While the presence and rate of glaucoma progression influence treatment decisions, the methods currently available to detect and monitor progression are imprecise and do not allow clinicians to make accurate assessments of the status of their patients. Models that focus on combining structural and functional parameters may improve our ability to detect and monitor glaucoma progression. Several of these models, however, are limited by their reliance on population statistics and on the static

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... mptions they make about the nature of glaucoma progression. Dynamic modeling of glaucoma progression may lead to a better understanding of glaucoma progression that could eventually translate into making individualized treatment decisions.