Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma

Mengyu Wang, Louis R. Pasquale, Lucy Q. Shen, Michael V. Boland, Sarah Wellik, Carlos Gustavo De Moraes, Jonathan S. Myers, Hui Wang, Neda Baniasadi, Dian Li, Rafaella Nascimento E. Silva, Peter J. Bex, Tobias Elze

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Purpose: To develop a visual field (VF) feature model to predict the reversal of glaucoma hemifield test (GHT) results to within normal limits (WNL) after 2 consecutive outside normal limits (ONL) results. Design: Retrospective cohort study. Participants: Visual fields of 44 503 eyes from 26 130 participants. Methods: Eyes with 3 or more consecutive reliable VFs measured with the Humphrey Field Analyzer (Swedish interactive threshold algorithm standard 24-2) were included. Eyes with ONL GHT results for the 2 baseline VFs were selected. We extracted 3 categories of VF features from the baseline tests: (1) VF global indices (mean deviation [MD] and pattern standard deviation), (2) mismatch between baseline VFs, and (3) VF loss patterns (archetypes). Logistic regression was applied to predict the GHT results reversal. Cross-validation was applied to evaluate the model on testing data by the area under the receiver operating characteristic curve (AUC). We ascertained clinical glaucoma status on a patient subset (n = 97) to determine the usefulness of our model. Main Outcome Measures: Predictive models for GHT results reversal using VF features. Results: For the 16 604 eyes with 2 initial ONL results, the prevalence of a subsequent WNL result increased from 0.1% for MD < -12 dB to 13.8% for MD ≥-3 dB. Compared with models with VF global indices, the AUC of predictive models increased from 0.669 (MD ≥-3 dB) and 0.697 (-6 dB ≤ MD < -3 dB) to 0.770 and 0.820, respectively, by adding VF mismatch features and computationally derived VF archetypes (P < 0.001 for both). The GHT results reversal was associated with a large mismatch between baseline VFs. Moreover, the GHT results reversal was associated more with VF archetypes of nonglaucomatous loss, severe widespread loss, and lens rim artifacts. For a subset of 97 eyes, using our model to predict absence of glaucoma based on clinical evidence after 2 ONL results yielded significantly better prediction accuracy (87.7%; P < 0.001) than predicting GHT results reversal (68.8%) with a prescribed specificity 67.7%. Conclusions: Using VF features may predict the GHT results reversal to WNL after 2 consecutive ONL results.

Original languageEnglish (US)
JournalOphthalmology
DOIs
StateAccepted/In press - Jan 1 2017

Fingerprint

Visual Field Tests
Visual Fields
Glaucoma
Area Under Curve
ROC Curve
Artifacts
Lenses
Cohort Studies
Retrospective Studies
Logistic Models
Outcome Assessment (Health Care)

ASJC Scopus subject areas

  • Ophthalmology

Cite this

Wang, M., Pasquale, L. R., Shen, L. Q., Boland, M. V., Wellik, S., De Moraes, C. G., ... Elze, T. (Accepted/In press). Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma. Ophthalmology. https://doi.org/10.1016/j.ophtha.2017.09.021

Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma. / Wang, Mengyu; Pasquale, Louis R.; Shen, Lucy Q.; Boland, Michael V.; Wellik, Sarah; De Moraes, Carlos Gustavo; Myers, Jonathan S.; Wang, Hui; Baniasadi, Neda; Li, Dian; Silva, Rafaella Nascimento E.; Bex, Peter J.; Elze, Tobias.

In: Ophthalmology, 01.01.2017.

Research output: Contribution to journalArticle

Wang, M, Pasquale, LR, Shen, LQ, Boland, MV, Wellik, S, De Moraes, CG, Myers, JS, Wang, H, Baniasadi, N, Li, D, Silva, RNE, Bex, PJ & Elze, T 2017, 'Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma', Ophthalmology. https://doi.org/10.1016/j.ophtha.2017.09.021
Wang, Mengyu ; Pasquale, Louis R. ; Shen, Lucy Q. ; Boland, Michael V. ; Wellik, Sarah ; De Moraes, Carlos Gustavo ; Myers, Jonathan S. ; Wang, Hui ; Baniasadi, Neda ; Li, Dian ; Silva, Rafaella Nascimento E. ; Bex, Peter J. ; Elze, Tobias. / Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma. In: Ophthalmology. 2017.
@article{9dd5b04906bd4a0aaa3fd9b845d63a5f,
title = "Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma",
abstract = "Purpose: To develop a visual field (VF) feature model to predict the reversal of glaucoma hemifield test (GHT) results to within normal limits (WNL) after 2 consecutive outside normal limits (ONL) results. Design: Retrospective cohort study. Participants: Visual fields of 44 503 eyes from 26 130 participants. Methods: Eyes with 3 or more consecutive reliable VFs measured with the Humphrey Field Analyzer (Swedish interactive threshold algorithm standard 24-2) were included. Eyes with ONL GHT results for the 2 baseline VFs were selected. We extracted 3 categories of VF features from the baseline tests: (1) VF global indices (mean deviation [MD] and pattern standard deviation), (2) mismatch between baseline VFs, and (3) VF loss patterns (archetypes). Logistic regression was applied to predict the GHT results reversal. Cross-validation was applied to evaluate the model on testing data by the area under the receiver operating characteristic curve (AUC). We ascertained clinical glaucoma status on a patient subset (n = 97) to determine the usefulness of our model. Main Outcome Measures: Predictive models for GHT results reversal using VF features. Results: For the 16 604 eyes with 2 initial ONL results, the prevalence of a subsequent WNL result increased from 0.1{\%} for MD < -12 dB to 13.8{\%} for MD ≥-3 dB. Compared with models with VF global indices, the AUC of predictive models increased from 0.669 (MD ≥-3 dB) and 0.697 (-6 dB ≤ MD < -3 dB) to 0.770 and 0.820, respectively, by adding VF mismatch features and computationally derived VF archetypes (P < 0.001 for both). The GHT results reversal was associated with a large mismatch between baseline VFs. Moreover, the GHT results reversal was associated more with VF archetypes of nonglaucomatous loss, severe widespread loss, and lens rim artifacts. For a subset of 97 eyes, using our model to predict absence of glaucoma based on clinical evidence after 2 ONL results yielded significantly better prediction accuracy (87.7{\%}; P < 0.001) than predicting GHT results reversal (68.8{\%}) with a prescribed specificity 67.7{\%}. Conclusions: Using VF features may predict the GHT results reversal to WNL after 2 consecutive ONL results.",
author = "Mengyu Wang and Pasquale, {Louis R.} and Shen, {Lucy Q.} and Boland, {Michael V.} and Sarah Wellik and {De Moraes}, {Carlos Gustavo} and Myers, {Jonathan S.} and Hui Wang and Neda Baniasadi and Dian Li and Silva, {Rafaella Nascimento E.} and Bex, {Peter J.} and Tobias Elze",
year = "2017",
month = "1",
day = "1",
doi = "10.1016/j.ophtha.2017.09.021",
language = "English (US)",
journal = "Ophthalmology",
issn = "0161-6420",
publisher = "Elsevier Inc.",

}

TY - JOUR

T1 - Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma

AU - Wang, Mengyu

AU - Pasquale, Louis R.

AU - Shen, Lucy Q.

AU - Boland, Michael V.

AU - Wellik, Sarah

AU - De Moraes, Carlos Gustavo

AU - Myers, Jonathan S.

AU - Wang, Hui

AU - Baniasadi, Neda

AU - Li, Dian

AU - Silva, Rafaella Nascimento E.

AU - Bex, Peter J.

AU - Elze, Tobias

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Purpose: To develop a visual field (VF) feature model to predict the reversal of glaucoma hemifield test (GHT) results to within normal limits (WNL) after 2 consecutive outside normal limits (ONL) results. Design: Retrospective cohort study. Participants: Visual fields of 44 503 eyes from 26 130 participants. Methods: Eyes with 3 or more consecutive reliable VFs measured with the Humphrey Field Analyzer (Swedish interactive threshold algorithm standard 24-2) were included. Eyes with ONL GHT results for the 2 baseline VFs were selected. We extracted 3 categories of VF features from the baseline tests: (1) VF global indices (mean deviation [MD] and pattern standard deviation), (2) mismatch between baseline VFs, and (3) VF loss patterns (archetypes). Logistic regression was applied to predict the GHT results reversal. Cross-validation was applied to evaluate the model on testing data by the area under the receiver operating characteristic curve (AUC). We ascertained clinical glaucoma status on a patient subset (n = 97) to determine the usefulness of our model. Main Outcome Measures: Predictive models for GHT results reversal using VF features. Results: For the 16 604 eyes with 2 initial ONL results, the prevalence of a subsequent WNL result increased from 0.1% for MD < -12 dB to 13.8% for MD ≥-3 dB. Compared with models with VF global indices, the AUC of predictive models increased from 0.669 (MD ≥-3 dB) and 0.697 (-6 dB ≤ MD < -3 dB) to 0.770 and 0.820, respectively, by adding VF mismatch features and computationally derived VF archetypes (P < 0.001 for both). The GHT results reversal was associated with a large mismatch between baseline VFs. Moreover, the GHT results reversal was associated more with VF archetypes of nonglaucomatous loss, severe widespread loss, and lens rim artifacts. For a subset of 97 eyes, using our model to predict absence of glaucoma based on clinical evidence after 2 ONL results yielded significantly better prediction accuracy (87.7%; P < 0.001) than predicting GHT results reversal (68.8%) with a prescribed specificity 67.7%. Conclusions: Using VF features may predict the GHT results reversal to WNL after 2 consecutive ONL results.

AB - Purpose: To develop a visual field (VF) feature model to predict the reversal of glaucoma hemifield test (GHT) results to within normal limits (WNL) after 2 consecutive outside normal limits (ONL) results. Design: Retrospective cohort study. Participants: Visual fields of 44 503 eyes from 26 130 participants. Methods: Eyes with 3 or more consecutive reliable VFs measured with the Humphrey Field Analyzer (Swedish interactive threshold algorithm standard 24-2) were included. Eyes with ONL GHT results for the 2 baseline VFs were selected. We extracted 3 categories of VF features from the baseline tests: (1) VF global indices (mean deviation [MD] and pattern standard deviation), (2) mismatch between baseline VFs, and (3) VF loss patterns (archetypes). Logistic regression was applied to predict the GHT results reversal. Cross-validation was applied to evaluate the model on testing data by the area under the receiver operating characteristic curve (AUC). We ascertained clinical glaucoma status on a patient subset (n = 97) to determine the usefulness of our model. Main Outcome Measures: Predictive models for GHT results reversal using VF features. Results: For the 16 604 eyes with 2 initial ONL results, the prevalence of a subsequent WNL result increased from 0.1% for MD < -12 dB to 13.8% for MD ≥-3 dB. Compared with models with VF global indices, the AUC of predictive models increased from 0.669 (MD ≥-3 dB) and 0.697 (-6 dB ≤ MD < -3 dB) to 0.770 and 0.820, respectively, by adding VF mismatch features and computationally derived VF archetypes (P < 0.001 for both). The GHT results reversal was associated with a large mismatch between baseline VFs. Moreover, the GHT results reversal was associated more with VF archetypes of nonglaucomatous loss, severe widespread loss, and lens rim artifacts. For a subset of 97 eyes, using our model to predict absence of glaucoma based on clinical evidence after 2 ONL results yielded significantly better prediction accuracy (87.7%; P < 0.001) than predicting GHT results reversal (68.8%) with a prescribed specificity 67.7%. Conclusions: Using VF features may predict the GHT results reversal to WNL after 2 consecutive ONL results.

UR - http://www.scopus.com/inward/record.url?scp=85034986968&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85034986968&partnerID=8YFLogxK

U2 - 10.1016/j.ophtha.2017.09.021

DO - 10.1016/j.ophtha.2017.09.021

M3 - Article

C2 - 29103791

AN - SCOPUS:85034986968

JO - Ophthalmology

JF - Ophthalmology

SN - 0161-6420

ER -