Monitoring Glaucoma Progression

By Vincent Michael Patella, Vice President, Professional Affairs at Carl Zeiss Meditec, Inc.

As a result of work over the past decade, many doctors have become more interested in knowing how fast a patient is getting worse and whether or not that rate is acceptable. In other words, given the patient’s life expectancy and given his or her current state of vision, what is the risk that this patient will become visually disabled in his or her lifetime? If there is significant risk of visual disability in the patient’s lifetime, then it may be necessary to adjust therapy.

In my view, managing glaucoma patients has evolved to be an activity in which you monitor staging, rates of change and life expectancy. In a typical scenario, the doctor makes the diagnosis that the patient has glaucoma, determines how much damage already exists, and decides what therapy is most appropriate. Then the question becomes one of determining if the patient is progressing under current therapy and, if so, how fast.

Determining the rate of progression may require investment of considerable diagnostic effort during the first few years after diagnosis. Only a fraction of glaucoma patients progress at vision-threatening rates — perhaps 15%. The other 85% may be fine with their current treatment, needing continued monitoring but no urgent change in therapy. Under this philosophy, the emphasis is on determining if this is the one patient in seven who is progressing so rapidly that he or she needs more aggressive treatment. If they’re not at high risk, you will, of course, continue to monitor their status. Those who are progressing more rapidly will then have the benefit of being considered for early and appropriate adjustments in therapy. Compared to twenty years ago, this represents a real change in the way we think about glaucoma management, but it probably isn’t very different from how other diseases are managed.

The two techniques for quantitative progression assessment are change from baseline — also known as event detection — and rate of change. Progression software should include both analyses, because detection of statistically significant change events is typically more sensitive and can be done sooner than rate of change. Rate of change estimation usually takes longer but provides critical information to help judge whether the patient is at risk for vision loss during their life expectancy. Guided Progression Analysis™ (GPA™ ) software from Carl Zeiss Meditec features both assessments. GPA is standard on the Humphrey^® Field Analyzer (HFA™), and also on the Cirrus™ HD-OCT.

The HFA measures visual field sensitivity, and Cirrus measures retinal nerve fiber layer thickness (RNFL), optic nerve parameters, and parameters related to ganglion cell thickness. For both instruments, the goal of GPA is to quickly identify change events that statistically exceed expected and normal testing variability and then to estimate the rate of change in parameters of interest for each instrument. Change events alert you as to which patients may need more careful assessment of rate of progression. Knowing the rate of progression helps you assess the clinical significance of the observed change. We recognize that there is a difference between statistical significance and clinical significance, and our goal is to help you bridge that gap.

This strategy frontloads the diagnostic investment. In essence, we’re saying let’s spend some intensive effort evaluating our glaucoma patients soon after diagnosis. Is their disease progressing quickly, slowly, or not at all? Once we’ve figured out who they are, we can focus our healthcare resources on the fast progressors, and perhaps manage less aggressively those who have demonstrated over the course of their clinical management that they are at minimal risk. ■

Ganglion Cell Analysis

New CIRRUS applications expand your glaucoma tools. Ganglion cell analysis lets you check for early change in the macula that may not be present in the disc region.

The ganglion cell thickness measurements are automatically centered using FoveaFinder™.

Measurements are compared to normative data in superpixel Deviation Maps.