Literature DB >> 22879418

The relationship between variability and sensitivity in large-scale longitudinal visual field data.

Richard A Russell1, David P Crabb, Rizwan Malik, David F Garway-Heath.   

Abstract

PURPOSE: Evaluation of progressive visual field (VF) damage is often based on pointwise sensitivity data from standard automated perimetry; however, frequency-of seeing and test-retest studies demonstrate that these measurements can be highly variable, especially in areas of damage. The aim of this study was to characterize VF variability by the level of sensitivity using a statistical method to quantify heteroscedasticity.
METHODS: A total of 14,887 Humphrey 24-2 SITA Standard VFs from 2736 patients (2736 eyes) attending Moorfields Eye Hospital from 1997 to 2009 were studied retrospectively. The VF series of each eye was analyzed using pointwise linear regression of sensitivity over time, with residuals (difference from fitted-value) from each regression pooled according to both observed and fitted sensitivities.
RESULTS: The median (interquartile range) patient age, follow-up, and series length was 64 (54-71) years, 5.5 (3.9-7.0) years, and 6 (5-7) VFs, respectively. The inferred variability as a function of fitted-sensitivity was in good agreement with previous estimates. Variability was also described as a function of measured sensitivity, which confirmed that variability increased rapidly as the observed sensitivity decreased.
CONCLUSIONS: This study highlights a new approach for characterizing VF variability by the level of sensitivity. A considerable strength of the method is that inference is based on thousands of clinic patients rather than the tens of subjects in test-retest studies. The results can help distinguish real VF progression from measurement variability and will be used in models for glaucoma progression detection.

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Year:  2012        PMID: 22879418     DOI: 10.1167/iovs.12-10428

Source DB:  PubMed          Journal:  Invest Ophthalmol Vis Sci        ISSN: 0146-0404            Impact factor:   4.799


  39 in total

1.  Are rates of vision loss in patients in English glaucoma clinics slowing down over time? Trends from a decade of data.

Authors:  T Boodhna; L J Saunders; D P Crabb
Journal:  Eye (Lond)       Date:  2015-08-28       Impact factor: 3.775

2.  A spatially varying change points model for monitoring glaucoma progression using visual field data.

Authors:  Samuel I Berchuck; Jean-Claude Mwanza; Joshua L Warren
Journal:  Spat Stat       Date:  2019-02-22

3.  Evaluation of Visual Field and Imaging Outcomes for Glaucoma Clinical Trials (An American Ophthalomological Society Thesis).

Authors:  David F Garway-Heath; Ana Quartilho; Philip Prah; David P Crabb; Qian Cheng; Haogang Zhu
Journal:  Trans Am Ophthalmol Soc       Date:  2017-08-22

4.  What rates of glaucoma progression are clinically significant?

Authors:  Luke J Saunders; Felipe A Medeiros; Robert N Weinreb; Linda M Zangwill
Journal:  Expert Rev Ophthalmol       Date:  2016-05-13

5.  Reproducibility in the global indices for multifocal visual evoked potentials and Humphrey visual fields in controls and glaucomatous eyes within a 2-year period.

Authors:  Yukako Inoue; Kei Kato; Seiko Kamata; Kumiko Ishikawa; Makoto Nakamura
Journal:  Doc Ophthalmol       Date:  2015-06-16       Impact factor: 2.379

6.  Improving the Feasibility of Glaucoma Clinical Trials Using Trend-Based Visual Field Progression Endpoints.

Authors:  Zhichao Wu; David P Crabb; Balwantray C Chauhan; Jonathan G Crowston; Felipe A Medeiros
Journal:  Ophthalmol Glaucoma       Date:  2019-01-17

7.  Comparison of regression models for serial visual field analysis.

Authors:  Jun Mo Lee; Kouros Nouri-Mahdavi; Esteban Morales; Abdelmonem Afifi; Fei Yu; Joseph Caprioli
Journal:  Jpn J Ophthalmol       Date:  2014-08-28       Impact factor: 2.447

8.  Agreement and Predictors of Discordance of 6 Visual Field Progression Algorithms.

Authors:  Osamah J Saeedi; Tobias Elze; Loris D'Acunto; Ramya Swamy; Vikram Hegde; Surabhi Gupta; Amin Venjara; Joby Tsai; Jonathan S Myers; Sarah R Wellik; Carlos Gustavo De Moraes; Louis R Pasquale; Lucy Q Shen; Michael V Boland
Journal:  Ophthalmology       Date:  2019-02-04       Impact factor: 12.079

Review 9.  Functional assessment of glaucoma: Uncovering progression.

Authors:  Rongrong Hu; Lyne Racette; Kelly S Chen; Chris A Johnson
Journal:  Surv Ophthalmol       Date:  2020-04-26       Impact factor: 6.048

10.  Nonlinear, multilevel mixed-effects approach for modeling longitudinal standard automated perimetry data in glaucoma.

Authors:  Manoj Pathak; Shaban Demirel; Stuart K Gardiner
Journal:  Invest Ophthalmol Vis Sci       Date:  2013-08-15       Impact factor: 4.799

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