Prediction of Glaucomatous Visual Field Progression Using Baseline Clinical Data

Purpose: To develop a prediction model for glaucomatous visual field progression using easily accessible baseline clinical data. Patients and Methods: We collected baseline data of 613 consecutive patients with open-angle glaucoma from 2001 to 2003. The rate of visual field progression was calculated using the Visual Field Index (VFI) of routine follow-up examinations until 2010. Baseline data of 333 patients from 3 hospitals were used to develop a model to predict the rate of VFI progression using a linear regression analysis and univariate preselection (P <0.1) of 8 candidate predictors. The performance of the model was investigated using R-2, the area under the receiver-operating characteristic curve, and calibration plots. The prediction model was internally validated using bootstrapping and externally validated in 280 patients from 2 other hospitals. Results: After a mean follow-up period of 5.8 years of all 613 eyes, the mean rate of VFI progression was -1.6% per year. The final model contained the following predictors: age, baseline intraocular pressure, and baseline visual field status. During model development, 10.3% of the observed variation in VFI rates was explained by the model. The area under the receiver-operating characteristic curve was 0.76 when the prediction model was used to detect a VFI rate of -3% per year or worse, which decreased to 0.71 at external validation. Conclusions: Although our prediction model could explain only a small amount of the variance in visual field progression, it may offer the possibility to identify subgroups of treated patients with high rates of visual field progression, thereby providing an opportunity to select those patients for more intensive treatment