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Relationship between Intraocular Pressure Fluctuation and Visual Field Progression Rates in the United Kingdom Glaucoma Treatment Study

Rabiolo, A. ORCID: 0000-0002-7772-5929, Montesano, G. ORCID: 0000-0002-9148-2804, Crabb, D. P. ORCID: 0000-0001-8754-3902 , Garway-Heath, D. F., Bunce, C., Lascaratos, G., Amalfitano, F., Anand, N., Azuara-Blanco, A., Bourne, R. R., Broadway, D. C., Cunliffe, I. A., Diamond, J. P., Fraser, S. G., Ho, T. A., Martin, K. R., McNaught, A. I., Negi, A., Patel, K., Russell, R. A., Shah, A., Spry, P. G., Suzuki, K., White, E. T., Wormald, R. P., Xing, W. & Zeyen, T. G. (2024). Relationship between Intraocular Pressure Fluctuation and Visual Field Progression Rates in the United Kingdom Glaucoma Treatment Study. Ophthalmology, doi: 10.1016/j.ophtha.2024.02.008


Purpose: To investigate whether intraocular pressure (IOP) fluctuation is associated independently with the rate of visual field (VF) progression in the United Kingdom Glaucoma Treatment Study. Design: Randomized, double-masked, placebo-controlled multicenter trial. Participants: Participants with ≥5 VFs (213 placebo, 217 treatment). Methods: Associations between IOP metrics and VF progression rates (mean deviation [MD] and five fastest locations) were assessed with linear mixed models. Fluctuation variables were mean Pascal ocular pulse amplitude (OPA), standard deviation (SD) of diurnal Goldmann IOP (diurnal fluctuation), and SD of Goldmann IOP at all visits (long-term fluctuation). Fluctuation values were normalized for mean IOP to make them independent from the mean IOP. Correlated nonfluctuation IOP metrics (baseline, peak, mean, supine, and peak phasing IOP) were combined with principal component analysis, and principal component 1 (PC1) was included as a covariate. Interactions between covariates and time from baseline modeled the effect of the variables on VF rates. Analyses were conducted separately in the two treatment arms. Main Outcome Measures: Associations between IOP fluctuation metrics and rates of MD and the five fastest test locations. Results: In the placebo arm, only PC1 was associated significantly with the MD rate (estimate, –0.19 dB/year [standard error (SE), 0.04 dB/year]; P < 0.001), whereas normalized IOP fluctuation metrics were not. No variable was associated significantly with MD rates in the treatment arm. For the fastest five locations in the placebo group, PC1 (estimate, –0.58 dB/year [SE, 0.16 dB/year]; P < 0.001), central corneal thickness (estimate, 0.26 dB/year [SE, 0.10 dB/year] for 10 μm thicker; P = 0.01) and normalized OPA (estimate, –3.50 dB/year [SE, 1.04 dB/year]; P = 0.001) were associated with rates of progression; normalized diurnal and long-term IOP fluctuations were not. In the treatment group, only PC1 (estimate, –0.27 dB/year [SE, 0.12 dB/year]; P = 0.028) was associated with the rates of progression. Conclusions: No evidence supports that either diurnal or long-term IOP fluctuation, as measured in clinical practice, are independent factors for glaucoma progression; other aspects of IOP, including mean IOP and peak IOP, may be more informative. Ocular pulse amplitude may be an independent factor for faster glaucoma progression. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Publication Type: Article
Additional Information: © 2024. This manuscript version is made available under the CC-BY-NC-ND 4.0 license
Publisher Keywords: Linear mixed models, Ocular pulse amplitude, Risk factors, Visual field progression
Departments: School of Health & Psychological Sciences
School of Health & Psychological Sciences > Optometry & Visual Sciences
SWORD Depositor:
[thumbnail of OPHTHA-D-23-01872_R3.pdf]
Text - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

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