Literature DB >> 35288335

Clinicians' Use of Quantitative Information while Assessing the Rate of Functional Progression in Glaucoma.

Stuart K Gardiner1, Robert M Kinast2, Carlos Gustavo De Moraes3, Donald L Budenz4, Jin Wook Jeoung5, John T Lind6, Jonathan S Myers7, Kouros Nouri-Mahdavi8, Lindsay A Rhodes9, Nicholas G Strouthidis10, Teresa C Chen11, Steven L Mansberger2.   

Abstract

PURPOSE: Clinicians use both global and point-wise information from visual fields to assess the rate of glaucomatous functional progression. We asked which objective, quantitative measures best correlated with subjective assessment by glaucoma experts. In particular, we aimed to determine how much that judgment was based on localized rates of change vs. on global indices reported by the perimeter.
DESIGN: Prospective cohort study. PARTICIPANTS: Eleven academic, expert glaucoma specialists independently scored the rate of functional progression, from 1 (improvement) to 7 (very rapid progression), for a series of 5 biannual clinical printouts from 100 glaucoma or glaucoma suspect eyes of 51 participants, 20 of which were scored twice to assess repeatability.
METHODS: Regression models were used to predict the average of the 11 clinicians' scores based on objective rates of change of mean deviation (MD), visual field index (VFI), pattern standard deviation (PSD), the Nth fastest progressing location, and the Nth fastest progressing of 10 anatomically defined clusters of locations after weighting by eccentricity. MAIN OUTCOME MEASURES: Correlation between the objective rates of change and the average of the 11 clinicians' scores.
RESULTS: The average MD of the study eyes was -2.4 dB (range, -16.8 to +2.8 dB). The mean clinician score was highly repeatable, with an intraclass correlation coefficient of 0.95. It correlated better with the rate of change of VFI (pseudo-R2 = 0.73, 95% confidence interval [CI, 0.60-0.83]) than with MD (pseudo-R2 = 0.63, 95% CI [0.45-0.76]) or PSD (pseudo-R2 = 0.41, 95% CI [0.26-0.55]). Using point-wise information, the highest correlations were found with the fifth-fastest progressing location (pseudo-R2 = 0.71, 95% CI [0.56-0.80]) and the fastest-progressing cluster after eccentricity weighting (pseudo-R2 = 0.61, 95% CI [0.48-0.72]). Among 25 eyes with an average VFI of > 99%, the highest observed pseudo-R2 value was 0.34 (95% CI [0.16-0.61]) for PSD.
CONCLUSIONS: Expert academic glaucoma specialists' assessment of the rate of change correlated best with VFI rates, except in eyes with a VFI near the ceiling of 100%. Sensitivities averaged within clusters of locations have been shown to detect change sooner, but the experts' opinions correlated more closely with global VFI. This could be because it is currently the only index for which the perimeter automatically provides a quantitative estimate of the rate of functional progression.
Copyright © 2022 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Clinical care; Diagnostics; Perimetry; Progression; Survey

Year:  2022        PMID: 35288335      PMCID: PMC9464792          DOI: 10.1016/j.ogla.2022.03.002

Source DB:  PubMed          Journal:  Ophthalmol Glaucoma        ISSN: 2589-4196


  26 in total

1.  Summarizing the goodness of fit of generalized linear models for longitudinal data.

Authors:  B Zheng
Journal:  Stat Med       Date:  2000-05-30       Impact factor: 2.373

2.  Detecting Preperimetric Glaucoma with Standard Automated Perimetry Using a Deep Learning Classifier.

Authors:  Ryo Asaoka; Hiroshi Murata; Aiko Iwase; Makoto Araie
Journal:  Ophthalmology       Date:  2016-07-07       Impact factor: 12.079

3.  Glaucoma Hemifield Test. Automated visual field evaluation.

Authors:  P Asman; A Heijl
Journal:  Arch Ophthalmol       Date:  1992-06

4.  A comparison of experienced clinical observers and statistical tests in detection of progressive visual field loss in glaucoma using automated perimetry.

Authors:  E B Werner; K I Bishop; J Koelle; G R Douglas; R P LeBlanc; R P Mills; B Schwartz; W R Whalen; J T Wilensky
Journal:  Arch Ophthalmol       Date:  1988-05

5.  Early detection of visual field progression in glaucoma: a comparison of PROGRESSOR and STATPAC 2.

Authors:  A C Viswanathan; F W Fitzke; R A Hitchings
Journal:  Br J Ophthalmol       Date:  1997-12       Impact factor: 4.638

6.  Comparison of methods to detect visual field progression in glaucoma .

Authors:  K Nouri-Mahdavi; L Brigatti; M Weitzman; J Caprioli
Journal:  Ophthalmology       Date:  1997-08       Impact factor: 12.079

7.  Interobserver agreement on visual field progression in glaucoma: a comparison of methods.

Authors:  A C Viswanathan; D P Crabb; A I McNaught; M C Westcott; D Kamal; D F Garway-Heath; F W Fitzke; R A Hitchings
Journal:  Br J Ophthalmol       Date:  2003-06       Impact factor: 4.638

8.  A visual field index for calculation of glaucoma rate of progression.

Authors:  Boel Bengtsson; Anders Heijl
Journal:  Am J Ophthalmol       Date:  2008-02       Impact factor: 5.258

9.  Detection of Functional Change Using Cluster Trend Analysis in Glaucoma.

Authors:  Stuart K Gardiner; Steven L Mansberger; Shaban Demirel
Journal:  Invest Ophthalmol Vis Sci       Date:  2017-05-01       Impact factor: 4.799

10.  Examining visual field loss in patients in glaucoma clinics during their predicted remaining lifetime.

Authors:  Luke J Saunders; Richard A Russell; James F Kirwan; Andrew I McNaught; David P Crabb
Journal:  Invest Ophthalmol Vis Sci       Date:  2014-01-07       Impact factor: 4.799

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