Abstract
Background
Neovascular age-related macular degeneration is a leading cause of sight loss, and early detection and treatment is important. For patients with neovascular age-related macular degeneration in one eye, it is usual practice to monitor the unaffected eye. The test used to diagnose neovascular age-related macular degeneration, fundus fluorescein angiography, is an invasive test. Non-invasive tests are available, but their diagnostic accuracy is unclear.
Objectives
The primary objective was to determine the diagnostic monitoring performance of tests for neovascular age-related macular degeneration in the second eye of patients with unilateral neovascular age-related macular degeneration. The secondary objectives were the cost-effectiveness of tests and to identify predictive factors of developing neovascular age-related macular degeneration.
Design
This was a multicentre, prospective, cohort, comparative diagnostic accuracy study in a monitoring setting for up to 3 years. A Cox regression risk prediction model and a Markov microsimulation model comparing cost-effectiveness of the index tests over 25 years were used.
Setting
This took place in hospital eye services.
Participants
Participants were adults (aged 50–95 years) with newly diagnosed (within the previous 6 weeks) neovascular age-related macular degeneration in one eye and an unaffected second (study) eye who were attending for treatment injections in the first eye and who had a study eye baseline visual acuity of ≥ 68 Early Treatment Diabetic Retinopathy Study letters.
Interventions
The index tests were Amsler chart (completed by participants), fundus clinical examination, optical coherence tomography, self-reported vision assessment (completed by participants) and visual acuity. The reference standard was fundus fluorescein angiography.
Main outcome measures
The main outcome measures were sensitivity and specificity; the performance of the risk predictor model; and costs and quality-adjusted life-years.
Results
In total, 552 out of 578 patients who consented from 24 NHS hospitals (n = 16 ineligible; n = 10 withdrew consent) took part. The mean age of the patients was 77.4 years (standard deviation 7.7 years) and 57.2% were female. For the primary analysis, 464 patients underwent follow-up fundus fluorescein angiography and 120 developed neovascular age-related macular degeneration on fundus fluorescein angiography. The diagnostic accuracy [sensitivity (%) (95% confidence interval); specificity (%) (95% confidence interval)] was as follows: optical coherence tomography 91.7 (85.2 to 95.6); 87.8 (83.8 to 90.9)], fundus clinical examination [53.8 (44.8 to 62.5); 97.6 (95.3 to 98.9)], Amsler [33.7 (25.1 to 43.5); 81.4 (76.4 to 85.5)], visual acuity [30.0 (22.5 to 38.7); 66.3 (61.0 to 71.1)] and self-reported vision [4.2 (1.6 to 9.8); 97.0 (94.6 to 98.5)]. Optical coherence tomography had the highest sensitivity across all secondary analyses. The final prediction model for neovascular age-related macular degeneration in the non-affected eye included smoking status, family history of neovascular age-related macular degeneration, the presence of nodular drusen with or without reticular pseudodrusen, and the presence of pigmentary abnormalities [c-statistic 0.66 (95% confidence interval 0.62 to 0.71)]. Optical coherence tomography monitoring generated the greatest quality-adjusted life-years gained per patient (optical coherence tomography, 5.830; fundus clinical examination, 5.787; Amsler chart, 5.736, self-reported vision, 5.630; and visual acuity, 5.600) for the lowest health-care and social care costs (optical coherence tomography, £19,406; fundus clinical examination, £19,649; Amsler chart, £19,751; self-reported vision, £20,198; and visual acuity, £20,444) over the lifetime of the simulated cohort. Optical coherence tomography dominated the other tests or had an incremental cost-effectiveness ratio below the accepted cost-effectiveness thresholds (£20,000) across the scenarios explored.
Limitations
The diagnostic performance may be different in an unselected population without any history of neovascular age-related macular degeneration; the prediction model did not include genetic profile data, which might have improved the discriminatory performance.
Conclusions
Optical coherence tomography was the most accurate in diagnosing conversion to neovascular age-related macular degeneration in the fellow eye of patients with unilateral neovascular age-related macular degeneration. Economic modelling suggests that optical coherence tomography monitoring is cost-effective and leads to earlier diagnosis of and treatment for neovascular age-related macular degeneration in the second eye of patients being treated for neovascular age-related macular degeneration in their first eye.
Future work
Future works should investigate the role of home monitoring, improved risk prediction models and impact on long-term visual outcomes.
Study registration
This study was registered as ISRCTN48855678.
Neovascular age-related macular degeneration is a leading cause of sight loss, and early detection and treatment is important. For patients with neovascular age-related macular degeneration in one eye, it is usual practice to monitor the unaffected eye. The test used to diagnose neovascular age-related macular degeneration, fundus fluorescein angiography, is an invasive test. Non-invasive tests are available, but their diagnostic accuracy is unclear.
Objectives
The primary objective was to determine the diagnostic monitoring performance of tests for neovascular age-related macular degeneration in the second eye of patients with unilateral neovascular age-related macular degeneration. The secondary objectives were the cost-effectiveness of tests and to identify predictive factors of developing neovascular age-related macular degeneration.
Design
This was a multicentre, prospective, cohort, comparative diagnostic accuracy study in a monitoring setting for up to 3 years. A Cox regression risk prediction model and a Markov microsimulation model comparing cost-effectiveness of the index tests over 25 years were used.
Setting
This took place in hospital eye services.
Participants
Participants were adults (aged 50–95 years) with newly diagnosed (within the previous 6 weeks) neovascular age-related macular degeneration in one eye and an unaffected second (study) eye who were attending for treatment injections in the first eye and who had a study eye baseline visual acuity of ≥ 68 Early Treatment Diabetic Retinopathy Study letters.
Interventions
The index tests were Amsler chart (completed by participants), fundus clinical examination, optical coherence tomography, self-reported vision assessment (completed by participants) and visual acuity. The reference standard was fundus fluorescein angiography.
Main outcome measures
The main outcome measures were sensitivity and specificity; the performance of the risk predictor model; and costs and quality-adjusted life-years.
Results
In total, 552 out of 578 patients who consented from 24 NHS hospitals (n = 16 ineligible; n = 10 withdrew consent) took part. The mean age of the patients was 77.4 years (standard deviation 7.7 years) and 57.2% were female. For the primary analysis, 464 patients underwent follow-up fundus fluorescein angiography and 120 developed neovascular age-related macular degeneration on fundus fluorescein angiography. The diagnostic accuracy [sensitivity (%) (95% confidence interval); specificity (%) (95% confidence interval)] was as follows: optical coherence tomography 91.7 (85.2 to 95.6); 87.8 (83.8 to 90.9)], fundus clinical examination [53.8 (44.8 to 62.5); 97.6 (95.3 to 98.9)], Amsler [33.7 (25.1 to 43.5); 81.4 (76.4 to 85.5)], visual acuity [30.0 (22.5 to 38.7); 66.3 (61.0 to 71.1)] and self-reported vision [4.2 (1.6 to 9.8); 97.0 (94.6 to 98.5)]. Optical coherence tomography had the highest sensitivity across all secondary analyses. The final prediction model for neovascular age-related macular degeneration in the non-affected eye included smoking status, family history of neovascular age-related macular degeneration, the presence of nodular drusen with or without reticular pseudodrusen, and the presence of pigmentary abnormalities [c-statistic 0.66 (95% confidence interval 0.62 to 0.71)]. Optical coherence tomography monitoring generated the greatest quality-adjusted life-years gained per patient (optical coherence tomography, 5.830; fundus clinical examination, 5.787; Amsler chart, 5.736, self-reported vision, 5.630; and visual acuity, 5.600) for the lowest health-care and social care costs (optical coherence tomography, £19,406; fundus clinical examination, £19,649; Amsler chart, £19,751; self-reported vision, £20,198; and visual acuity, £20,444) over the lifetime of the simulated cohort. Optical coherence tomography dominated the other tests or had an incremental cost-effectiveness ratio below the accepted cost-effectiveness thresholds (£20,000) across the scenarios explored.
Limitations
The diagnostic performance may be different in an unselected population without any history of neovascular age-related macular degeneration; the prediction model did not include genetic profile data, which might have improved the discriminatory performance.
Conclusions
Optical coherence tomography was the most accurate in diagnosing conversion to neovascular age-related macular degeneration in the fellow eye of patients with unilateral neovascular age-related macular degeneration. Economic modelling suggests that optical coherence tomography monitoring is cost-effective and leads to earlier diagnosis of and treatment for neovascular age-related macular degeneration in the second eye of patients being treated for neovascular age-related macular degeneration in their first eye.
Future work
Future works should investigate the role of home monitoring, improved risk prediction models and impact on long-term visual outcomes.
Study registration
This study was registered as ISRCTN48855678.
| Original language | English |
|---|---|
| Number of pages | 176 |
| Journal | Health Technology Assessment |
| Volume | 26 |
| Issue number | 8 |
| Early online date | 31 Jan 2022 |
| DOIs | |
| Publication status | Published - Feb 2022 |
Bibliographical note
FundingThis 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. 26, No. 8. See the NIHR Journals Library website for further project information.
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