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.
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.
Authors: Henriët Springelkamp; Kyungmoo Lee; Roger C W Wolfs; Gabriëlle H S Buitendijk; Wishal D Ramdas; Albert Hofman; Johannes R Vingerling; Caroline C W Klaver; Michael D Abràmoff; Nomdo M Jansonius Journal: Invest Ophthalmol Vis Sci Date: 2014-11-20 Impact factor: 4.799
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Authors: Puya Gharahkhani; Kathryn P Burdon; Jessica N Cooke Bailey; Alex W Hewitt; Matthew H Law; Louis R Pasquale; Jae H Kang; Jonathan L Haines; Emmanuelle Souzeau; Tiger Zhou; Owen M Siggs; John Landers; Mona Awadalla; Shiwani Sharma; Richard A Mills; Bronwyn Ridge; David Lynn; Robert Casson; Stuart L Graham; Ivan Goldberg; Andrew White; Paul R Healey; John Grigg; Mitchell Lawlor; Paul Mitchell; Jonathan Ruddle; Michael Coote; Mark Walland; Stephen Best; Andrea Vincent; Jesse Gale; Graham RadfordSmith; David C Whiteman; Grant W Montgomery; Nicholas G Martin; David A Mackey; Janey L Wiggs; Stuart MacGregor; Jamie E Craig Journal: Sci Rep Date: 2018-02-15 Impact factor: 4.379
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