Ординатура / Офтальмология / Английские материалы / Ocular Neuroprotection_Levin, Polo _2003

these tests have been selected for use in current clinical trials. To my knowledge, there is no study currently using HPRP. Although this test has numerous advantages, it has not received widespread acceptance due to the lack of standardized test equipment and no self-calibrating feature. Results obtained on the same eye may vary from one unit to another. The other three tests are all involved in clinical trials at present. SWAP is not an outcome measure but is an ancillary test in the NEI-sponsored Ocular Hypertension Treatment Study (OHTS) [55] and FDT is a secondary outcome measure in an Allergan-sponsored clinical trial of the drug Memantine. This study should help us determine the effectiveness of FDT in longitudinal studies assessing change in visual function.

In nearly all clinical trials involving perimetry, SAP is the method of choice to date. SAP is currently the standard of care for visual field testing. The availability, standardization, and sophisticated statistical analyses are useful in clinical trials. However, in clinical trials that must identify small changes in visual performance, it may be less than ideal. SWAP identifies change 1 to 3 years sooner than SAP [20,21] and the results indicating change are more likely to be repeatable [56,57]. However, the increased variability and full threshold only strategy of SWAP have been detrimental to its acceptance. SITA (see below) for SWAP, when available, should go a long way toward alleviating these problems as it has reduced both test time and variability for SAP.

5. Swedish Interactive Thresholding Algorithm

Swedish interactive thresholding algorithm (SITA) is a new way of obtaining threshold for SAP [58,59]. It has led to an increased interest in SAP despite evidence that the visual function specific subtests, SWAP and FDT, are much more sensitive for detection [51] and SWAP and HPRP are better for following progression [20,21,31]. This new enthusiasm for standard fields is based on two attributes of SITA. The test time for a visual field is reduced in half relative to full threshold SAP [59–61] and the test-retest variability may also be reduced, which should make the results more reliable for measuring change over time [62–64]. Because SITA is a change in threshold procedure, which utilizes information collected during the test to better determine the intensity of the next flash at a given location [65,66], it easily could be applied to other forms of perimetry, such as SWAP.

Studies comparing SITA with the original full threshold algorithm indicate that SITA will show approximately 1 dB better thresholds than standard full threshold testing, but with a statistically deeper defect on the pattern and total deviation plots in glaucoma patients [60,62,66,67]. The smaller intersubject variance and greater reproducibility in patient eyes may mean shallower defects are needed in SITA fields for statistical significance to be reached than for the standard full threshold algorithm, but this has not been tested [62,63]. For trials that have already begun testing with full threshold strategy, it is not advisable to

switch to SITA. Clinically, when switching from standard full threshold to the SITA strategy to follow patients, it is necessary to obtain new baseline fields and to make comparisons between the two types of algorithms based on the total and pattern deviation probability plots rather than on absolute threshold values [64]. Clinical trials often initiate treatment after obtaining baselines, so there is no opportunity to reassess baselines with SITA. However, trials that were initiated after the development of SITA, such as the Neuroprotection in Ischemic Optic Neuropathy Trial sponsored by Allergan, have selected SITA for use with SAP as a secondary efficacy measure.

III.THE DEFINITION OF CHANGE IN CLINICAL TRIALS

Because it is often necessary in clinical trials to determine if progression is occurring before a series of five to seven fields can be obtained, linear regression has not been the method of choice. Instead, the statistical methods for identifying field progression relative to two baseline visits provided by the GCP and global indices of Statpac II have been incorporated into several large clinical trials: (1) Normal Tension Glaucoma Study (NTG); (2) Early Manifest Glaucoma Trial (EMGT); (3) Advanced Glaucoma Intervention Study (AGIS); (4) Collaborative Initial Glaucoma Treatment Study (CIGTS); and (5) Ocular Hypertension Treatment Study (OHTS).

A. Normal Tension Glaucoma Study

The Normal Tension Glaucoma Study was developed to assess the effect of lowering intraocular pressure on the progression rate of normal tension glaucoma [68]. To be eligible for this study, patient eyes had to have glaucomatous excavation of the optic disc and a field defect, standard achromatic perimetry, consisting of a cluster of three non-edge points depressed by 5 dB, with one of the points also depressed by 10 dB. This defect had to be confirmed by two of three baseline fields performed within a 4-week window. Patients with a history of IOP greater than 24 mmHg were excluded.

Progression was suspected when (1) at least two contiguous points within or adjacent to a baseline defect showed a reduction is sensitivity from baseline of at least 10 dB, or three times the average baseline short-term fluctuation for that patient, whichever is greater; (2) the sensitivity of each suspected point is outside the range of values observed during baseline testing; or (3) when a defect occurs in a previously normal part of the field. To reach a definitive decision of progression, four confirmatory tests were required. This large number of confirmatory fields was a consequence of looking for smaller field changes, which were

tion probability plot, which adjusts the total deviation values at each point relative to the most normal region in the visual field; (2) each abnormal test location must be accompanied by at least two adjacent abnormal points; and (3) each abnormal point is given a score from one to four based on the probability level (5% to 0.5%) of the three contiguous depressed points. The value for each of the 52 locations within the visual field is combined to get a maximum possible score of 208. The total score is then divided by a conversion factor (10.4) to get a final score ranging from 0 to 20. Two pre-intervention field tests must be reliable (reliability score 4); the GHT must read “outside normal limits”; there must be at least three contiguous points on the total deviation plot with a p 0.02; and if the points are in the nasal field, they cannot cross the horizontal midline. The two pre-intervention field scores are averaged to create a baseline CIGTS score. If the two baseline fields are more than 7 points apart, then a third field is conducted and the three are used to compute a baseline CIGTS score. Progression is quantified as an increase in score from baseline reference by three or more points on two consecutive reliable fields.

E.The Ocular Hypertension Treatment Study

The previously mentioned studies all involve assessment of change in an already abnormal visual field. The Ocular Hypertension Treatment Study (OHTS) [55] looks for change from a designation of normal visual field to abnormal visual field using SAP 30-2 full threshold visual fields. Fields are identified as abnormal if they have a glaucoma hemifield test results of “outside normal limits” or a corrected pattern standard deviation at the 5% probability or worse with a cluster of abnormal points consistent with glaucoma. Two confirming fields are required to call the fields glaucomatous.

What these descriptions of progression or change make clear is that there is no agreed-upon method for identifying progression and each clinical trial has developed methods specific to the study population involved. A few studies have compared some of the methods [72,73]. Regardless of the algorithm employed, it is still difficult to identify and confirm change without sufficient follow-up.

IV. FOLLOWING CHANGE MORE EFFECTIVELY

In addition to the obvious need to reduce the variability inherent in psychophysical tests of visual function and to confirm changes seen, there are other strategies that may assist us in identifying change more reliably. Each ganglion cell axon crosses the retina and enters the optic nerve. These fibers travel in bundles in a specific pattern. Several studies have correlated the location of visual field defect to location of optic nerve damage with good results [74–79]. We have found these

correlations hold for focal defects found on SAP, SWAP, and non-commercially available motion automated perimetry (MAP) [46,80,81]. In addition, there is an important and direct relationship between these measures of visual function and location of damage. In a study comparing SAP, SWAP, FDT, and MAP, we found that when a given individual had vision loss on more than one test, the same area of the visual field was affected [51]. Finally, in early glaucoma there is little evidence for secondary effects of neural degeneration as demonstrated by a lack of crossover of defect at the horizontal midline [82]. This does not rule out the presence of secondary degeneration but may be indicative of the limitations of our current testing strategies.

Since we now have information about different visual functions, location of visual field loss and the relationship to optic nerve damage, how can we use this information to improve tests for monitoring the effectiveness of neuroprotection therapies in clinical trials? Here we are not only interested in detection of a defect but also in change over time. Will those eyes receiving the neuroprotective agent show less progression of glaucoma than those that do not receive neuroprotection? For this, we also must understand something about how visual fields progress.

To determine typical patterns of visual field progression and their relationship to the 24-2 field grid, we prospectively followed, in a multicenter study, 115 glaucoma patients, who were experienced with fields, having two abnormal baseline visual fields, abnormal optic nerves, and repeated testing for fields that progressed [83]. Progression was categorized as (1) deepening of an existing scotoma; (2) expansion of an existing scotoma; or (3) a new scotoma. Three methods for classifying progression were used: (1) a clinically determined method; (2) the glaucoma change probability (GCP) based on total deviation (TD); and (3) the GCP based on pattern deviation (PD). Regardless of the classification method used, the glaucomatous visual fields progressed in the area of the visual field where baseline testing showed an existing scotoma. Because an individual’s location of defect overlaps on different visual function tests and progression occurs in this area, we can maximize finding repeatable change by concentrating testing on the defective areas determined at study entry.

V.CONCLUSIONS

Tests of visual function and measures of optic nerve structure that take into account the location of damage at baseline for each individual and incorporate this information in their designs for following change should be most successful for determining the effectiveness of neuroprotection. Since there is no gold standard for progression, it is still necessary for each clinical trial to identify an algorithm that best fits the needs of the study population under test. It would be prudent to incorporate a variety of visual function tests in these studies, because

we do not know if one type of ganglion cell may be more susceptible to a given neuroprotection therapy than another. It will be necessary to continue to improve our methods for identifying change in visual fields. This includes improving visual field techniques and improved analysis of results over time. As it stands now, more time for follow-up will be necessary to determine the effectiveness of a given neuroprotective agent than was needed in past studies to show the effectiveness of IOP-lowering agents. This is because glaucoma progresses slowly and possible change requires confirmation on more than one subsequent visit.

ACKNOWLEDGMENTS

This work is supported by NEI EY08208 and a Lew R. Wasserman award from Research to Prevent Blindness (PAS).

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