Literature DB >> 21812943

The evidence base to select a method for assessing glaucomatous visual field progression.

Paul J G Ernest1, Jan S A G Schouten, Henny J M Beckers, Fred Hendrikse, Martin H Prins, Carroll A B Webers.   

Abstract

A large number of methods have been developed for assessing glaucomatous visual field progression, but their properties have not yet been systematically evaluated. In this systematic literature review, we summarize the evidence base for selecting a method by providing answers to ten relevant questions on the variety, validity and reproducibility of methods. In total, we found 301 different methods in 412 articles. The majority of studies (54%) used the Humphrey Field Analyzer. No data have been published about the reproducibility of methods. Although there is no gold standard to assess glaucomatous visual field progression, we found evidence on validity for 48 different methods. Some methods were less capable of distinguishing between progressive and nonprogressive patients. Choosing among twelve methods is supported by some evidence of their validity. These methods still differ in sensitivity, specificity and predictive values of test results within studies comparing several methods. In conclusion, the current evidence base is not perfect. A selection should be made from a limited number of methods, according to the clinical purpose of progression assessment. Methods that quantify the rate of visual field progression seem to be the most appropriate for guiding subsequent medical actions in individual patients. Future studies should investigate whether using one method to monitor patients is superior to another method in preventing loss of quality of life.
© 2011 The Authors. Acta Ophthalmologica © 2011 Acta Ophthalmologica Scandinavica Foundation.

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Year:  2011        PMID: 21812943     DOI: 10.1111/j.1755-3768.2011.02206.x

Source DB:  PubMed          Journal:  Acta Ophthalmol        ISSN: 1755-375X            Impact factor:   3.761


  5 in total

1.  Perimetric progression using the Visual Field Index and the Advanced Glaucoma Intervention Study score and its clinical correlations.

Authors:  Juan Gros-Otero; Miguel Castejón; Javier Paz-Moreno; Dimitrios Mikropoulos; Miguel Teus
Journal:  J Optom       Date:  2014-09-01

2.  Novel Machine-Learning Based Framework Using Electroretinography Data for the Detection of Early-Stage Glaucoma.

Authors:  Mohan Kumar Gajendran; Landon J Rohowetz; Peter Koulen; Amirfarhang Mehdizadeh
Journal:  Front Neurosci       Date:  2022-05-04       Impact factor: 5.152

3.  New insights into measurement variability in glaucomatous visual fields from computer modelling.

Authors:  Richard A Russell; David F Garway-Heath; David P Crabb
Journal:  PLoS One       Date:  2013-12-30       Impact factor: 3.240

4.  Comparison of Visual Field Point-Wise Event-Based and Global Trend-Based Analysis for Detecting Glaucomatous Progression.

Authors:  Zhichao Wu; Felipe A Medeiros
Journal:  Transl Vis Sci Technol       Date:  2018-08-27       Impact factor: 3.283

5.  Classification and Statistical Trend Analysis in Detecting Glaucomatous Visual Field Progression.

Authors:  Cristiana Valente; Elisa D'Alessandro; Michele Iester
Journal:  J Ophthalmol       Date:  2019-05-28       Impact factor: 1.909

  5 in total

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