Katie Banister

Can Automated Imaging for Optic Disc and Retinal Nerve Fiber Layer Analysis Aid Glaucoma Detection

Purpose To compare the diagnostic performance of automated imaging for glaucoma. Design Prospective, direct comparison study. Participants Adults with suspected glaucoma or ocular hypertension referred to hospital eye services in the United Kingdom. Methods We evaluated 4 automated imaging test algorithms: the Heidelberg Retinal Tomography (HRT; Heidelberg Engineering, Heidelberg, Germany) glaucoma probability score (GPS), the HRT Moorfields regression analysis (MRA), scanning laser polarimetry (GDx enhanced corneal compensation; Glaucoma Diagnostics (GDx), Carl Zeiss Meditec, Dublin, CA) nerve fiber indicator (NFI), and Spectralis optical coherence tomography (OCT; Heidelberg Engineering) retinal nerve fiber layer (RNFL) classification. We defined abnormal tests as an automated classification of outside normal limits for HRT and OCT or NFI ≥ 56 (GDx). We conducted a sensitivity analysis, using borderline abnormal image classifications. The reference standard was clinical diagnosis by a masked glaucoma expert including standardized clinical assessment and automated perimetry. We analyzed 1 eye per patient (the one with more advanced disease). We also evaluated the performance according to severity and using a combination of 2 technologies. Main Outcome Measures Sensitivity and specificity, likelihood ratios, diagnostic, odds ratio, and proportion of indeterminate tests. Results We recruited 955 participants, and 943 were included in the analysis. The average age was 60.5 years (standard deviation, 13.8 years); 51.1% were women. Glaucoma was diagnosed in at least 1 eye in 16.8%; 32% of participants had no glaucoma-related findings. The HRT MRA had the highest sensitivity (87.0%; 95% confidence interval [CI], 80.2%–92.1%), but lowest specificity (63.9%; 95% CI, 60.2%–67.4%); GDx had the lowest sensitivity (35.1%; 95% CI, 27.0%–43.8%), but the highest specificity (97.2%; 95% CI, 95.6%–98.3%). The HRT GPS sensitivity was 81.5% (95% CI, 73.9%–87.6%), and specificity was 67.7% (95% CI, 64.2%–71.2%); OCT sensitivity was 76.9% (95% CI, 69.2%–83.4%), and specificity was 78.5% (95% CI, 75.4%–81.4%). Including only eyes with severe glaucoma, sensitivity increased: HRT MRA, HRT GPS, and OCT would miss 5% of eyes, and GDx would miss 21% of eyes. A combination of 2 different tests did not improve the accuracy substantially. Conclusions Automated imaging technologies can aid clinicians in diagnosing glaucoma, but may not replace current strategies because they can miss some cases of severe glaucoma.

Monitoring ocular hypertension, how much and how often? A cost-effectiveness perspective

Objective To assess the efficiency of alternative monitoring services for people with ocular hypertension (OHT), a glaucoma risk factor. Design Discrete event simulation model comparing five alternative care pathways: treatment at OHT diagnosis with minimal monitoring; biennial monitoring (primary and secondary care) with treatment if baseline predicted 5-year glaucoma risk is ≥6%; monitoring and treatment aligned to National Institute for Health and Care Excellence (NICE) glaucoma guidance (conservative and intensive). Setting UK health services perspective. Participants Simulated cohort of 10 000 adults with OHT (mean intraocular pressure (IOP) 24.9 mm Hg (SD 2.4). Main outcome measures Costs, glaucoma detected, quality-adjusted life years (QALYs). Results Treating at diagnosis was the least costly and least effective in avoiding glaucoma and progression. Intensive monitoring following NICE guidance was the most costly and effective. However, considering a wider cost–utility perspective, biennial monitoring was less costly and provided more QALYs than NICE pathways, but was unlikely to be cost-effective compared with treating at diagnosis (£86 717 per additional QALY gained). The findings were robust to risk thresholds for initiating monitoring but were sensitive to treatment threshold, National Health Service costs and treatment adherence. Conclusions For confirmed OHT, glaucoma monitoring more frequently than every 2 years is unlikely to be efficient. Primary treatment and minimal monitoring (assessing treatment responsiveness (IOP)) could be considered; however, further data to refine glaucoma risk prediction models and value patient preferences for treatment are needed. Consideration to innovative and affordable service redesign focused on treatment responsiveness rather than more glaucoma testing is recommended.

Comparative study of new imaging technologies for the diagnosis of glaucoma: design and conduct of a multi-centre diagnostic accuracy study

Purpose The detection and diagnosis of glaucoma is challenging for health professionals. In the UK, approximately 45% of patients are discharged from secondary care after one visit. Automated imaging technologies are easy to perform and could potentially be used by trained technicians as triage tests for glaucoma diagnosis. The GATE study aims to compare the diagnostic performance of three technologies, Heidelberg Retina Tomograph (HRT-III), Scanning laser polarimetry (GDx-ECC) and Optical Coherence Tomography (Spectralis), as triage tests in secondary care for glaucoma diagnosis.

Diagnostic accuracy of optical coherence tomography for diagnosing glaucoma: secondary analyses of the GATE study

Background/Aims To assess the diagnostic performance of retinal nerve fibre layer (RNFL) data of optical coherence tomography (OCT) for detecting glaucoma. Methods Secondary analyses of a prospective, multicentre diagnostic study (Glaucoma Automated Tests Evaluation (GATE)) referred to hospital eye services in the UK were conducted. We included data from 899 of 966 participants referred to hospital eye services with suspected glaucoma or ocular hypertension. We used both eyes’ data and logistic regression-based receiver operator characteristics analysis to build a set of models to measure the sensitivity and specificity of the average and inferior quadrant RNFL thickness data of OCT. The reference standard was expert clinician examination including automated perimetry. The main outcome measures were sensitivity at 0.95 specificity and specificity at 0.95 sensitivity and the corresponding RNFL thickness thresholds. We explored the possibility of accuracy improvement by adding measures of within-eye and between-eye variation, scan quality, intraocular pressure (IOP) and age. Results Glaucoma was diagnosed in at least one eye in 17% of participants. Areas under the curve were between 0.83 and 0.88. When specificity was fixed at 0.95, the sensitivity was between 0.38 and 0.55, and the highest values were reached with models including the inferior quadrant rather than the average RNFL thickness. Fixing sensitivity at 0.95, the specificity was between 0.36 and 0.58. The addition of age, refractive error, IOP or within-subject variation did not improve the accuracy. Conclusion RNFL thickness data of OCT can be used as a diagnostic test, but accuracy estimates remain moderate even in exploratory multivariable modelling of aiming to improve accuracy.

Difficulties with defining diagnostic accuracy study outcomes

Evaluation of diagnostic tests raises unique methodological challenges. Outcomes include measures of test performance compared to a reference standard. When reporting diagnostic test accuracy, other factors to consider include the rate of indeterminate results and missing data [1]. However, there is little guidance on how this should be considered and represented within a diagnostic study.