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dc.contributor.authorBurr, Jennifer Margaret
dc.contributor.authorBotello-Pinzon, P.
dc.contributor.authorTakwoingi, Y.
dc.contributor.authorHernandez, R.
dc.contributor.authorVazquez-Montes, M.
dc.contributor.authorElders, A.
dc.contributor.authorAsaoka, R.
dc.contributor.authorBanister, K.
dc.contributor.authorvan der Schoot, J.
dc.contributor.authorFraser, C.
dc.contributor.authorKing, A.
dc.contributor.authorLemij, H.
dc.contributor.authorSanders, R.
dc.contributor.authorVernon, S.
dc.contributor.authorTuulonen, A.
dc.contributor.authorKotecha, A.
dc.contributor.authorGlasziou, P.
dc.contributor.authorGarway-Heath, D.
dc.contributor.authorCrabb, D.
dc.contributor.authorVale, L.
dc.contributor.authorAzuara-Blanco, A.
dc.contributor.authorPerera, R.
dc.contributor.authorRyan, Mandy
dc.contributor.authorDeeks, J.
dc.contributor.authorCook, J.
dc.identifier.citationBurr , J M , Botello-Pinzon , P , Takwoingi , Y , Hernandez , R , Vazquez-Montes , M , Elders , A , Asaoka , R , Banister , K , van der Schoot , J , Fraser , C , King , A , Lemij , H , Sanders , R , Vernon , S , Tuulonen , A , Kotecha , A , Glasziou , P , Garway-Heath , D , Crabb , D , Vale , L , Azuara-Blanco , A , Perera , R , Ryan , M , Deeks , J & Cook , J 2012 , Surveillance for ocular hypertension : an evidence synthesis and economic evaluation . Health Technology Assessment , no. 29 , vol. 16 , The Stationery Office (HMSO) .
dc.identifier.otherPURE: 70455244
dc.identifier.otherPURE UUID: f7a20106-dbd6-4d8b-af39-c7ac5521a463
dc.identifier.otherRIS: urn:D40E9F039C7FFD5D3B912ECD2FCE73C3
dc.identifier.otherWOS: 000307263800001
dc.identifier.otherScopus: 84863639433
dc.identifier.otherORCID: /0000-0002-9478-738X/work/60196214
dc.description.abstractOBJECTIVES: To determine effective and efficient monitoring criteria for ocular hypertension [raised intraocular pressure (IOP)] through (i) identification and validation of glaucoma risk prediction models; and (ii) development of models to determine optimal surveillance pathways. DESIGN: A discrete event simulation economic modelling evaluation. Data from systematic reviews of risk prediction models and agreement between tonometers, secondary analyses of existing datasets (to validate identified risk models and determine optimal monitoring criteria) and public preferences were used to structure and populate the economic model. SETTING: Primary and secondary care. PARTICIPANTS: Adults with ocular hypertension (IOP > 21mmHg) and the public (surveillance preferences). INTERVENTIONS: We compared five pathways: two based on National Institute for Health and Clinical Excellence (NICE) guidelines with monitoring interval and treatment depending on initial risk stratification, 'NICE intensive' (4-monthly to annual monitoring) and 'NICE conservative' (6-monthly to biennial monitoring); two pathways, differing in location (hospital and community), with monitoring biennially and treatment initiated for a >/= 6% 5-year glaucoma risk; and a 'treat all' pathway involving treatment with a prostaglandin analogue if IOP > 21 mmHg and IOP measured annually in the community. MAIN OUTCOME MEASURES: Glaucoma cases detected; tonometer agreement; public preferences; costs; willingness to pay and quality-adjusted life-years (QALYs). RESULTS: The best available glaucoma risk prediction model estimated the 5-year risk based on age and ocular predictors (IOP, central corneal thickness, optic nerve damage and index of visual field status). Taking the average of two IOP readings, by tonometry, true change was detected at two years. Sizeable measurement variability was noted between tonometers. There was a general public preference for monitoring; good communication and understanding of the process predicted service value. 'Treat all' was the least costly and 'NICE intensive' the most costly pathway. Biennial monitoring reduced the number of cases of glaucoma conversion compared with a 'treat all' pathway and provided more QALYs, but the incremental cost-effectiveness ratio (ICER) was considerably more than pound30,000. The 'NICE intensive' pathway also avoided glaucoma conversion, but NICE-based pathways were either dominated (more costly and less effective) by biennial hospital monitoring or had a ICERs > pound30,000. Results were not sensitive to the risk threshold for initiating surveillance but were sensitive to the risk threshold for initiating treatment, NHS costs and treatment adherence. LIMITATIONS: Optimal monitoring intervals were based on IOP data. There were insufficient data to determine the optimal frequency of measurement of the visual field or optic nerve head for identification of glaucoma. The economic modelling took a 20-year time horizon which may be insufficient to capture long-term benefits. Sensitivity analyses may not fully capture the uncertainty surrounding parameter estimates. CONCLUSIONS: For confirmed ocular hypertension, findings suggest that there is no clear benefit from intensive monitoring. Consideration of the patient experience is important. A cohort study is recommended to provide data to refine the glaucoma risk prediction model, determine the optimum type and frequency of serial glaucoma tests and estimate costs and patient preferences for monitoring and treatment. FUNDING: The National Institute for Health Research Health Technology Assessment Programme.
dc.publisherThe Stationery Office (HMSO)
dc.relation.ispartofseriesHealth Technology Assessmenten
dc.rights(c) Queen's Printer and Controller of HMSO 2012. This work was produced by Burr et al. under the terms of a commissioning contract issued by the Secretary of State for Health.en
dc.subjectRE Ophthalmologyen
dc.titleSurveillance for ocular hypertension : an evidence synthesis and economic evaluationen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Medicineen

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