Qualitative analysis still the gold standard for detecting glaucoma progression

April 11, 2008

Which is better at detecting glaucomatous progression: the physician's judgment, based on skills such as interpreting optic disk photographs, or new technologies?

Which is better at detecting glaucomatous progression: the physician's judgment, based on skills such as interpreting optic disk photographs, or new technologies? Both have a role, but to Joseph Caprioli, MD, FACS, who discussed detection strategies in a presentation at the American Academy of Ophthalmology annual meeting, qualitative evaluation techniques retain an edge.

According to Dr. Caprioli, the best way to detect progression is through careful evaluation of structure.

Disk photographs are still the gold standard, whereas quantitative measurements are adjunctive. Selective use of short-wavelength automated perimetry and frequency doubling perimetry is helpful in making an early diagnosis of glaucoma in ocular hypertensive patients or otherwise suspect patients, he said, but the variability of those tools makes assessing changes over time difficult. Instead, serial evaluation of standard automated perimetry, multiple tests, and validation are the keys to detecting progression.

"A machine can certainly make a measurement; exactly how to use these measurements to monitor change is being worked out," said Dr. Caprioli, professor of ophthalmology and chief, glaucoma division, Jules Stein Eye Institute, University of California, Los Angeles. "I think the story as yet is still being unfolded. Qualitative evaluation is still important. Quantitative techniques can detect structural change, but so far nothing has been shown to be better than an informed evaluation of disk photographs. The biggest mistake is not to look.

"I'd like to put forward a concept that measurement of progression rate is more important than early detection, and that the functional and structural scales by which we measure progression are not synchronous or even linear. They may not be synchronous in early disease and particularly in late disease," Dr. Caprioli said.

For example, he continued, it would be important to be able to differentiate slow progressors from fast progressors, since fast progressors require aggressive treatment, particularly early rather than late, to preserve visual function.

The main challenge in functional testing is long-term fluctuation, due to an inherent signal-to-noise problem, Dr. Caprioli said, with the signal being real progression and the noise being long-term fluctuation. "To solve that problem, we need multiple tests that tend to average out or cancel out the noise and reveal the true signal, and the true signal needs confirmation with subsequent tests."

Dr. Caprioli also pointed out that many patients have such high long-term fluctuation that evaluating any two visual fields could show that the patient is getting better, getting worse, or remaining stable. "Important lesson: never evaluate visual fields based on two measurements," he said.

Dr. Caprioli also described some of the new technology designed to identify progression with visual fields. Glaucoma Change Probability Analysis and its upgraded version, Glaucoma Progression Analysis, are software programs used with a visual field testing platform (Humphrey Field Analyzer, Carl Zeiss Meditec). Those programs compare every point to a baseline set of points from two, three, or more fields and determine whether there is a probability for change and whether that change has been confirmed. When interpreting the results, look for a solid triangle showing a statistical change at a point that has been confirmed twice and for groupings of those points, which makes sense clinically, Dr. Caprioli said. If the disk is examined over the same period, it is likely that significant change will be seen, he added.

Dr. Caprioli also discussed the merits of probability in predicting whether the visual field will progress over time. He suggested, based on work he has done, statistical software can help with that type of prediction.

He concluded by offering his seven rules for recognizing visual field progression:

  • Examine the entire series of visual fields, not just a few of them.

  • Gauge the magnitude of the long-term fluctuation.

  • Demand that progression exceed that magnitude of fluctuation, which can vary considerably from patient to patient.

  • Get confirmation of progression.

  • Don't compare just two visual fields, which can be misleading.

  • Don't evaluate fields in a vacuum; you must include other clinical data, such as correlation with the disk and the patient's risk factors.

  • The software should be your assistant but should not be the final arbiter of change.