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Comparison of Analytic Algorithms for Detecting Glaucomatous Visual Field Loss

Comparison of Analytic Algorithms for Detecting Glaucomatous Visual Field Loss Abstract • The sensitivity and specificity of alternate analytic strategies for recognizing glaucomatous visual field loss from automated threshold perimetry (C-30-2 test of the Humphrey Field Analyzer) were compared among one eye each of 106 patients with glaucoma and 249 normal subjects. Algorithms included commercially available global indexes and cross-meridional differences (Statpac 1 and Statpac 2), as well as cross-meridional and cluster analyses that were developed independently for natural history studies and clinical trials. The sensitivity of most algorithms was high, except for those that used only diffuse loss as an indicator of abnormality. Specificity was acceptably high for all algorithms. Subjects who failed to meet the manufacturer's standard for reliability had much reduced specificity, but sensitivity was also affected. Algorithms that were based on any of the alternate definitions of localized reduction in retinal sensitivity performed equally well, which suggests that any of these approaches is useful in searching for glaucomatous visual loss as typified by this database. Availability, familiarity, and convenience may govern the selection of any one analytic approach for use in a particular setting. References 1. Hotchkiss ML, Robin AL, Quigley HA, Pollack IP. A comparison of Peritest automated perimetry and Goldmann perimetry . Arch Ophthalmol . 1985;103:397-403.Crossref 2. Mills RP, Hopp RH, Drance SM. Comparison of quantitative testing with the Octopus, Humphrey, and Tubingen perimeters . Am J Ophthalmol . 1986;102:496-504. 3. Katz J, Sommer A. Similarities between the visual fields of ocular hypertensive and normal eyes . Arch Ophthalmol . 1986;104:1648-1651.Crossref 4. Dyster-Aas K, Heijl A, Lundqvist L. Computerized visual field screening in the management of patients with ocular hypertension . Acta Ophthalmol (Copenh) . 1980;58:918-928.Crossref 5. Keltner JL, Johnson CA. Effectiveness of automated perimetry in following glaucomatous visual field progression . Ophthalmology . 1982;89:247-254.Crossref 6. Flammer J, Drance SM, Augustiny L, Funkhouser A. Quantification of glaucomatous visual field defects with automated perimetry . Invest Ophthalmol Vis Sci . 1985;26:176-181. 7. Brechner RJ, Whalen WR. Creation of the transformed Q statistic probability distribution to aid in the detection of abnormal computerized visual fields . Ophthalmic Surg . 1984;15:833-836. 8. Heijl A, Drance SM, Douglas GR. Automated perimetry (COMPETER): ability to detect early glaucomatous field defects . Arch Ophthalmol . 1980;98:1560-1563.Crossref 9. Gollamudi SR, Liao PM, Hirsch J. Evaluation of corrected loss variance as a visual field index, II: corrected loss variance in conjunction with mean defect may identify stages of glaucoma . Ophthalmologica . 1988;197:144-150.Crossref 10. Bebie H, Fankhauser F. Statistical program for the analysis of perimetric data . Doc Ophthalmol Proc Ser . 1981;26:9-10. 11. Flammer J, Jenni F, Bebie H, Keller B. The Octopus G1 program . Glaucoma . 1987;9:67-72. 12. Heijl A, Drance SM. A clinical comparison of three computerized automatic perimeters in the detection of glaucomatous defects . Arch Ophthalmol . 1981;99:832-836.Crossref 13. Chauhan BC, Drance SM, Lai C. A cluster analysis for threshold perimetry . Graefes Arch Clin Exp Ophthalmol . 1989;277:216-220.Crossref 14. Duggan C, Sommer A, Auer C, Burkhard K. Automated differential threshold perimetry for detecting glaucomatous visual field loss . Am J Ophthalmol . 1985;100:420-423. 15. Sommer A, Enger C, Witt K. Screening for glaucomatous field loss with automated threshold perimetry . Am J Ophthalmol . 1987;103:681-684. 16. Statpac User's Guide . San Leandro, Calif: Allergan Humphrey; 1986. 17. Heijl A, Lindgren G, Olsson J. A package for the statistical analysis of visual fields . Doc Ophthalmol Proc Ser . 1987;49:153-168. 18. Heijl A, Lindgren G, Olsson J, Asman P. Visual field interpretation with empiric probability maps . Arch Ophthalmol . 1989;107:204-208.Crossref 19. Statpac 2 User's Guide . San Leandro, Calif: Allergan Humphrey; 1989. 20. Sommer A, Quigley HA, Robin AL, Miller NR, Katz J, Arkell S. Evaluation of nerve fiber layer assessment . Arch Ophthalmol . 1984;102:1766-1771.Crossref 21. Sommer A, Katz J, Quigley HA, et al. Clinically detectable nerve fiber atrophy precedes the onset of glaucomatous field loss . Arch Ophthalmol . 1991;109:77-83.Crossref 22. Katz J, Sommer A. Reliability indexes of automated perimetric tests . Arch Ophthalmol . 1988;106:1252-1254.Crossref 23. Nelson-Quigg JM, Twelker JD, Johnson CA. Response properties of normal observers and patients during automated perimetry . Arch Ophthalmol . 1989;107:1612-1615.Crossref 24. Heijl A, Lindgren G, Olsson J. Reliability parameters in computerized perimetry . Doc Ophthalmol Proc Ser . 1987;49:593-600. 25. Katz J, Sommer A. Screening for glaucomatous visual field loss: the effect of patient reliability . Ophthalmology . 1990;97:1032-1037.Crossref 26. Katz J, Sommer A, Witt K. Reliability of visual field results over repeat testing . Ophthalmology . 1991;98:70-75.Crossref 27. The Optic Neuritis Study Group. Visual field reading center optic neuritis treatment trial . Invest Ophthalmol Vis Sci . 1990;31( (suppl 4) ):609. 28. Sanabria O, Feuer WJ, Anderson DR. Pseudo-loss of fixation in automated perimetry . Ophthalmology . 1991;98:76-78.Crossref 29. Canner JK, Sommer A, Katz J, Enger C. ICEPACK: a user friendly software package for processing Humphrey field analyzer diskettes . Invest Ophthalmol Vis Sci . 1988;29( (suppl) ):356. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Ophthalmology American Medical Association

Comparison of Analytic Algorithms for Detecting Glaucomatous Visual Field Loss

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Publisher
American Medical Association
Copyright
Copyright © 1991 American Medical Association. All Rights Reserved.
ISSN
0003-9950
eISSN
1538-3687
DOI
10.1001/archopht.1991.01080120068028
Publisher site
See Article on Publisher Site

Abstract

Abstract • The sensitivity and specificity of alternate analytic strategies for recognizing glaucomatous visual field loss from automated threshold perimetry (C-30-2 test of the Humphrey Field Analyzer) were compared among one eye each of 106 patients with glaucoma and 249 normal subjects. Algorithms included commercially available global indexes and cross-meridional differences (Statpac 1 and Statpac 2), as well as cross-meridional and cluster analyses that were developed independently for natural history studies and clinical trials. The sensitivity of most algorithms was high, except for those that used only diffuse loss as an indicator of abnormality. Specificity was acceptably high for all algorithms. Subjects who failed to meet the manufacturer's standard for reliability had much reduced specificity, but sensitivity was also affected. Algorithms that were based on any of the alternate definitions of localized reduction in retinal sensitivity performed equally well, which suggests that any of these approaches is useful in searching for glaucomatous visual loss as typified by this database. Availability, familiarity, and convenience may govern the selection of any one analytic approach for use in a particular setting. References 1. Hotchkiss ML, Robin AL, Quigley HA, Pollack IP. A comparison of Peritest automated perimetry and Goldmann perimetry . Arch Ophthalmol . 1985;103:397-403.Crossref 2. Mills RP, Hopp RH, Drance SM. Comparison of quantitative testing with the Octopus, Humphrey, and Tubingen perimeters . Am J Ophthalmol . 1986;102:496-504. 3. Katz J, Sommer A. Similarities between the visual fields of ocular hypertensive and normal eyes . Arch Ophthalmol . 1986;104:1648-1651.Crossref 4. Dyster-Aas K, Heijl A, Lundqvist L. Computerized visual field screening in the management of patients with ocular hypertension . Acta Ophthalmol (Copenh) . 1980;58:918-928.Crossref 5. Keltner JL, Johnson CA. Effectiveness of automated perimetry in following glaucomatous visual field progression . Ophthalmology . 1982;89:247-254.Crossref 6. Flammer J, Drance SM, Augustiny L, Funkhouser A. Quantification of glaucomatous visual field defects with automated perimetry . Invest Ophthalmol Vis Sci . 1985;26:176-181. 7. Brechner RJ, Whalen WR. Creation of the transformed Q statistic probability distribution to aid in the detection of abnormal computerized visual fields . Ophthalmic Surg . 1984;15:833-836. 8. Heijl A, Drance SM, Douglas GR. Automated perimetry (COMPETER): ability to detect early glaucomatous field defects . Arch Ophthalmol . 1980;98:1560-1563.Crossref 9. Gollamudi SR, Liao PM, Hirsch J. Evaluation of corrected loss variance as a visual field index, II: corrected loss variance in conjunction with mean defect may identify stages of glaucoma . Ophthalmologica . 1988;197:144-150.Crossref 10. Bebie H, Fankhauser F. Statistical program for the analysis of perimetric data . Doc Ophthalmol Proc Ser . 1981;26:9-10. 11. Flammer J, Jenni F, Bebie H, Keller B. The Octopus G1 program . Glaucoma . 1987;9:67-72. 12. Heijl A, Drance SM. A clinical comparison of three computerized automatic perimeters in the detection of glaucomatous defects . Arch Ophthalmol . 1981;99:832-836.Crossref 13. Chauhan BC, Drance SM, Lai C. A cluster analysis for threshold perimetry . Graefes Arch Clin Exp Ophthalmol . 1989;277:216-220.Crossref 14. Duggan C, Sommer A, Auer C, Burkhard K. Automated differential threshold perimetry for detecting glaucomatous visual field loss . Am J Ophthalmol . 1985;100:420-423. 15. Sommer A, Enger C, Witt K. Screening for glaucomatous field loss with automated threshold perimetry . Am J Ophthalmol . 1987;103:681-684. 16. Statpac User's Guide . San Leandro, Calif: Allergan Humphrey; 1986. 17. Heijl A, Lindgren G, Olsson J. A package for the statistical analysis of visual fields . Doc Ophthalmol Proc Ser . 1987;49:153-168. 18. Heijl A, Lindgren G, Olsson J, Asman P. Visual field interpretation with empiric probability maps . Arch Ophthalmol . 1989;107:204-208.Crossref 19. Statpac 2 User's Guide . San Leandro, Calif: Allergan Humphrey; 1989. 20. Sommer A, Quigley HA, Robin AL, Miller NR, Katz J, Arkell S. Evaluation of nerve fiber layer assessment . Arch Ophthalmol . 1984;102:1766-1771.Crossref 21. Sommer A, Katz J, Quigley HA, et al. Clinically detectable nerve fiber atrophy precedes the onset of glaucomatous field loss . Arch Ophthalmol . 1991;109:77-83.Crossref 22. Katz J, Sommer A. Reliability indexes of automated perimetric tests . Arch Ophthalmol . 1988;106:1252-1254.Crossref 23. Nelson-Quigg JM, Twelker JD, Johnson CA. Response properties of normal observers and patients during automated perimetry . Arch Ophthalmol . 1989;107:1612-1615.Crossref 24. Heijl A, Lindgren G, Olsson J. Reliability parameters in computerized perimetry . Doc Ophthalmol Proc Ser . 1987;49:593-600. 25. Katz J, Sommer A. Screening for glaucomatous visual field loss: the effect of patient reliability . Ophthalmology . 1990;97:1032-1037.Crossref 26. Katz J, Sommer A, Witt K. Reliability of visual field results over repeat testing . Ophthalmology . 1991;98:70-75.Crossref 27. The Optic Neuritis Study Group. Visual field reading center optic neuritis treatment trial . Invest Ophthalmol Vis Sci . 1990;31( (suppl 4) ):609. 28. Sanabria O, Feuer WJ, Anderson DR. Pseudo-loss of fixation in automated perimetry . Ophthalmology . 1991;98:76-78.Crossref 29. Canner JK, Sommer A, Katz J, Enger C. ICEPACK: a user friendly software package for processing Humphrey field analyzer diskettes . Invest Ophthalmol Vis Sci . 1988;29( (suppl) ):356.

Journal

Archives of OphthalmologyAmerican Medical Association

Published: Dec 1, 1991

References

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