• Graham Mowatt, Rodolfo Hernández, Mayret Castillo, Noemi Lois, Andrew Elders, Cynthia Fraser, Olatunde Aremu, Winfried Amoaku, Jennifer Burr, Andrew Lotery, Craig Ramsay, and Augusto Azuara-Blanco.
• Health Services Research Unit, University of Aberdeen, Aberdeen, UK.
• Health Technol Assess. 2014 Dec 1;18(69):1-254.

BackgroundAge-related macular degeneration is the most common cause of sight impairment in the UK. In neovascular age-related macular degeneration (nAMD), vision worsens rapidly (over weeks) due to abnormal blood vessels developing that leak fluid and blood at the macula.ObjectivesTo determine the optimal role of optical coherence tomography (OCT) in diagnosing people newly presenting with suspected nAMD and monitoring those previously diagnosed with the disease.Data SourcesDatabases searched: MEDLINE (1946 to March 2013), MEDLINE In-Process & Other Non-Indexed Citations (March 2013), EMBASE (1988 to March 2013), Biosciences Information Service (1995 to March 2013), Science Citation Index (1995 to March 2013), The Cochrane Library (Issue 2 2013), Database of Abstracts of Reviews of Effects (inception to March 2013), Medion (inception to March 2013), Health Technology Assessment database (inception to March 2013).Review MethodsTypes of studies: direct/indirect studies reporting diagnostic outcomes.Index Testtime domain optical coherence tomography (TD-OCT) or spectral domain optical coherence tomography (SD-OCT).Comparatorsclinical evaluation, visual acuity, Amsler grid, colour fundus photographs, infrared reflectance, red-free images/blue reflectance, fundus autofluorescence imaging, indocyanine green angiography, preferential hyperacuity perimetry, microperimetry. Reference standard: fundus fluorescein angiography (FFA). Risk of bias was assessed using quality assessment of diagnostic accuracy studies, version 2. Meta-analysis models were fitted using hierarchical summary receiver operating characteristic curves. A Markov model was developed (65-year-old cohort, nAMD prevalence 70%), with nine strategies for diagnosis and/or monitoring, and cost-utility analysis conducted. NHS and Personal Social Services perspective was adopted. Costs (2011/12 prices) and quality-adjusted life-years (QALYs) were discounted (3.5%). Deterministic and probabilistic sensitivity analyses were performed.ResultsIn pooled estimates of diagnostic studies (all TD-OCT), sensitivity and specificity [95% confidence interval (CI)] was 88% (46% to 98%) and 78% (64% to 88%) respectively. For monitoring, the pooled sensitivity and specificity (95% CI) was 85% (72% to 93%) and 48% (30% to 67%) respectively. The FFA for diagnosis and nurse-technician-led monitoring strategy had the lowest cost (£ 39,769; QALYs 10.473) and dominated all others except FFA for diagnosis and ophthalmologist-led monitoring (£ 44,649; QALYs 10.575; incremental cost-effectiveness ratio £ 47,768). The least costly strategy had a 46.4% probability of being cost-effective at £ 30,000 willingness-to-pay threshold.LimitationsVery few studies provided sufficient information for inclusion in meta-analyses. Only a few studies reported other tests; for some tests no studies were identified. The modelling was hampered by a lack of data on the diagnostic accuracy of strategies involving several tests.ConclusionsBased on a small body of evidence of variable quality, OCT had high sensitivity and moderate specificity for diagnosis, and relatively high sensitivity but low specificity for monitoring. Strategies involving OCT alone for diagnosis and/or monitoring were unlikely to be cost-effective. Further research is required on (i) the performance of SD-OCT compared with FFA, especially for monitoring but also for diagnosis; (ii) the performance of strategies involving combinations/sequences of tests, for diagnosis and monitoring; (iii) the likelihood of active and inactive nAMD becoming inactive or active respectively; and (iv) assessment of treatment-associated utility weights (e.g. decrements), through a preference-based study.Study RegistrationThis study is registered as PROSPERO CRD42012001930.FundingThe National Institute for Health Research Health Technology Assessment programme.

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