Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.721209
Title: Statistical evaluation of surrogate outcomes : methodological extensions to ordinal outcomes with applications in acute stroke
Author: Ensor, Hannah Margaret
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2016
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Abstract:
Background Surrogate outcomes are measures of treatment effect that can be used to predict treatment effect on the true outcome of interest. Surrogates are valued as they can be used in place of true outcomes to reduce the length, size, or intrusiveness of a clinical trial. However, validation of surrogacy is a conceptually complicated area and much theoretical and practical statistical development has been conducted in recent years. Methods A systematic review was conducted to identify which surrogate evaluation approach was best suited to be extended to ordinal outcomes. I extended a foremost approach to the case where the surrogate, the true clinical outcome, or both are ordinal outcomes. This extension investigated surrogacy at both the trial and individual levels; trial level surrogacy was based on a two stage method. The extension was developed through large simulation studies and used to investigate whether deep venous thromboembolism (DVT) was a surrogate for the ongoing measure of death and disability the Oxford Handicap Scale (OHS), using data from the stroke trial CLOTS3. CLOTS3 was a large multi-centre randomised clinical trial which investigated whether intermittent pneumatic compression (IPC) applied to the legs reduced the occurrence of deep venous thromboembolism (DVT) in stroke clinical trial patients. Results The systematic review identified the information theory approach as the most intuitively and practically worthwhile approach to surrogacy evaluation. I extended this approach to: a binary surrogate and ordinal true outcome (the binary-ordinal setting); the ordinal-binary and the ordinal-ordinal settings. The simulation studies showed that the approach worked well in most scenarios tested. However, trial level surrogacy was impacted by loss of efficiency due to the use of the two stage method. Bias imposed at the trial level by separation of discrete outcomes was effectively dealt with using a penalised likelihood method. The information theory approach for ordinal outcomes identified no surrogate that would predict treatment effect of IPC on the true outcome OHS measured at six months in the stroke trial CLOTS3.
Supervisor: Weir, Christopher ; Sudlow, Cathie Sponsor: Medical Research Council (MRC)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.721209  DOI: Not available
Keywords: surrogate ; clinical trials ; methodology ; ordinal
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