title: Identifying "preperimetric" glaucoma in standard automated perimetry visual fields.
abstract: OBJECTIVE
  To compare the visual fields (VFs) of preperimetric open angle glaucoma (OAG) patients (preperimetric glaucoma VFs, PPGVFs) with the VFs of healthy eyes, and to discriminate these two groups by using the Random Forests machine-learning method.
  
  
  METHODS
  All VFs before a first diagnosis of manifest glaucoma (Anderson-Patella's criteria) were classified as PPGVFs. Series of VFs were obtained with the Humphrey Field Analyzer 30-2 program from 171 PPGVFs from 53 eyes in 51 OAG or OAG suspect patients and 108 healthy eyes of 87 normal subjects. The area under the receiver operating characteristic curve (AROC) in discriminating between PPGVFs and healthy VFs was calculated by using the Random Forests method, with 52 total deviation (TD) values, mean deviation (MD), and pattern standard deviation (PSD) as predictors.
  
  
  RESULTS
  There was a significant difference in MD between healthy VFs and PPGVFs (-0.03 ± 1.11 and -0.91 ± 1.56 dB [mean ± standard deviation], respectively; P < 0.001, linear mixed model) and in PSD (1.56 ± 0.33 and 1.97 ± 0.43 dB, respectively; P < 0.001). A significant difference was observed in the TD values between healthy VFs and PPGVFs at 25 (P < 0.001) of 52 test points (linear mixed model). The AROC obtained by using the Random Forests method was 79.0% (95% confidence interval, 73.5%-84.5%).
  
  
  CONCLUSIONS
  Differences exist between healthy VFs and VFs of preperimetric glaucoma eyes, which go on to develop manifest glaucoma; these two groups of VFs could be well distinguished by using the Random Forests classifier.
authors.affiliation: Department of Ophthalmology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
authors.forename: Ryo
authors.initials: R
authors.lastname: Asaoka
authors.affiliation: Tajimi Iwase Eye Clinic, Tajimi, Japan.
authors.forename: Aiko
authors.initials: A
authors.lastname: Iwase
authors.affiliation: Department of Ophthalmology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan Department of Ophthalmology, Graduate School of Medical Science, Kitasato University, Kanagawa, Japan.
authors.forename: Kazunori
authors.initials: K
authors.lastname: Hirasawa
authors.affiliation: Department of Ophthalmology, The University of Tokyo Graduate School of Medicine, Tokyo, Japan.
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Murata
authors.affiliation: Kanto Central Hospital of the Mutual Aid Association of Public School Teachers, Tokyo, Japan.
authors.forename: Makoto
authors.initials: M
authors.lastname: Araie
mesh_terms: D000368:Aged; D016022:Case-Control Studies; D005260:Female; D005901:Glaucoma / Q000175:diagnosis*; D006801:Humans; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D058609:Visual Field Tests / Q000379:methods*; D014794:Visual Fields
keywords: Random Forests method; glaucoma; preperimetric stage; visual field