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Prediction of Visual Field Progression in Myopic Normal Tension Glaucoma Using a Nomogram-Based Model.

Ji Eun Song1, Eun Ji Lee2, Tae-Woo Kim2

  • 1Department of Ophthalmology, Kangwon National University Hospital, Kangwon National University College of Medicine, Chuncheon 24289, Republic of Korea.

Journal of Clinical Medicine
|April 14, 2026
PubMed
Summary
This summary is machine-generated.

A new nomogram predicts visual field progression in myopic normal-tension glaucoma (mNTG) using structural and vascular markers. This tool aids early identification of high-risk patients for personalized treatment.

Keywords:
myopianomogramnormal tension glaucomaprediction

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Area of Science:

  • Ophthalmology
  • Glaucoma Research
  • Medical Imaging

Background:

  • Myopic normal-tension glaucoma (mNTG) poses a risk for visual field (VF) progression.
  • Accurate prediction of VF progression is crucial for managing mNTG.
  • Integrating structural and vascular parameters may improve predictive models.

Purpose of the Study:

  • To develop a nomogram-based prediction tool for estimating VF progression in mNTG.
  • To integrate key structural and vascular parameters into the predictive model.
  • To identify independent predictors of VF progression in mNTG patients.

Main Methods:

  • Retrospective cohort study of 150 eyes from 75 treatment-naïve mNTG patients.
  • Evaluation of lamina cribrosa steepness index (LCSI) and choroidal microvascular dropout (cMvD) using OCT and OCTA.
  • Development of a predictive nomogram using clustered logistic regression and bootstrap iterations.

Main Results:

  • 38.7% of eyes exhibited VF progression over a minimum five-year follow-up.
  • Steeper LCSI and presence of parapapillary cMvD were significant independent predictors of progression.
  • The nomogram demonstrated high predictive accuracy (AUC 0.922, C-index ~0.92).

Conclusions:

  • A nomogram integrating LCSI and cMvD can predict VF progression in mNTG.
  • This tool facilitates individualized risk assessment and personalized treatment planning.
  • Early identification of high-risk patients can optimize long-term visual outcomes.