk factor.

The study does not fully explain the model building procedure for the multivariable statistical model such as a stepwise entering of variables, or entering all eligible variables using the enter function. This may alter the final multivariable model. Previous studies suggest that CH is correlated with both IOP and CCT, while other studies only show a correlation with CCT. A correlation matrix would have been informative to determine whether IOP and CCT were associated with CH, and whether this is the explanation for those factors becoming not statistically significant in a multivariable model with CH. The model building procedure should explain why it used PSD as an explanatory variable when PSD is part of the definition of repeatable visual field loss (see above). It would also be helpful to know whether a model would have similar or worse explanatory power using IOP and CCT, which are more commonly used clinically.

We clearly need more information regarding the contribution of CH to our understanding of glaucoma pathophysiology and risk of glaucoma progression

Previous studies have shown this contribution of CH to glaucoma using retrospective and prospective studies in glaucoma patients. Susanna and colleagues should be congratulated for adding to this evidence by showing explanatory results of CH in glaucoma suspects. While research has suggested an association of CH with biomechanical stress and strain of the eye, we clearly need more information regarding the contribution of CH to our understanding of glaucoma pathophysiology and risk of glaucoma progression.

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