Predicting Variability and Reliability in Visual Field Testing: Short- and Long-Term Approaches

Purpose: To predict intrinsic measurement variability and reliability (any cause of data loss) in visual field (VF) results using a computer simulation model. Design: Computer simulation study. Subjects: One hundred thousand subjects simulated with empirical mean deviation, progression rate, variability, and reliability characteristics. Methods: One hundred thousand subjects were simulated to undergo 4 VF tests per visit, 3 monthly, over 20 years (long-term condition) and 4 VF tests per visit daily over 28 days (short-term condition). Permutations of 1-4 tests per visit over 3-, 6-, and 12-monthly (long-term) and 1-, 2-, and 4-daily (short-term) review intervals were used. Visual field variabilities were estimated sequentially until 3 consecutive visits returned variabilities within 5% of each other using a rolling window. The same was applied to reliability. The last visit of the window denoted the critical time to estimating variability using the consecutive clinical criterion (TcV) and critical time to estimating reliability using the consecutive clinical criterion (TcR) estimation. Additionally, we identified the critical time at which 3 consecutive visits were within 5% of the ground truth (critical time to estimating variability using the consecutive clinical criterion and comparison with the ground truth [TgV] and critical time to estimating reliability using the consecutive clinical criterion and comparison with the ground truth [TgR]). Main Measures: Critical time to estimating intrinsic variability and reliability. Results: < 0.0001). Only reliability predicted TcR and TgR. Predictors had low coefficients of determination (