Comparing the Accuracy of Peripapillary OCT Scans and Visual Fields to Detect Glaucoma Worsening

Multiple (frontloaded) visual field tests increase identification of very slow mean deviation progression in glaucoma

OBJECTIVE

To determine the effect of frontloading (multiple) visual field (VF) tests at the same visit for detecting mean deviation (MD) change in slowly progressive glaucoma.

METHODS

This was a computer simulation study. Baseline MD (range, 0 to -12 dB) and progression rate (range, 0 to -0.4 dB/year, non-inclusive) were generated for 10,000 patients. Each patient had 6 simulated "stable" baseline VF tests. Then follow-up VFs (up to 10 years) were generated by incorporating progression rate and within-visit and between-visit variability. The independent variables were number of VF tests per visit (one non-frontloaded or two frontloaded), VF reliability (100%, 85%, or 70%), repeat testing because of unreliable results (yes or no), and follow-up interval (6-monthly or yearly). The outcomes were detection of progression (MD slope that was negative and significant at p < 0.05), MD at detection, and number of years to detection.

RESULTS

Frontloading identified more progressors (62.7%-79.2%) compared with non-frontloading (31.0%-36.7%) at 10 years (p < 0.0001). Six-monthly follow-ups led to greater detection than yearly intervals. Progressors detected by both methods were detected by the non-frontloaded method sooner (up to 0.26 years), but this was small and not clinically significant (MD difference, 0.06 dB). An increase (less severe) in MD, an increase (slower) in progression rate, and an increase in SD of baseline VFs decreased the likelihood of detecting progression.

CONCLUSIONS

Frontloading VF tests at 6-monthly intervals improve detection rates of MD progression in slowly progressive glaucoma patients compared with performing 1 test per visit at yearly intervals.

Racial-ethnic disparities in concurrent rates of peripapillary & macular OCT parameters among a large glaucomatous clinical population

OBJECTIVES

To compare rates of change in peripapillary retinal nerve fibre layer (pRNFL) and macular ganglion cell-inner plexiform layer (mGCIPL) parameters among different race-ethnicities from a large electronic health record database of subjects with or suspected of glaucoma.

METHODS

In this retrospective cohort study, rates of change were obtained using joint longitudinal linear mixed models for eyes with ≥3 visits and ≥1 year of follow-up, adjusting for age, sex, intraocular pressure, central corneal thickness, and baseline pRNFL and mGCIPL thickness. Best linear unbiased predictor estimates of various parameters were stratified by baseline glaucoma severity and analysed by racial-ethnic group.

RESULTS

A total of 21,472 spectral domain optical coherence tomography (OCT) pRNFL scans and 14,431 mGCIPL scans from 2002 eyes were evaluated. A total of 200 (15.6%) and 601 (46.8%) subjects identified as non-Hispanic Black (NHB) and Hispanic, respectively. NHB eyes exhibited faster rates of change in pRNFL among glaucoma suspect (global pRNFL -0.57 ± 0.55 µm/year vs. -0.37 ± 0.62 µm/year among Hispanics, p < 0.001), mild glaucoma (superior pRNFL quadrant -1.20 ± 1.06 µm/year vs. -0.75 ± 1.51 µm/year among non-Hispanic Whites (NHW), p = 0.043), and moderate glaucoma eyes (superior pRNFL quadrant -1.31 ± 1.49 µm/year vs. -0.52 ± 1.26 µm/year among Hispanics, p = 0.003). NHB eyes exhibited faster rates of mGCIPL loss corresponding to pRNFL rates. Global pRNFL and mGCIPL rates were strongly correlated (R2 = 0.70).

CONCLUSIONS

Adjusted rates of pRNFL and mGCIPL loss significantly differed between racial-ethnic groups when stratified by glaucoma severity, with faster rates among NHB patients. These differences highlight key racial-ethnic disparities in adjusted rates of glaucoma OCT parameters.

Visual field testing in glaucoma using the Swedish Interactive Thresholding Algorithm (SITA)

The Swedish Interactive Thresholding Algorithm (SITA) is the main measurement acquisition algorithm used on the Humphrey Field Analyser, the most commonly used instrument for visual field (VF) assessment worldwide. We compare the sensitivity outputs and reliability parameters of the three currently available SITA algorithms-SITA Standard (SS), Fast (SF), and Faster (SFR), with a focus on the newly released SFR and the 24-2C test grid. SFR displays similar sensitivity outputs to SS and SF, but may not be interchangeable with SS in eyes with more severe VF loss. The reliability metric with the greatest impact on VF reliability is the level of false positives, although the recommended 15 % false positive cut off may be inappropriate as a threshold for judging whether a test is reliable and should be included for use in SFR. Finally, the 24-2C grid may be useful in flagging the presence of a clustered central VF defect, while the 10-2 grid can be used to more comprehensively characterize central field defects. We also discuss strategies to improve testing frequency in clinical practice.

Time to Glaucoma Progression Detection by Optical Coherence Tomography and Visual Field in Glaucoma Individuals of African Descent

PURPOSE

To examine the time to glaucoma progression detection by retinal nerve fiber layer thickness (RNFLT) and visual field (VF) among individuals of African descent (AD).

DESIGN

Retrospective cohort study.

METHODS

This multicenter study included eyes with glaucoma from individuals of AD from the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study with ≥2 years/5 visits of optic nerve head RNFLT and 24-2 VF examinations.

INTERVENTION OR OBSERVATION PROCEDURE

Rates of VF mean deviation (MD) and RNFLT worsening were analyzed using linear mixed-effects models, and longitudinal data were simulated using the variability estimates.

MAIN OUTCOME MEASURE

The simulated time to detect trend-based glaucoma progression was assessed with assumed rates of VF MD and RNFLT change derived from the cohort (25th, 50th, and 75th percentile [as p25, median, and p75] slopes and mean slopes). Severity-stratified analyses were also performed.

RESULTS

We included 184 eyes from 128 subjects of AD (mean baseline age 63.4 years; VF MD -4.2 dB; RNFLT 80.2 µm). The p25, median, mean, and p75 rates of change were -0.43, -1.01, -1.15, and -1.64 µm per year for RNFLT, and 0.00, -0.21, -0.30, and -0.51 dB per year for VF MD, respectively. Compared with VF MD, RNFLT showed an overall shorter mean time to progression detection (time difference 0.4-1.7 years), with the mean rates showing the largest difference (RNFLT 5.2 years vs VF MD 6.9 years). Similarly, we found an overall shorter time to detect RNFLT progression, compared with that of VF MD progression, in eyes with mild glaucoma (≥1 year earlier) and in eyes with moderate to advanced glaucoma (∼0.5 year earlier).

CONCLUSIONS

Computer simulation showed a potentially shorter time to detect RNFLT progression than VF MD progression in eyes from individuals of AD. Our findings support the importance of using RNFLT to detect progressive glaucoma in individuals of AD.

Long-term variability of retinal nerve fibre layer thickness measurement in patients with glaucoma of African and European descents

BACKGROUND

To examine long-term retinal nerve fibre layer thickness (RNFLT) variability and associated clinical factors in African (AD) and European descent (ED) individuals with glaucoma.

METHODS

This retrospective cohort study included glaucoma eyes of AD and ED from Diagnostic Innovations in Glaucoma Study/The African Descent and Glaucoma Evaluation Study with ≥4 visits/2 years of follow-up. We calculated optic nerve head RNFLT variability per-examination/visit as the absolute error of its residuals across follow-up. Full, baseline and parsimonious linear-mixed models were fit to evaluate the effects of clinical factors (demographics and ocular characteristics, prior/intervening glaucoma surgeries and cataract extraction (CE), RNFLT thinning rate, scan quality, visit/testing frequency, etc) on RNFLT variability in both races.

RESULTS

There were 376 and 625 eyes (226 and 349 participants) of AD and ED, and the mean (95% CI) RNFLT variability was 1.62 (1.52, 1.71) µm and 1.42 (1.34, 1.50) µm, respectively (p=0.002). AD and ED had some shared predictors of RNFLT variability, including intraocular pressure fluctuation and scan quality, although the effects varied (p<0.05). In both races, intervening CE was most strongly correlated with higher RNFLT variability (β: 0.24-0.92, p<0.05). After excluding eyes with intervening CE, RNFLT variability was reduced and the small racial difference was no longer significant (AD: 1.40 (1.31, 1.48) µm vs ED: 1.34 (1.27, 1.40) µm; p=0.280).

CONCLUSIONS

Although some predictors were identified, long-term RNFLT variability appeared small for both AD and ED eyes. Moreover, the racial difference did not remain once intervening CE, the strongest predictor of variability, was eliminated. Our findings inform on strategies to optimise structural assessment and suggest that, when accounting for relevant factors, RNFLT is reliable across races.

Visual Field Testing Frequency and Associations in Children With Glaucoma

PRCIS

Children with glaucoma had an average of 1.3 visual field tests per year. Self-reported black and multiracial patients had lower visual field testing rates, whereas older children with better visual acuity had more frequent testing.

PURPOSE

To evaluate frequency of visual field (VF) testing in children with glaucoma and identify characteristics associated with VF frequency.

METHODS

A retrospective cohort study of 82 children 6-18 years of age with glaucoma seen between August 2018 and May 2023. Patients were divided into those who had ≥1 VF test (303 VF tests of 61 children) and 0 VFs (21 children). Eyes were excluded if best corrected visual acuity (BCVA) was counting fingers or worse. Characteristics obtained included age, self-reported race and ethnicity, sex, primary language, glaucoma diagnosis, distance to provider, office visit frequency, follow-up compliance, insurance type, and BCVA. The main outcome measure was VF testing frequency.

RESULTS

Among children with ≥1 VF test, mean age at first VF was 11.8±2.8 years, mean number of VF/year was 1.3±0.8, and 44.9% of all VFs were reliable. Thirty nine percent of patients underwent <1 VF/year, 45.9% ≥1 to <2 VFs/year, and 14.8% ≥2 VF/year. Children who were black or multiracial had significantly lower VF testing frequency [estimated difference (ED) -1.2 (95% CI, -2.0 to -0.4, P =0.002) and ED -1.3 (95% CI, -2.2 to -0.3, P =0.008), respectively]. Better visual acuity and greater office visit frequency were significantly associated with higher VF testing frequency [ED 0.052 (95% CI, 0.001-0.103, P =0.045) and ED 0.2 (95% CI, 0.1-0.3, P <0.001), respectively].

CONCLUSIONS

Most children had between 1 and 2 VF/year, although less than half of all VFs were reliable. Ophthalmologists should consider barriers to care in glaucoma monitoring.

Opportunities for Improving Glaucoma Clinical Trials via Deep Learning-Based Identification of Patients with Low Visual Field Variability

PURPOSE

Develop and evaluate the performance of a deep learning model (DLM) that forecasts eyes with low future visual field (VF) variability, and study the impact of using this DLM on sample size requirements for neuroprotective trials.

DESIGN

Retrospective cohort and simulation study.

METHODS

We included 1 eye per patient with baseline reliable VFs, OCT, clinical measures (demographics, intraocular pressure, and visual acuity), and 5 subsequent reliable VFs to forecast VF variability using DLMs and perform sample size estimates. We estimated sample size for 3 groups of eyes: all eyes (AE), low variability eyes (LVE: the subset of AE with a standard deviation of mean deviation [MD] slope residuals in the bottom 25th percentile), and DLM-predicted low variability eyes (DLPE: the subset of AE predicted to be low variability by the DLM). Deep learning models using only baseline VF/OCT/clinical data as input (DLM1), or also using a second VF (DLM2) were constructed to predict low VF variability (DLPE1 and DLPE2, respectively). Data were split 60/10/30 into train/val/test. Clinical trial simulations were performed only on the test set. We estimated the sample size necessary to detect treatment effects of 20% to 50% in MD slope with 80% power. Power was defined as the percentage of simulated clinical trials where the MD slope was significantly worse from the control. Clinical trials were simulated with visits every 3 months with a total of 10 visits.

RESULTS

A total of 2817 eyes were included in the analysis. Deep learning models 1 and 2 achieved an area under the receiver operating characteristic curve of 0.73 (95% confidence interval [CI]: 0.68, 0.76) and 0.82 (95% CI: 0.78, 0.85) in forecasting low VF variability. When compared with including AE, using DLPE1 and DLPE2 reduced sample size to achieve 80% power by 30% and 38% for 30% treatment effect, and 31% and 38% for 50% treatment effect.

CONCLUSIONS

Deep learning models can forecast eyes with low VF variability using data from a single baseline clinical visit. This can reduce sample size requirements, and potentially reduce the burden of future glaucoma clinical trials.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Validation of a Wearable Virtual Reality Perimeter for Glaucoma Staging, The NOVA Trial: Novel Virtual Reality Field Assessment

Purpose

Compare estimated sensitivities of SITA-Standard to the RATA-Standard algorithm of the Radius virtual reality perimeter (VRP), and measure concordance in glaucoma staging.

Methods

One hundred adult glaucoma patients-half with suspect or mild glaucoma, and half with moderate or severe-from five clinics performed four 24-2 visual field tests during a single visit, two with the Humphrey Field Analyzer (HFA) and two with Radius, in randomized order: HRHR or RHRH. Only one eye was tested per participant. We used the Wilcoxon rank sum test with Bonferroni correction to compare distributions of estimated sensitivities across all 54 test locations over the 15 to 40 dB measurement range of the Radius. Weighted kappa measured concordance in glaucoma staging between two masked glaucoma experts using Medicare definitions of severity.

Results

A total of 62 OD and 38 OS eyes were tested. Estimated sensitivities for SITA-Standard and RATA-Standard were not significantly different for OD, but were for OS-likely because of SITA-Standard OD and OS being significantly different in our sample, but not for RATA-Standard. Low agreement was observed between 15 to 22 dB. Concordance in glaucoma staging was high for both graders: kappa = 0.91 and kappa = 0.93. Average test duration was 298 seconds for RATA-Standard and 341 seconds for SITA-Standard. The correlation in mean deviation was 0.94.

Conclusions

Estimated sensitivities of RATA-Standard are comparable to SITA-Standard between 23 to 40 dB with high concordance in glaucoma staging.

Translational Relevance

Radius VRP is statistically noninferior to HFA when staging glaucoma using Medicare definitions.