Purpose: Diseases characterized by a continuous trait can be defined by setting a cut-off point for the disease measure in question, accepting some misclassification. The 97.5th percentile is commonly used as a cut-off point. However, it is unclear whether this percentile is the optimal cut-off point from the point of view of risk-factor analysis. The optimal cut-off point for risk-factor analysis can be found with a statistical method that minimizes the effect of misclassification. We applied this method to glaucomatous optic neuropathy. Here, the continuous trait is the cup-disc ratio. The aim of this study was to determine the optimal cup-disc ratio cut-off point for risk-factor analysis in population-based epidemiology. Methods: All participants in the population-based Rotterdam Study underwent intraocular pressure (IOP) measurements, assessment of the cup-disc ratio with the Heidelberg Retina Tomograph (HRT) and visual field testing. In the statistical method, the cup-disc ratio (the continuous trait) and the IOP (a major risk factor) were independent variables and glaucomatous visual field loss (the true glaucoma endpoint) the dependent variable in a logistic regression model. The optimal cup-disc ratio cut-off point was found by minimizing the influence of IOP in this model. Variability of the approach was assessed by using a bootstrap resampling technique. Results: Of 2444 included participants, 93 had glaucomatous visual field loss. The median optimal cup-disc ratio cut-off point was the 97.0th percentile with a 95% central range from 95.5 to 98.5. Conclusion: The optimal cup-disc ratio cut-off point for risk-factor analysis is close to the commonly used 97.5th percentile.

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doi.org/10.3109/09286586.2011.595038, hdl.handle.net/1765/67118
Ophthalmic Epidemiology
Department of Ophthalmology

Ramdas, W., Rizopoulos, D., Wolfs, R., Hofman, A., de Jong, P., Vingerling, H., & Jansonius, N. (2011). Defining glaucomatous optic neuropathy from a continuous measure of optic nerve damage the optimal cut-off point for risk-factor analysis in population-based epidemiology. Ophthalmic Epidemiology, 18(5), 211–216. doi:10.3109/09286586.2011.595038