Frequency of visual field testing when monitoring patients newly diagnosed with glaucoma: mixed methods and modelling

Crabb, David P.; Russell, Richard A.; Malik, Rizwan; Anand, Nitin; Baker, Helen; Boodhna, Trishal; Bronze, Carol; Fung, S.; Garway-Heath, David; Glen, Fiona; Hernández, Rodolfo; Kirwan, James; Lemer, Claire; McNaught, Andrew; Viswanathan, Ananth C.

doi:10.3310/hsdr02270

Cited by 47 publications

(53 citation statements)

References 112 publications

(193 reference statements)

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“…Recent research evidence, reflected in clinical guidelines, has suggested that more frequent VF testing would help to identify rapidly progressing patients and this would have both clinical and potential health economic benefits. 32,33 At the same time, this would require a shift in resources, clinician opinion, and patient views about automated perimetry. 34,35 This study clearly shows a worse rate of VF loss was associated with older age and, albeit to a lesser extent, level of VF damage at diagnosis.…”

Section: Discussionmentioning

confidence: 99%

Are rates of vision loss in patients in English glaucoma clinics slowing down over time? Trends from a decade of data

Boodhna

Saunders

Crabb

2015

Eye

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Purpose To examine changes in rates of visual field (VF) progression in patients attending a sample of glaucoma clinics in England between 1999 and 2012. Methods An archive of 473 252 Humphrey VFs recorded across the UK was retrospectively examined. Distribution of rates recorded in the first half of the decade was compared with the second. The relationship between age and severity of MD loss at baseline with rates of loss and frequency of testing was examined. Results VF series from 18 926 eyes were analysed. Median rate of MD loss for the period before and after 2003 was − 0.11 and − 0.06 dB/year, respectively, but the proportion of eyes with medium or fast rates of MD loss remained constant. Median rate of MD loss in older (470 years) eyes was faster than that observed in younger (o60 years) eyes (−0.21 compared with − 0.01 dB/ year). Median rate of loss did not vary with severity of MD loss at baseline. Frequency of testing, typically carried out annually, did not vary by age, rate of loss or disease severity. Conclusions VFs of eyes treated in the first half of the decade deteriorated more rapidly than those in the second half. Several factors might explain these differences but average effects were small and there was no reduction in the proportion of rapidly progressing eyes over the decade. Older age and, to a lesser extent, worse VF damage at diagnosis are indicators for faster VF loss in clinics, but frequency of VF testing was similar for all patients.

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Section: Discussionmentioning

confidence: 99%

Are rates of vision loss in patients in English glaucoma clinics slowing down over time? Trends from a decade of data

Boodhna

Saunders

Crabb

2015

Eye

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“…At the moment, certainly in England, there is a tendency to have a 'one size fits all' approach to monitoring the diagnosed patient. 18 We ought to think more about the use of monitoring resources in glaucoma, especially in those patients who present with more advanced disease as compared with those with little visual loss at diagnosis, or those with ocular hypertension only. Moreover, there appears to be a 'research obsession' with 'pre-perimetric' glaucoma and newer detection technology, but are these really required to prevent visual impairment?…”

Section: Discussionmentioning

confidence: 99%

“…16,17 Allocating perimetry resources correctly and installing perimetry at the centre of glaucoma follow-up is also a challenge. 18 Next, how do we best summarise visual field loss and the worsening of visual field loss? This is often done with a number (or series of numbers).…”

Section: The Burden Of Glaucomamentioning

confidence: 99%

A view on glaucoma—are we seeing it clearly?

Crabb

2015

Eye

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Successful clinical management of glaucoma should not simply be about control of intraocular pressure, but must equate to correct decisions about intensifying treatment when patients are at risk of developing 'visual disability'. Yet little is known about what visual field defects, at different stages of glaucoma, specifically affect patients' abilities to perform everyday visual tasks. One way to do this is to measure patient performance in tasks in a lab setting. Another way is to ask patients themselves. The latter can be revealing and demystify views about how patients perceive the world. This short commentary highlights some of the current research in this area.

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“…l Evaluation of patient experience and the clinical effectiveness and cost-effectiveness of including imaging outcomes with VF testing in managing patients with glaucoma. 12 Patient focus groups indicated that, although patients do not like VF testing, they accept it as a critical part of their care. This research explored the 'diagnostic gain' from including imaging data.…”

Section: (4-5)mentioning

confidence: 99%

“…10,11 The requirement for frequent VF tests over extended periods of time results in delayed identification of vision loss and is a burden to patients and the NHS. 12 The vision loss in glaucoma is a consequence of structural damage to the ONH. 13 Nerve cells in the retina (retinal ganglion cells) transmit light sensitivity information to the brain through fibres that form a layer on the retinal surface, known as the RNFL.…”

Section: Trial Registrationmentioning

confidence: 99%

Combining optical coherence tomography with visual field data to rapidly detect disease progression in glaucoma: a diagnostic accuracy study

Garway-Heath

Zhu

Qian

et al. 2018

Health Technol Assess

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Background Progressive optic nerve damage in glaucoma results in vision loss, quantifiable with visual field (VF) testing. VF measurements are, however, highly variable, making identification of worsening vision (‘progression’) challenging. Glaucomatous optic nerve damage can also be measured with imaging techniques such as optical coherence tomography (OCT). Objective To compare statistical methods that combine VF and OCT data with VF-only methods to establish whether or not these allow (1) more rapid identification of glaucoma progression and (2) shorter or smaller clinical trials. Design Method ‘hit rate’ (related to sensitivity) was evaluated in subsets of the United Kingdom Glaucoma Treatment Study (UKGTS) and specificity was evaluated in 72 stable glaucoma patients who had 11 VF and OCT tests within 3 months (the RAPID data set). The reference progression detection method was based on Guided Progression Analysis™ (GPA) Software (Carl Zeiss Meditec Inc., Dublin, CA, USA). Index methods were based on previously described approaches [Analysis with Non-Stationary Weibull Error Regression and Spatial enhancement (ANSWERS), Permutation analyses Of Pointwise Linear Regression (PoPLR) and structure-guided ANSWERS (sANSWERS)] or newly developed methods based on Permutation Test (PERM), multivariate hierarchical models with multiple imputation for censored values (MaHMIC) and multivariate generalised estimating equations with multiple imputation for censored values (MaGIC). Setting Ten university and general ophthalmology units (UKGTS) and a single university ophthalmology unit (RAPID). Participants UKGTS participants were newly diagnosed glaucoma patients randomised to intraocular pressure-lowering drops or placebo. RAPID participants had glaucomatous VF loss, were on treatment and were clinically stable. Interventions 24-2 VF tests with the Humphrey Field Analyzer and optic nerve imaging with time-domain (TD) Stratus OCT™ (Carl Zeiss Meditec Inc., Dublin, CA, USA). Main outcome measures Criterion hit rate and specificity, time to progression, future VF prediction error, proportion progressing in UKGTS treatment groups, hazard ratios (HRs) and study sample size. Results Criterion specificity was 95% for all tests; the hit rate was 22.2% for GPA, 41.6% for PoPLR, 53.8% for ANSWERS and 61.3% for sANSWERS (all comparisons p ≤ 0.042). Mean survival time (weeks) was 93.6 for GPA, 82.5 for PoPLR, 72.0 for ANSWERS and 69.1 for sANSWERS. The median prediction errors (decibels) when the initial trend was used to predict the final VF were 3.8 (5th to 95th percentile 1.7 to 7.6) for PoPLR, 3.0 (5th to 95th percentile 1.5 to 5.7) for ANSWERS and 2.3 (5th to 95th percentile 1.3 to 4.5) for sANSWERS. HRs were 0.57 [95% confidence interval (CI) 0.34 to 0.90; p = 0.016] for GPA, 0.59 (95% CI 0.42 to 0.83; p = 0.002) for PoPLR, 0.76 (95% CI 0.56 to 1.02; p = 0.065) for ANSWERS and 0.70 (95% CI 0.53 to 0.93; p = 0.012) for sANSWERS. Sample size estimates were not reduced using methods including OCT data. PERM hit rates were between 8.3% and 17.4%. Treatment effects were non-significant in MaHMIC and MaGIC analyses; statistical significance was altered little by incorporating imaging. Limitations TD OCT is less precise than current imaging technology; current OCT technology would likely perform better. The size of the RAPID data set limited the precision of criterion specificity estimates. Conclusions The sANSWERS method combining VF and OCT data had a higher hit rate and identified progression more quickly than the reference and other VF-only methods, and produced more accurate estimates of the progression rate, but did not increase treatment effect statistical significance. Similar studies with current OCT technology need to be undertaken and the statistical methods need refinement. Trial registration Current Controlled Trials ISRCTN96423140. Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 22, No. 4. See the NIHR Journals Library website for further project information. Data analysed in the study were from the UKGTS. Funding for the UKGTS was provided through an unrestricted investigator-initiated research grant from Pfizer Inc. (New York, NY, USA), with supplementary funding from the NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK. Imaging equipment loans were made by Heidelberg Engineering, Carl Zeiss Meditec and Optovue (Fremont, CA, USA). Pfizer, Heidelberg Engineering, Carl Zeiss Meditec and Optovue had no input into the design, conduct, analysis or reporting of any of the UKGTS findings or this work. The sponsor for both the UKGTS and RAPID data collection was Moorfields Eye Hospital NHS Foundation Trust. David F Garway-Heath, Tuan-Anh Ho and Haogang Zhu are partly funded by the NIHR Biomedical Research Centre based at Moorfields Eye Hospital and UCL Institute of Ophthalmology. David F Garway-Heath’s chair at University College London (UCL) is supported by funding from the International Glaucoma Association.

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Frequency of visual field testing when monitoring patients newly diagnosed with glaucoma: mixed methods and modelling

Cited by 47 publications

References 112 publications

Are rates of vision loss in patients in English glaucoma clinics slowing down over time? Trends from a decade of data

Are rates of vision loss in patients in English glaucoma clinics slowing down over time? Trends from a decade of data

A view on glaucoma—are we seeing it clearly?

Combining optical coherence tomography with visual field data to rapidly detect disease progression in glaucoma: a diagnostic accuracy study

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