Researchers have demonstrated that commonly used visual field progression algorithms show poor to moderate agreement with each other. Major predictors of discordance, or lack of agreement, among the algorithms included more depressed initial mean deviation and older age at first available visual field. A greater number of visual fields, more years of follow up and eye care institution also were associated with discordance. 

The analysis included a subset of 90,713 visual fields of 13,156 eyes of 8,499 patients who met the inclusion criteria. The subset had at least five SITA-standard 24-2 visual fields. Researchers applied six progression algorithms to the date—mean deviation slope, visual field index slope, Advanced Glaucoma Intervention Study, Collaborative Initial Glaucoma Treatment Study, point-wise linear regression and permutation of point-wise linear regression—and each eye was determined as stable or progressing using each measure. The study found that 11.7% of eyes progressed based on at least four algorithms. The researchers noted discordance when three algorithms indicated progression and three indicated stable visual fields.

“These issues underscore the challenges to the clinical use and application of progression algorithms and of applying ‘big data’ results to individual practices,” the researchers concluded in their paper.